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Red Hat JBoss BPM Suite 6.4

Red Hat JBoss BPM Suite Development Guide for Red Hat JBoss Developers

Red Hat Customer Content Services

Emily Murphy

Gemma Sheldon

Michele Haglund

Mikhail Ramendik

Stetson Robinson

Vidya Iyengar

Abstract

A guide to using API's in Red Hat JBoss BPM Suite for developers.

Part I. Overview

Chapter 1. About This Guide

This guide is intended for users who are implementing a standalone Red Hat JBoss BRMS solution or the complete Red Hat JBoss BPM Suite solution. It discusses the following topics:

  • Detailed Architecture of Red Hat JBoss BRMS and Red Hat JBoss BPM Suite.
  • Detailed description of how to author, test, debug, and package simple and complex business rules and processes using Integrated Development environment (IDE).
  • Red Hat JBoss BRMS runtime environment.
  • Domain specific languages (DSLs) and how to use them in a rule.
  • Complex event processing.

This guide comprises the following sections:

  1. Overview

    This section provides detailed information on Red Hat JBoss BRMS and Red Hat JBoss BPM suite, their architecture, key components. It also discusses the role of Maven in project building and deploying.

  2. All About Rules

    This section provides details on all you have to know to author rules with Red Hat JBoss Developer Studio. It describes the rule algorithms, rule structure, components, advanced conditions, constraints, commands, Domain Specific Languages and Complex Event Processing. It provides details on how to use the various views, editors, and perspectives that Red Hat JBoss Developer Studio offers.

  3. All About Processes

    This section describes what comprises a business process and how you can author and test them using Red Hat JBoss Developer Studio.

  4. KIE

    This section highlights the KIE API with detailed description of how to create, build, deploy, and run KIE projects.

  5. Appendix

    This section comprises important reference material such as key knowledge terms, and examples.

1.1. Audience

This book has been designed to be understood by:

  • Author of rules and processes who are responsible for authoring and testing business rules and processes using Red Hat JBoss Developer Studio.
  • Java application developers responsible for developing and integrating business rules and processes into Java and Java EE enterprise applications.

1.2. Prerequisites

Users of this guide must meet one or more of the following prerequisites:

  • Basic Java/Java EE programming experience
  • Knowledge of the Eclipse IDE, Maven, and GIT

Chapter 2. Red Hat JBoss BRMS and Red Hat JBoss BPM Suite Architecture

2.1. Red Hat JBoss Business Rules Management System

Red Hat JBoss BRMS is an open source business rule management system that provides rules development, access, change, and management capabilities. In today’s world, when IT organizations consistently face changes in terms of policies, new products, government imposed regulations, a system like JBoss BRMS makes it easy by separating business logic from the underlying code. It includes a rule engine, a rules development environment, a management system, and a repository. It allows both developers and business analysts to view, manage, and verify business rules as they are executed within an IT application infrastructure.

Red Hat JBoss BRMS can be executed in any Java EE-compliant container. It supports an open choice of authoring and management consoles and language and decision table inputs.

2.1.1. Red Hat JBoss BRMS Key Components

Red Hat JBoss BRMS comprises the following components:

  • Drools Expert

    Drools Expert is a pattern matching based rule engine that runs on Java EE application servers, Red Hat JBoss BRMS platform, or bundled with Java applications. It comprises an inference engine, a production memory, and a working memory. Rules are stored in the production memory and the facts that the inference engine matches the rules against, are stored in the working memory.

  • Business Central

    Business Central is a web-based application intended for business analysts for creation and maintenance of business rules and rule artifacts. It is designed to ease creation, testing, and packaging of rules for business users.

  • Drools Flow

    Drools flow provides business process capabilities to the Red Hat JBoss BRMS platform. This framework can be embedded into any Java application or can even run standalone on a server. A business process provides stepwise tasks using a flow chart, for the Rule Engine to execute.

  • Drools Fusion

    Drools Fusion provides event processing capabilities to the Red Hat JBoss BRMS platform. Drools Fusion defines a set of goals to be achieved such as:

    • Support events as first class citizens.
    • Support detection, correlation, aggregation and composition of events.
    • Support processing streams of events.
    • Support temporal constraints in order to model the temporal relationships between events.
  • Drools Integrated Development Environment (IDE)

    We encourage you to use Red Hat JBoss Developer Studio (JBDS) with Red Hat JBoss BRMS plug-ins to develop and test business rules. The Red Hat JBoss Developer Studio builds upon an extensible, open source Java-based IDE Eclipse providing platform and framework capabilities, making it ideal for Red Hat JBoss BRMS rules development.

2.1.2. Red Hat JBoss BRMS Features

The Red Hat JBoss BRMS provides the following key features:

  • Centralized repository of business assets (JBoss BRMS artifacts).
  • IDE tools to define and govern decision logic.
  • Building, deploying, and testing the decision logic.
  • Packages of business assets.
  • Categorization of business assets.
  • Integration with development tools.
  • Business logic and data separation.
  • Business logic open to reuse and changes.
  • Easy to maintain business logic.
  • Enables several stakeholders (business analysts, developer, administrators) to contribute in defining the business logic.

2.2. Red Hat JBoss Business Process Management Suite

Red Hat JBoss BPM Suite is an open source business process management system that combines business process management and business rules management. Red Hat JBoss BRMS offers tools to author rules and business processes, but does not provide tools to start or manage the business processes. Red Hat JBoss BPM Suite includes all the Red Hat JBoss BRMS functionality, with additional capabilities of business activity monitoring, starting business processes, and managing tasks using Business Central. Red Hat JBoss BPM Suite also provides a central repository to store rules and processes.

2.2.1. Red Hat JBoss BPM Suite Key Components

The Red Hat JBoss BPM Suite comprises the following components:

  • JBoss BPM Central (Business Central)

    Business Central is a web-based application for creating, editing, building, managing, and monitoring Red Hat JBoss BPM Suite business assets. It also allows execution of business processes and management of tasks created by those processes.

  • Business Activity Monitoring Dashboards

    The Business Activity Monitor (BAM) dashboard provides report generation capabilities. It enables you to use a pre-defined dashboard and even create your own customized dashboard.

  • Maven Artifact Repository

    Red Hat JBoss BPM Suite projects are built as Apache Maven projects and the default location of the Maven repository is WORKING_DIRECTORY/repositories/kie. You can specify an alternate repository location by changing the org.guvnor.m2repo.dir property.

    Each project builds a JAR artifact file called a KJAR. You can store your project artifacts and dependent JAR files in this repository.

  • Execution Engine

    The Red Hat JBoss BPM Suite execution engine is responsible for executing business processes and managing the tasks, which result from these processes. Business Central provides a user interface for executing processes and managing tasks.

    Note

    To execute your business processes, you can use Business Central web application that bundles the execution engine, enabling a ready-to-use process execution environment. Alternatively, you can create your own execution server and embed the Red Hat JBoss BPM Suite and Red Hat JBoss BRMS libraries with your application using Java EE.

    For example, if you are developing a web application, include the Red Hat JBoss BPM Suite or Red Hat JBoss BRMS libraries in the WEB-INF/lib folder of your application.

  • Business Central Repository

    The business artifacts of a Red Hat JBoss BPM Suite project, such as process models, rules, and forms, are stored in Git repositories managed through the Business Central. You can also access these repositories outside of Business Central through the Git or SSH protocols.

2.2.2. Red Hat JBoss BPM Suite Features

Red Hat JBoss BPM Suite provides the following features:

  • Pluggable human task service for including tasks that need to be performed by human actors (based on the WS-HumanTask specification).
  • Pluggable persistence and transactions (based on JPA/JTA).
  • Web-based process designer to support the graphical creation and simulation of your business processes (drag and drop).
  • Web-based data modeler and form modeler to support the creation of data models and process and task forms.
  • Web-based, customizable dashboards and reporting.
  • A web-based workbench called Business Central, supporting the complete BPM life cycle:

    • Modeling and deployment: to author your processes, rules, data models, forms and other assets.
    • Execution: to execute processes, tasks, rules and events on the core runtime engine.
    • Runtime Management: to work on assigned task, manage process instances.
    • Reporting: to monitor the execution using Business Activity Monitoring capabilities.
  • Eclipse-based developer tools to support the modeling, testing and debugging of processes.
  • Remote API to process engine as a service (REST, JMS, Remote Java API).
  • Integration with Maven, Spring, and OSGi.

2.3. Supported Platforms and APIs

For a list of supported containers and configurations, see section Supported Platforms of Red Hat JBoss BPM Suite Installation Guide.

The kie-api is a fully supported API and it is the recommended way to interact with your project. For further information about API supportability, see Knowledgebase article What Are the Public and Internal APIs for BPM Suite and BRMS 6?.

2.4. Use Cases

2.4.1. Use Case: Business Decision Management in Insurance Industry with Red Hat JBoss BRMS

Red Hat JBoss BRMS comprises a high performance rule engine, a rule repository, easy to use rule authoring tools, and complex event processing rule engine extensions. The following use case describes how these features of Red Hat JBoss BRMS are implemented in insurance industry.

The consumer insurance market is extremely competitive, and it is imperative that customers receive efficient, competitive, and comprehensive services when visiting an online insurance quotation solution. An insurance provider increased revenue from their online quotation solution by upselling relevant, additional products during the quotation process to the visitors of the solution.

The diagram below shows integration of Red Hat JBoss BRMS with the insurance provider’s infrastructure. This integration is fruitful in such a way that when a request for insurance is processed, Red Hat JBoss BRMS is consulted and appropriate additional products are presented with the insurance quotation.

Figure 2.1. JBoss BRMS Use Case: Insurance Industry Decision Making

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Red Hat JBoss BRMS provides the decision management functionality, that automatically determines the products to present to the applicant based on the rules defined by the business analysts. The rules are implemented as decision tables, so they can be easily understood and modified without requiring additional support from IT.

2.4.2. Use Case: Process­-Based Solution in Loan Industry

This section describes a use case of deploying Red Hat JBoss BPM Suite to automate business processes (such as loan approval process) at a retail bank. This use case is a typical process-based specific deployment that might be the first step in a wider adoption of Red Hat JBoss BPM Suite throughout an enterprise. It leverages features of both business rules and processes of Red Hat JBoss BPM Suite.

A retail bank offers several types of loan products each with varying terms and eligibility requirements. Customers requiring a loan must file a loan application with the bank. The bank then processes the application in several steps, such as verifying eligibility, determining terms, checking for fraudulent activity, and determining the most appropriate loan product. Once approved, the bank creates and funds a loan account for the applicant, who can then access funds. The bank must be sure to comply with all relevant banking regulations at each step of the process, and has to manage its loan portfolio to maximize profitability. Policies are in place to aid in decision making at each step, and those policies are actively managed to optimize outcomes for the bank.

Business analysts at the bank model the loan application processes using the BPMN2 authoring tools (Process Designer) in Red Hat JBoss BPM Suite. Here is the process flow:

High-Level Loan Application Process Flow

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Business rules are developed with the rule authoring tools in Red Hat JBoss BPM Suite to enforce policies and make decisions. Rules are linked with the process models to enforce the correct policies at each process step.

The bank’s IT organization deploys the Red Hat JBoss BPM Suite so that the entire loan application process can be automated.

Figure 2.2. Loan Application Process Automation

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The entire loan process and rules can be modified at any time by the bank’s business analysts. The bank is able to maintain constant compliance with changing regulations, and is able to quickly introduce new loan products and improve loan policies in order to compete effectively and drive profitability.

Chapter 3. Apache Maven

Apache Maven is a distributed build automation tool used in Java application development to build and manage software projects. Apart from building, publishing, and deploying capabilities, using Maven for your Red Hat JBoss BRMS and Red Hat JBoss BPM suite projects ensures the following:

  • The build process is easy and a uniform build system is implemented across projects.
  • All of the required JAR files for a project are made available at compile time.
  • A proper project structure is configured.
  • Dependencies and versions are well managed.
  • No need for additional build processing, as Maven builds output into a number of predefined types, such as JAR and WAR.

3.1. Maven Repositories

Maven uses repositories to store Java libraries, plug-ins, and other build artifacts. These repositories can be local or remote. Red Hat JBoss BRMS and Red Hat JBoss BPM Suite products maintain local and remote maven repositories that you can add to your project for accessing the rules, processes, events, and other project dependencies. You must configure Maven to use these repositories and the Maven Central Repository to provide correct build functionality.

When building projects and archetypes, Maven dynamically retrieves Java libraries and Maven plug-ins from local or remote repositories. Doing so promotes sharing and reuse of dependencies across projects.

3.2. Using the Maven Repository in Your Project

You can direct Maven to use the Red Hat JBoss Enterprise Application Platform Maven repository in your project in one of the following ways:

  • Configure the Project Object Model (POM) file (pom.xml).
  • Modify the Maven settings file (settings.xml).

The recommended approach is to direct Maven to use the Red Hat JBoss Enterprise Application Platform Maven repository across all projects by using the Maven global or user settings.

From version 6.1.0 onwards, Red Hat JBoss BPM Suite and Red Hat JBoss BRMS are designed to be used in combination with Red Hat JBoss Middleware Maven Repository and Maven Central repository as dependency sources. Ensure that both repositories are available for project builds.

3.3. Maven Project Configuration File

To use Maven for building and managing your Red Hat JBoss BRMS and Red Hat JBoss BPM Suite projects, you must configure your projects to be built with Maven. To do so, Maven provides the POM file (pom.xml) that holds configuration details for your project.

pom.xml is an XML file that contains information about the project (such as project name, version, description, developers, mailing list, and license), and build details (such as dependencies, location of the source, test, target directories, repositories, and plug-ins).

When you generate a Maven project, a pom.xml file is automatically generated. You can edit pom.xml to add more dependencies and new repositories. Maven downloads all of the JAR files and the dependent JAR files from the Maven repository when you compile and package your project.

Find the schema for the pom.xml file at http://maven.apache.org/maven-v4_0_0.xsd.

For more information about POM files, see Apache Maven Project POM Reference.

3.4. Maven Settings File

The Maven settings file (settings.xml) is used to configure Maven execution. You can locate this file in the following locations:

  • In the Maven install directory at $M2_HOME/conf/settings.xml. These settings are called global settings.
  • In the user’s install directory at $USER_HOME/.m2/settings.xml. These settings are called user settings.
  • A custom location specified by the system property kie.maven.settings.custom.
Note

The settings used is a merge of the files located in these locations.

The following is an example of a Maven settings.xml file. Note the activeByDefault tag, which specifies the default profile. In the following example, it is a profile with a remote Maven repository.

<settings>
  <profiles>
    <profile>
      <id>my-profile</id>
      <activation>
        <activeByDefault>true</activeByDefault>
      </activation>
      <repositories>
        <repository>
          <id>fusesource</id>
          <url>http://repo.fusesource.com/nexus/content/groups/public/</url>
          <snapshots>
            <enabled>false</enabled>
          </snapshots>
          <releases>
            <enabled>true</enabled>
          </releases>
        </repository>
        ...
      </repositories>
    </profile>
  </profiles>
  ...
</settings>

3.5. Dependency Management

In order to use the correct Maven dependencies in your Red Hat JBoss BPM Suite project, you must add relevant Bill Of Materials (BOM) files to the project’s pom.xml file. Adding the BOM files ensures that the correct versions of transitive dependencies from the provided Maven repositories are included in the project.

See the Supported Component Versions chapter of Red Hat JBoss BPM Suite Installation Guide to view the supported BOM components.

Declare the BOM in pom.xml. For example:

Example 3.1. BOM for Red Hat JBoss BPM Suite 6.4.0

<dependencyManagement>
 <dependencies>
  <dependency>
   <groupId>org.jboss.bom.brms</groupId>
   <artifactId>jboss-brms-bpmsuite-platform-bom</artifactId>
   <version>6.4.2.GA-redhat-2</version>
   <type>pom</type>
   <scope>import</scope>
  </dependency>
 </dependencies>
</dependencyManagement>
<dependencies>
<!-- Your dependencies -->
</dependencies>

To check the current BOM version, see the Supported Component Versions chapter of Red Hat JBoss BPM Suite Installation Guide.

Furthermore, declare dependencies needed for your project in the dependencies tag.

  • For a basic Red Hat JBoss BPM Suite project, declare the following dependencies:

    Embedded jBPM Engine Dependencies

    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-kie-services</artifactId>
    </dependency>
    
    <!-- Dependency needed for default WorkItemHandler implementations. -->
    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-workitems</artifactId>
    </dependency>
    
    <!-- Logging dependency. You can use any logging framework compatible with slf4j. -->
    <dependency>
      <groupId>ch.qos.logback</groupId>
      <artifactId>logback-classic</artifactId>
      <version>${logback.version}</version>
    </dependency>
    
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-api</artifactId>
    </dependency>

  • For a Red Hat JBoss BPM Suite project that uses CDI, declare the following dependencies:

    CDI-Enabled jBPM Engine dependencies

    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-api</artifactId>
    </dependency>
    
    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-kie-services</artifactId>
    </dependency>
    
    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-services-cdi</artifactId>
    </dependency>

  • For a basic Red Hat JBoss BRMS project, declare the following dependencies:

    Embedded Drools Engine Dependencies

    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-compiler</artifactId>
    </dependency>
    
    <!-- Dependency for persistence support. -->
    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-persistence-jpa</artifactId>
    </dependency>
    
    <!-- Dependencies for decision tables, templates, and scorecards.
    For other assets, declare org.drools:drools-workbench-models-* dependencies. -->
    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-decisiontables</artifactId>
    </dependency>
    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-templates</artifactId>
    </dependency>
    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-scorecards</artifactId>
    </dependency>
    
    <!-- Dependency for loading KJARs from a Maven repository using KieScanner. -->
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-ci</artifactId>
    </dependency>
    
    <!-- Dependency for loading KJARs from a Maven repository using KieScanner in an OSGi environment. -->
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-ci-osgi</artifactId>
    </dependency>
    
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-api</artifactId>
    </dependency>

    Do not use both kie-ci and kie-ci-osgi in one pom.xml file.

  • To use the Intelligent Process Server, declare the following dependencies:

    Client Application Intelligent Process Server Dependencies

    <dependency>
      <groupId>org.kie.server</groupId>
      <artifactId>kie-server-client</artifactId>
    </dependency>
    <dependency>
        <groupId>org.kie.server</groupId>
        <artifactId>kie-server-api</artifactId>
    </dependency>
    
    <!-- Dependency for Red Hat JBoss BRMS functionality. -->
    <dependency>
      <groupId>org.drools</groupId>
      <artifactId>drools-core</artifactId>
    </dependency>
    
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-api</artifactId>
    </dependency>

  • To create a remote client for Red Hat JBoss BPM Suite or Red Hat JBoss BRMS, declare the following dependencies:

    Client Dependencies

    <dependency>
      <groupId>org.kie.remote</groupId>
      <artifactId>kie-remote-client</artifactId>
    </dependency>

  • To use assets in KJAR packaging, the preferred way is to include kie-maven-plugin:

    Kie Maven Plugin

    <!-- BOM does not resolve plugin versioning. Consult section Supported Components of Red Hat JBoss BPM Suite Installation Guide for newest version number. -->
    
    <packaging>kjar</packaging>
    <build>
     <plugins>
      <plugin>
       <groupId>org.kie</groupId>
       <artifactId>kie-maven-plugin</artifactId>
       <version>6.5.0.Final-redhat-7</version>
       <extensions>true</extensions>
      </plugin>
     </plugins>
    </build>

  • For testing purposes, declare the following dependencies:

    Testing Dependencies

    <!-- JUnit dependency -->
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>${junit.version}</version>
      <scope>test</scope>
    </dependency>
    
    <!-- Red Hat JBoss BPM Suite integration services dependency -->
    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-shared-services</artifactId>
      <classifier>btm</classifier>
      <scope>test</scope>
    </dependency>
    
    <!-- Logging dependency -->
    <dependency>
      <groupId>ch.qos.logback</groupId>
      <artifactId>logback-classic</artifactId>
      <version>${logback.version}</version>
      <scope>test</scope>
    </dependency>
    
    <!-- Persistence tests dependencies -->
    <dependency>
      <groupId>org.hibernate</groupId>
      <artifactId>hibernate-entitymanager</artifactId>
      <version>${hibernate.version}</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>org.hibernate</groupId>
      <artifactId>hibernate-core</artifactId>
      <version>${hibernate.core.version}</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>com.h2database</groupId>
      <artifactId>h2</artifactId>
      <version>${h2.version}</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>org.codehaus.btm</groupId>
      <artifactId>btm</artifactId>
      <version>${btm.version}</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>org.kie</groupId>
      <artifactId>kie-api</artifactId>
    </dependency>

    Alternatively, for extensive testing of Red Hat JBoss BPM Suite, include the jbpm-test dependency. Note that jbpm-test includes some of the previous dependencies, for example the junit dependency, dependencies required for persistence tests, and others.

    Declaring jbpm-test Dependency

    <dependency>
      <groupId>org.jbpm</groupId>
      <artifactId>jbpm-test</artifactId>
    </dependency>

    To include the jbpm-test dependency as part of your KJAR, set the dependency scope to provided. Doing so ensures that the dependency is available at runtime, thereby avoiding unresolved dependency errors. The recommended practice is to use only business resources in your KJAR and not include jbpm-test dependency in it. It is a best practice to keep the test suite for the KJAR in a separate project.

    Note

    If you are deploying Red Hat JBoss BRMS or Red Hat JBoss BPM Suite on Red Hat JBoss EAP 7, you must make changes to the project BOM files. For more information on the BOM changes, see the Red Hat JBoss EAP Migration chapter in the Red Hat JBoss BPM Suite Migration Guide.

    For more information on BOM usage in Red Hat JBoss EAP 7, see the Using Maven with JBoss EAP chapter in the Red Hat JBoss EAP Development Guide.

3.6. Integrated Maven Dependencies

Throughout the Red Hat JBoss BRMS and BPM Suite documentation, various code samples are presented with KIE API for the 6.1.x releases. These code samples will require Maven dependencies in the various pom.xml file and should be included like the following example:

<dependency>
  <groupId>commons-logging</groupId>
  <artifactId>commons-logging</artifactId>
  <version>1.1.1-redhat-2</version>
  <scope>compile</scope>
</dependency>

All the Red Hat JBoss related product dependencies can be found at the following location: Red Hat Maven Repository.

3.7. Uploading Artifacts to Maven Repository

There may be scenarios when your project may fail to fetch dependencies from a remote repository configured in its pom.xml. In such cases, you can programmatically upload dependencies to Red Hat JBoss BPM Suite by uploading artifacts to the embedded maven repository through Business Central. Red Hat JBoss BPM Suite uses a servlet for the maven repository interactions. This servlet processes a GET request to download an artifact and a POST request to upload one. You can leverage the servlet’s POST request to upload an artifact to the repository using REST. To do this, implement the Http basic authentication and issue an HTTP POST request in the following format:

PROTOCOL://HOST_NAME:PORT/CONTEXT_ROOT/maven2/[GROUP_ID replacing '.' with '/']/ARTIFACT_ID/VERSION/ARTIFACT_ID-VERSION.jar

For example, to upload the org.slf4j:slf4j-api:1.7.7.jar, where ARTIFACT_ID is slf4j-api, GROUP_ID is slf4j, and VERSION is 1.7.7, the URI must be:

http://localhost:8080/business-central/maven2/org/slf4j/slf4j-api/1.7.7/slf4j-api-1.7.7.jar

The following example illustrates uploading a JAR located at /tmp directory as a user bpmsAdmin with the password abcd1234!, to an instance of Red Hat JBoss BPM Suite running locally:

package com.rhc.example;

import java.io.File;
import java.io.IOException;

import org.apache.http.HttpEntity;
import org.apache.http.HttpHost;
import org.apache.http.auth.AuthScope;
import org.apache.http.auth.UsernamePasswordCredentials;
import org.apache.http.client.AuthCache;
import org.apache.http.client.ClientProtocolException;
import org.apache.http.client.CredentialsProvider;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.client.protocol.HttpClientContext;
import org.apache.http.entity.mime.HttpMultipartMode;
import org.apache.http.entity.mime.MultipartEntityBuilder;
import org.apache.http.entity.mime.content.FileBody;
import org.apache.http.impl.auth.BasicScheme;
import org.apache.http.impl.client.BasicAuthCache;
import org.apache.http.impl.client.BasicCredentialsProvider;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class UploadMavenArtifact {
  private static final Logger LOG = LoggerFactory.getLogger(UploadMavenArtifact.class);

  public static void main(String[] args) {

    // Maven coordinates:
    String groupId = "com.rhc.example";
    String artifactId = "bpms-upload-jar";
    String version = "1.0.0-SNAPSHOT";

    // File to upload:
    File file = new File("/tmp/" + artifactId + "-" + version + ".jar");

    // Server properties:
    String protocol = "http";
    String hostname = "localhost";
    Integer port = 8080;
    String username = "bpmsAdmin";
    String password = "abcd1234!";

    // Create the HttpEntity (body of our POST):
    FileBody fileBody = new FileBody(file);
    MultipartEntityBuilder builder = MultipartEntityBuilder.create();
    builder.setMode(HttpMultipartMode.BROWSER_COMPATIBLE);
    builder.addPart("upfile", fileBody);
    HttpEntity entity = builder.build();

    // Calculate the endpoint from the Maven coordinates:
    String resource = "/business-central/maven2/" + groupId.replace('.', '/') + "/" + artifactId +"/" + version + "/" + artifactId + "-" + version + ".jar";

    LOG.info("POST " + hostname + ":" + port + resource);

    // Set up HttpClient to use Basic pre-emptive authentication with the provided credentials:
    HttpHost target = new HttpHost(hostname, port, protocol);
    CredentialsProvider credsProvider = new BasicCredentialsProvider();
    credsProvider.setCredentials(
      new AuthScope(target.getHostName(), target.getPort()),
      new UsernamePasswordCredentials(username,password));
    CloseableHttpClient httpclient = HttpClients.custom().setDefaultCredentialsProvider(credsProvider).build();
    HttpPost httpPost = new HttpPost(resource);
    httpPost.setEntity(entity);
    AuthCache authCache = new BasicAuthCache();
    BasicScheme basicAuth = new BasicScheme();
    authCache.put(target, basicAuth);
    HttpClientContext localContext = HttpClientContext.create();
    localContext.setAuthCache(authCache);

    try {
      // Perform the HTTP POST:
      CloseableHttpResponse response = httpclient.execute(target, httpPost, localContext);
      LOG.info(response.toString());
      // Now check your artifact repository!
    } catch (ClientProtocolException e) {
      LOG.error("Protocol Error", e);
      throw new RuntimeException(e);
    } catch (IOException e) {
      LOG.error("IOException while getting response", e);
      throw new RuntimeException(e);
    }
  }
}
Alternative Maven Approach

An alternative Maven approach is to configure your projects pom.xml by adding the repository as shown below:

<distributionManagement>
  <repository>
    <id>guvnor-m2-repo</id>
    <name>maven repo</name>
    <url>http://localhost:8080/business-central/maven2/</url>
    <layout>default</layout>
  </repository>
</distributionManagement>

Once you specify the repository information in the pom.xml, add the corresponding configuration in settings.xml as shown below:

<server>
  <id>guvnor-m2-repo</id>
  <username>bpmsAdmin</username>
  <password>abcd1234!</password>
  <configuration>
    <wagonProvider>httpclient</wagonProvider>
    <httpConfiguration>
      <all>
        <usePreemptive>true</usePreemptive>
      </all>
    </httpConfiguration>
  </configuration>
</server>

Now when you run the mvn deploy command, the JAR file gets uploaded.

3.8. Deploying Red Hat JBoss BPM Suite Artifacts to Red Hat JBoss Fuse

Red Hat JBoss Fuse is an open source Enterprise Service Bus (ESB) with an elastic footprint and is based on Apache Karaf. The 6.4 version of Red Hat JBoss BPM Suite supports deployment of runtime artifacts to Fuse.

With the 6.1 release, Red Hat JBoss BPM Suite runtime components (in the form of JARs) are OSGi enabled. The runtime engines JARs MANIFEST.MF files describe their dependencies, amongst other things. You can plug these JARs directly into an OSGi environment, like Fuse.

POM Parser Limitations in OSGi Environments

Red Hat JBoss BPM Suite uses a scanner to enable continuous integration, resolution, and fetching of artifacts from remote Maven repositories. This scanner, called KIE-CI, uses a native Maven parser called Plexus to parse Maven POMs. However, this parser is not OSGi compatible and fails to instantiate in an OSGi environment. KIE-CI automatically switches to a simpler POM parser called MinimalPomParser.

The MinimalPomParser is a very simple POM parser implementation provided by Drools and is limited in what it can parse. It ignores some POM file parts, such as the parent POM of a KJAR. This means that users must not rely on those POM features (such as dependencies declared in the parent POM in their KJARs) when using KIE-CI in an OSGi environment.

Separating Assets and Code

One of the main advantage of deploying Red Hat JBoss BPM Suite artifacts on Red Hat JBoss Fuse is that each bundle is isolated, running in its own classloader. This allows you to separate the logic (code) from the assets. Business users can produce and change the rules and processes (assets) and package them in their own bundle, keeping them separate from the project bundle (code), created by the developer team. Assets can be updated without needing to change the project code.

Chapter 4. Install and Set up Red Hat JBoss Developer Studio

Red Hat JBoss Developer Studio is the JBoss Integrated Development Environment (IDE) based on Eclipse. Get the latest Red Hat JBoss Developer Studio from the Red Hat Customer Portal. Red Hat JBoss Developer Studio provides plug-ins with tools and interfaces for Red Hat JBoss BRMS and Red Hat JBoss BPM Suite. These plugins are based on the community version of these products. So, the Red Hat JBoss BRMS plug-in is called the Drools plug-in and the Red Hat JBoss BPM Suite plug-in is called the jBPM plug-in.

See the Red Hat JBoss Developer Studio documentation for installation and setup instructions.

Warning

Due to an issue in the way multi-byte rule names are handled, you must ensure that the instance of Red Hat JBoss Developer Studio is started with the file encoding set to UTF-8. You can do this by editing the $JBDS_HOME/studio/jbdevstudio.ini file and adding the following property: "-Dfile.encoding=UTF-8".

4.1. Installing Red Hat JBoss Developer Studio Plug-ins

Get the latest Red Hat JBoss Developer Studio from the Red Hat Customer Portal. The Red Hat JBoss BRMS and Red Hat JBoss BPM Suite plug-ins for Red Hat JBoss Developer Studio are available using the update site.

Installing Red Hat JBoss BRMS and Red Hat JBoss BPM Suite Plug-ins in Red Hat JBoss Developer Studio

  1. Start Red Hat JBoss Developer Studio.
  2. Click HelpInstall New Software.
  3. Click Add to enter the Add Repository menu.
  4. Provide a name next to the Name field and add the following URL in the Location field: https://devstudio.jboss.com/10.0/stable/updates/integration-stack/.
  5. Click OK.
  6. Select the JBoss Business Process and Rule Development feature from the available options, click Next and then Next again.
  7. Read the license and accept it by selecting the appropriate radio button, and click Finish.
  8. Restart Red Hat JBoss Developer Studio after the installation process finishes.

4.2. Configuring Red Hat JBoss BRMS/BPM Suite Server

Red Hat JBoss Developer Studio can be configured to run the Red Hat JBoss BRMS and Red Hat JBoss BPM Suite server.

Configuring Red Hat JBoss BRMS and Red Hat JBoss BPM Suite Server

  1. Open the Drools view: click WindowOpen PerspectiveOther, select Drools and click OK.

    To open the Red Hat JBoss BPM Suite view, go to WindowOpen PerspectiveOther, select jBPM and click OK.

  2. Click WindowShow ViewOther…​ and select ServerServers to add the server view.
  3. Right click the Servers panel and select NewServer to open the server menu.
  4. Click JBoss Enterprise MiddlewareJBoss Enterprise Application Platform 6.1+ and click Next to define the server.
  5. Set the home directory by clicking Browse button. Navigate to the Red Hat JBoss EAP directory which has Red Hat JBoss BRMS installed.

    For configuring Red Hat JBoss BPM Suite server, select the Red Hat JBoss EAP directory which has Red Hat JBoss BPM Suite installed.

  6. Provide a name for the server in the Name field, ensure that the configuration file is set, and click Finish.

4.3. Importing Projects from Git Repository into Red Hat JBoss Developer Studio

You can configure Red Hat JBoss Developer Studio to connect to a central Git asset repository. The repository stores rules, models, functions, and processes.

You can either clone a remote Git repository or import a local Git repository.

Cloning Remote Git Repository

  1. Select the server from the Server tab and click the start icon to start your server.
  2. Start the Secure Shell server, if not running already, by using the following command. The command is Linux and Mac specific only. On these platforms, if sshd has already been started, this command fails. In that case, you may safely ignore this step.

    /sbin/service sshd start
  3. In Red Hat JBoss Developer Studio , select FileImport…​ and navigate to the Git folder. Open the Git folder to select Projects from Git and click Next.
  4. Select the repository source as Clone URI and click Next.
  5. Enter the details of the Git repository in the next window and click Next.
  6. Select the branch you wish to import in the following window and click Next.
  7. To define the local storage for this project, enter (or select) a non-empty directory, make any configuration changes and click Next.
  8. Import the project as a general project in the following window and click Next.
  9. Name the project and click Finish.

Importing Local Git Repository

  1. Select your server from the Server tab and click the start icon to start the server.
  2. In Red Hat JBoss Developer Studio, select FileImport…​ and navigate to the Git folder. Open the Git folder to select Projects from Git and click Next.
  3. Select the repository source as Existing local repository and click Next.
  4. Select the repository that is to be configured from the list of available repositories and click Next.
  5. In the dialog window that opens, select the Import as general project radio button from the Wizard for project import group and click Next.
  6. Name the project and click Finish.

4.4. Kie Navigator

Kie Navigator enables you to browse, change, and deploy the content of your Red Hat JBoss BPM Suite server. As a result, you can integrate Red Hat JBoss Developer Studio with Red Hat JBoss BPM Suite. For further information about Kie Navigator, see chapter Kie Navigator of the Red Hat JBoss BPM Suite Getting Started Guide.

Part II. All About Rules

Chapter 5. Rule Algorithms

5.1. PHREAK Algorithm

The new PHREAK algorithm is evolved from the RETE algorithm. While RETE is considered eager and data oriented, PHREAK on the other hand follows lazy and goal oriented approach. The RETE algorithm does a lot of work during the insert, update and delete actions in order to find partial matches for all rules. In case of PHREAK, this partial matching of rule is delayed deliberately.

The eagerness of RETE algorithm during rule matching wastes a lot of time in case of large systems as it does result in a rule firing eventually. PHREAK algorithm addresses this issue and therefore is able to handle large data more efficiently.

PHREAK is derived from a number of algorithms including the following LEAPS, RETE/UL and Collection-Oriented Match algorithms.

In addition to the enhancements listed in the Rete00 algorithm, PHREAK algorithm adds the following set of enhancements:

  • Three layers of contextual memory: Node, Segment, and Rule memories.
  • Rule, segment, and node based linking.
  • Lazy (delayed) rule evaluation.
  • Stack-based evaluations with pause and resume.
  • Isolated rule evaluation.
  • Set-oriented propagations.

5.2. Rule Evaluation With PHREAK Algorithm

When the rule engine starts, all the rules are unlinked. At this stage, there is no rule evaluation. The insert, update, and delete actions are queued before entering the beta network. The rule engine uses a simple heuristic—​based on the rule most likely to result in firings—​to calculate and select the next rule for evaluation. This delays the evaluation and firing of the other rules. When a rule has all the right input values populated, it gets linked in—​a goal representing this rule is created and placed into a priority queue, which is ordered by salience. Each queue is associated with an AgendaGroup. The engine only evaluates rules for the active AgendaGroup by inspecting the queue and popping the goal for the rule with the highest salience. This means the work done shifts from the insert, update, delete phase to the fireAllRules phase. Only the rule for which the goal was created is evaluated, and other potential rule evaluations are delayed. While individual rules are evaluated, node sharing is still achieved through the process of segmentation.

Unlike the tuple-oriented RETE, the PHREAK propagation is collection-oriented. For the rule that is being evaluated, the engine accesses the first node and processes all queued insert, update, and delete actions. The results are added to a set, and the set is propagated to the child node. In the child node, all queued insert, update, and delete actions are processed, adding the results to the same set. Once finished, this set is propagated to the next child node and the same process repeats until it reaches the terminal node. This creates a batch process effect, which can provide performance advantages for certain rule constructs.

This linking and unlinking of rules happens through a layered bit mask system, based on network segmentation. When the rule network is built, segments are created for nodes that are shared by the same set of rules. A rule itself is made up from a path of segments. In case a rule does not share any node with any other rule, it becomes a single segment.

A bit-mask offset is assigned to each node in the segment. Furthermore, another bit mask is assigned to each segment in the rule’s path according to these rules:

  • If there is at least one input, the node’s bit is set to the on state.
  • If each node in a segment has its bit set to the on state, the segment’s bit is also set to the on state.
  • If any node’s bit is set to the off state, the segment is also set to the off state.
  • If each segment in the rule’s path is set to the on state, the rule is said to be linked in, and a goal is created to schedule the rule for evaluation.

The same bit-mask technique is used to also track dirty nodes, segments, and rules. This allows for an already linked rule to be scheduled for evaluation if it has been considered dirty since it was last evaluated. This ensures that no rule will ever evaluate partial matches.

As opposed to a single unit of memory in RETE, PHREAK has three levels of memory. This allows for much more contextual understanding during the evaluation of a rule.

PHREAK and Sequential Mode

The sequential mode is supported for the PHREAK algorithm: the modify and update rule statements are now allowed. Any rule that has not yet been evaluated will have access to data modified by the previous rules that used modify or update. This results in a more intuitive behavior of the sequential mode.

For example, consider the following rule:

rule "Rule1"
salience 100
when
   $fact : MyFact( field1 == false )
then
   System.out.println("Rule1 : " + $fact);
   $fact.setField1(true);
   update($fact);
end


rule "Rule2"
salience 95
when
    $fact : MyFact( field1 == true )
then
    System.out.println("Rule2 : " + $fact);
    update($fact);
end

When you insert a MyFact with the value field1==false:

  • The ReteOO algorithm executes only Rule1.
  • The PHREAK algorithm executes both Rule1 and Rule2.

For more information about the sequential mode, see Section 20.1.11.2.1, “Sequential Mode”.

5.3. Rete Algorithm

5.3.1. ReteOO

The Rete implementation used in BRMS is called ReteOO. It is an enhanced and optimized implementation of the Rete algorithm specifically for object-oriented systems. The Rete Algorithm has now been deprecated, and PHREAK is an enhancement of Rete. However, Rete can still be used by developers. This section describes how the Rete Algorithm functions.

Rete Root Node

When using ReteOO, the root node is where all objects enter the network. From there, it immediately goes to the ObjectTypeNode.

Figure 5.1. ReteNode

5944
ObjectTypeNode

The ObjectTypeNode helps to reduce the workload of the rules engine. If there are several objects, the rule engine wastes a lot of cycles trying to evaluate every node against every object. To make things efficient, the ObjectTypeNode is used so that the engine only passes objects to the nodes that match the object’s type. This way, if an application asserts a new Account, it does not propagate to the nodes for the Order object.

In Red Hat JBoss BRMS, an inserted object retrieves a list of valid ObjectTypesNodes through a lookup in a HashMap from the object’s class. If this list does not exist, it scans all the ObjectTypeNodes to find valid matches. It then caches these matched nodes in the list. This enables Red Hat JBoss BRMS to match against any class type that matches with an instanceof check.

AlphaNodes

AlphaNodes are used to evaluate literal conditions. When a rule has multiple literal conditions for a single object type, they are linked together. This means that if an application asserts an Account object, it must first satisfy the first literal condition before it can proceed to the next AlphaNode.

AlphaNodes are propagated using ObjectTypeNodes.

Hashing

Red Hat JBoss BRMS uses hashing to extend Rete by optimizing the propagation from ObjectTypeNode to AlphaNode. Each time an AlphaNode is added to an ObjectTypeNode, it adds the literal value as a key to the HashMap with the AlphaNode as the value. When a new instance enters the ObjectType node, rather than propagating to each AlphaNode, it retrieves the correct AlphaNode from the HashMap. This avoids unnecessary literal checks.

When facts enter from one side, you may do a hash lookup returning potentially valid candidates (referred to as indexing). At any point a valid join is found, the Tuple joins with the Object (referred to as a partial match) and then propagates to the next node.

BetaNodes

BetaNodes are used to compare two objects and their fields. The objects may be of the same or different types.

Alpha Memory and Beta Memory

Alpha memory refers to the left input on a BetaNode. In Red Hat JBoss BRMS, this input remembers all incoming objects.

Beta memory is the term used to refer to the right input of a BetaNode. It remembers all incoming tuples.

Lookups with BetaNodes

When facts enter from one side, you can do a hash lookup returning potentially valid candidates (referred to as indexing). If a valid join is found, the Tuple joins with the Object (referred to as a partial match) and then propagates to the next node.

LeftInputNodeAdapters

A LeftInputNodeAdapter takes an Object as an input and propagates a single Object Tuple.

Terminal Nodes

Terminal nodes are used to indicate when a single rule matches all its conditions (that is, the rule has a full match). A rule with an OR conditional disjunctive connective results in a sub-rule generation for each possible logical branch. Because of this, one rule can have multiple terminal nodes.

Node Sharing

Node sharing is used to prevent redundancy. As many rules repeat the same patterns, node sharing allows users to collapse those patterns so that the patterns need not be reevaluated for every single instance.

The following rules share the first pattern but not the last:

rule
when
  Cheese($cheddar : name == "cheddar")
  $person: Person(favouriteCheese == $cheddar)
then
  System.out.println($person.getName() + "likes cheddar");
end
rule
when
  Cheese($cheddar : name == "cheddar")
  $person : Person(favouriteCheese != $cheddar)
then
  System.out.println($person.getName() + " does not like cheddar");
end

The Rete network displayed below denotes that the alpha node is shared but the beta nodes are not. Each beta node has its own TerminalNode.

Figure 5.2. Node Sharing

5954

5.4. Switching Between PHREAK and ReteOO

It is possible to switch between PHREAK and ReteOO either by setting system properties, or in KieBase configuration. PHREAK is the default algorithm in both cases.

Switching to ReteOO requires the drools-reteoo-VERSION.jar file to be available on the class path. To include the file, add the following ReteOO Maven dependency to the pom.xml file in your project:

<dependency>
  <groupId>org.drools</groupId>
  <artifactId>drools-reteoo</artifactId>
  <version>DROOLS_VERSION</version>
</dependency>

For the supported Maven artifact version, see the Supported Component Versions section of the Red Hat JBoss BPM Suite Installation Guide.

Note

If the ReteOO Maven dependency is not specified in the pom.xml file in your project, the BRMS engine uses PHREAK instead and issues a warning.

Switching Between PHREAK and ReteOO in System Properties

To switch between the PHREAK and ReteOO algorithms, edit the drools.ruleEngine system property to contain one the following values:

drools.ruleEngine=phreak
drools.ruleEngine=reteoo

The default value is phreak.

Switching Between PHREAK and ReteOO in KieBaseConfiguration

When creating a KieBase, specify the rule engine algorithm in KieBaseConfiguration. See the following example:

import org.kie.api.KieBase;
import org.kie.api.KieBaseConfiguration;
import org.kie.api.KieServices;
import org.kie.api.runtime.KieContainer;
import org.kie.internal.builder.conf.RuleEngineOption;
...
KieServices kservices = KieServices.Factory.get();
KieBaseConfiguration kconfig = kieServices.Factory.get().newKieBaseConfiguration();

// You can either specify PHREAK (default):
kconfig.setOption(RuleEngineOption.PHREAK);

// or legacy ReteOO:
kconfig.setOption(RuleEngineOption.RETEOO);

// ... and then create a KieBase for the selected algorithm
// (getKieClasspathContainer() is just an example):
KieContainer container = kservices.getKieClasspathContainer();
KieBase kbase = container.newKieBase(kieBaseName, kconfig);

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see example Embedded Drools Engine Dependencies.

Additionally, if you want to switch to ReteOO, use the drools-reteoo dependency:

<dependency>
  <groupId>org.drools</groupId>
  <artifactId>drools-reteoo</artifactId>
  <version>6.5.0.Final-redhat-2</version>
</dependency>

For the current Maven artifact version, see chapter Supported Component Versions of the Red Hat JBoss BPM Suite Installation Guide.

Note

Switching to ReteOO requires drools-reteoo-(version).jar to exist on the classpath. If not present, the BRMS Engine reverts back to PHREAK and issues a warning. This applies for switching with KieBaseConfiguration and system properties.

Chapter 6. Getting Started with Rules and Facts

To create business rules, an appropriate fact model on which the business rules operate must be present. A fact is an instance of an application object represented as POJO. Rules that contain the business logic can then be authored by using either the Business Central web user interface or Red Hat JBoss Developer Studio.

The structure of a rule is as follows:

rule "NAME"
when
  RULE CONDITIONS
then
  RULE CONSEQUENCES
end

Conditions inside the when clause of a rule query for fact combinations that match the criteria. If such a fact combination is found, consequences specified in the then clause are executed. These actions can assert a fact, retract a fact, or update a fact within the rule engine. As a result, other rules can be fired as well.

Rules Processing Steps

  1. BRMS parses all .drl rule files into the knowledge base.
  2. Each fact is asserted into the working memory. As the facts are being asserted, BRMS uses the PHREAK or ReteOO algorithm to infer how the facts relate to the rules. After that, the working memory contains copies of the parsed rules and a reference to the facts.
  3. The fireAllRules() method is called. All rules and facts are evaluated by the rule engine and rule-facts pairs are created, based on which rules match against which set of facts.
  4. All the rule-facts combinations are queued within a data construct called an agenda.
  5. Finally, activations are processed one by one from the agenda, calling the rule consequences on the facts. Note that executing an activation can modify the contents of the agenda before the next activation is performed. The PHREAK and ReteOO algorithms handle such situations efficiently.

6.1. Creating and Executing Rules

In this section, procedures describing how to create and execute rules using plain Java, Maven, Red Hat JBoss Developer Studio, and Business Central in Red Hat JBoss BPM Suite are provided.

6.1.1. Creating and Executing Rules Using Plain Java

  1. Create a fact model.

    Create a Plain old Java object (POJO) on which a rule will operate. In this example, a Person.java file in a directory my-project is created. The Person class contains getter and setter methods to set and retrieve the first name, last name, hourly rate, and the wage of a person:

    import org.kie.api.KieServices;
    import org.kie.api.runtime.KieContainer;
    import org.kie.api.runtime.KieSession;
    
      public class Person {
        private String firstName;
        private String lastName;
        private Integer hourlyRate;
        private Integer wage;
    
        public String getFirstName() {
          return firstName;
        }
    
        public void setFirstName(String firstName) {
          this.firstName = firstName;
        }
    
        public String getLastName() {
          return lastName;
        }
    
        public void setLastName(String lastName) {
          this.lastName = lastName;
        }
    
        public Integer getHourlyRate() {
          return hourlyRate;
        }
    
        public void setHourlyRate(Integer hourlyRate) {
          this.hourlyRate = hourlyRate;
        }
    
        public Integer getWage(){
          return wage;
        }
    
        public void setWage(Integer wage){
          this.wage = wage;
        }
      }
  2. Create a rule.

    Create a rule file in the .drl format under the my-project directory. The following Person.drl rule calculates the wage and hourly rate values and displays a message based on the result afterwards.

    dialect "java"
    
    rule "Wage"
      when
        Person(hourlyRate * wage > 100)
        Person(name : firstName, surname : lastName)
      then
        System.out.println("Hello" + " " + name + " " + surname + "!");
        System.out.println("You are rich!");
    end
  3. Create a main class.

    Create a main class and save it to the same directory as the POJO created earlier. The main class will load the knowledge base and fire rules. In the following example, a main class DroolsTest.java is created.

    In the main class:

    1. Add the following import statements to import KIE services, a KIE container, and a KIE session:

      import org.kie.api.KieServices;
      import org.kie.api.runtime.KieContainer;
      import org.kie.api.runtime.KieSession;
    2. Load the knowledge base, insert facts, and fire the rule from the main() method which passes the fact model to the rule:

      public class DroolsTest {
        public static final void main(String[] args) {
          try {
            // Load the knowledge base:
            KieServices ks = KieServices.Factory.get();
            KieContainer kContainer = ks.getKieClasspathContainer();
            KieSession kSession = kContainer.newKieSession();
      
            // Go!
            Person p = new Person();
            p.setWage(12);
            p.setFirstName("Tom");
            p.setLastName("Summers");
            p.setHourlyRate(10);
      
            kSession.insert(p);
            kSession.fireAllRules();
          }
      
          catch (Throwable t) {
            t.printStackTrace();
          }
        }
      }
  4. Download the Red Hat JBoss BRMS 6.4 Core Engine ZIP file from the Red Hat Customer Portal and extract it under my-project/BRMS-engine-jars/.
  5. In the my-project/META-INF directory, create a kmodule.xml metadata file with the following content:

    <?xml version="1.0" encoding="UTF-8"?>
    <kmodule xmlns="http://www.drools.org/xsd/kmodule">
    </kmodule>
  6. Build the example.

    To compile and build your Java files, navigate to the my-project directory on the command line and run the following command:

    javac -classpath "./BRMS-engine-jars/*:." DroolsTest.java
  7. Run the example.

    If there are no compilation errors, run the following command to execute the rule:

    java -classpath "./BRMS-engine-jars/*:." DroolsTest

    The expected output looks similar to the following:

    Hello Tom Summers!
    You are rich!

6.1.2. Creating and Executing Rules Using Maven

  1. Create a basic Maven archetype.

    Navigate to a directory where you want to create a Maven archetype and run the following command:

    mvn archetype:generate -DgroupId=com.sample.app -DartifactId=my-app -DarchetypeArtifactId=maven-archetype-quickstart -DinteractiveMode=false

    This creates a directory my-app with the following structure:

    my-app
    |-- pom.xml
    `-- src
        |-- main
        |   `-- java
        |       `-- com
        |           `-- mycompany
        |               `-- app
        |                   `-- App.java
        `-- test
            `-- java
                `-- com
                    `-- mycompany
                        `-- app
                            `-- AppTest.java

    The my-app directory contains:

    • A src/main directory for storing the application’s sources.
    • A src/test directory for storing the test sources.
    • A pom.xml file with the project’s configuration.
  2. Create a fact model.

    A fact model is a POJO, based on which a rule will operate. Create a Person.java file under the my-app/src/main/java/com/mycompany/app directory. The Person class contains getter and setter methods to set and retrieve the first name, last name, hourly rate, and the wage of a person.

    package com.mycompany.app;
    
      public class Person {
    
        private String firstName;
        private String lastName;
        private Integer hourlyRate;
        private Integer wage;
    
        public String getFirstName() {
          return firstName;
        }
    
        public void setFirstName(String firstName) {
          this.firstName = firstName;
        }
    
        public String getLastName() {
          return lastName;
        }
    
        public void setLastName(String lastName) {
          this.lastName = lastName;
        }
    
        public Integer getHourlyRate() {
          return hourlyRate;
        }
    
        public void setHourlyRate(Integer hourlyRate) {
          this.hourlyRate = hourlyRate;
        }
    
        public Integer getWage(){
          return wage;
        }
    
        public void setWage(Integer wage){
          this.wage = wage;
        }
      }
  3. Create a rule.

    Create a rule file in the .drl format under the my-app/src/main/resources/rules directory. See the following example with a simple rule Person.drl which imports the Person class:

    package com.mycompany.app;
    import com.mycompany.app.Person;
    
    dialect "java"
    
    rule "Wage"
      when
        Person(hourlyRate * wage > 100)
        Person(name : firstName, surname : lastName)
      then
        System.out.println("Hello " + name + " " + surname + "!");
        System.out.println("You are rich!");
    end

    The rule above calculates the wage and hourly rate values and displays a message based on the result afterwards.

  4. In the my-app/src/main/resources/META-INF directory, create a metadata file kmodule.xml with the following content:

    <?xml version="1.0" encoding="UTF-8"?>
    <kmodule xmlns="http://www.drools.org/xsd/kmodule">
    </kmodule>
  5. Set project dependencies.

    Specify the libraries your application requires in the my-app/pom.xml configuration file. Provide the Red Hat JBoss BRMS dependencies as well as the group ID, artifact ID, and version (GAV) of your application as shown below:

    <?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>com.mycompany.app</groupId>
    <artifactId>my-app</artifactId>
    <version>1.0.0</version>
    <repositories>
      <repository>
        <id>jboss-ga-repository</id>
        <url>http://maven.repository.redhat.com/ga/</url>
      </repository>
    </repositories>
    <dependencies>
      <dependency>
        <groupId>org.drools</groupId>
        <artifactId>drools-compiler</artifactId>
        <version>VERSION</version>
      </dependency>
      <dependency>
        <groupId>org.kie</groupId>
        <artifactId>kie-api</artifactId>
        <version>VERSION</version>
      </dependency>
      <dependency>
        <groupId>junit</groupId>
        <artifactId>junit</artifactId>
        <version>4.11</version>
        <scope>test</scope>
      </dependency>
    </dependencies>
    </project>

    For the supported Maven artifact version, see section Supported Component Versions of the Red Hat JBoss BPM Suite Installation Guide.

  6. Test the example.

    Use the testApp method in my-app/src/test/java/com/mycompany/app/AppTest.java to test the rule. The AppTest.java file is created by Maven by default.

    In the AppTest.java file:

    1. Add the following import statements to import KIE services, a KIE container, and a KIE session:

      import org.kie.api.KieServices;
      import org.kie.api.runtime.KieContainer;
      import org.kie.api.runtime.KieSession;
    2. Load the knowledge base, insert facts, and fire the rule from the testApp() method which passes the fact model to the rule:

      public void testApp() {
      
        // Load the knowledge base:
        KieServices ks = KieServices.Factory.get();
        KieContainer kContainer = ks.getKieClasspathContainer();
        KieSession kSession = kContainer.newKieSession();
      
        // Set up the fact model:
        Person p = new Person();
        p.setWage(12);
        p.setFirstName("Tom");
        p.setLastName("Summers");
        p.setHourlyRate(10);
      
        // Insert the person into the session:
        kSession.insert(p);
      
        // Fire all rules:
        kSession.fireAllRules();
      }
  7. Build the example.

    On the command line, navigate to the my-app directory and run the following command:

    mvn clean install

    Note that executing this command for the first time may take a while.

    The expected output looks similar to the following:

    Hello Tom Summers!
    You are rich!
    Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 1.194 sec
    
    Results :
    
    Tests run: 1, Failures: 0, Errors: 0, Skipped: 0
    
    [INFO]
    ...
    [INFO] --------------------------------------------------------------
    [INFO] BUILD SUCCESS
    [INFO] --------------------------------------------------------------
    [INFO] Total time: 6.393 s
    ...
    [INFO] --------------------------------------------------------------

6.1.3. Creating and Executing Rules Using Red Hat JBoss Developer Studio

Note

Make sure you have Red Hat JBoss Developer Studio properly set before proceeding further. See chapter Red Hat JBoss Developer Studio of Red Hat JBoss BPM Suite Installation Guide for more information.

  1. Create a BRMS project.

    To create a BRMS project in Red Hat JBoss Developer Studio:

    1. Start Red Hat JBoss Developer Studio and click FileNewProject.
    2. In the New Project dialog window that opens, select DroolsDrools Project and click Next.
    3. Click on the second icon to create a project and populate it with some example files to help you get started quickly. Click Next.
    4. Enter a name of the project a select the Maven radio button as the project building option. Specify the GAV values which form the project’s fully qualified name, for example:

      • Group ID: com.mycompany.app
      • Artifact ID: my-app
      • Version: 1.0.0
    5. Click Finish.

    This configuration sets up a basic project structure, class path, and sample rules. The project structure is as follows:

    My-Project
     `-- src/main/java
        | `-- com.sample
        |    `-- DecisionTable.java
        |    `-- DroolsTest.java
        |    `-- ProcessTest.java
        |
     `-- src/main/resources
        | `-- dtables
        |    `-- Sample.xls
        | `-- process
        |    `-- sample.bpmn
        | `-- rules
        |    `-- Sample.drl
        | `-- META-INF
        |
     `-- JRE System Library
        |
     `-- Maven Dependencies
        |
     `-- Drools Library
        |
     `-- src
        |
     `-- target
        |
     `-- pom.xml

    Notice the following:

    • A Sample.drl rule file in the src/main/resources directory, containing an example Hello World and GoodBye rules.
    • A DroolsTest.java file under the src/main/java directory in the com.sample package. The DroolsTest class can be used to execute rules.
    • The Drools Library directory which acts as a custom class path containing JAR files necessary for execution.
  2. Create a fact model.

    The DroolsTest.java file contains a sample POJO Message with getter and setter methods. You can edit this class or create a different POJO. In this example, a class Person containing methods to set and retrieve the first name, last name, hourly rate, and wage of a person is used.

    public static class Person {
    
      private String firstName;
      private String lastName;
      private Integer hourlyRate;
      private Integer wage;
    
      public String getFirstName() {
        return firstName;
      }
    
      public void setFirstName(String firstName) {
        this.firstName = firstName;
      }
    
      public String getLastName() {
        return lastName;
      }
    
      public void setLastName(String lastName) {
        this.lastName = lastName;
      }
    
      public Integer getHourlyRate() {
        return hourlyRate;
      }
    
      public void setHourlyRate(Integer hourlyRate) {
        this.hourlyRate = hourlyRate;
      }
    
      public Integer getWage(){
        return wage;
      }
    
      public void setWage(Integer wage){
        this.wage = wage;
      }
    }
  3. Update the main() method.

    The DroolsTest.java file contains a main() method that loads the knowledge base, inserts facts, and fires rules. Update the method to pass the object Person to a rule:

    public static final void main(String[] args) {
      try {
        // Load the knowledge base:
        KieServices ks = KieServices.Factory.get();
        KieContainer kContainer = ks.getKieClasspathContainer();
        KieSession kSession = kContainer.newKieSession("ksession-rules");
    
        // Go!
        Person p = new Person();
        p.setWage(12);
        p.setFirstName("Tom");
        p.setLastName("Summers");
        p.setHourlyRate(10);
    
        kSession.insert(p);
        kSession.fireAllRules();
      }
    
      catch (Throwable t) {
        t.printStackTrace();
      }
    }

    To load the knowledge base, get a KieServices instance and a class-path-based KieContainer and build the KieSession with the KieContainer. In the example above, a session ksession-rules matching the one defined in kmodule.xml file is passed.

  4. Create a rule.

    The rule file Sample.drl contains an example of two rules. Edit this file or create a new one. In your rule file:

    1. Specify the package name:

      package com.sample
    2. Import facts:

      import com.sample.DroolsTest.Person;
    3. Write the rule:

      dialect "java"
      
      rule "Wage"
        when
          Person(hourlyRate * wage > 100)
          Person(name : firstName, surname : lastName)
        then
          System.out.println("Hello" + " " + name + " " + surname + "!");
          System.out.println("You are rich!");
      end
  5. Test the rule.

    Right-click the DroolsTest.java file and select Run AsJava Application.

    The expected output looks similar to the following:

    Hello Tom Summers!
    You are rich!

6.1.4. Creating and Executing Rules Using Business Central

Note

Make sure you have Red Hat JBoss BPM Suite successfully installed before proceeding further.

  1. Start the server and log in to Business Central. For more information how to do so, see sections Starting Server and Logging into Business Central of Red Hat JBoss BPM Suite Installation Guide.
  2. Create a repository structure and a project.

    1. In Business Central, click AuthoringAdministration.
    2. Click Organizational UnitsManage Organizational Units.
    3. In the displayed Organizational Unit Manager, click Add.
    4. In the Add New Organizational Unit dialog window, define the unit properties. For example:

      • Name: EmployeeWage
      • Owner: Employee
    5. Click Ok.
    6. Click RepositoriesNew repository.
    7. In the New Repository dialog window, define the repository properties. For example:

      • Repository Name: EmployeeRepo
      • In Organizational Unit: EmployeeWage
    8. Click Finish.
    9. In the main menu, click AuthoringProject Authoring.
    10. In Project Explorer, navigate to the EmployeeWage organizational unit and the EmployeeRepo repository.
    11. Click New ItemProject.
    12. In the New Project dialog window, enter a name of the project, for example MyProject, and specify project’s Maven properties. For example:

      • Group ID: org.bpms
      • Artifact ID: MyProject
      • Version: 1.0.0
    13. Click Finish.
  3. Create a fact model.

    1. Click New ItemData Object.
    2. In the Create new Data Object dialog window, enter the object’s name and specify a package. For example:

      • Data Object: Person
      • Package: org.bpms.myproject
    3. Click Ok.
    4. In the Editor than opens, click Add field and create four fields with the following values by clicking Create and continue:

      • Id: firstName, Type: String
      • Id: lastName, Type: String
      • Id: hourlyRate, Type: Integer
      • Id: wage, Type: Integer
    5. Save the project.
  4. Create a rule.

    1. Click New ItemDRL file.
    2. In the Create new DRL file dialog window, enter a name of the rule and specify a package. For example:

      • DRL file: MyRule
      • Package: org.bpms.myproject
    3. Click Ok.
    4. Paste the definition of a rule shown below into the DRL Editor or create your own rule.

      package org.bpms.myproject;
      
      rule "MyRule"
      ruleflow-group "MyProjectGroup"
        when
          Person(hourlyRate * wage > 100)
          Person(name : firstName, surname : lastName)
        then
          System.out.println("Hello" + " " + name + " " + surname + "!");
          System.out.println("You are rich!");
      end
    5. Click Save.
  5. Create a business process with a business rule task.

    1. Click New ItemBusiness Process.
    2. In the Create new Business Process dialog window, enter a name of the business process and specify a package. For example:

      • Business Process: MyProcess
      • Package: org.bpms.myproject
    3. Click Ok. The Business Process Editor opens with a Start Event element on the canvas.
    4. Expand the Object Library palette on the left and drag and drop a Business Rule task (TasksBusiness Rule) on the canvas.
    5. Click on an empty space on the canvas and open the Properties panel on the right. Click on the Value text field of the Variable Definitions property. Click on the arrow that appears on the right to open the Editor for Variable Definitions dialog window.
    6. Click Add Variable and define the following variable:

      • Name: person
      • Defined Types: Person [org.bpms.myproject]
    7. Click Ok.
    8. Click on the Business Rule task on the canvas and in the Properties panel on the right, set the Name of the task, for example My_Rule.
    9. Click on the Value text field of the Ruleflow Group property. Click on the arrow that appears on the right to open the Editor for RuleFlow Groups dialog window. Select MyProjectGroup and click Save.
    10. Click on the Value text field of the Assignments property. Click on the arrow that appears on the right to open the My_Rule Data I/O dialog window and click Add next to the Data Inputs and Assignments option to add the following:

      • Name: Person
      • Data Type: Person [org.bpms.myproject]
      • Source: person
    11. Click Save.

      You have now successfully created an object that maps to the variables you set before in your fact model. Your business process passes this object as an input to the rule.

    12. Add an End Event and connect all events on the canvas to complete the process.
    13. Click development guide 6565 and select Generate all Forms.
    14. Save the process.
  6. Build and deploy the rule.

    1. Click Open Project Editor on the left, change the version of the project and click BuildBuild & Deploy.

      A notification appears in the upper part of the screen informing you that the project has been built successfully.

    2. Click Process ManagementProcess Definitions.
    3. Click Start next to the newly built process.
    4. In the opened MyProcess dialog window, provide the following values of the variables defined in your fact model and click Submit:

      • firstName: Tom
      • lastName: Summers
      • hourlyRate: 12
      • wage: 10

      As these values satisfy the rule condition, the expected output looks similar to the following:

      16:19:58,479 INFO  [org.jbpm.kie.services.impl.store.DeploymentSynchronizer] (http-/127.0.0.1:8080-1) Deployment unit org.bpms:MyProject:1.0 stored successfully
      16:26:56,119 INFO  [stdout] (http-/127.0.0.1:8080-5) Hello Tom Summers!
      16:26:56,119 INFO  [stdout] (http-/127.0.0.1:8080-5) You are rich!

6.2. Execution of Rules

6.2.1. Agenda

The Agenda is a Rete feature. During actions on the WorkingMemory, rules may become fully matched and eligible for execution. A single Working Memory Action can result in multiple eligible rules. When a rule is fully matched an Activation is created, referencing the rule and the matched facts, and placed onto the Agenda. The Agenda controls the execution order of these Activations using a Conflict Resolution strategy.

6.2.2. Agenda Processing

The engine cycles repeatedly through two phases:

  1. Working Memory Actions. This is where most of the work takes place, either in the Consequence (the RHS itself) or the main Java application process. Once the Consequence has finished or the main Java application process calls fireAllRules() the engine switches to the Agenda Evaluation phase.
  2. Agenda Evaluation. This attempts to select a rule to fire. If no rule is found it exits, otherwise it fires the found rule, switching the phase back to Working Memory Actions.

The process repeats until the agenda is clear, in which case control returns to the calling application. When Working Memory Actions are taking place, no rules are being fired.

6.2.3. Conflict Resolution

Conflict resolution is required when there are multiple rules on the agenda. As firing a rule may have side effects on the working memory, the rule engine needs to know in what order the rules should fire (for instance, firing ruleA may cause ruleB to be removed from the agenda).

6.2.4. AgendaGroup

Agenda groups are a way to partition rules on the agenda. At any one time, only one group has "focus" which means that activations for rules in that group only will take effect. You can also have rules with "auto focus" which means that the focus is taken for its agenda group when that rule’s conditions are true.

Agenda groups are known as "modules" in CLIPS terminology. Agenda groups provide a way to create a "flow" between grouped rules. You can switch the group which has focus either from within the rule engine, or via the API. If your rules have a clear need for multiple "phases" or "sequences" of processing, consider using agenda-groups for this purpose.

6.2.5. setFocus()

Each time setFocus() is called it pushes the specified Agenda Group onto a stack. When the focus group is empty it is popped from the stack and the focus group that is now on top evaluates. An Agenda Group can appear in multiple locations on the stack. The default Agenda Group is "MAIN", with all rules which do not specify an Agenda Group being in this group. It is also always the first group on the stack, given focus initially, by default.

The setFocus() method call looks like follows:

ksession.getAgenda().getAgendaGroup("Group A").setFocus();

6.2.6. ActivationGroup

An activation group is a set of rules bound together by the same activation-group rule attribute. In this group only one rule can fire, and after that rule has fired all the other rules are cancelled from the agenda. The clear() method can be called at any time, which cancels all of the activations before one has had a chance to fire.

An activation group looks like follows:

ksession.getAgenda().getActivationGroup("Group B").clear();

6.3. Inference

6.3.1. The Inference Engine

The inference engine is the part of the Red Hat JBoss BRMS engine which matches production facts and data to rules. It is often called the brain of a Production Rules System as it is able to scale to a large number of rules and facts. It makes inferences based on its existing knowledge and performs the actions based on what it infers from the information.

The rules are stored in the production memory and the facts that the inference engine matches against, are stored in the working memory. Facts are asserted into the working memory where they may get modified or retracted. A system with a large number of rules and facts may result in many rules being true for the same fact assertion. Such conflicting rules are managed using a conflict resolution strategy. This strategy determines the order of execution of the rules by assigning a priority level to each rule.

Inferences can be forward chaining or backward chaining. In a forward chaining inference mechanism, when some data gets inserted into the working memory, the related rules are triggered and if the data satisfies the rule conditions, corresponding actions are taken. These actions may insert new data into the working memory and therefore trigger more rules and so on. Thus, the forward chaining inference is data driven. On the contrary, the backward chaining inference is goal driven. In this case, the system looks for a particular goal, which the engine tries to satisfy. If it cannot do so it searches for sub-goals, that is, conclusions that will complete part of the current goal. It continues this process until either the initial conclusion is satisfied or there are no more unsatisfied sub-goals. Correct use of inference can create agile and less error prone business rules, which are easier to maintain.

6.3.2. Inference Example

The following example illustrates how an inference is made about whether a person is eligible to have a bus pass based on the rule conditions. Here is a rule that provides the age policy for a person to hold a bus pass:

rule "Infer Adult"
when
  $p : Person(age >= 18)
then
  insert(new IsAdult($p))
end

Based on this rule, a rule engine infers whether a person is an adult or a child and act on it. Every person who is 18 years or above will have an instance of IsAdult inserted for them in the working memory. This inferred relation of age and bus pass can be inferred in any rule, such as:

$p : Person()
IsAdult(person == $p)

6.4. Truth Maintenance

The inference engine is responsible for logical decisions on assertions and retractions of facts. After regular insertions, facts are generally retracted explicitly. However, in case of logical assertions, the facts that were asserted are automatically retracted when the conditions that asserted the facts in the first place are no longer true. In other words, the facts are retracted when there is no single condition that supports the logical assertion.

The inference engine uses a mechanism of truth maintenance to efficiently handle the inferred information from rules. A Truth Maintenance System (TMS) refers to an inference engine’s ability to enforce truthfulness when applying rules. It provides justified reasoning for each and every action taken by the inference engine and validates the conclusions of the engine. If the inference engine asserts data as a result of firing a rule, the engine uses the truth maintenance to justify the assertion.

A Truth Maintenance System also helps to identify inconsistencies and handle contradictions. For example, if there are two rules to be fired, each resulting in a contradictory action, the Truth Maintenance System enables the inference engine to decide its actions based on assumptions and derivations of previously calculated conclusions.

The usual insertion of facts, referred to as stated insertions, are straightforward and do not need a reasoning. However, the logical assertions need to be justified. If the inference engine tries to logically insert an object when there is an equal stated object, it fails as it cannot justify a stated fact. If the inference engine tries for a stated insertion of an existing equal object that is justified, then it overrides the justified insertion, and removes the justifications.

The following flowcharts illustrate the lifecycle of stated and logical insertions:

Figure 6.1. Stated Assertion

7165

Figure 6.2. Logical Assertion

7166
Important

For the Truth Maintenance System and logical assertions to work, your fact objects (POJOs) must override the equals and hashCode methods from java.lang.Object as per the Java standard. Two objects are equal if and only if their equals methods return true for each other and if their hashCode methods return the same values. For more information, see the Java API documentation.

The following example illustrates how the Truth Maintenance System helps in the inference mechanism. The rules in the example provide information on basic policies on issuing child and adult bus passes.

rule "Issue Child Bus Pass"
when
  $p : Person(age < 16)
then
  insert(new ChildBusPass($p));
end

rule "Issue Adult Bus Pass"
when
  $p : Person(age >= 16)
then
  insert(new AdultBusPass($p));
end

These rules are monolithic and provide poor separation of concerns. The truth maintenance mechanism in an inference engine makes the system become more robust and have a clear separation of concerns. For example, the following rule uses logical insertion of facts, which makes the fact dependent on the truth of the when clause:

rule "Infer Child"
when
  $p : Person(age < 16)
then
  insertLogical(new IsChild($p))
end

rule "Infer Adult"
when
  $p : Person(age >= 16)
then
  insertLogical(new IsAdult($p))
end

When the condition in the rule is false, the fact is automatically retracted. This works particularly well as the two rules are mutually exclusive. In the above rules, if the person is under 16 years, it inserts an IsChild fact. Once the person is 16 years or above, the IsChild fact is automatically retracted and the IsAdult fact inserted.

Now the two rules for issuing child and adult bus pass can logically insert the ChildBusPass and AdultBusPass facts, as the Truth Maintenance System supports chaining of logical insertions for a cascading set of retracts.

rule "Issue Child Bus Pass"
when
  $p : Person()
    IsChild(person == $p)
then
  insertLogical(new ChildBusPass($p));
end

rule "Issue Adult Bus Pass"
when
  $p : Person(age >= 16)
    IsAdult(person =$p)
then
  insertLogical(new AdultBusPass($p));
end

When a person turns 16 years old, the IsChild fact as well as the person’s ChildBusPass fact is retracted. To these set of conditions, you can relate another rule which states that a person must return the child pass after turning 16 years old. When the Truth Maintenance System automatically retracts the ChildBusPass object, this rule triggers and sends a request to the person:

rule "Return ChildBusPass Request"
when
  $p : Person()
    not(ChildBusPass(person == $p))
then
  requestChildBusPass($p);
end

6.5. Using Decision Tables in Spreadsheets

Decision tables are a way of representing conditional logic in a precise manner, and are well suited to business-level rules.

Red Hat JBoss BRMS supports managing rules in a spreadsheet format. Since two formats are currently supported, XLS and CSV, a variety of spreadsheet programs, such as Microsoft Excel, Apache OpenOffice Calc, and LibreOffice Calc, can be utilized.

Note

Use the XLS format if you are building and uploading decision tables using Business Central. Business Central does not support decision tables in the CSV format.

6.5.1. OpenOffice Example

Figure 6.3. OpenOffice Screenshot

1248

In the above examples, the technical aspects of the decision table have been collapsed away (using a standard spreadsheet feature).

The rules start from row 17, with each row resulting in a rule. The conditions are in columns C, D, E, and the actions are off-screen. The values' meanings are indicated by the headers in Row 16. Column B is just a description.

Note

Although the decision tables look like they process top down, this is not necessarily the case. Ideally, rules are authored without regard for the order of rows. This makes maintenance easier, as rows will not need to be shifted around all the time.

6.5.2. Rules and Spreadsheets

Rules Inserted into Rows
As each row is a rule, the same principles apply as with written code. As the rule engine processes the facts, any rules that match may fire.
Agendas
It is possible to clear the agenda when a rule fires and simulate a very simple decision table where only the first match effects an action.
Multiple Tables
You can have multiple tables on one spreadsheet. This way, rules can be grouped where they share common templates, but are still all combined into one rule package.

6.5.3. The RuleTable Keyword

When using decision tables, the spreadsheet searches for the RuleTable keyword to indicate the start of a rule table (both the starting row and column).

Important

Keywords should all be in the same column.

6.5.4. The RuleSet Keyword

The RuleSet keyword indicates the name to be used in the rule package that will encompass all the rules. This name is optional, using a default, but it must have the RuleSet keyword in the cell immediately to the right.

6.5.5. Data-Defining Cells

There are two types of rectangular areas defining data that is used for generating a DRL file. One, marked by a cell labelled RuleSet, defines all DRL items except rules. The other one may occur repeatedly and is to the right and below a cell whose contents begin with RuleTable. These areas represent the actual decision tables, each area resulting in a set of rules of similar structure.

A Rule Set area may contain cell pairs, one below the RuleSet cell and containing a keyword designating the kind of value contained in the other one that follows in the same row.

6.5.6. Rule Table Columns

The columns of a Rule Table area define patterns and constraints for the left hand sides of the rules derived from it, actions for the consequences of the rules, and the values of individual rule attributes. A Rule Table area should contain one or more columns, both for conditions and actions, and an arbitrary selection of columns for rule attributes, at most one column for each of these. The first four rows following the row with the cell marked with RuleTable are earmarked as header area, mostly used for the definition of code to construct the rules. It is any additional row below these four header rows that spawns another rule, with its data providing for variations in the code defined in the Rule Table header.

Note

All keywords are case insensitive.

Only the first worksheet is examined for decision tables.

6.5.7. Rule Set Entries

Entries in a Rule Set area may define DRL constructs (except rules), and specify rule attributes. While entries for constructs may be used repeatedly, each rule attribute may be given at most once, and it applies to all rules unless it is overruled by the same attribute being defined within the Rule Table area.

Entries must be given in a vertically stacked sequence of cell pairs. The first one contains a keyword and the one to its right the value. This sequence of cell pairs may be interrupted by blank rows or even a Rule Table, as long as the column marked by RuleSet is upheld as the one containing the keyword.

Table 6.1. Entries in the Rule Set area
KeywordValueUsage

RuleSet

The package name for the generated DRL file. Optional, the default is rule_table.

Must be the first entry.

Sequential

true or false. If true, then salience is used to ensure that rules fire from the top down.

Optional, at most once. If omitted, no firing order is imposed.

EscapeQuotes

true or false. If true, then quotation marks are escaped so that they appear literally in the DRL.

Optional, at most once. If omitted, quotation marks are escaped.

Import

A comma-separated list of Java classes to import.

Optional, may be used repeatedly.

Variables

Declarations of DRL globals, for example a type followed by a variable name. Multiple global definitions must be separated with a comma.

Optional, may be used repeatedly.

Functions

One or more function definitions, according to DRL syntax.

Optional, may be used repeatedly.

Queries

One or more query definitions, according to DRL syntax.

Optional, may be used repeatedly.

Declare

One or more declarative types, according to DRL syntax.

Optional, may be used repeatedly.

6.5.8. Rule Attribute Entries in Rule Set Area

Important

Rule attributes specified in a Rule Set area will affect all rule assets in the same package (not only in the spreadsheet). Unless you are sure that the spreadsheet is the only one rule asset in the package, the recommendation is to specify rule attributes not in a Rule Set area but in a Rule Table columns for each rule instead.

Table 6.2. Rule Attribute Entries in Rule Set Area
KeywordInitialValue

PRIORITY

P

An integer defining the "salience" value for the rule. Overridden by the "Sequential" flag.

DURATION

D

A long integer value defining the "duration" value for the rule.

TIMER

T

A timer definition. See Section 8.10.2, “Timers”.

CALENDARS

E

A calendars definition. See Section 8.10.4, “Calendars”.

NO-LOOP

U

A Boolean value. true inhibits looping of rules due to changes made by its consequence.

LOCK-ON-ACTIVE

L

A Boolean value. true inhibits additional activations of all rules with this flag set within the same ruleflow or agenda group.

AUTO-FOCUS

F

A Boolean value. true for a rule within an agenda group causes activations of the rule to automatically give the focus to the group.

ACTIVATION-GROUP

X

A string identifying an activation (or XOR) group. Only one rule within an activation group will fire, for example the first one to fire cancels any existing activations of other rules within the same group.

AGENDA-GROUP

G

A string identifying an agenda group, which has to be activated by giving it the "focus", which is one way of controlling the flow between groups of rules.

RULEFLOW-GROUP

R

A string identifying a rule-flow group.

DATE-EFFECTIVE

V

A string containing a date and time definition. A rule can only activate if the current date and time is after DATE-EFFECTIVE attribute.

DATE-EXPIRES

Z

A string containing a date and time definition. A rule cannot activate if the current date and time is after the DATE-EXPIRES attribute.

6.5.9. The RuleTable Cell

All Rule Tables begin with a cell containing RuleTable, optionally followed by a string within the same cell. The string is used as the initial part of the name for all rules derived from this Rule Table, with the row number appended for distinction. This automatic naming can be overridden by using a NAME column. All other cells defining rules of this Rule Table are below and to the right of this cell.

6.5.10. Column Types

The next row after the RuleTable cell defines the column type. Each column results in a part of the condition or the consequence, or provides some rule attribute, the rule name or a comment. Each attribute column may be used at most once.

Table 6.3. Column Headers in the Rule Table
KeywordInitialValueUsage

NAME

N

Provides the name for the rule generated from that row. The default is constructed from the text following the RuleTable tag and the row number.

At most one column.

DESCRIPTION

I

A text, resulting in a comment within the generated rule.

At most one column.

CONDITION

C

Code snippet and interpolated values for constructing a constraint within a pattern in a condition.

At least one per rule table.

ACTION

A

Code snippet and interpolated values for constructing an action for the consequence of the rule.

At least one per rule table.

METADATA

@

Code snippet and interpolated values for constructing a metadata entry for the rule.

Optional, any number of columns.

6.5.11. Conditional Elements

Given a column headed CONDITION, the cells in successive lines result in a conditional element.

  • Text in the first cell below CONDITION develops into a pattern for the rule condition, with the snippet in the next line becoming a constraint. If the cell is merged with one or more neighbours, a single pattern with multiple constraints is formed: all constraints are combined into a parenthesized list and appended to the text in this cell. The cell may be left blank, which means that the code snippet in the next row must result in a valid conditional element on its own.

    To include a pattern without constraints, you can write the pattern in front of the text for another pattern.

    The pattern may be written with or without an empty pair of parentheses. A "from" clause may be appended to the pattern.

    If the pattern ends with "eval", code snippets are supposed to produce boolean expressions for inclusion into a pair of parentheses after "eval".

  • Text in the second cell below CONDITION is processed in two steps.

    • The code snippet in this cell is modified by interpolating values from cells farther down in the column. If you want to create a constraint consisting of a comparison using "==" with the value from the cells below, the field selector alone is sufficient. Any other comparison operator must be specified as the last item within the snippet, and the value from the cells below is appended. For all other constraint forms, you must mark the position for including the contents of a cell with the symbol $param. Multiple insertions are possible by using the symbols $1, $2, etc., and a comma-separated list of values in the cells below.

      A text according to the pattern forall(DELIMITER){SNIPPET} is expanded by repeating the SNIPPET once for each of the values of the comma-separated list of values in each of the cells below, inserting the value in place of the symbol $ and by joining these expansions by the given DELIMITER. Note that the forall construct may be surrounded by other text.

    • If the cell in the preceding row is not empty, the completed code snippet is added to the conditional element from that cell. A pair of parentheses is provided automatically, as well as a separating comma if multiple constraints are added to a pattern in a merged cell.

      If the cell above is empty, the interpolated result is used as is.

  • Text in the third cell below CONDITION is for documentation only. It should be used to indicate the column’s purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the conditional element or constraint for this rule.

6.5.12. Action Statements

Given a column headed ACTION, the cells in successive lines result in an action statement:

  • Text in the first cell below ACTION is optional. If present, it is interpreted as an object reference.
  • Text in the second cell below ACTION is processed in two steps.

    • The code snippet in this cell is modified by interpolating values from cells farther down in the column. For a singular insertion, mark the position for including the contents of a cell with the symbol $param. Multiple insertions are possible by using the symbols $1, $2, etc., and a comma-separated list of values in the cells below.

      A method call without interpolation can be achieved by a text without any marker symbols. In this case, use any non-blank entry in a row below to include the statement.

      The forall construct is available here, too.

    • If the first cell is not empty, its text, followed by a period, the text in the second cell and a terminating semicolon are stringed together, resulting in a method call which is added as an action statement for the consequence.

      If the cell above is empty, the interpolated result is used as is.

  • Text in the third cell below ACTION is for documentation only. It should be used to indicate the column’s purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the action statement for this rule.
Note

Using $1 instead of $param will fail if the replacement text contains a comma.

6.5.13. Metadata Statements

Given a column headed METADATA, the cells in successive lines result in a metadata annotation for the generated rules:

  • Text in the first cell below METADATA is ignored.
  • Text in the second cell below METADATA is subject to interpolation, as described above, using values from the cells in the rule rows. The metadata marker character @ is prefixed automatically, and should not be included in the text for this cell.
  • Text in the third cell below METADATA is for documentation only. It should be used to indicate the column’s purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the metadata annotation for this rule.

6.5.14. Interpolating Cell Data Example

  • If the template is Foo(bar == $param) and the cell is 42, then the result is Foo(bar == 42).
  • If the template is Foo(bar < $1, baz == $2) and the cell contains 42,43, the result will be Foo(bar < 42, baz ==43).
  • The template forall(&&){bar != $} with a cell containing 42,43 results in bar != 42 && bar != 43.

6.5.15. Tips for Working Within Cells

  • Multiple package names within the same cell must be comma-separated.
  • Pairs of type and variable names must be comma-separated.
  • Functions must be written as they appear in a DRL file. This should appear in the same column as the RuleSet keyword. It can be above, between or below all the rule rows.
  • You can use Import, Variables, Functions and Queries repeatedly instead of packing several definitions into a single cell.
  • Trailing insertion markers can be omitted.
  • You can provide the definition of a binding variable.
  • Anything can be placed in the object type row. Apart from the definition of a binding variable, it could also be an additional pattern that is to be inserted literally.
  • The cell below the ACTION header can be left blank. Using this style, anything can be placed in the consequence, not just a single method call. The same technique is applicable within a CONDITION column.

6.5.16. The SpreadsheetCompiler Class

The SpreadsheetCompiler class is the main class used with API spreadsheet-based decision tables in the drools-decisiontables module. This class takes spreadsheets in various formats and generates rules in DRL.

The SpreadsheetCompiler can be used to generate partial rule files and assemble them into a complete rule package after the fact. This allows the separation of technical and non-technical aspects of the rules if needed.

6.5.17. Using Spreadsheet-Based Decision Tables

Procedure: Task

  1. Generate a sample spreadsheet that you can use as the base.
  2. If the Red Hat JBoss BRMS plug-in is being used, use the wizard to generate a spreadsheet from a template.
  3. Use an XSL-compatible spreadsheet editor to modify the XSL.

6.5.18. Lists

In Excel, you can create lists of values. These can be stored in other worksheets to provide valid lists of values for cells.

6.5.19. Revision Control

When changes are being made to rules over time, older versions are archived. Some applications in Red Hat JBoss BRMS provide a limited ability to keep a history of changes, but it is recommended to use an alternative means of revision control.

6.5.20. Tabular Data Sources

A tabular data source can be used as a source of rule data. It can populate a template to generate many rules. This can allow both for more flexible spreadsheets, but also rules in existing databases for instance (at the cost of developing the template up front to generate the rules).

6.6. Dependency Management for Guided Decision Tables, Scorecards, and Rule Templates

When you build your own application with the embedded Drools or jBPM engine, that uses guided decision tables, guided scorecards, or guided templates, you need to add the drools-workbench-models-guided-dtable, drools-workbench-models-guided-scorecard, and drools-workbench-models-guided-template dependencies respectively, on the class path.

If you want to use a kJAR in the Intelligent Process server, you do not need to add these dependencies, as the server already has them.

When using Maven, declare the dependencies in the pom.xml file as shown below:

<dependency>
  <groupId>org.drools</groupId>
  <artifactId>drools-workbench-models-guided-dtable</artifactId>
</dependency>

<dependency>
  <groupId>org.drools</groupId>
  <artifactId>drools-workbench-models-guided-scorecard</artifactId>
</dependency>

<dependency>
  <groupId>org.drools</groupId>
  <artifactId>drools-workbench-models-guided-template</artifactId>
</dependency>

6.7. Logging

The logging feature enables you to investigate what the Rule Engine does at the back-end. The rule engine uses Java logging API SLF4J for logging. The underlying logging back-end can be Logback, Apache Commons Logging, Log4j, or java.util.logging. You can add a dependency to the logging adaptor for your logging framework of choice.

Here is an example of how to use Logback by adding a Maven dependency:

<dependency>
  <groupId>ch.qos.logback</groupId>
  <artifactId>logback-classic</artifactId>
  <version>1.x</version>
</dependency>
Note

If you are developing for an ultra light environment, use slf4j-nop or slf4j-simple.

6.7.1. Configuring Logging Level

Here is an example of how you can configure the logging level on the package org.drools in your logback.xml file when you are using Logback:

<configuration>
  <logger name="org.drools" level="debug"/>
  ...
  ...
<configuration>

Here is an example of how you can configure the logging level in your log4j.xml file when you are using Log4J:

<log4j:configuration xmlns:log4j="http://jakarta.apache.org/log4j/">
  <category name="org.drools">
    <priority value="debug" />
  </category>
  ...
</log4j:configuration>

Chapter 7. Complex Event Processing

7.1. Introduction to Complex Event Processing

JBoss BRMS Complex Event Processing provides the JBoss Enterprise BRMS Platform with complex event processing capabilities.

For the purpose of this guide, Complex Event Processing, or CEP, refers to the ability to process multiple events and detect interesting events from within a collection of events, uncover relationships that exist between events, and infer new data from the events and their relationships.

An event can best be described as a record of a significant change of state in the application domain. Depending on how the domain is modeled, the change of state may be represented by a single event, multiple atomic events, or even hierarchies of correlated events. Using a stock broker application as an example, a change in security prices, a change in ownership from seller to buyer, or a change in an account holder’s balance are all considered to be events as a change has occurred in the state of the application domain.

Event processing use cases, in general, share several requirements and goals with business rules use cases.

From a business perspective, business rule definitions are often defined based on the occurrence of scenarios triggered by events. For example:

  • On an algorithmic trading application: Take an action if the security price increases X% above the day’s opening price.

    The price increases are denoted by events on a stock trade application.

  • On a monitoring application: Take an action if the temperature in the server room increases X degrees in Y minutes.

    The sensor readings are denoted by events.

Both business rules and event processing queries change frequently and require an immediate response for the business to adapt to new market conditions, regulations, and corporate policies.

From a technical perspective:

  • Both business rules and event processing require seamless integration with the enterprise infrastructure and applications. This is particularly important with regard to life-cycle management, auditing, and security.
  • Both business rules and event processing have functional requirements like pattern matching and non-functional requirements like response time limits and query/rule explanations.
Note

JBoss BRMS Complex Event Processing provides the complex event processing capabilities of JBoss Business Rules Management System. The Business Rules Management and Business Process Management capabilities are provided by other modules.

Complex event processing scenarios share these distinguishing characteristics:

  • They usually process large numbers of events, but only a small percentage of the events are of interest.
  • The events are usually immutable, as they represent a record of change in state.
  • The rules and queries run against events and must react to detected event patterns.
  • There are usually strong temporal relationships between related events.
  • Individual events are not important. The system is concerned with patterns of related events and the relationships between them.
  • It is often necessary to perform composition and aggregation of events.

As such, JBoss BRMS Complex Event Processing supports the following behaviors:

  • Support events, with their proper semantics, as first class citizens.
  • Allow detection, correlation, aggregation, and composition of events.
  • Support processing streams of events.
  • Support temporal constraints in order to model the temporal relationships between events.
  • Support sliding windows of interesting events.
  • Support a session-scoped unified clock.
  • Support the required volumes of events for complex event processing use cases.
  • Support reactive rules.
  • Support adapters for event input into the engine (pipeline).

7.2. Events

Events are a record of significant change of state in the application domain. From a complex event processing perspective, an event is a special type of fact or object. A fact is a known piece of data. For instance, a fact could be a stock’s opening price. A rule is a definition of how to react to the data. For instance, if a stock price reaches $X, sell the stock.

The defining characteristics of events are the following:

Events are immutable

An event is a record of change which has occurred at some time in the past, and as such it cannot be changed.

Note

The rules engine does not enforce immutability on the Java objects representing events; this makes event data enrichment possible.

The application should be able to populate un-populated event attributes, which can be used to enrich the event with inferred data; however, event attributes that have already been populated should not be changed.

Events have strong temporal constraints
Rules involving events usually require the correlation of multiple events that occur at different points in time relative to each other.
Events have managed life-cycles
Because events are immutable and have temporal constraints, they are usually only of interest for a specified period of time. This means the engine can automatically manage the life-cycle of events.
Events can use sliding windows
It is possible to define and use sliding windows with events since all events have timestamps associated with them. Therefore, sliding windows allow the creation of rules on aggregations of values over a time period.

Events can be declared as either interval-based events or point-in-time events. Interval-based events have a duration time and persist in working memory until their duration time has lapsed. Point-in-time events have no duration and can be thought of as interval-based events with a duration of zero.

7.2.1. Event Declaration

To declare a fact type as an event, assign the @role metadata tag to the fact with the event parameter. The @role metadata tag can accept two possible values:

  • fact: assigning the fact role declares the type is to be handled as a regular fact. Fact is the default role.
  • event: assigning the event role declares the type is to be handled as an event.

This example declares that a stock broker application’s StockTick fact type will be handled as an event:

Example 7.1. Declaring Fact Type as Event

import some.package.StockTick

declare StockTick
  @role( event )
end

Facts can also be declared inline. If StockTick was a fact type declared in the DRL instead of in a pre-existing class, the code would be as follows:

Example 7.2. Declaring Fact Type and Assigning it to Event Role

declare StockTick
  @role(event)

  datetime : java.util.Date
  symbol : String
  price : double
end

For more information about type declarations, see Section 8.9, “Type Declaration”.

7.2.2. Event Metadata

Every event has associated metadata. Typically, the metadata is automatically added as each event is inserted into working memory. The metadata defaults can be changed on an event-type basis using the metadata tags:

  • @role
  • @timestamp
  • @duration
  • @expires

The following examples assume the application domain model includes the following class:

Example 7.3. The VoiceCall Fact Class

/**
 * A class that represents a voice call in a Telecom domain model.
 */
public class VoiceCall {
  private String  originNumber;
  private String  destinationNumber;
  private Date    callDateTime;
  private long    callDuration;  // in milliseconds

  // Constructors, getters, and setters.
}
@role

The @role metadata tag indicates whether a given fact type is either a regular fact or an event. It accepts either fact or event as a parameter. The default is fact.

@role(<fact|event>)

Example 7.4. Declaring VoiceCall as Event Type

declare VoiceCall
  @role(event)
end
@timestamp

A timestamp is automatically assigned to every event. By default, the time is provided by the session clock and assigned to the event at insertion into the working memory. Events can have their own timestamp attribute, which can be included by telling the engine to use the attribute’s timestamp instead of the session clock.

To use the attribute’s timestamp, use the attribute name as the parameter for the @timestamp tag.

@timestamp(<attributeName>)

Example 7.5. Declaring VoiceCall Timestamp Attribute

declare VoiceCall
  @role(event)
  @timestamp(callDateTime)
end
@duration

JBoss BRMS Complex Event Processing supports both point-in-time and interval-based events. A point-in-time event is represented as an interval-based event with a duration of zero time units. By default, every event has a duration of zero. To assign a different duration to an event, use the attribute name as the parameter for the @duration tag.

@duration(<attributeName>)

Example 7.6. Declaring VoiceCall Duration Attribute

declare VoiceCall
  @role(event)
  @timestamp(callDateTime)
  @duration(callDuration)
end
@expires

Events may be set to expire automatically after a specific duration in the working memory. By default, this happens when the event can no longer match and activate any of the current rules. You can also explicitly define when an event should expire. The @expires tag is only used when the engine is running in stream mode.

@expires(<timeOffset>)

The value of timeOffset is a temporal interval that sets the relative duration of the event.

[#d][#h][#m][#s][#[ms]]

All parameters are optional and the # parameter should be replaced by the appropriate value.

To declare that the VoiceCall facts should expire one hour and thirty-five minutes after insertion into the working memory, use the following:

Example 7.7. Declaring Expiration Offset for VoiceCall Events

declare VoiceCall
  @role(event)
  @timestamp(callDateTime)
  @duration(callDuration)
  @expires(1h35m)
end

7.3. Clock Implementation in Complex Event Processing

7.3.1. Session Clock

Events have strong temporal constraints making it is necessary to use a reference clock. If a rule needs to determine the average price of a given stock over the last sixty minutes, it is necessary to compare the stock price event’s timestamp with the current time. The reference clock provides the current time.

Because the rules engine can simultaneously run an array of different scenarios that require different clocks, multiple clock implementations can be used by the engine.

Scenarios that require different clocks include the following:

  • Rules testing: Testing always requires a controlled environment, and when the tests include rules with temporal constraints, it is necessary to control the input rules, facts, and the flow of time.
  • Regular execution: A rules engine that reacts to events in real time needs a real-time clock.
  • Special environments: Specific environments may have specific time control requirements. For instance, clustered environments may require clock synchronization or JEE environments may require you to use an application server-provided clock.
  • Rules replay or simulation: In order to replay or simulate scenarios, it is necessary that the application controls the flow of time.

7.3.2. Available Clock Implementations

JBoss BRMS Complex Event Processing comes equipped with two clock implementations:

Real-Time Clock

The real-time clock is the default implementation based on the system clock. The real-time clock uses the system clock to determine the current time for timestamps.

To explicitly configure the engine to use the real-time clock, set the session configuration parameter to realtime:

import org.kie.api.KieServices.Factory;
import org.kie.api.runtime.conf.ClockTypeOption;
import org.kie.api.runtime.KieSessionConfiguration;

KieSessionConfiguration config = KieServices.Factory.get().newKieSessionConfiguration();

config.setOption(ClockTypeOption.get("realtime"));
Pseudo-Clock

The pseudo-clock is useful for testing temporal rules since it can be controlled by the application.

To explicitly configure the engine to use the pseudo-clock, set the session configuration parameter to pseudo:

import org.kie.api.runtime.conf.ClockTypeOption;
import org.kie.api.runtime.KieSessionConfiguration;
import org.kie.api.KieServices.Factory;

KieSessionConfiguration config = KieServices.Factory.get().newKieSessionConfiguration();

config.setOption(ClockTypeOption.get("pseudo"));

This example shows how to control the pseudo-clock:

import java.util.concurrent.TimeUnit;

import org.kie.api.runtime.KieSessionConfiguration;
import org.kie.api.KieServices.Factory;
import org.kie.api.runtime.KieSession;
import org.drools.core.time.SessionPseudoClock;
import org.kie.api.runtime.rule.FactHandle;
import org.kie.api.runtime.conf.ClockTypeOption;

KieSessionConfiguration conf = KieServices.Factory.get().newKieSessionConfiguration();

conf.setOption( ClockTypeOption.get("pseudo"));
KieSession session = kbase.newKieSession(conf, null);

SessionPseudoClock clock = session.getSessionClock();

// Then, while inserting facts, advance the clock as necessary:
FactHandle handle1 = session.insert(tick1);
clock.advanceTime(10, TimeUnit.SECONDS);

FactHandle handle2 = session.insert(tick2);
clock.advanceTime(30, TimeUnit.SECONDS);

FactHandle handle3 = session.insert(tick3);

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

7.4. Event Processing Modes

Rules engines process facts and rules to provide applications with results. Regular facts (facts with no temporal constraints) are processed independent of time and in no particular order. Red Hat JBoss BRMS processes facts of this type in cloud mode. Events (facts which have strong temporal constraints) must be processed in real-time or near real-time. Red Hat JBoss BRMS processes these events in stream mode. Stream mode deals with synchronization and makes it possible for Red Hat JBoss BRMS to process events.

7.4.1. Cloud Mode

Cloud mode is the default operating mode of Red Hat JBoss Business Rules Management System.

Running in Cloud mode, the engine applies a many-to-many pattern matching algorithm, which treats the events as an unordered cloud. Events still have timestamps, but there is no way for the rules engine running in Cloud mode to draw relevance from the timestamp because Cloud mode is unaware of the present time.

This mode uses the rules constraints to find the matching tuples, activate, and fire rules.

Cloud mode does not impose any kind of additional requirements on facts; however, because it has no concept of time, it cannot take advantage of temporal features such as sliding windows or automatic life-cycle management. In Cloud mode, it is necessary to explicitly retract events when they are no longer needed.

Certain requirements that are not imposed include the following:

  • No need for clock synchronization since there is no notion of time.
  • No requirement on ordering events since the engine looks at the events as an unordered cloud against which the engine tries to match rules.

Cloud mode can be specified either by setting a system property, using configuration property files, or using the API.

The API call follows:

import org.kie.api.conf.EventProcessingOption;
import org.kie.api.KieBaseConfiguration;
import org.kie.api.KieServices.Factory;

KieBaseConfiguration config = KieServices.Factory.get().newKieBaseConfiguration();

config.setOption(EventProcessingOption.CLOUD);

The equivalent property follows:

drools.eventProcessingMode = cloud

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

7.4.2. Stream Mode

Stream mode processes events chronologically as they are inserted into the rules engine. Stream mode uses a session clock that enables the rules engine to process events as they occur in time. The session clock enables processing events as they occur based on the age of the events. Stream mode also synchronizes streams of events (so events in different streams can be processed in chronological order), implements sliding windows of interest, and enables automatic life-cycle management.

The requirements for using stream mode are the following:

  • Events in each stream must be ordered chronologically.
  • A session clock must be present to synchronize event streams.
Note

The application does not need to enforce ordering events between streams, but the use of event streams that have not been synchronized may cause unexpected results.

Stream mode can be enabled by setting a system property, using configuration property files, or using the API.

The API call follows:

import org.kie.api.conf.EventProcessingOption;
import org.kie.api.KieBaseConfiguration;
import org.kie.api.KieServices.Factory;

KieBaseConfiguration config = KieServices.Factory.get().newKieBaseConfiguration();

config.setOption(EventProcessingOption.STREAM);

The equivalent property follows:

drools.eventProcessingMode = stream

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

7.5. Event Streams

Complex event processing use cases deal with streams of events. The streams can be provided to the application using JMS queues, flat text files, database tables, raw sockets, or even web service calls.

Streams share a common set of characteristics:

  • Events in the stream are ordered by timestamp. The timestamps may have different semantics for different streams, but they are always ordered internally.
  • There is usually a high volume of events in the stream.
  • Atomic events contained in the streams are rarely useful by themselves.
  • Streams are either homogeneous (they contain a single type of event) or heterogeneous (they contain events of different types).

A stream is also known as an entry point.

Facts from one entry point, or stream, may join with facts from any other entry point in addition to facts already in working memory. Facts always remain associated with the entry point through which they entered the engine. Facts of the same type may enter the engine through several entry points, but facts that enter the engine through entry point A will never match a pattern from entry point B.

7.5.1. Declaring and Using Entry Points

Entry points are declared implicitly by making direct use of them in rules. Referencing an entry point in a rule will make the engine, at compile time, identify and create the proper internal structures to support that entry point.

For example, a banking application that has transactions fed into the engine using streams could have one stream for all of the transactions executed at ATMs. A rule for this scenario could state, "A withdrawal is only allowed if the account balance is greater than the withdrawal amount the customer has requested."

Example 7.8. ATM Rule

rule "Authorize Withdraw"
when
  WithdrawRequest($ai : accountId, $am : amount) from entry-point "ATM Stream"
  CheckingAccount(accountId == $ai, balance > $am)
then
  // authorize withdraw
end

When the engine compiles this rule, it will identify that the pattern is tied to the entry point ATM Stream. The engine will create all the necessary structures for the rule-base to support the ATM Stream, and this rule will only match WithdrawRequest events coming from the ATM Stream.

Note the ATM example rule joins the event (WithdrawalRequest) from the stream with a fact from the main working memory (CheckingAccount).

The banking application may have a second rule that states, "A fee of $2 must be applied to a withdraw request made using a branch teller."

Example 7.9. Using Multiple Streams

rule "Apply Fee on Withdraws on Branches"
when
  WithdrawRequest($ai : accountId, processed == true) from entry-point "Branch Stream"
  CheckingAccount(accountId == $ai)
then
  // apply a $2 fee on the account
end

This rule matches events of the same type (WithdrawRequest) as the example ATM rule but from a different stream. Events inserted into the ATM Stream will never match the pattern on the second rule, which is tied to the Branch Stream; accordingly, events inserted into the Branch Stream will never match the pattern on the example ATM rule, which is tied to the ATM Stream.

Declaring the stream in a rule states that the rule is only interested in events coming from that stream.

Events can be inserted manually into an entry point instead of directly into the working memory.

Example 7.10. Inserting Facts into Entry Point

import org.kie.api.runtime.KieSession;
import org.kie.api.runtime.rule.EntryPoint;

// Create your rulebase and your session as usual:
KieSession session = ...

// Get a reference to the entry point:
EntryPoint atmStream = session.getEntryPoint("ATM Stream");

// ...and start inserting your facts into the entry point:
atmStream.insert(aWithdrawRequest);

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

7.5.2. Negative Pattern in Stream Mode

A negative pattern is concerned with conditions that are not met. Negative patterns make reasoning in the absence of events possible. For instance, a safety system could have a rule that states "If a fire is detected and the sprinkler is not activated, sound the alarm."

In Cloud mode, the engine assumes all facts (regular facts and events) are known in advance and evaluates negative patterns immediately.

Example 7.11. Rule with Negative Pattern

rule "Sound the Alarm"
when
  $f : FireDetected()
  not(SprinklerActivated())
then
  // sound the alarm
end

An example in stream mode is displayed below. This rule keeps consistency when dealing with negative patterns and temporal constraints at the same time interval.

Example 7.12. Rule with Negative Pattern, Temporal Constraints, and Explicit Duration Parameter

rule "Sound the Alarm"
  duration(10s)
when
  $f : FireDetected()
  not(SprinklerActivated(this after[0s,10s] $f))
then
  // sound the alarm
end

In stream mode, negative patterns with temporal constraints may force the engine to wait for a set time before activating a rule. A rule may be written for an alarm system that states, "If a fire is detected and the sprinkler is not activated after 10 seconds, sound the alarm." Unlike the previous stream mode example, this one does not require the user to calculate and write the duration parameter.

Example 7.13. Rule with Negative Pattern with Temporal Constraints

rule "Sound the Alarm"
when
  $f : FireDetected()
  not(SprinklerActivated(this after[0s,10s] $f))
then
  // sound the alarm
end

The rule depicted below expects one "Heartbeat" event to occur every 10 seconds; if not, the rule fires. What is special about this rule is that it uses the same type of object in the first pattern and in the negative pattern. The negative pattern has the temporal constraint to wait between 0 to 10 seconds before firing, and it excludes the Heartbeat bound to $h. Excluding the bound Heartbeat is important since the temporal constraint [0s, …​] does not exclude by itself the bound event $h from being matched again, thus preventing the rule to fire.

Example 7.14. Excluding Bound Events in Negative Patterns

rule "Sound the Alarm"
when
  $h: Heartbeat() from entry-point "MonitoringStream"
  not(Heartbeat(this != $h, this after[0s,10s] $h) from entry-point "MonitoringStream")
then
  // sound the alarm
end

7.6. Temporal Operations

7.6.1. Temporal Reasoning

Complex Event Processing requires the rules engine to engage in temporal reasoning. Events have strong temporal constraints so it is vital the rules engine can determine and interpret an event’s temporal attributes, both as they relate to other events and the 'flow of time' as it appears to the rules engine. This makes it possible for rules to take time into account; for instance, a rule could state "Calculate the average price of a stock over the last 60 minutes."

Note

JBoss BRMS Complex Event Processing implements interval-based time events, which have a duration attribute that is used to indicate how long an event is of interest. Point-in-time events are also supported and treated as interval-based events with a duration of 0 (zero).

7.6.2. Temporal Operations

JBoss BRMS Complex Event Processing implements the following temporal operators and their logical complements (negation):

  • after
  • before
  • coincides
  • during
  • finishes
  • finishes by
  • includes
  • meets
  • met by
  • overlaps
  • overlapped by
  • starts
  • started by

7.6.3. After

The after operator correlates two events and matches when the temporal distance (the time between the two events) from the current event to the event being correlated falls into the distance range declared for the operator.

For example:

$eventA : EventA(this after[3m30s, 4m] $eventB)

This pattern only matches if the temporal distance between the time when $eventB finished and the time when $eventA started is between the lower limit of three minutes and thirty seconds and the upper limit of four minutes.

This can also be represented as follows:

3m30s <= $eventA.startTimestamp - $eventB.endTimeStamp <= 4m

The after operator accepts one or two optional parameters:

  • If two values are defined, the interval starts on the first value (3 minutes and 30 seconds in the example) and ends on the second value (4 minutes in the example).
  • If only one value is defined, the interval starts on the provided value and runs indefinitely with no end time.
  • If no value is defined, the interval starts at one millisecond and runs indefinitely with no end time.

The after operator also accepts negative temporal distances.

For example:

$eventA : EventA(this after[-3m30s, -2m] $eventB)

If the first value is greater than the second value, the engine will automatically reverse them.

The following two patterns are equivalent to each other:

$eventA : EventA(this after[-3m30s, -2m] $eventB)
$eventA : EventA(this after[-2m, -3m30s] $eventB)

7.6.4. Before

The before operator correlates two events and matches when the temporal distance (time between the two events) from the event being correlated to the current event falls within the distance range declared for the operator.

For example:

$eventA : EventA(this before[3m30s, 4m] $eventB)

This pattern only matches if the temporal distance between the time when $eventA finished and the time when $eventB started is between the lower limit of three minutes and thirty seconds and the upper limit of four minutes.

This can also be represented as follows:

3m30s <= $eventB.startTimestamp - $eventA.endTimeStamp <= 4m

The before operator accepts one or two optional parameters:

  • If two values are defined, the interval starts on the first value (3 minutes and 30 seconds in the example) and ends on the second value (4 minutes in the example).
  • If only one value is defined, the interval starts on the provided value and runs indefinitely with no end time.
  • If no value is defined, the interval starts at one millisecond and runs indefinitely with no end time.

The before operator also accepts negative temporal distances.

For example:

$eventA : EventA(this before[-3m30s, -2m] $eventB)

If the first value is greater than the second value, the engine will automatically reverse them.

The following two patterns are equivalent to each other:

$eventA : EventA(this before[-3m30s, -2m] $eventB)
$eventA : EventA(this before[-2m, -3m30s] $eventB)

7.6.5. Coincides

The coincides operator correlates two events and matches when both events happen at the same time.

For example:

$eventA : EventA(this coincides $eventB)

This pattern only matches if both the start timestamps of $eventA and $eventB are identical and the end timestamps of both $eventA and $eventB are also identical.

The coincides operator accepts optional thresholds for the distance between the events' start times and the events' end times, so the events do not have to start at exactly the same time or end at exactly the same time, but they need to be within the provided thresholds.

The following rules apply when defining thresholds for the coincides operator:

  • If only one parameter is given, it is used to set the threshold for both the start and end times of both events.
  • If two parameters are given, the first is used as a threshold for the start time and the second one is used as a threshold for the end time.

For example:

$eventA : EventA(this coincides[15s, 10s] $eventB)

This pattern will only match if the following conditions are met:

abs($eventA.startTimestamp - $eventB.startTimestamp) <= 15s
&&
abs($eventA.endTimestamp - $eventB.endTimestamp) <= 10s
Warning

The coincides operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance internals.

7.6.6. During

The during operator correlates two events and matches when the current event happens during the event being correlated.

For example:

$eventA : EventA(this during $eventB)

This pattern only matches if $eventA starts after $eventB and ends before $eventB ends.

This can also be represented as follows:

$eventB.startTimestamp < $eventA.startTimestamp <= $eventA.endTimestamp < $eventB.endTimestamp

The during operator accepts one, two, or four optional parameters:

The following rules apply when providing parameters for the during operator:

  • If one value is defined, this value will represent the maximum distance between the start times of the two events and the maximum distance between the end times of the two events.
  • If two values are defined, these values represent a threshold that the current event’s start time and end time must occur between in relation to the correlated event’s start and end times.

    If the values 5s and 10s are provided, the current event must start between 5 and 10 seconds after the correlated event, and similarly the current event must end between 5 and 10 seconds before the correlated event.

  • If four values are defined, the first and second values will be used as the minimum and maximum distances between the starting times of the events, and the third and fourth values will be used as the minimum and maximum distances between the end times of the two events.

7.6.7. Finishes

The finishes operator correlates two events and matches when the current event’s start timestamp post-dates the correlated event’s start timestamp and both events end simultaneously.

For example:

$eventA : EventA(this finishes $eventB)

This pattern only matches if $eventA starts after $eventB starts and ends at the same time as $eventB ends.

This can be represented as follows:

$eventB.startTimestamp < $eventA.startTimestamp
&&
$eventA.endTimestamp == $eventB.endTimestamp

The finishes operator accepts one optional parameter. If defined, the optional parameter sets the maximum time allowed between the end times of the two events.

For example:

$eventA : EventA(this finishes[5s] $eventB)

This pattern matches if these conditions are met:

$eventB.startTimestamp < $eventA.startTimestamp
&&
abs($eventA.endTimestamp - $eventB.endTimestamp) <= 5s
Warning

The finishes operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.6.8. Finishes By

The finishedby operator correlates two events and matches when the current event’s start time predates the correlated event’s start time but both events end simultaneously. finishedby is the symmetrical opposite of the finishes operator.

For example:

$eventA : EventA(this finishedby $eventB)

This pattern only matches if $eventA starts before $eventB starts and ends at the same time as $eventB ends.

This can be represented as follows:

$eventA.startTimestamp < $eventB.startTimestamp
&&
$eventA.endTimestamp == $eventB.endTimestamp

The finishedby operator accepts one optional parameter. If defined, the optional parameter sets the maximum time allowed between the end times of the two events.

$eventA : EventA(this finishedby[5s] $eventB)

This pattern matches if these conditions are met:

$eventA.startTimestamp < $eventB.startTimestamp
&&
abs($eventA.endTimestamp - $eventB.endTimestamp) <= 5s
Warning

The finishedby operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.6.9. Includes

The includes operator examines two events and matches when the event being correlated happens during the current event. It is the symmetrical opposite of the during operator.

For example:

$eventA : EventA(this includes $eventB)

This pattern only matches if $eventB starts after $eventA and ends before $eventA ends.

This can be represented as follows:

$eventA.startTimestamp < $eventB.startTimestamp <= $eventB.endTimestamp < $eventA.endTimestamp

The includes operator accepts 1, 2 or 4 optional parameters:

  • If one value is defined, this value will represent the maximum distance between the start times of the two events and the maximum distance between the end times of the two events.
  • If two values are defined, these values represent a threshold that the current event’s start time and end time must occur between in relation to the correlated event’s start and end times.

    If the values 5s and 10s are provided, the current event must start between 5 and 10 seconds after the correlated event, and similarly the current event must end between 5 and 10 seconds before the correlated event.

  • If four values are defined, the first and second values will be used as the minimum and maximum distances between the starting times of the events, and the third and fourth values will be used as the minimum and maximum distances between the end times of the two events.

7.6.10. Meets

The meets operator correlates two events and matches when the current event ends at the same time as the correlated event starts.

For example:

$eventA : EventA(this meets $eventB)

This pattern matches if $eventA ends at the same time as $eventB starts.

This can be represented as follows:

abs($eventB.startTimestamp - $eventA.endTimestamp) == 0

The meets operator accepts one optional parameter. If defined, it determines the maximum time allowed between the end time of the current event and the start time of the correlated event.

For example:

$eventA : EventA(this meets[5s] $eventB)

This pattern matches if these conditions are met:

abs($eventB.startTimestamp - $eventA.endTimestamp) <= 5s
Warning

The meets operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.6.11. Met By

The metby operator correlates two events and matches when the current event starts at the same time as the correlated event ends.

For example:

$eventA : EventA(this metby $eventB)

This pattern matches if $eventA starts at the same time as $eventB ends.

This can be represented as follows:

abs($eventA.startTimestamp - $eventB.endTimestamp) == 0

The metby operator accepts one optional parameter. If defined, it sets the maximum distance between the end time of the correlated event and the start time of the current event.

For example:

$eventA : EventA(this metby[5s] $eventB)

This pattern matches if these conditions are met:

abs($eventA.startTimestamp - $eventB.endTimestamp) <= 5s
Warning

The metby operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.6.12. Overlaps

The overlaps operator correlates two events and matches when the current event starts before the correlated event starts and ends after the correlated event starts, but it ends before the correlated event ends.

For example:

$eventA : EventA(this overlaps $eventB)

This pattern matches if these conditions are met:

$eventA.startTimestamp < $eventB.startTimestamp < $eventA.endTimestamp < $eventB.endTimestamp

The overlaps operator accepts one or two optional parameters:

  • If one parameter is defined, it will define the maximum distance between the start time of the correlated event and the end time of the current event.
  • If two values are defined, the first value will be the minimum distance, and the second value will be the maximum distance between the start time of the correlated event and the end time of the current event.

7.6.13. Overlapped By

The overlappedby operator correlates two events and matches when the correlated event starts before the current event, and the correlated event ends after the current event starts but before the current event ends.

For example:

$eventA : EventA(this overlappedby $eventB)

This pattern matches if these conditions are met:

$eventB.startTimestamp < $eventA.startTimestamp < $eventB.endTimestamp < $eventA.endTimestamp

The overlappedby operator accepts one or two optional parameters:

  • If one parameter is defined, it sets the maximum distance between the start time of the correlated event and the end time of the current event.
  • If two values are defined, the first value will be the minimum distance, and the second value will be the maximum distance between the start time of the correlated event and the end time of the current event.

7.6.14. Starts

The starts operator correlates two events and matches when they start at the same time, but the current event ends before the correlated event ends.

For example:

$eventA : EventA(this starts $eventB)

This pattern matches if $eventA and $eventB start at the same time, and $eventA ends before $eventB ends.

This can be represented as follows:

$eventA.startTimestamp == $eventB.startTimestamp
&&
$eventA.endTimestamp < $eventB.endTimestamp

The starts operator accepts one optional parameter. If defined, it determines the maximum distance between the start times of events in order for the operator to still match:

$eventA : EventA(this starts[5s] $eventB)

This pattern matches if these conditions are met:

abs($eventA.startTimestamp - $eventB.startTimestamp) <= 5s
&&
$eventA.endTimestamp < $eventB.endTimestamp
Warning

The starts operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.6.15. Started By

The startedby operator correlates two events. It matches when both events start at the same time and the correlating event ends before the current event.

For example:

$eventA : EventA(this startedby $eventB)

This pattern matches if $eventA and $eventB start at the same time, and $eventB ends before $eventA ends.

This can be represented as follows:

$eventA.startTimestamp == $eventB.startTimestamp
&&
$eventA.endTimestamp > $eventB.endTimestamp

The startedby operator accepts one optional parameter. If defined, it sets the maximum distance between the start time of the two events in order for the operator to still match:

$eventA : EventA( this starts[5s] $eventB)

This pattern matches if these conditions are met:

abs( $eventA.startTimestamp - $eventB.startTimestamp ) <= 5s
&&
$eventA.endTimestamp > $eventB.endTimestamp
Warning

The startedby operator does not accept negative intervals, and the rules engine will throw an exception if an attempt is made to use negative distance intervals.

7.7. Sliding Windows

7.7.1. Sliding Time Windows

Stream mode allows events to be matched over a sliding time window. A sliding window is a time period that stretches back in time from the present. For instance, a sliding window of two minutes includes any events that have occurred in the past two minutes. As events fall out of the sliding time window (in this case because they occurred more than two minutes ago), they will no longer match against rules using this particular sliding window.

For example:

StockTick() over window:time(2m)

JBoss BRMS Complex Event Processing uses the over keyword to associate windows with patterns.

Sliding time windows can also be used to calculate averages and over time. For instance, a rule could be written that states "If the average temperature reading for the last ten minutes goes above a certain point, sound the alarm."

Example 7.15. Average Value over Time

rule "Sound the Alarm in Case Temperature Rises Above Threshold"
when
  TemperatureThreshold($max : max)
  Number(doubleValue > $max) from accumulate(
    SensorReading($temp : temperature) over window:time(10m),
    average($temp))
then
  // sound the alarm
end

The engine will automatically discard any SensorReading more than ten minutes old and keep re-calculating the average.

7.7.2. Sliding Length Windows

Similar to Time Windows, Sliding Length Windows work in the same manner; however, they consider events based on order of their insertion into the session instead of flow of time.

The pattern below demonstrates this order by only considering the last 10 RHT Stock Ticks independent of how old they are. Unlike the previous StockTick from the Sliding Time Windows pattern, this pattern uses window:length.

StockTick(company == "RHT") over window:length(10)

The example below portrays window length instead of window time; that is, it allows the user to sound an alarm in case the average temperature over the last 100 readings from a sensor is above the threshold value.

Example 7.16. Average Value over Length

rule "Sound the Alarm in Case Temperature Rises Above Threshold"
when
  TemperatureThreshold($max : max)
  Number(doubleValue > $max) from accumulate(
    SensorReading($temp : temperature) over window:length(100),
    average($temp))
then
  // sound the alarm
end
Note

The engine disregards events that fall off a window when calculating that window, but it does not remove the event from the session based on that condition alone as there might be other rules that depend on that event.

Note

Length based windows do not define temporal constraints for event expiration from the session, and the engine will not consider them. If events have no other rules defining temporal constraints and no explicit expiration policy, the engine will keep them in the session indefinitely.

7.8. Memory Management for Events

Automatic memory management for events is available when running the rules engine in Stream mode. Events that no longer match any rule due to their temporal constraints can be safely retracted from the session by the rules engine without any side effects, releasing any resources held by the retracted events.

The rules engine has two ways of determining if an event is still of interest:

Explicitly
Event expiration can be explicitly set with the @expires.
Implicitly
The rules engine can analyze the temporal constraints in rules to determine the window of interest for events.

7.8.1. Explicit Expiration

Explicit expiration is set with a declare statement and the metadata @expires tag.

For example:

Example 7.17. Declaring Explicit Expiration

declare StockTick
  @expires(30m)
end

Declaring expiration against an event-type will, in the above example StockTick events, remove any StockTick events from the session automatically after the defined expiration time if no rules still need the events.

7.8.2. Inferred Expiration

The rules engine can calculate the expiration offset for a given event implicitly by analyzing the temporal constraints in the rules.

For example:

Example 7.18. Rule with Temporal Constraints

rule "correlate orders"
when
  $bo : BuyOrder($id : id)
  $ae : AckOrder(id == $id, this after[0,10s] $bo)
then
  // do something
end

For the example rule, the rules engine automatically calculates that whenever a BuyOrder event occurs it needs to store the event for up to ten seconds to wait for the matching AckOrder event, making the implicit expiration offset for BuyOrder events ten seconds. An AckOrder event can only match an existing BuyOrder event making its implicit expiration offset zero seconds.

The engine analyzes the entire rule-base to find the offset for every event-type. Whenever an implicit expiration clashes with an explicit expiration the engine uses the greater value of the two.

Chapter 8. Working With Rules

8.1. About Rule Files

8.1.1. Rule File

A rule file is typically a file with a .drl extension. In a DRL file you can have multiple rules, queries and functions, as well as some resource declarations like imports, globals, and attributes that are assigned and used by your rules and queries. However, you are also able to spread your rules across multiple rule files (in that case, the extension .rule is suggested, but not required) - spreading rules across files can help with managing large numbers of rules. A DRL file is simply a text file.

8.1.2. Structure of Rule Files

The overall structure of a rule file is the following:

Example 8.1. Rule File

package package-name

imports

globals

functions

queries

rules

The order in which the elements are declared is not important, except for the package name that, if declared, must be the first element in the rules file. All elements are optional, so you will use only those you need.

8.2. Operating on Facts

Facts are domain model objects that BRMS uses to evaluate conditions and execute consequences. A rule specifies that when a particular set of conditions occur, then the specified list of actions must be executed. The inference engine matches facts against rules, and when matches are found, rule actions are placed on the agenda. The agenda is the place where rules are queued ready to have their actions fired. The rule engine then determines which eligible rules on the agenda must fire.

8.2.1. Accessing Working Memory

The working memory is a stateful object that provides temporary storage and enables manipulation of facts. The working memory includes an API that contains methods which enable access to the working memory from rule files. The available methods are:

  • update(OBJECT, HANDLE)

    Used to inform the engine that an object has changed and rules can need to be reconsidered.

  • update(OBJECT)

    This method causes KieSession to search for a fact handle of the passed object using an identity check. You do not have to call this method when the object changes if property change listeners are provided. For more infomartion, see Section 8.12.15, “Fine Grained Property Change Listeners”.

    If field values of a fact have changed, call this method or use the modify keyword before changing another fact to avoid issues with indexing within the engine.

  • insert(OBJECT)

    Used to place a new object into the working memory.

  • insertLogical(OBJECT)

    This method is similar to the insert method. The newly inserted object is automatically retracted from the working memory if there are no more facts supporting the truth of the rule that inserted the fact.

  • retract(HANDLE)

    Used to remove an object from the working memory. This method is mapped to the delete method in KieSession.

  • halt()

    Used to terminate a rule execution immediately. Calling fireUntilHalt() causes continuous firing of the rules. To stop the firing, call halt().

  • getKieRuntime()

    The whole KIE API is exposed through a predefined kcontext variable of type RuleContext. The inherited getKieRuntime() method returns a KieRuntime object that provides access to various methods, many of which are useful for coding the rule logic.

    For example, calling kcontext.getKieRuntime().halt() terminates a rule execution immediately.

8.3. Using Rule Keywords

8.3.1. Hard Keywords

Hard keywords are words which you cannot use when naming your domain objects, properties, methods, functions, and other elements that are used in the rule text. The hard keywords are true, false, and null.

8.3.2. Soft Keywords

Soft keywords can be used for naming domain objects, properties, methods, functions, and other elements. The rules engine recognizes their context and processes them accordingly.

8.3.3. List of Soft Keywords

Rule attributes can be both simple and complex properties that provide a way to influence the behavior of the rule. They are usually written as one attribute per line and can be optional to the rule. Listed below are various rule attributes:

Figure 8.1. Rule Attributes

6124
no-loop BOOLEAN

When a rule’s consequence modifies a fact, it may cause the rule to activate again, causing an infinite loop. Setting no-loop to true will skip the creation of another activation for the rule with the current set of facts.

Default value: false.

lock-on-active BOOLEAN

Whenever a ruleflow-group becomes active or an agenda-group receives the focus, any rule within that group that has lock-on-active set to true will not be activated any more. Regardless of the origin of the update, the activation of a matching rule is discarded. This is a stronger version of no-loop because the change is not only caused by the rule itself. It is ideal for calculation rules where you have a number of rules that modify a fact, and you do not want any rule re-matching and firing again. Only when the ruleflow-group is no longer active or the agenda-group loses the focus, those rules with lock-on-active set to true become eligible again for their activations to be placed onto the agenda.

Default value: false.

salience INTEGER

Each rule has an integer salience attribute which defaults to zero and can be negative or positive. Salience is a form of priority where rules with higher salience values are given higher priority when ordered in the activation queue.

Default value: 0.

Red Hat JBoss BRMS also supports dynamic salience where you can use an expression involving bound variables like the following:

rule "Fire in rank order 1,2,.."
salience(-$rank)
when
  Element($rank : rank,...)
then
  ...
end
ruleflow-group STRING
Ruleflow is a BRMS feature that lets you exercise control over the firing of rules. Rules that are assembled by the same ruleflow-group identifier fire only when their group is active. This attribute has been merged with agenda-group and the behaviours are basically the same.
agenda-group STRING

Agenda groups enable you to partition the agenda, which provides more execution control. Only rules in the agenda group that have acquired the focus are allowed to fire. This attribute has been merged with ruleflow-group and the behaviours are basically the same.

Default value: MAIN.

auto-focus BOOLEAN

When a rule is activated where the auto-focus value is true and the rule’s agenda group does not have focus yet, it is automatically given focus, allowing the rule to potentially fire.

Default value: false.

activation-group STRING
Rules that belong to the same activation-group identified by this attribute’s String value, will only fire exclusively. More precisely, the first rule in an activation-group to fire will cancel all pending activations of all rules in the group, for example stop them from firing.
dialect STRING

Java and MVEL are the possible values of the dialect attribute. This attribute specifies the language to be used for any code expressions in the LHS or the RHS code block. While the dialect can be specified at the package level, this attribute allows the package definition to be overridden for a rule.

Default value: specified by the package.

date-effective STRING

A rule can only activate if the current date and time is after the date-effective attribute. Note that STRING is a date and time definition. An example date-effective attribute is displayed below:

rule "Start Exercising"
date-effective "4-Sep-2014"
when
  $m : org.drools.compiler.Message()
then
  $m.setFired(true);
end
date-expires STRING

A rule cannot activate if the current date and time is after the date-expires attribute. Note that STRING is a date and time definition. An example date-expires attribute is displayed below:

rule "Run 4km"
date-effective "4-Sep-2014"
date-expires "9-Sep-2014"
when
  $m : org.drools.compiler.Message()
then
  $m.setFired(true);
end
duration LONG
If a rule is still true, the duration attribute will dictate that the rule will fire after a specified duration.
Note

The attributes ruleflow-group and agenda-group have been merged and now behave the same. The GET methods have been left the same, for deprecations reasons, but both attributes return the same underlying data.

8.4. Adding Comments to Rule File

Comments are sections of text that are ignored by the rule engine. They are stripped out when they are encountered, except inside semantic code blocks (like a rule’s RHS).

8.4.1. Single Line Comment Example

This is what a single line comment looks like. To create single line comments, you can use //. The parser will ignore anything in the line after the comment symbol:

rule "Testing Comments"
when
  // this is a single line comment
  eval(true) // this is a comment in the same line of a pattern
then
  // this is a comment inside a semantic code block
end

8.4.2. Multi-Line Comment Example

This is what a multi-line comment looks like. This configuration comments out blocks of text, both in and outside semantic code blocks:

rule "Test Multi-Line Comments"
when
  /* this is a multi-line comment
     in the left hand side of a rule */
  eval( true )
then
  /* and this is a multi-line comment
     in the right hand side of a rule */
end

8.5. Error Messages in Rules

Red Hat JBoss BRMS provides standardized error messages. This standardization aims to help users to find and resolve problems in a easier and faster way.

8.5.1. Error Message Format

This is the standard error message format.

Figure 8.2. Error Message Format Example

1598

1st Block: This area identifies the error code.

2nd Block: Line and column information.

3rd Block: Some text describing the problem.

4th Block: This is the first context. Usually indicates the rule, function, template, or query where the error occurred. This block is not mandatory.

5th Block: Identifies the pattern where the error occurred. This block is not mandatory.

8.5.2. Error Message Description

[ERR 101] Line 4:4 no viable alternative at input 'exits' in rule one

Indicates when the parser came to a decision point but couldn’t identify an alternative. For example:

1: rule one
2:  when
3:    exists Foo()
4:    exits Bar()
5:  then
6: end
[ERR 101] Line 3:2 no viable alternative at input 'WHEN

This message means the parser has encountered the token WHEN (a hard keyword) which is in the wrong place, since the rule name is missing. For example:

1: package org.drools;
2: rule
3:   when
4:     Object()
5:   then
6:     System.out.println("A RHS");
7: end
[ERR 101] Line 0:-1 no viable alternative at input '<eof>' in rule simple_rule in pattern [name]

Indicates an open quote, apostrophe or parentheses. For example:

1: rule simple_rule
2:   when
3:     Student(name == "Andy)
4:   then
5: end
[ERR 102] Line 0:-1 mismatched input '<eof>' expecting ')' in rule simple_rule in pattern Bar

Indicates that the parser was looking for a particular symbol that it didn’t end at the current input position.

1: rule simple_rule
2:   when
3:     foo3 : Bar(
[ERR 102] Line 0:-1 mismatched input '<eof>' expecting ')' in rule simple_rule in pattern [name]

This error is the result of an incomplete rule statement. Usually when you get a 0:-1 position, it means that parser reached the end of source. To fix this problem, it is necessary to complete the rule statement.

1: package org.drools;
2:
3: rule "Avoid NPE on wrong syntax"
4:   when
5:     not(Cheese((type == "stilton", price == 10) \|\| (type == "brie", price == 15)) from $cheeseList)
6:   then
7:     System.out.println("OK");
8: end
[ERR 103] Line 7:0 rule 'rule_key' failed predicate: {(validateIdentifierKey( DroolsSoftKeywords.RULE ))}? in rule

A validating semantic predicate evaluated to false. Usually these semantic predicates are used to identify soft keywords.

 1: package nesting;
 2: dialect "mvel"
 3:
 4: import org.drools.Person
 5: import org.drools.Address
 6:
 7: fdsfdsfds
 8:
 9: rule "test something"
10:   when
11:     p: Person(name=="Michael")
12:   then
13:     p.name = "other";
14:     System.out.println(p.name);
15: end
[ERR 104] Line 3:4 trailing semi-colon not allowed in rule simple_rule

This error is associated with the eval clause, where its expression may not be terminated with a semicolon. This problem is simple to fix: just remove the semi-colon.

1: rule simple_rule
2:   when
3:     eval(abc();)
4:   then
5: end
[ERR 105] Line 2:2 required (…​)+ loop did not match anything at input 'aa' in template test_error

The recognizer came to a subrule in the grammar that must match an alternative at least once, but the subrule did not match anything. To fix this problem it is necessary to remove the numeric value as it is neither a valid data type which might begin a new template slot nor a possible start for any other rule file construct.

1: template test_error
2:   aa s 11;
3: end

8.6. Packaging

A package is a collection of rules and other related constructs, such as imports and globals. The package members are typically related to each other, such as HR rules. A package represents a namespace, which ideally is kept unique for a given grouping of rules. The package name itself is the namespace, and is not related to files or folders in any way.

It is possible to assemble rules from multiple rule sources, and have one top-level package configuration that all the rules are kept under (when the rules are assembled). It is not possible to merge into the same package resources declared under different names. A single Rulebase may, however, contain multiple packages built on it. A common structure is to have all the rules for a package in the same file as the package declaration (so that is it entirely self-contained).

8.6.1. Import Statements

Import statements work like import statements in Java. You need to specify the fully qualified paths and type names for any objects you want to use in the rules. Red Hat JBoss BRMS automatically imports classes from the Java package of the same name, and also from the package java.lang.

8.6.2. Using Globals

In DRL files, globals represent global variables. To use globals in rules:

  1. Declare the global variable:

    global java.util.List myGlobalList;
    
    rule "Using a Global"
    when
      eval(true)
    then
      myGlobalList.add("Hello World");
    end
  2. Set the global value in the working memory. The best practice is to set all global values before asserting any fact into the working memory. For example:

    List list = new ArrayList();
    KieSession kieSession = kieBase.newKieSession();
    kieSession.setGlobal("myGlobalList", list);

8.6.3. From Element

The from element allows you to pass a Hibernate session as a global. It also lets you pull data from a named Hibernate query.

8.6.4. Using Globals with E-Mail Service

Procedure: Task

  1. Open the integration code that is calling the rule engine.
  2. Obtain your emailService object and then set it in the working memory.
  3. In the DRL, declare that you have a global of type emailService and give it the name email.
  4. In your rule consequences, you can use things like email.sendSMS(number, message).

    Warning

    Globals are not designed to share data between rules and they should never be used for that purpose. Rules always reason and react to the working memory state, so if you want to pass data from rule to rule, assert the data as facts into the working memory.

    Important

    Do not set or change a global value from inside the rules. We recommend to you always set the value from your application using the working memory interface.

8.7. Functions in Rules

Functions are a way to put semantic code in a rule source file, as opposed to in normal Java classes. The main advantage of using functions in a rule is that you can keep the logic all in one place. You can change the functions as needed.

Functions are most useful for invoking actions on the consequence (then) part of a rule, especially if that particular action is used repeatedly.

A typical function declaration looks like the following:

function String hello(String name) {
  return "Hello " + name + "!";
}
Note

Note that the function keyword is used, even though it is not technically part of Java. Parameters to the function are defined as for a method. You do not have to have parameters if they are not needed. The return type is defined just like in a regular method.

8.7.1. Importing Static Method Example

In the following example, a static method Foo.hello() from a helper class is imported as a function. To import a method, enter the following into your DRL file:

import function my.package.Foo.hello

8.7.2. Calling Function Declaration Example

Irrespective of the way the function is defined or imported, you use a function by calling it by its name, in the consequence or inside a semantic code block. This is shown below:

rule "Using a Static Function"
when
  eval(true)
then
  System.out.println(hello("Bob"));
end

8.7.3. Type Declarations

Type declarations have two main goals in the rules engine: to allow the declaration of new types, and to allow the declaration of metadata for types.

Table 8.1. Type Declaration Roles
RoleDescription

Declaring new types

Red Hat JBoss BRMS uses plain Java objects as facts out of the box. However, if you wish to define the model directly to the rules engine, you can do so by declaring a new type. You can also declare a new type when there is a domain model already built and you want to complement this model with additional entities that are used mainly during the reasoning process.

Declaring metadata

Facts may have meta information associated to them. Examples of meta information include any kind of data that is not represented by the fact attributes and is consistent among all instances of that fact type. This meta information may be queried at runtime by the engine and used in the reasoning process.

8.7.4. Declaring New Types

To declare a new type, the keyword declare is used, followed by the list of fields and the keyword end. A new fact must have a list of fields, otherwise the engine will look for an existing fact class in the classpath and raise an error if not found.

8.7.5. Declaring New Fact Type Example

In this example, a new fact type called Address is used. This fact type will have three attributes: number, streetName and city. Each attribute has a type that can be any valid Java type, including any other class created by the user or other fact types previously declared:

declare Address
  number : int
  streetName : String
  city : String
end

8.7.6. Declaring New Fact Type Additional Example

This fact type declaration uses a Person example. dateOfBirth is of the type java.util.Date (from the Java API) and address is of the fact type Address.

declare Person
  name : String
  dateOfBirth : java.util.Date
  address : Address
end

8.7.7. Using Import Example

To avoid using fully qualified class names, use the import statement:

import java.util.Date

declare Person
  name : String
  dateOfBirth : Date
  address : Address
end

8.7.8. Generated Java Classes

When you declare a new fact type, Red Hat JBoss BRMS generates bytecode that implements a Java class representing the fact type. The generated Java class is a one-to-one Java Bean mapping of the type definition.

8.7.9. Generated Java Class Example

This is an example of a generated Java class using the Person fact type:

public class Person implements Serializable {
  private String name;
  private java.util.Date dateOfBirth;
  private Address address;

  // empty constructor
  public Person() {...}

  // constructor with all fields
  public Person(String name, Date dateOfBirth, Address address) {...}

  // if keys are defined, constructor with keys
  public Person( ...keys... ) {...}

  // getters and setters
  // equals/hashCode
  // toString
}

8.7.10. Using Declared Types in Rules Example

Since the generated class is a simple Java class, it can be used transparently in the rules like any other fact:

rule "Using a declared Type"
when
  $p : Person(name == "Bob")
then
  // Insert Mark, who is Bob's manager.
  Person mark = new Person();
  mark.setName("Mark");
  insert(mark);
end

8.7.11. Declaring Metadata

Metadata may be assigned to several different constructions in Red Hat JBoss BRMS, such as fact types, fact attributes and rules. Red Hat JBoss BRMS uses the at sign (@) to introduce metadata and it always uses the form:

@metadata_key(metadata_value)

The parenthesized metadata_value is optional.

8.7.12. Working with Metadata Attributes

Red Hat JBoss BRMS allows the declaration of any arbitrary metadata attribute. Some have special meaning to the engine, while others are available for querying at runtime. Red Hat JBoss BRMS allows the declaration of metadata both for fact types and for fact attributes. Any metadata that is declared before the attributes of a fact type are assigned to the fact type, while metadata declared after an attribute are assigned to that particular attribute.

8.7.13. Declaring Metadata Attribute with Fact Types Example

This is an example of declaring metadata attributes for fact types and attributes. There are two metadata items declared for the fact type (@author and @dateOfCreation) and two more defined for the name attribute (@key and @maxLength). The @key metadata has no required value, and so the parentheses and the value were omitted:

import java.util.Date

declare Person
  @author(Bob)
  @dateOfCreation(01-Feb-2009)

  name : String @key @maxLength(30)
  dateOfBirth : Date
  address : Address
end

8.7.14. @position Attribute

The @position attribute can be used to declare the position of a field, overriding the default declared order. This is used for positional constraints in patterns.

8.7.15. @position Example

This is what the @position attribute looks like in use:

declare Cheese
  name : String @position(1)
  shop : String @position(2)
  price : int @position(0)
end

8.7.16. Predefined Class Level Annotations

@role( <fact\|event>)
This attribute can be used to assign roles to facts and events.
@typesafe(<boolean>)
By default, all type declarations are compiled with type safety enabled. @typesafe(false) provides a means to override this behavior by permitting a fall-back, to type unsafe evaluation where all constraints are generated as MVEL constraints and executed dynamically. This is useful when dealing with collections that do not have any generics or mixed type collections.
@timestamp(<attribute name>)
Creates a timestamp.
@duration(<attribute name>)
Sets a duration for the implementation of an attribute.
@expires(<time interval>)
Allows you to define when the attribute should expire.
@propertyChangeSupport
Facts that implement support for property changes as defined in the Javabean spec can now be annotated so that the engine register itself to listen for changes on fact properties.
@propertyReactive
Makes the type property reactive.

8.7.17. @key Attribute Functions

Declaring an attribute as a key attribute has two major effects on generated types:

  1. The attribute is used as a key identifier for the type, and thus the generated class implements the equals() and hashCode() methods taking the attribute into account when comparing instances of this type.
  2. Red Hat JBoss BRMS generates a constructor using all the key attributes as parameters.

8.7.18. @key Declaration Example

This is an example of @key declarations for a type. Red Hat JBoss BRMS generates equals() and hashCode() methods that checks the firstName and lastName attributes to determine if two instances of Person are equal to each other. It does not check the age attribute. It also generates a constructor taking firstName and lastName as parameters:

declare Person
  firstName : String @key
  lastName : String @key
  age : int
end

8.7.19. Creating Instance with Key Constructor Example

This is what creating an instance using the key constructor looks like:

Person person = new Person("John", "Doe");

8.7.20. Positional Arguments

Patterns support positional arguments on type declarations and are defined by the @position attribute.

Positional arguments are when you do not need to specify the field name, as the position maps to a known named field. That is, Person(name == "mark") can be rewritten as Person("mark";). The semicolon ; is important so that the engine knows that everything before it is a positional argument. You can mix positional and named arguments on a pattern by using the semicolon ; to separate them. Any variables used in a positional that have not yet been bound will be bound to the field that maps to that position.

8.7.21. Positional Argument Example

Observe the example below:

declare Cheese
  name : String
  shop : String
  price : int
end

The default order is the declared order, but this can be overridden using @position.

declare Cheese
  name : String @position(1)
  shop : String @position(2)
  price : int @position(0)
end

8.7.22. @position Annotation

The @position annotation can be used to annotate original pojos on the classpath. Currently only fields on classes can be annotated. Inheritance of classes is supported, but not interfaces of methods.

8.7.23. Example Patterns

These example patterns have two constraints and a binding. The semicolon ; is used to differentiate the positional section from the named argument section. Variables and literals and expressions using just literals are supported in positional arguments, but not variables:

Cheese("stilton", "Cheese Shop", p;)
Cheese("stilton", "Cheese Shop"; p : price)
Cheese("stilton"; shop == "Cheese Shop", p : price)
Cheese(name == "stilton"; shop == "Cheese Shop", p : price)

8.8. Backward-Chaining

8.8.1. Backward-Chaining Systems

Backward-Chaining is a feature recently added to the BRMS Engine. This process is often referred to as derivation queries, and it is not as common compared to reactive systems since BRMS is primarily reactive forward chaining. That is, it responds to changes in your data. The backward-chaining added to the engine is for product-like derivations.

8.8.2. Cloning Transitive Closures

Figure 8.3. Reasoning Graph

6135

The previous chart demonstrates a House example of transitive items. A similar reasoning chart can be created by implementing the following rules:

Configuring Transitive Closures

  1. First, create some java rules to develop reasoning for transitive items. It inserts each of the locations.
  2. Next, create the Location class; it has the item and where it is located.
  3. Type the rules for the House example as depicted below:

    ksession.insert(new Location("office", "house"));
    ksession.insert(new Location("kitchen", "house"));
    ksession.insert(new Location("knife", "kitchen"));
    ksession.insert(new Location("cheese", "kitchen"));
    ksession.insert(new Location("desk", "office"));
    ksession.insert(new Location("chair", "office"));
    ksession.insert(new Location("computer", "desk"));
    ksession.insert(new Location("drawer", "desk"));
  4. A transitive design is created in which the item is in its designated location such as a "desk" located in an "office."

    Figure 8.4. Transitive Reasoning Graph of House

    An example transitive closure graph.
Note

Notice compared to the previous graph, there is no "key" item in a "drawer" location. This will become evident in a later topic.

8.8.3. Defining Query

  1. Create a query to search for data inserted into the rule engine:

    query isContainedIn(String x, String y)
      Location(x, y;)
      or
      (Location(z, y;) and isContainedIn(x, z;))
    end

    Note that the query in the example above is recursive, calling isContainedIn.

  2. To see implementation details, create a rule similar to the following for printing each string inserted into the system:

    rule "go" salience 10
    when
      $s : String()
    then
      System.out.println($s);
    end
  3. Create a rule that uses the isContainedIn query from the first step.

    rule "go1"
    when
      String(this == "go1")
      isContainedIn("office", "house";)
    then
      System.out.println("office is in the house");
    end

    The rule checks whether the item office is in the location house. The query created in the first step is triggered when the string go1 is inserted.

  4. Insert a fact into the engine and call fireAllRules().

    ksession.insert("go1");
    ksession.fireAllRules();

    The output of the engine should look like the following:

    go1
    office is in the house

    The following holds:

    • The salience ensures that the go rule is fired first and the message output is printed.
    • The go1 rule matches the query and office is in the house is printed.

8.8.4. Transitive Closure Example

Creating Transitive Closure

  1. Create a transitive closure by implementing the following rule:

    rule "go2"
    when
      String(this == "go2")
      isContainedIn("drawer", "house";)
    then
      System.out.println("Drawer in the House");
    end
  2. Recall from the cloning transitive closure topic, there was no instance of "drawer" in "house." "Drawer" was located in "desk."

    Figure 8.5. Transitive Reasoning Graph of a Drawer.

    An example transitive closure graph.
  3. Use the previous query for this recursive information.

    query isContainedIn(String x, String y)
      Location(x, y;)
      or
      (Location(z, y;) and isContainedIn(x, z;))
    end
  4. Create the go2, insert it into the engine, and call the fireAllRules.

    ksession.insert( "go2" );
    ksession.fireAllRules();
    ---
    go2
    Drawer in the House

    When the rule is fired, it correctly tells you go2 has been inserted and that the "drawer" is in the "house."

  5. Check how the engine determined this outcome.

    • The query has to recurse down several levels to determine this.
    • Instead of using Location(x, y;), the query uses the value of (z, y;) since "drawer" is not in "house."
    • The z is currently unbound which means it has no value and will return everything that is in the argument.
    • y is currently bound to "house," so z will return "office" and "kitchen."
    • Information is gathered from "office" and checks recursively if the "drawer" is in the "office." The following query line is being called for these parameters: isContainedIn(x ,z;)

      There is no instance of "drawer" in "office"; therefore, it does not match. With z being unbound, it will return data that is within the "office", and it will gather that z == desk.

      isContainedIn(x==drawer, z==desk)

      isContainedIn recurses three times. On the final recurse, an instance triggers of "drawer" in the "desk".

      Location(x==drawer, y==desk)

      This matches on the first location and recurses back up, so we know that "drawer" is in the "desk", the "desk" is in the "office", and the "office" is in the "house"; therefore, the "drawer" is in the "house" and returns true.

8.8.5. Reactive Transitive Queries

Creating a Reactive Transitive Query

  1. Create a reactive transitive query by implementing the following rule:

    rule "go3"
    when
      String( this == "go3" )
      isContainedIn("key", "office"; )
    then
      System.out.println( "Key in the Office" );
    end

    Reactive transitive queries can ask a question even if the answer can not be satisfied. Later, if it is satisfied, it will return an answer.

    Note

    Recall from the cloning transitive closures example that there was no key item in the system.

  2. Use the same query for this reactive information.

    query isContainedIn(String x, String y)
      Location(x, y;)
      or
      (Location(z, y;) and isContainedIn(x, z;))
    end
  3. Create the go3, insert it into the engine, and call the fireAllRules.

    ksession.insert("go3");
    ksession.fireAllRules();
    ---
    go3
    • go3 is inserted
    • fireAllRules(); is called

    The first rule that matches any String returns go3 but nothing else is returned because there is no answer; however, while go3 is inserted in the system, it will continuously wait until it is satisfied.

  4. Insert a new location of "key" in the "drawer":

    ksession.insert( new Location("key", "drawer"));
    ksession.fireAllRules();
    ---
    Key in the Office

    This new location satisfies the transitive closure because it is monitoring the entire graph. In addition, this process now has four recursive levels in which it goes through to match and fire the rule.

8.8.6. Queries with Unbound Arguments

Creating Unbound Argument Query

  1. Create a query with unbound arguments by implementing the following rule:

    rule "go4"
    when
      String(this == "go4")
      isContainedIn(thing, "office";)
    then
      System.out.println("thing" + thing + "is in the office");
    end

    This rule is asking for everything in the "office", and it will tell everything in all the rows below. The unbound argument (out variable thing) in this example will return every possible value; accordingly, it is very similar to the z value used in the reactive transitive query example.

  2. Use the query for the unbound arguments.

    query isContainedIn(String x, String y)
      Location(x, y;)
      or
      (Location(z, y;) and isContainedIn(x, z;))
    end
  3. Create the go4, insert it into the engine, and call the fireAllRules.

    ksession.insert( "go4" );
    ksession.fireAllRules();
    ---
    go4
    thing Key is in the Office
    thing Computer is in the Office
    thing Drawer is in the Office
    thing Desk is in the Office
    thing Chair is in the Office

    When go4 is inserted, it returns all the previous information that is transitively below "office."

8.8.7. Multiple Unbound Arguments

Creating Multiple Unbound Arguments

  1. Create a query with multiple unbound arguments by implementing the following rule:

    rule "go5"
    when
      String(this == "go5")
      isContainedIn(thing, location;)
    then
      System.out.println("thing" + thing + "is in" + location);
    end

    Both thing and location are unbound out variables, and without bound arguments, everything is called upon.

  2. Use the query for multiple unbound arguments.

    query isContainedIn(String x, String y)
      Location(x, y;)
      or
      (Location(z, y;) and isContainedIn(x, z;))
    end
  3. Create the go5, insert it into the engine, and call the fireAllRules.

    ksession.insert("go5");
    ksession.fireAllRules();
    ---
    go5
    thing Knife is in House
    thing Cheese is in House
    thing Key is in House
    thing Computer is in House
    thing Drawer is in House
    thing Desk is in House
    thing Chair is in House
    thing Key is in Office
    thing Computer is in Office
    thing Drawer is in Office
    thing Key is in Desk
    thing Office is in House
    thing Computer is in Desk
    thing Knife is in Kitchen
    thing Cheese is in Kitchen
    thing Kitchen is in House
    thing Key is in Drawer
    thing Drawer is in Desk
    thing Desk is in Office
    thing Chair is in Office

    When go5 is called, it returns everything within everything.

8.9. Type Declaration

8.9.1. Declaring Metadata for Existing Types

Red Hat JBoss BRMS allows the declaration of metadata attributes for existing types in the same way as when declaring metadata attributes for new fact types. The only difference is that there are no fields in that declaration.

8.9.2. Declaring Metadata for Existing Types Example

This example shows how to declare metadata for an existing type:

import org.drools.examples.Person

declare Person
  @author(Bob)
  @dateOfCreation(01-Feb-2009)
end

8.9.3. Declaring Metadata Using Fully Qualified Class Name Example

This example shows how you can declare metadata using the fully qualified class name instead of using the import annotation:

declare org.drools.examples.Person
  @author(Bob)
  @dateOfCreation(01-Feb-2009)
end

8.9.4. Parametrized Constructors for Declared Types Example

For a declared type like the following:

declare Person
  firstName : String @key
  lastName : String @key
  age : int
end

The compiler will implicitly generate 3 constructors: one without parameters, one with the @key fields and one with all fields.

Person() // parameterless constructor
Person(String firstName, String lastName)
Person(String firstName, String lastName, int age)

8.9.5. Non-Typesafe Classes

The @typesafe(BOOLEAN) annotation has been added to type declarations. By default all type declarations are compiled with type safety enabled. @typesafe(false) provides a means to override this behaviour by permitting a fall-back, to type unsafe evaluation where all constraints are generated as MVEL constraints and executed dynamically. This is useful when dealing with collections that do not have any generics or mixed type collections.

8.9.6. Accessing Declared Types from Application Code

Sometimes applications need to access and handle facts from the declared types. In such cases, Red Hat JBoss BRMS provides a simplified API for the most common fact handling the application wishes to do. A declared fact belongs to the package where it is declared.

8.9.7. Declaring Type

This illustrates the process of declaring a type:

package org.drools.examples

import java.util.Date

declare Address
  street : String
  city : String
  code : String
end

declare Person
  name : String
  dateOfBirth : Date
  address : Address
end

8.9.8. Handling Declared Fact Types Through API Example

This example illustrates the handling of declared fact types through the API:

import java.util.Date;

import org.kie.api.definition.type.FactType;
import org.kie.api.KieBase;
import org.kie.api.runtime.KieSession;

...

// Get a reference to a knowledge base with a declared type:
KieBase kbase = ...

// Get the declared FactType:
FactType personType = kbase.getFactType("org.drools.examples", "Person");

// Handle the type as necessary:
// Create instances:
Object bob = personType.newInstance();

// Set attributes values:
personType.set(bob, "name", "Bob" );
personType.set(bob, "dateOfBirth", new Date());
personType.set(bob, "address", new Address("King's Road","London","404"));

// Insert fact into a session:
KieSession ksession = ...
ksession.insert(bob);
ksession.fireAllRules();

// Read attributes:
String name = (String) personType.get(bob, "name");
Date date = (Date) personType.get(bob, "dateOfBirth");

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

The API also includes other helpful methods, like setting all the attributes at once, reading values from a Map, or reading all attributes at once, into a Map.

8.9.9. Type Declaration Extends

Type declarations support the extends keyword for inheritance. To extend a type declared in Java by a DRL declared subtype, repeat the supertype in a declare statement without any fields.

8.9.10. Type Declaration Extends Example

This illustrates the use of the extends annotation:

import org.people.Person

declare Person
end

declare Student extends Person
  school : String
end

declare LongTermStudent extends Student
  years : int
  course : String
end

8.9.11. Traits

Traits allow you to model multiple dynamic types which do not fit naturally in a class hierarchy. A trait is an interface that can be applied (and eventually removed) to an individual object at runtime. To create a trait out of an interface, a @format(trait) annotation is added to its declaration in DRL.

8.9.12. Traits Example

declare GoldenCustomer
  @format(trait)
  // fields will map to getters/setters
  code     : String
  balance  : long
  discount : int
  maxExpense : long
end

In order to apply a trait to an object, the new don keyword is added:

when
  $c : Customer()
then
  GoldenCustomer gc = don($c, Customer.class);
end

8.9.13. Core Objects and Traits

When a core object dons a trait, a proxy class is created on the fly (one such class will be generated lazily for each core/trait class combination). The proxy instance, which wraps the core object and implements the trait interface, is inserted automatically and will possibly activate other rules. An immediate advantage of declaring and using interfaces, getting the implementation proxy for free from the engine, is that multiple inheritance hierarchies can be exploited when writing rules. The core classes, however, need not implement any of those interfaces statically, also facilitating the use of legacy classes as cores. Any object can don a trait. For efficiency reasons, however, you can add the @traitable annotation to a declared bean class to reduce the amount of glue code that the compiler will have to generate. This is optional and will not change the behavior of the engine.

8.9.14. @traitable Example

This illustrates the use of the @traitable annotation:

declare Customer
  @traitable
  code    : String
  balance : long
end

8.9.15. Writing Rules with Traits

The only connection between core classes and trait interfaces is at the proxy level. (That is, a trait is not specifically tied to a core class.) This means that the same trait can be applied to totally different objects. For this reason, the trait does not transparently expose the fields of its core object. When writing a rule using a trait interface, only the fields of the interface will be available, as usual. However, any field in the interface that corresponds to a core object field, will be mapped by the proxy class.

8.9.16. Rules with Traits Example

This example illustrates the trait interface being mapped to a field:

when
  $o: OrderItem($p : price, $code : custCode)
  $c: GoldenCustomer(code == $code, $a : balance, $d: discount)
then
  $c.setBalance( $a - $p*$d );
end

8.9.17. Hidden Fields

Hidden fields are fields in the core class not exposed by the interface.

8.9.18. Two-Part Proxy

The two-part proxy has been developed to deal with soft and hidden fields which are not processed intuitively. Internally, proxies are formed by a proper proxy and a wrapper. The former implements the interface, while the latter manages the core object fields, implementing a name/value map to supports soft fields. The proxy uses both the core object and the map wrapper to implement the interface, as needed.

8.9.19. Wrappers

The wrapper provides a looser form of typing when writing rules. However, it has also other uses. The wrapper is specific to the object it wraps, regardless of how many traits have been attached to an object. All the proxies on the same object will share the same wrapper. Additionally, the wrapper contains a back-reference to all proxies attached to the wrapped object, effectively allowing traits to see each other.

8.9.20. Wrapper Example

This is an example of using the wrapper:

when
  $sc : GoldenCustomer($c : code, // hard getter
                       $maxExpense : maxExpense > 1000 // soft getter)
then
  $sc.setDiscount( ... ); // soft setter
end

8.9.21. Wrapper with isA Annotation Example

This illustrates a wrapper in use with the isA annotation:

$sc : GoldenCustomer($maxExpense : maxExpense > 1000, this isA "SeniorCustomer")

8.9.22. Removing Traits

The business logic may require that a trait is removed from a wrapped object. There are two ways to do so:

Logical don

Results in a logical insertion of the proxy resulting from the traiting operation.

then
  don($x, // core object
      Customer.class, // trait class
      true // optional flag for logical insertion)
The shed keyword

The shed keyword causes the retraction of the proxy corresponding to the given argument type.

then
  Thing t = shed($x, GoldenCustomer.class)

This operation returns another proxy implementing the org.drools.factmodel.traits.Thing interface, where the getFields() and getCore() methods are defined. Internally, all declared traits are generated to extend this interface (in addition to any others specified). This allows to preserve the wrapper with the soft fields which would otherwise be lost.

8.10. Rule Attributes

For the list of all rule attributes and their description, see Section 8.3.2, “Soft Keywords”.

See an example of rule attributes below:

rule "my rule"
  salience 42
  agenda-group "number-1"
when
  ...

8.10.1. Timer Attribute Example

This is what the timer attribute looks like:

timer(int: INITIAL_DELAY REPEAT_INTERVAL?)
timer(int: 30s)
timer(int: 30s 5m)

timer(cron: CRON_EXPRESSION)
timer(cron:* 0/15 * * * ?)

8.10.2. Timers

The following timers are available in Red Hat JBoss BRMS:

Interval
Interval (indicated by int:) timers follow the semantics of java.util.Timer objects, with an initial delay and an optional repeat interval.
Cron
Cron (indicated by cron:) timers follow standard Unix cron expressions.

A rule controlled by a timer becomes active when it matches, and once for each individual match. Its consequence is executed repeatedly, according to the timer’s settings. This stops as soon as the condition doesn’t match any more.

Consequences are executed even after control returns from a call to fireUntilHalt. Moreover, the Engine remains reactive to any changes made to the Working Memory. For instance, removing a fact that was involved in triggering the timer rule’s execution causes the repeated execution to terminate, or inserting a fact so that some rule matches will cause that rule to fire. But the Engine is not continually active, only after a rule fires, for whatever reason. Thus, reactions to an insertion done asynchronously will not happen until the next execution of a timer-controlled rule.

Disposing a session puts an end to all timer activity.

8.10.3. Cron Timer Example

This is what the Cron timer looks like:

rule "Send SMS every 15 minutes"
  timer (cron:* 0/15 * * * ?)
when
  $a : Alarm(on == true)
then
  channels["sms"].insert(new Sms($a.mobileNumber, "The alarm is still on");
end

8.10.4. Calendars

Calendars are used to control when rules can fire. Red Hat JBoss BRMS uses the Quartz calendar.

8.10.5. Quartz Calendar Example

This is what the Quartz calendar looks like:

Calendar weekDayCal = QuartzHelper.quartzCalendarAdapter(org.quartz.Calendar quartzCal)

8.10.6. Registering Calendar

Procedure: Task

  1. Start a StatefulKnowledgeSession.
  2. Use the following code to register the calendar:

    ksession.getCalendars().set("weekday", weekDayCal);
  3. If you wish to utilize the calendar and a timer together, use the following code:

    rule "Weekdays are high priority"
      calendars "weekday"
      timer (int:0 1h)
    when
      Alarm()
    then
      send("priority high - we have an alarm”);
    end
    
    rule "Weekend are low priority"
      calendars "weekend"
      timer (int:0 4h)
    when
      Alarm()
    then
      send("priority low - we have an alarm”);
    end

8.10.7. Left Hand Side

The Left Hand Side (LHS) is a common name for the conditional part of the rule. It consists of zero or more conditional elements. If the LHS is empty, it will be considered as a condition element that is always true and it will be activated once, when a new WorkingMemory session is created.

8.10.8. Conditional Elements

Conditional elements work on one or more patterns. The most common conditional element is and. It is implicit when you have multiple patterns in the LHS of a rule that is not connected in any way.

8.10.9. Rule Without Conditional Element Example

This is what a rule without a conditional element looks like:

rule "no CEs"
when
  // empty
then
  ... // actions (executed once)
end

// The above rule is internally rewritten as:

rule "eval(true)"
when
  eval( true )
then
  ... // actions (executed once)
end

8.11. Patterns

A pattern element is the most important conditional element. It can potentially match on each fact that is inserted in the working memory. A pattern contains constraints and has an optional pattern binding.

8.11.1. Pattern Example

This is what a pattern looks like:

rule "Two unconnected patterns"
when
  Pattern1()
  Pattern2()
then
    ... // actions
end

// The above rule is internally rewritten as:

rule "Two and connected patterns"
when
  Pattern1()
  and Pattern2()
then
  ... // actions
end
Note

An and cannot have a leading declaration binding. This is because a declaration can only reference a single fact at a time, and when the and is satisfied it matches both facts.

8.11.2. Pattern Matching

A pattern matches against a fact of the given type. The type need not be the actual class of some fact object. Patterns may refer to superclasses or even interfaces, thereby potentially matching facts from many different classes. The constraints are defined inside parentheses.

8.11.3. Pattern Binding

Patterns can be bound to a matching object. This is accomplished using a pattern binding variable such as $p.

8.11.4. Pattern Binding with Variable Example

This is what pattern binding using a variable looks like:

rule ...
when
  $p : Person()
then
  System.out.println("Person " + $p);
end
Note

The prefixed dollar symbol ($) is not mandatory.

8.11.5. Constraints

A constraint is an expression that returns true or false. For example, you can have a constraint that states "five is smaller than six".

8.12. Elements and Variables

8.12.1. Property Access on Java Beans (POJOs)

Any bean property can be used directly. A bean property is exposed using a standard Java bean getter: a method getMyProperty() (or isMyProperty() for a primitive boolean) which takes no arguments and return something.

Red Hat JBoss BRMS uses the standard JDK Introspector class to do this mapping, so it follows the standard Java bean specification.

Warning

Property accessors must not change the state of the object in a way that may effect the rules. The rule engine effectively caches the results of its matching in between invocations to make it faster.

8.12.2. POJO Example

This is what the bean property looks like:

Person(age == 50)

// this is the same as:
Person(getAge() == 50)
The age property
The age property is written as age in DRL instead of the getter getAge().
Property accessors
You can use property access (age) instead of getters explicitly (getAge()) because of performance enhancements through field indexing.

8.12.3. Working with POJOs

Procedure: Task

  1. Observe the example below:

    public int getAge() {
      Date now = DateUtil.now(); // Do NOT do this.
      return DateUtil.differenceInYears(now, birthday);
    }
  2. To solve this, insert a fact that wraps the current date into working memory and update that fact between fireAllRules as needed.

8.12.4. POJO Fallbacks

When working with POJOs, a fallback method is applied. If the getter of a property cannot be found, the compiler will resort to using the property name as a method name and without arguments. Nested properties are also indexed.

8.12.5. Fallback Example

This is what happens when a fallback is implemented:

Person(age == 50)

// If Person.getAge() does not exists, this falls back to:
Person(age() == 50)

This is what it looks like as a nested property:

Person(address.houseNumber == 50)

// this is the same as:
Person(getAddress().getHouseNumber() == 50)
Warning

In a stateful session, care should be taken when using nested accessors as the Working Memory is not aware of any of the nested values and does not know when they change. Consider them immutable while any of their parent references are inserted into the Working Memory. If you wish to modify a nested value you should mark all of the outer facts as updated. In the above example, when the houseNumber changes, any Person with that Address must be marked as updated.

8.12.6. Java Expressions

Table 8.2. Java Expressions
CapabilityExample

You can use any Java expression that returns a boolean as a constraint inside the parentheses of a pattern. Java expressions can be mixed with other expression enhancements, such as property access.

Person(age == 50)

You can change the evaluation priority by using parentheses, as in any logic or mathematical expression.

Person(age > 100 && (age % 10 == 0))

You can reuse Java methods.

Person(Math.round(weight / (height * height)) < 25.0)

Type coercion is always attempted if the field and the value are of different types; exceptions will be thrown if a bad coercion is attempted.

Person(age == "10") // "10" is coerced to 10
Warning

Methods must not change the state of the object in a way that may affect the rules. Any method executed on a fact in the LHS should be a read only method.

Warning

The state of a fact should not change between rule invocations (unless those facts are marked as updated to the working memory on every change):

Person(System.currentTimeMillis() % 1000 == 0) // Do NOT do this.
Important

All operators have normal Java semantics except for == and !=.

The == operator has null-safe equals() semantics:

// Similar to: java.util.Objects.equals(person.getFirstName(), "John")
// so (because "John" is not null) similar to:
// "John".equals(person.getFirstName())
Person(firstName == "John")

The != operator has null-safe !equals() semantics:

// Similar to: !java.util.Objects.equals(person.getFirstName(), "John")
Person(firstName != "John")

8.12.7. Comma-Separated Operators

The comma character (,) is used to separate constraint groups. It has implicit and connective semantics.

The comma operator is used at the top-level constraint as it makes them easier to read and the engine will be able to optimize them.

8.12.8. Comma-Separated Operator Example

The following illustrates comma-separated scenarios in implicit and connective semantics:

// Person is at least 50 and weighs at least 80 kg.
Person(age > 50, weight > 80)
// Person is at least 50, weighs at least 80 kg and is taller than 2 meter.
Person(age > 50, weight > 80, height > 2)
Note

The comma (,) operator cannot be embedded in a composite constraint expression, such as parentheses.

8.12.9. Binding Variables

You can bind properties to variables in Red Hat JBoss BRMS. It allows for faster execution and performance.

8.12.10. Binding Variable Examples

This is an example of a property bound to a variable:

// Two people of the same age:
Person($firstAge : age) // binding
Person(age == $firstAge) // constraint expression
Note

For backwards compatibility reasons, it’s allowed (but not recommended) to mix a constraint binding and constraint expressions as such:

// Not recommended:
Person($age : age * 2 < 100)
// Recommended (separates bindings and constraint expressions):
Person(age * 2 < 100, $age : age)

8.12.11. Unification

You can unify arguments across several properties. While positional arguments are always processed with unification, the unification symbol, :=, exists for named arguments.

8.12.12. Unification Example

This is what unifying two arguments looks like:

Person($age := age)
Person($age := age)

8.12.13. Options and Operators in Red Hat JBoss BRMS

Date literal

The date format dd-mmm-yyyy is supported by default. You can customize this by providing an alternative date format mask as the System property named drools.dateformat. If more control is required, use a restriction.

Cheese(bestBefore < "27-Oct-2009")
List and Map access

You can directly access a List value by index.

// Same as childList(0).getAge() == 18
Person(childList[0].age == 18)
Value key

You can directly access a Map value by key.

// Same as credentialMap.get("jsmith").isValid()
Person(credentialMap["jsmith"].valid)
Abbreviated combined relation condition

This allows you to place more than one restriction on a field using the restriction connectives && or \|\|. Grouping via parentheses is permitted, resulting in a recursive syntax pattern.

// Simple abbreviated combined relation condition using a single &&
Person(age > 30 && < 40)
// Complex abbreviated combined relation using groupings
Person(age ((> 30 && < 40) \|\| (> 20 && < 25)))
// Mixing abbreviated combined relation with constraint connectives
Person(age > 30 && < 40 \|\| location == "london")
Operators

Operators can be used on properties with natural ordering. For example, for Date fields, < means before, for String fields, it means alphabetically lower.

Person(firstName < $otherFirstName)
Person(birthDate < $otherBirthDate)
Operator matches

Matches a field against any valid Java regular expression. Typically that regexp is a string literal, but variables that resolve to a valid regexp are also allowed. It only applies on String properties. Using matches against a null value always evaluates to false.

Cheese(type matches "(Buffalo)?\\S*Mozarella")
Operator not matches

The operator returns true if the String does not match the regular expression. The same rules apply as for the matches operator. It only applies on String properties.

Cheese(type not matches "(Buffulo)?\\S*Mozarella")
The operator contains

The operator contains is used to check whether a field that is a Collection or array and contains the specified value. It only applies on Collection properties.

CheeseCounter(cheeses contains "stilton") // contains with a String literal
CheeseCounter(cheeses contains $var) // contains with a variable
The operator not contains

The operator not contains is used to check whether a field that is a Collection or array and does not contain the specified value. It only applies on Collection properties.

CheeseCounter(cheeses not contains "cheddar") // not contains with a String literal
CheeseCounter(cheeses not contains $var) // not contains with a variable
The operator memberOf

The operator memberOf is used to check whether a field is a member of a collection or array; that collection must be a variable.

CheeseCounter(cheese memberOf $matureCheeses)
The operator not memberOf

The operator not memberOf is used to check whether a field is not a member of a collection or array. That collection must be a variable.

CheeseCounter(cheese not memberOf $matureCheeses)
The operator soundslike

This operator is similar to matches, but it checks whether a word has almost the same sound (using English pronunciation) as the given value.

// match cheese "fubar" or "foobar"
Cheese(name soundslike 'foobar')
The operator str

The operator str is used to check whether a field that is a String starts with or ends with a certain value. It can also be used to check the length of the String.

Message(routingValue str[startsWith] "R1")
Message(routingValue str[endsWith] "R2")
Message(routingValue str[length] 17)
Compound Value Restriction

Compound value restriction is used where there is more than one possible value to match. Currently only the in and not in evaluators support this. The second operand of this operator must be a comma-separated list of values, enclosed in parentheses. Values may be given as variables, literals, return values or qualified identifiers. Both evaluators are actually syntactic sugar, internally rewritten as a list of multiple restrictions using the operators != and ==.

Person($cheese : favouriteCheese)
Cheese(type in ("stilton", "cheddar", $cheese))
Inline Eval Operator (deprecated)

An inline eval constraint can use any valid dialect expression as long as it results to a primitive boolean. The expression must be constant over time. Any previously bound variable, from the current or previous pattern, can be used; autovivification is also used to auto-create field binding variables. When an identifier is found that is not a current variable, the builder looks to see if the identifier is a field on the current object type, if it is, the field binding is auto-created as a variable of the same name. This is called autovivification of field variables inside of inline eval’s.

Person(girlAge : age, sex = "F")
Person(eval(age == girlAge + 2), sex = 'M') // eval() is actually obsolete in this example

8.12.14. Operator Precedence

Table 8.3. Operator Precedence
Operator TypeOperatorsNotes

(nested) property access

.

Not normal Java semantics.

List/Map access

[ ]

Not normal Java semantics.

constraint binding

:

Not normal Java semantics.

multiplicative

* /%

 

additive

+ -

 

shift

<< >> >>>

 

relational

< > <= >= instanceof

 

equality

== !=

Does not use normal Java (not) same semantics: uses (not) equals semantics instead.

non-short circuiting AND

&

 

non-short circuiting exclusive OR

^

 

non-short circuiting inclusive OR

|

 

logical AND

&&

 

logical OR

||

 

ternary

? :

 

comma-separated AND

,

Not normal Java semantics.

8.12.15. Fine Grained Property Change Listeners

This feature allows the pattern matching to only react to modification of properties actually constrained or bound inside of a given pattern. This helps with performance and recursion and avoid artificial object splitting.

Note

By default this feature is off in order to make the behavior of the rule engine backward compatible with the former releases. When you want to activate it on a specific bean you have to annotate it with @propertyReactive.

8.12.16. Fine Grained Property Change Listener Example

DRL example
declare Person
  @propertyReactive
  firstName : String
  lastName : String
end
Java class example
@PropertyReactive
 public static class Person {
 private String firstName;
 private String lastName;
  }

8.12.17. Working with Fine Grained Property Change Listeners

Using these listeners means you do not need to implement the no-loop attribute to avoid an infinite recursion. The engine recognizes that the pattern matching is done on the property while the RHS of the rule modifies other the properties. On Java classes, you can also annotate any method to say that its invocation actually modifies other properties.

8.12.18. Using Patterns with @watch

Annotating a pattern with @watch allows you to modify the inferred set of properties for which that pattern will react. The properties named in the @watch annotation are added to the ones automatically inferred. You can explicitly exclude one or more of them by beginning their name with a ! and to make the pattern to listen for all or none of the properties of the type used in the pattern respectively with the wildcards * and !*.

8.12.19. @watch Example

This is the @watch annotation in a rule’s LHS:

// Listens for changes on both firstName (inferred) and lastName:
Person(firstName == $expectedFirstName) @watch(lastName)

// Listens for all the properties of the Person bean:
Person(firstName == $expectedFirstName) @watch(*)

// Listens for changes on lastName and explicitly exclude firstName:
Person(firstName == $expectedFirstName) @watch(lastName, !firstName)

// Listens for changes on all the properties except the age one:
Person(firstName == $expectedFirstName) @watch(*, !age)
Note

Since it does not make sense to use this annotation on a pattern using a type not annotated with @PropertyReactive the rule compiler will raise a compilation error if you try to do so. Also the duplicated usage of the same property in @watch (for example like in: @watch(firstName, ! firstName)) will end up in a compilation error.

8.12.20. Using @PropertySpecificOption

You can enable @watch by default or completely disallow it using the on option of the KnowledgeBuilderConfiguration. This new PropertySpecificOption can have one of the following 3 values:

  • DISABLED: the feature is turned off and all the other related annotations are just ignored.
  • ALLOWED: this is the default behavior: types are not property reactive unless they are not annotated with @PropertySpecific.
  • ALWAYS: all types are property reactive by default.

Alternatively, you can use the drools.propertySpecific system property. For example, if you use Red Hat JBoss EAP, add the property into EAP_HOME/standalone/configuration/standalone.xml:

<system-properties>
  ...
  <property name="drools.propertySpecific" value="DISABLED"/>
  ...
</system-properties>

8.12.21. Basic Conditional Elements

and

The conditional element and is used to group other conditional elements into a logical conjunction. Red Hat JBoss BRMS supports both prefix and and infix and. It supports explicit grouping with parentheses. You can also use traditional infix and prefix and.

//infixAnd
Cheese(cheeseType : type) and Person(favouriteCheese == cheeseType)
//infixAnd with grouping
(Cheese(cheeseType : type) and (Person(favouriteCheese == cheeseType) or Person(favouriteCheese == cheeseType))

Prefix and is also supported:

(and Cheese(cheeseType : type) Person(favouriteCheese == cheeseType))

The root element of the LHS is an implicit prefix and and does not need to be specified:

when
  Cheese(cheeseType : type)
  Person(favouriteCheese == cheeseType)
then
  ...
or

This is a shortcut for generating two or more similar rules. Red Hat JBoss BRMS supports both prefix or and infix or. You can use traditional infix, prefix and explicit grouping parentheses.

//infixOr
Cheese(cheeseType : type) or Person(favouriteCheese == cheeseType)
//infixOr with grouping
(Cheese(cheeseType : type) or
  (Person(favouriteCheese == cheeseType) and
   Person(favouriteCheese == cheeseType))
(or Person(sex == "f", age > 60)
    Person(sex == "m", age > 65)

Allows for optional pattern binding. Each pattern must be bound separately.

pensioner : (Person(sex == "f", age > 60) or Person(sex == "m", age > 65))
(or pensioner : Person(sex == "f", age > 60)
    pensioner : Person(sex == "m", age > 65))
not

This checks to ensure an object specified as absent is not included in the Working Memory. It may be followed by parentheses around the condition elements it applies to. In a single pattern you can omit the parentheses.

// Brackets are optional:
not Bus(color == "red")
// Brackets are optional:
not (Bus(color == "red", number == 42))
// "not" with nested infix and - two patterns,
// brackets are requires:
not (Bus(color == "red") and
     Bus(color == "blue"))
exists

This checks the working memory to see if a specified item exists. The keyword exists must be followed by parentheses around the CEs that it applies to. In a single pattern you can omit the parentheses.

exists Bus(color == "red")
// brackets are optional:
exists (Bus(color == "red", number == 42))
// "exists" with nested infix and,
// brackets are required:
exists (Bus(color == "red") and
        Bus(color == "blue"))
Note

The behavior of the Conditional Element or is different from the connective || for constraints and restrictions in field constraints. The engine cannot interpret the Conditional Element or. Instead, a rule with or is rewritten as a number of subrules. This process ultimately results in a rule that has a single or as the root node and one subrule for each of its CEs. Each subrule can activate and fire like any normal rule; there is no special behavior or interaction between these subrules.

8.12.22. Conditional Element forall

This element evaluates to true when all facts that match the first pattern match all the remaining patterns. It is a scope delimiter. Therefore, it can use any previously bound variable, but no variable bound inside it will be available for use outside of it.

forall can be nested inside other CEs. For instance, forall can be used inside a not CE. Only single patterns have optional parentheses, so with a nested forall parentheses must be used.

8.12.23. forall Examples

Evaluating to true
rule "All English buses are red"
when
  forall($bus : Bus(type == 'english')
                Bus(this == $bus, color = 'red'))
then
    // all English buses are red
end
Single pattern forall
rule "All buses are red"
when
  forall(Bus(color == 'red'))
then
  // all Bus facts are red
end
Multi-pattern forall
rule "All employees have health and dental care programs"
when
  forall($emp : Employee()
         HealthCare(employee == $emp)
         DentalCare(employee == $emp))
then
  // all employees have health and dental care
end
Nested forall
rule "Not all employees have health and dental care"
when
  not (forall($emp : Employee()
              HealthCare(employee == $emp)
              DentalCare(employee == $emp)))
then
    // not all employees have health and dental care
end

8.12.24. Conditional Element from

The conditional element from enables users to specify an arbitrary source for data to be matched by LHS patterns. This allows the engine to reason over data not in the Working Memory. The data source could be a sub-field on a bound variable or the results of a method call. It is a powerful construction that allows out of the box integration with other application components and frameworks. One common example is the integration with data retrieved on-demand from databases using hibernate named queries.

The expression used to define the object source is any expression that follows regular MVEL syntax. Therefore, it allows you to easily use object property navigation, execute method calls and access maps and collections elements.

Important

Using from with lock-on-active rule attribute can result in rules not being fired.

There are several ways to address this issue:

  • Avoid the use of from when you can assert all facts into working memory or use nested object references in your constraint expressions (shown below).
  • Place the variable assigned used in the modify block as the last sentence in your condition (LHS).
  • Avoid the use of lock-on-active when you can explicitly manage how rules within the same rule-flow group place activations on one another.

8.12.25. from Examples

Reasoning and binding on patterns
rule "Validate zipcode"
when
  Person($personAddress : address)
  Address(zipcode == "23920W") from $personAddress
then
  // zip code is ok
end
Using a graph notation
rule "Validate zipcode"
when
  $p : Person()
  $a : Address(zipcode == "23920W") from $p.address
then
  // zip code is ok
end
Iterating over all objects
rule "Apply 10% discount to all items over US$ 100,00 in an order"
when
  $order : Order()
  $item  : OrderItem( value > 100) from $order.items
then
  // apply discount to $item
end
Use with lock-on-active
rule "Assign people in North Carolina (NC) to sales region 1"
ruleflow-group "test"
lock-on-active true
when
  $p : Person(address.state == "NC")
then
  modify ($p) {} // Assign person to sales region 1 in a modify block
end

rule "Apply a discount to people in the city of Raleigh"
ruleflow-group "test"
lock-on-active true
when
  $p : Person(address.city == "Raleigh")
then
  modify ($p) {} //Apply discount to person in a modify block
end

8.12.26. Conditional Element collect

The conditional element collect allows rules to reason over a collection of objects obtained from the given source or from the working memory. In First Oder Logic terms this is the cardinality quantifier.

The result pattern of collect can be any concrete class that implements the java.util.Collection interface and provides a default no-arg public constructor. You can use Java collections like ArrayList, LinkedList and HashSet or your own class, as long as it implements the java.util.Collection interface and provide a default no-arg public constructor.

Variables bound before the collect CE are in the scope of both source and result patterns and therefore you can use them to constrain both your source and result patterns. Any binding made inside collect is not available for use outside of it.

8.12.27. Conditional Element accumulate

The conditional element accumulate is a more flexible and powerful form of the collect element and allows a rule to iterate over a collection of objects while executing custom actions for each of the elements. The accumulate element returns a result object.

The element accumulate supports the use of predefined accumulate functions, as well as the use of inline custom code. However, using inline custom code is not recommended, as it is harder to maintain and might lead to code duplication. On the other hand, accumulate functions are easier to test and reuse.

The conditional element accumulate supports multiple different syntaxes. The preferred is the top-level syntax (as noted below), but all other syntaxes are supported as well for backward compatibility.

Top-Level accumulate Syntax

The top-level accumulate syntax is the most compact and flexible. The simplified syntax is as follows:

accumulate(SOURCE_PATTERN ; FUNCTIONS [;CONSTRAINTS])

Example 8.2. Top-Level accumulate Syntax Example

rule "Raise Alarm"
when
  $s : Sensor()
  accumulate(Reading(sensor == $s, $temp : temperature);
    $min : min($temp),
    $max : max($temp),
    $avg : average($temp);
    $min < 20, $avg > 70)
then
  // raise the alarm
end

In the example above, min, max, and average are accumulate functions that calculate the minimum, maximum, and average temperature values over all the readings for each sensor.

Built-in accumulate Functions

Only user-defined custom accumulate functions have to be explicitly imported. The following accumulate functions are imported automatically by the engine:

  • average
  • min
  • max
  • count
  • sum
  • collectList
  • collectSet

These common functions accept any expression as an input. For instance, if you want to calculate an average profit on all items of an order, you can write a rule using the average function as follows:

rule "Average Profit"
when
  $order : Order()
  accumulate(
    OrderItem(order == $order, $cost : cost, $price : price);
    $avgProfit : average(1 - $cost / $price))
then
  // average profit for $order is $avgProfit
end
Accumulate Functions Pluggability

Accumulate functions are all pluggable; if needed, custom and domain-specific functions can be easily added to the engine and rules can start to use them without any restrictions.

To implement a new accumulate function, create a Java class that implements the org.kie.api.runtime.rule.AccumulateFunction interface. To use the function in the rules, import it using the import accumulate statement:

import accumulate CLASS_NAME FUNCTION_NAME

Example 8.3. Importing and Using Custom Accumulate Function

import accumulate some.package.VarianceFunction variance

rule "Calculate Variance"
when
  accumulate(Test($s : score), $v : variance($s))
then
  // variance of the test scores is $v
end

Example 8.4. Implementation of average Function

As an example of an accumulate function, see the following implementation of the average function:

import java.io.Externalizable;
import java.io.IOException;
import java.io.ObjectInput;
import java.io.ObjectOutput;
import java.io.Serializable;

import org.kie.api.runtime.rule.AccumulateFunction;

/**
 * Implementation of an accumulator capable of calculating average values.
 */
public class AverageAccumulateFunction implements AccumulateFunction {

  public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {}

  public void writeExternal(ObjectOutput out) throws IOException {}

  public static class AverageData implements Externalizable {
    public int    count = 0;
    public double total = 0;

    public AverageData() {}

    public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {
      count = in.readInt();
      total = in.readDouble();
    }

    public void writeExternal(ObjectOutput out) throws IOException {
      out.writeInt(count);
      out.writeDouble(total);
    }
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#createContext()
   */
  public Serializable createContext() {
    return new AverageData();
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#init(java.lang.Object)
   */
  public void init(Serializable context) throws Exception {
    AverageData data = (AverageData) context;
    data.count = 0;
    data.total = 0;
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#accumulate(java.lang.Object,
   * java.lang.Object)
   */
  public void accumulate(Serializable context, Object value) {
    AverageData data = (AverageData) context;
    data.count++;
    data.total += ((Number) value).doubleValue();
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#reverse(java.lang.Object,
   * java.lang.Object)
   */
  public void reverse(Serializable context, Object value) throws Exception {
    AverageData data = (AverageData) context;
    data.count--;
    data.total -= ((Number) value).doubleValue();
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#getResult(java.lang.Object)
   */
  public Object getResult(Serializable context) throws Exception {
    AverageData data = (AverageData) context;
    return new Double(data.count == 0 ? 0 : data.total / data.count);
  }

  /* (non-Javadoc)
   * @see org.kie.base.accumulators.AccumulateFunction#supportsReverse()
   */
  public boolean supportsReverse() {
    return true;
  }

  /**
   * {@inheritDoc}
   */
  public Class< ? > getResultType() {
    return Number.class;
  }
}

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies. If you use Red Hat JBoss BRMS, see Embedded Drools Engine Dependencies.

Alternative Syntax

Previous accumulate syntaxes are still supported for backward compatibility.

In case the rule uses a single accumulate function on a given accumulate element, you can add a pattern for the result object and use the from keyword to link it to the accumulate result. See the following example:

Example 8.5. Rule with Alternative Syntax

rule "Apply 10% Discount on Orders over US $100.00"
when
  $order : Order()
  $total : Number(doubleValue > 100)
    from accumulate(OrderItem(order == $order, $value : value), sum($value))
then
  # apply discount on $order
end

In this example, the element accumulate uses only one function – sum. In this case, it is possible to write a pattern for the result type of the accumulate function with the constraints inside.

Important

Note that it is not possible to use both the return type and the function binding in the same accumulate statement.

accumulate with Inline Custom Code

Instead of using the accumulate functions, you can define inline custom code.

Warning

The use of accumulate with inline custom code is not recommended. It is difficult to maintain and test the rules, as well as reuse the code. Implementing your own accumulate functions allows you to test and use them easily.

The general syntax of the accumulate with inline custom code is as follows:

RESULT_PATTERN from accumulate(
	SOURCE_PATTERN,
	init(INIT_CODE),
	action(ACTION_CODE),
	reverse(REVERSE_CODE),
	result(RESULT_EXPRESSION))
RESULT_PATTERN

A regular pattern that the engine tries to match against the object returned from the RESULT_EXPRESSION.

If the attempt succeeds, the accumulate conditional element returns true and the engine proceeds with an evaluation of the next conditional element in the rule. In the second case, accumulate returns false and the engine stops evaluating conditional elements for this rule.

SOURCE_PATTERN
A regular pattern that the engine tries to match against each of the source objects.
INIT_CODE
A semantic block of code in the selected dialect that is executed once for each tuple before iterating over the source objects.
ACTION_CODE
A semantic block of code in the selected dialect that is executed for each of the source objects.
REVERSE_CODE

An optional semantic block of code in the selected dialect that is executed for each source object that no longer matches the source pattern.

The objective of this code block is to undo any calculation done in the ACTION_CODE block, so that the engine can do decremental calculation when a source object is modified or retracted. This significantly improves the performance of these operations.

RESULT_EXPRESSION
A semantic expression in the selected dialect that is executed after all source objects are iterated.

Example 8.6. Example of Inline Custom Code

rule "Apply 10% Discount on Orders over US $100.00"
when
  $order : Order()
  $total : Number(doubleValue > 100)
    from accumulate(OrderItem(order == $order, $value : value),
      init(double total = 0;),
      action(total += $value;),
      reverse(total -= $value;),
      result(total))
then
  # apply discount on $order
end

In this example, the engine executes the INIT_CODE for each Order in the working memory, initializing the total variable to zero. The engine then iterates over all OrderItem objects for that Order, executing the action for each one. After the iteration, the engine returns the value corresponding to the RESULT_EXPRESSION (in this case, a value of the total variable). Finally, the engine tries to match the result with the Number pattern. If the doubleValue is greater than 100, the rule fires.

The example is using Java programming language as a semantic dialect. In this case, a semicolon as a statement delimiter is mandatory in the init, action, and reverse code blocks. However, since the result is an expression, it does not require a semicolon. If you want to use any other dialect, note that you have to observe the principles of its specific syntax.

Custom Objects

The accumulate conditional element can be used to execute any action on source objects. The following example instantiates and populates a custom object:

Example 8.7. Instantiating Custom Objects

rule "accumulate Using Custom Objects"
when
  $person : Person($likes : likes)
  $cheesery : Cheesery(totalAmount > 100)
    from accumulate($cheese : Cheese(type == $likes),
      init(Cheesery cheesery = new Cheesery();),
      action(cheesery.addCheese($cheese);),
      reverse(cheesery.removeCheese($cheese);),
      result(cheesery));
then
  // do something
end

8.12.28. Conditional Element eval

The conditional element eval is essentially a catch-all which allows any semantic code (that returns a primitive boolean) to be executed. This code can refer to variables that were bound in the LHS of the rule, and functions in the rule package. Overuse of eval reduces the declarativeness of your rules and can result in a poorly performing engine. While eval can be used anywhere in the patterns, the best practice is to add it as the last conditional element in the LHS of a rule.

Evals cannot be indexed and thus are not as efficient as field constraints. However this makes them ideal for being used when functions return values that change over time, which is not allowed within field constraints.

8.12.29. eval Conditional Element Examples

This is what eval looks like in use:

p1 : Parameter()
p2 : Parameter()
eval(p1.getList().containsKey( p2.getItem()))
p1 : Parameter()
p2 : Parameter()
// call function isValid in the LHS
eval(isValid( p1, p2))

8.12.30. Right Hand Side

The Right Hand Side (RHS) is a common name for the consequence part of a rule. The main purpose of the RHS is to insert, retract (delete), or modify working memory data. The RHS usually contains a list of actions to be executed and should be kept small, thus keeping it declarative and readable.

Note

In case you need imperative or conditional code in the RHS, divide the rule into more rules.

8.12.31. RHS Convenience Methods

See the following list of the RHS convenience methods:

  • update(OBJECT, HANDLE);
  • update(OBJECT);
  • insert(OBJECT);
  • insertLogical(OBJECT);
  • retract(HANDLE);

For more information, see Section 8.2.1, “Accessing Working Memory”.

8.12.32. Convenience Methods Using Drools Variable

  • The call drools.halt() terminates rule execution immediately. This is required for returning control to the point whence the current session was put to work with fireUntilHalt().
  • Methods insert(Object o), update(Object o) and retract(Object o) can be called on drools as well, but due to their frequent use they can be called without the object reference.
  • drools.getWorkingMemory() returns the WorkingMemory object.
  • drools.setFocus(String s) sets the focus to the specified agenda group.
  • drools.getRule().getName(), called from a rule’s RHS, returns the name of the rule.
  • drools.getTuple() returns the Tuple that matches the currently executing rule, and drools.getActivation() delivers the corresponding Activation. (These calls are useful for logging and debugging purposes.)

8.12.33. Convenience Methods Using kcontext Variable

  • The call kcontext.getKieRuntime().halt() terminates rule execution immediately.
  • The accessor getAgenda() returns a reference to the session’s Agenda, which in turn provides access to the various rule groups: activation groups, agenda groups, and rule flow groups. A fairly common paradigm is the activation of some agenda group, which could be done with the lengthy call:

    // Give focus to the agenda group CleanUp:
    kcontext.getKieRuntime().getAgenda().getAgendaGroup("CleanUp").setFocus();

    You can achieve the same using drools.setFocus("CleanUp").

  • To run a query, you call getQueryResults(String query), whereupon you may process the results.
  • A set of methods dealing with event management lets you add and remove event listeners for the Working Memory and the Agenda.
  • Method getKieBase() returns the KieBase object, the backbone of all the Knowledge in your system, and the originator of the current session.
  • You can manage globals with setGlobal(…​), getGlobal(…​) and getGlobals().
  • Method getEnvironment() returns the runtime’s Environment.

8.12.34. Modify Statement

modify

This provides a structured approach to fact updates. It combines the update operation with a number of setter calls to change the object’s fields.

modify (FACT_EXPRESSION)
{
 EXPRESSION [, EXPRESSION]*
}

The parenthesized FACT_EXPRESSION must yield a fact object reference. The expression list in the block should consist of setter calls for the given object, to be written without the usual object reference, which is automatically prepended by the compiler.

rule "Modify stilton"
when
  $stilton : Cheese(type == "stilton")
then
  modify($stilton){
    setPrice(20),
    setAge("overripe")
  }
end

8.12.35. Query Examples

Note

To return the results use ksession.getQueryResults("name"), where "name" is the query’s name. This returns a list of query results, which allow you to retrieve the objects that matched the query.

Query for people over the age of 30
query "People over the age of 30"
  person : Person(age > 30)
end
Query for people over the age of X, and who live in Y
query "People over the age of x"  (int x, String y)
  person : Person(age > x, location == y)
end

8.12.36. QueryResults Example

We iterate over the returned QueryResults using a standard for loop. Each element is a QueryResultsRow which we can use to access each of the columns in the tuple. These columns can be accessed by bound declaration name or index position:

QueryResults results = ksession.getQueryResults("people over the age of 30");
System.out.println("we have " + results.size() + " people over the age  of 30");

System.out.println("These people are are over 30:");

for (QueryResultsRow row : results) {
  Person person = (Person) row.get("person");
  System.out.println(person.getName() + "\n");
}

8.12.37. Queries Calling Other Queries

Queries can call other queries. This combined with optional query arguments provides derivation query style backward chaining. Positional and named syntax is supported for arguments. It is also possible to mix both positional and named, but positional must come first, separated by a semi colon. Literal expressions can be passed as query arguments, but you cannot mix expressions with variables.

Note

Using the ? symbol in this process means the query is pull only and once the results are returned you will not receive further results as the underlying data changes.

8.12.38. Queries Calling Other Queries Example

Query calling another query
declare Location
  thing : String
  location : String
end

query isContainedIn(String x, String y)
  Location(x, y;)
  or
  (Location(z, y;) and ?isContainedIn(x, z;))
end
Using live queries to reactively receive changes over time from query results
query isContainedIn(String x, String y)
  Location(x, y;)
  or
  (Location(z, y;) and isContainedIn(x, z;))
end

rule look when
  Person($l : likes)
  isContainedIn($l, 'office';)
then
  insertLogical($l 'is in the office');
end

8.12.39. Unification for Derivation Queries

Red Hat JBoss BRMS supports unification for derivation queries. This means that arguments are optional. It is possible to call queries from Java leaving arguments unspecified using the static field org.drools.runtime.rule.Variable.v. You must use v and not an alternative instance of Variable. These are referred to as out arguments.

Note

The query itself does not declare at compile time whether an argument is in or an out. This can be defined purely at runtime on each use.

8.13. Searching Working Memory Using Query

8.13.1. Queries

Queries are used to retrieve fact sets based on patterns, as they are used in rules. Patterns may make use of optional parameters. Queries can be defined in the Knowledge Base, from where they are called up to return the matching results. While iterating over the result collection, any identifier bound in the query can be used to access the corresponding fact or fact field by calling the get method with the binding variable’s name as its argument. If the binding refers to a fact object, its FactHandle can be retrieved by calling getFactHandle, again with the variable’s name as the parameter. Illustrated below is a query example:

QueryResults results = ksession.getQueryResults("my query", new Object[] {"string"});
for (QueryResultsRow row : results) {
  System.out.println(row.get("varName"));
}

8.13.2. Live Queries

Invoking queries and processing the results by iterating over the returned set is not a good way to monitor changes over time.

To alleviate this, Red Hat JBoss BRMS provides live queries, which have a listener attached instead of returning an iterable result set. These live queries stay open by creating a view and publishing change events for the contents of this view. To activate, start your query with parameters and listen to changes in the resulting view. The dispose method terminates the query and discontinues this reactive scenario.

8.13.3. ViewChangedEventListener Implementation Example

final List updated = new ArrayList();
final List removed = new ArrayList();
final List added = new ArrayList();

ViewChangedEventListener listener = new ViewChangedEventListener() {
  public void rowUpdated(Row row) {
    updated.add(row.get("$price"));
  }

  public void rowRemoved(Row row) {
    removed.add(row.get("$price"));
  }

  public void rowAdded(Row row) {
    added.add(row.get("$price"));
  }
}

// Open the LiveQuery:
LiveQuery query = ksession.openLiveQuery("cars", new Object[] {"sedan", "hatchback"}, listener);
...
query.dispose() // calling dispose to terminate the live query
Note

For an example of Glazed Lists integration for live queries, read the Glazed Lists examples for Drools Live Querries article.

8.14. Domain Specific Languages (DSLs)

Domain Specific Languages (or DSLs) are a way of creating a rule language that is dedicated to your problem domain. A set of DSL definitions consists of transformations from DSL "sentences" to DRL constructs, which lets you use of all the underlying rule language and engine features. You can write rules in DSL rule (or DSLR) files, which will be translated into DRL files.

DSL and DSLR files are plain text files and you can use any text editor to create and modify them. There are also DSL and DSLR editors you can use, both in the IDE as well as in the web based BRMS, although they may not provide you with the full DSL functionality.

8.14.1. DSL Editor

The DSL editor provides a tabular view of the mapping of Language to Rule Expressions. The Language Expression feeds the content assistance for the rule editor so that it can suggest Language Expressions from the DSL configuration. The rule editor loads the DSL configuration when the rule resource is loaded for editing.

Note

DSL feature is useful for simple use cases for non technical users to easily define rules based on sentence snippets. For more complex use cases, we recommend you to use other advanced features like decision tables and DRL rules, that are more expressive and flexible.

8.14.2. Using DSLs

DSLs can serve as a layer of separation between rule authoring (and rule authors) and the technical intricacies resulting from the modeling of domain object and the rule engine’s native language and methods. A DSL hides implementation details and focuses on the rule logic proper. DSL sentences can also act as "templates" for conditional elements and consequence actions that are used repeatedly in your rules, possibly with minor variations. You may define DSL sentences as being mapped to these repeated phrases, with parameters providing a means for accommodating those variations.

8.14.3. DSL Example

[when]Something is {colour}=Something(colour=="{colour}")

[when] indicates the scope of the expression (that is, whether it is valid for the LHS or the RHS of a rule).

The part after the bracketed keyword is the expression that you use in the rule.

The part to the right of the equal sign (=) is the mapping of the expression into the rule language. The form of this string depends on its destination, RHS or LHS. If it is for the LHS, then it ought to be a term according to the regular LHS syntax; if it is for the RHS then it might be a Java statement.

8.14.4. About DSL Parser

Whenever the DSL parser matches a line from the rule file written in the DSL with an expression in the DSL definition, it performs three steps of string manipulation:

  • The DSL extracts the string values appearing where the expression contains variable names in brackets.
  • The values obtained from these captures are interpolated wherever that name occurs on the right hand side of the mapping.
  • The interpolated string replaces whatever was matched by the entire expression in the line of the DSL rule file.
Note

You can use (for instance) a ? to indicate that the preceding character is optional. One good reason to use this is to overcome variations in natural language phrases of your DSL. But, given that these expressions are regular expression patterns, this means that all wildcard characters in Java’s pattern syntax have to be escaped with a preceding backslash (\).

8.14.5. About DSL Compiler

The DSL compiler transforms DSL rule files line by line. If you do not wish for this to occur, ensure that the captures are surrounded by characteristic text (words or single characters). As a result, the matching operation done by the parser plucks out a substring from somewhere within the line. In the example below, quotes are used as distinctive characters. The characters that surround the capture are not included during interpolation, just the contents between them.

8.14.6. DSL Syntax Examples

Quotes

Use quotes for textual data that a rule editor may want to enter. You can also enclose the capture with words to ensure that the text is correctly matched.

[when]something is "{color}"=Something(color=="{color}")
[when]another {state} thing=OtherThing(state=="{state}"
Braces

In a DSL mapping, the braces "{" and "}" should only be used to enclose a variable definition or reference, resulting in a capture. If they should occur literally, either in the expression or within the replacement text on the right hand side, they must be escaped with a preceding backslash (\).

[then]do something= if (foo) \{ doSomething(); \}
Mapping with correct syntax example
# This is a comment to be ignored.
[when]There is a person with name of "{name}"=Person(name=="{name}")
[when]Person is at least {age} years old and lives in "{location}"=Person(age >= {age}, location=="{location}")
[then]Log "{message}"=System.out.println("{message}");
[when]And = and
Expanded DSL example
There is a person with name of "Kitty"
   ==> Person(name="Kitty")
Person is at least 42 years old and lives in "Atlanta"
   ==> Person(age >= 42, location="Atlanta")
Log "boo"
   ==> System.out.println("boo");
There is a person with name of "Bob" and Person is at least 30 years old and lives in "Utah"
   ==> Person(name="Bob") and Person(age >= 30, location="Utah")
Note

If you are capturing plain text from a DSL rule line and want to use it as a string literal in the expansion, you must provide the quotes on the right hand side of the mapping.

8.14.7. Chaining DSL Expressions

DSL expressions can be chained together one one line to be used at once. It must be clear where one ends and the next one begins and where the text representing a parameter ends. Otherwise you risk getting all the text until the end of the line as a parameter value. The DSL expressions are tried, one after the other, according to their order in the DSL definition file. After any match, all remaining DSL expressions are investigated, too.

8.14.8. Adding Constraints to Facts

Expressing LHS conditions

The DSL facility allows you to add constraints to a pattern by a simple convention: if your DSL expression starts with a hyphen (minus character, -) it is assumed to be a field constraint and, consequently, is is added to the last pattern line preceding it.

In the example, the class Cheese, has these fields: type, price, age, and country. You can express some LHS condition in normal DRL.

Cheese(age < 5, price == 20, type=="stilton", country=="ch")
DSL definitions

The DSL definitions given in this example result in three DSL phrases which may be used to create any combination of constraint involving these fields.

[when]There is a Cheese with=Cheese()
[when]- age is less than {age}=age<{age}
[when]- type is '{type}'=type=='{type}'
[when]- country equal to '{country}'=country=='{country}'
-

The parser will pick up a line beginning with - and add it as a constraint to the preceding pattern, inserting a comma when it is required.

There is a Cheese with
  - age is less than 42
  - type is 'stilton'
Cheese(age<42, type=='stilton')
Defining DSL phrases

Defining DSL phrases for various operators and even a generic expression that handles any field constraint reduces the amount of DSL entries.

[when][]is less than or equal to=<=
[when][]is less than=<
[when][]is greater than or equal to=>=
[when][]is greater than=>
[when][]is equal to===
[when][]equals===
[when][]There is a Cheese with=Cheese()
DSL definition rule
There is a Cheese with
  - age is less than 42
  - rating is greater than 50
  - type equals 'stilton'

In this specific case, a phrase such as "is less than" is replaced by <, and then the line matches the last DSL entry. This removes the hyphen, but the final result is still added as a constraint to the preceding pattern. After processing all of the lines, the resulting DRL text is:

Cheese(age<42, rating > 50, type=='stilton')
Note

The order of the entries in the DSL is important if separate DSL expressions are intended to match the same line, one after the other.

8.14.9. Tips for Developing DSLs

  • Write representative samples of the rules your application requires and test them as you develop.
  • Rules, both in DRL and in DSLR, refer to entities according to the data model representing the application data that should be subject to the reasoning process defined in rules.
  • Writing rules is easier if most of the data model’s types are facts.
  • Mark variable parts as parameters. This provides reliable leads for useful DSL entries.
  • You may postpone implementation decisions concerning conditions and actions during this first design phase by leaving certain conditional elements and actions in their DRL form by prefixing a line with a greater sign (">"). (This is also handy for inserting debugging statements.)
  • New rules can be written by reusing the existing DSL definitions, or by adding a parameter to an existing condition or consequence entry.
  • Keep the number of DSL entries small. Using parameters lets you apply the same DSL sentence for similar rule patterns or constraints.

8.14.10. DSL and DSLR Reference

A DSL file is a text file in a line-oriented format. Its entries are used for transforming a DSLR file into a file according to DRL syntax:

  • A line starting with # or // (with or without preceding white space) is treated as a comment. A comment line starting with #/ is scanned for words requesting a debug option, see below.
  • Any line starting with an opening bracket ([) is assumed to be the first line of a DSL entry definition.
  • Any other line is appended to the preceding DSL entry definition, with the line end replaced by a space.

8.14.11. DSL Entry Description

A DSL entry consists of the following four parts:

  1. A scope definition, written as one of the keywords when or condition, then or consequence, * and keyword, enclosed in brackets ([ and ]). This indicates whether the DSL entry is valid for the condition or the consequence of a rule, or both. A scope indication of keyword means that the entry has global significance, that is, it is recognized anywhere in a DSLR file.
  2. A type definition, written as a Java class name, enclosed in brackets. This part is optional unless the next part begins with an opening bracket. An empty pair of brackets is valid, too.
  3. A DSL expression consists of a (Java) regular expression, with any number of embedded variable definitions, terminated by an equal sign (=). A variable definition is enclosed in braces ({ and }). It consists of a variable name and two optional attachments, separated by colons (:). If there is one attachment, it is a regular expression for matching text that is to be assigned to the variable. If there are two attachments, the first one is a hint for the GUI editor and the second one the regular expression.

    Note that all characters that are "magic" in regular expressions must be escaped with a preceding backslash (\) if they should occur literally within the expression.

  4. The remaining part of the line after the delimiting equal sign is the replacement text for any DSLR text matching the regular expression. It may contain variable references, for example a variable name enclosed in braces. Optionally, the variable name may be followed by an exclamation mark (!) and a transformation function, see below.

    Note that braces ({ and }) must be escaped with a preceding backslash (\) if they should occur literally within the replacement string.

8.14.12. Debug Options for DSL Expansion

Table 8.4. Debug Options for DSL Expansion
WordDescription

result

Prints the resulting DRL text, with line numbers.

steps

Prints each expansion step of condition and consequence lines.

keyword

Dumps the internal representation of all DSL entries with scope keyword.

when

Dumps the internal representation of all DSL entries with scope when or *.

then

Dumps the internal representation of all DSL entries with scope then or *.

usage

Displays a usage statistic of all DSL entries.

8.14.13. DSL Definition Example

This is what a DSL definition looks like:

# Comment: DSL examples

#/ debug: display result and usage

# keyword definition: replaces "regula" by "rule"
[keyword][]regula=rule

# conditional element: "T" or "t", "a" or "an", convert matched word
[when][][Tt]here is an? {entity:\w+}=${entity!lc}: {entity!ucfirst} ()

# consequence statement: convert matched word, literal braces
[then][]update {entity:\w+}=modify(${entity!lc})\{ \}

8.14.14. Transformation of DSLR File

The transformation of a DSLR file proceeds as follows:

  1. The text is read into memory.
  2. Each of the keyword entries is applied to the entire text. The regular expression from the keyword definition is modified by replacing white space sequences with a pattern matching any number of white space characters, and by replacing variable definitions with a capture made from the regular expression provided with the definition, or with the default (.*?). Then, the DSLR text is searched exhaustively for occurrences of strings matching the modified regular expression. Substrings of a matching string corresponding to variable captures are extracted and replace variable references in the corresponding replacement text, and this text replaces the matching string in the DSLR text.
  3. Sections of the DSLR text between when and then, and then and end, respectively, are located and processed in a uniform manner, line by line, as described below.

    For a line, each DSL entry pertaining to the line’s section is taken in turn, in the order it appears in the DSL file. Its regular expression part is modified: white space is replaced by a pattern matching any number of white space characters; variable definitions with a regular expression are replaced by a capture with this regular expression, its default being .*?. If the resulting regular expression matches all or part of the line, the matched part is replaced by the suitably modified replacement text.

    Modification of the replacement text is done by replacing variable references with the text corresponding to the regular expression capture. This text may be modified according to the string transformation function given in the variable reference; see below for details.

    If there is a variable reference naming a variable that is not defined in the same entry, the expander substitutes a value bound to a variable of that name, provided it was defined in one of the preceding lines of the current rule.

  4. If a DSLR line in a condition is written with a leading hyphen, the expanded result is inserted into the last line, which should contain a pattern CE, that is, a type name followed by a pair of parentheses. if this pair is empty, the expanded line (which should contain a valid constraint) is simply inserted, otherwise a comma (,) is inserted beforehand.

    If a DSLR line in a consequence is written with a leading hyphen, the expanded result is inserted into the last line, which should contain a modify statement, ending in a pair of braces ({ and }). If this pair is empty, the expanded line (which should contain a valid method call) is simply inserted, otherwise a comma (,) is inserted beforehand.

Note

It is currently not possible to use a line with a leading hyphen to insert text into other conditional element forms (for example accumulate) or it may only work for the first insertion (for example eval).

8.14.15. String Transformation Functions

Table 8.5. String Transformation Functions
NameDescription

uc

Converts all letters to upper case.

lc

Converts all letters to lower case.

ucfirst

Converts the first letter to upper case, and all other letters to lower case.

num

Extracts all digits and - from the string. If the last two digits in the original string are preceded by . or ,, a decimal period is inserted in the corresponding position.

a?b/c

Compares the string with string a, and if they are equal, replaces it with b, otherwise with c. But c can be another triplet a, b, c, so that the entire structure is, in fact, a translation table.

8.14.16. Stringing DSL Transformation Functions

.dsl

A file containing a DSL definition is customarily given the extension .dsl. It is passed to the Knowledge Builder with ResourceType.DSL. For a file using DSL definition, the extension .dslr should be used. The Knowledge Builder expects ResourceType.DSLR. The IDE, however, relies on file extensions to correctly recognize and work with your rules file.

# definitions for conditions
[when][]There is an? {entity}=${entity!lc}: {entity!ucfirst}()
[when][]- with an? {attr} greater than {amount}={attr} <= {amount!num}
[when][]- with a {what} {attr}={attr} {what!positive?>0/negative?%lt;0/zero?==0/ERROR}
DSL passing

The DSL must be passed to the Knowledge Builder ahead of any rules file using the DSL.

For parsing and expanding a DSLR file the DSL configuration is read and supplied to the parser. Thus, the parser can "recognize" the DSL expressions and transform them into native rule language expressions.

KnowledgeBuilder kBuilder = new KnowledgeBuilder();
Resource dsl = ResourceFactory.newClassPathResource(dslPath, getClass());
kBuilder.add(dsl, ResourceType.DSL);
Resource dslr = ResourceFactory.newClassPathResource(dslrPath, getClass());
kBuilder.add(dslr, ResourceType.DSLR);

Chapter 9. Using Red Hat JBoss Developer Studio to Create and Test Rules

There are many ways to author rules in BRMS, however as a developer you would prefer an Integrated Development Environment (IDE) such as Red Hat JBoss Developer Studio that offers you advanced tooling and content assistance. Red Hat JBoss BRMS and Red Hat JBoss BPM Suite tooling are compatible with Red Hat JBoss Developer Studio version 7 and above. The Red Hat JBoss Developer Studio with Red Hat JBoss BPM Suite/BRMS plug-ins simplify your development tasks. These plug-ins provide the following features:

  • Simple wizards for rule and project creation.
  • Content assistance for generating the basic rule structure. For example, If you open a .drl file in the Red Hat JBoss Developer Studio editor and type ru, and press Ctrl+Space , the template rule structure is created.
  • Syntax coloring.
  • Error highlighting.
  • IntelliSense code completion.
  • Outline view to display an outline of your structured rule project.
  • Debug perspective for rules and process debugging.
  • Rete tree view to display Rete network.
  • Editor for modifying business process diagram.
  • Support for unit testing using JUnit and TestNG.

9.1. Red Hat JBoss Developer Studio Drools Perspective

Red Hat JBoss Developer Studio comes with all the BRMS and BPM Suite plug-in requirements pre-packaged with it. It offers the following perspectives:

  • Drools: allows you to work with Red Hat JBoss BRMS specific resources.
  • Business Central Repository Exploring.
  • jBPM: allows you to work with Red Hat JBoss BPM Suite resources.

9.2. Red Hat JBoss BRMS Runtimes

A Drools runtime is a collection of JAR files on your file system that represent one specific release of the Drools project JARs. While creating a new runtime, you must either point to the release of your choice or create a new runtime on your file system from the jars included in the Drools plug-in. For creating a new runtime, you need to specify a default Drools runtime for your Eclipse workspace, but each individual project can override the default and select the appropriate runtime for that project specifically. You can add as many Drools runtimes as you need. In order to use the Red Hat JBoss BRMS plug-in with Red Hat JBoss Developer Studio, it is necessary to set up the runtime.

9.2.1. Defining a Red Hat JBoss BRMS Runtime

  1. Extract the runtime JAR files located in the jboss-brms-engine.zip archive of the Red Hat JBoss BRMS 6.4.0 Core Engine ZIP archive available on the Red Hat Customer Portal.
  2. From the Red Hat JBoss Developer Studio menu, click WindowPreferences.
  3. Select DroolsInstalled Drools Runtimes.
  4. Click Add…​, provide a name for the new runtime, and click Browse to navigate to the directory where you extracted the runtime files in the first step. Click OK to register the selected runtime in Red Hat JBoss Developer Studio.
  5. Mark the runtime you have created as the default Drools runtime by clicking on the check box next to it.
  6. Click OK. If you already have projects in Red Hat JBoss Developer Studio, a dialog box will indicate that you have to restart Red Hat JBoss Developer Studio to update the runtime.

9.2.2. Selecting a Runtime for Your Red Hat JBoss BRMS Project

Whenever you create a Drools project either by using the New Drools Project wizard or by converting an existing Java project to a Drools project, the Drools plug-in automatically adds all the required JAR files to the classpath of your project.

If you are creating a new Drools project, the plug-in uses the default Drools runtime for that project, unless you specify a project-specific one.

To define a project-specific runtime, create a new Drools project and choose the desired runtime in the final step of the New Drools Project wizard. Alternatively, you can create a new runtime by clicking Manage Runtime Definitions.

9.2.3. Changing the Runtime of Your Red Hat JBoss BRMS Project

To change the runtime of a Drools project:

  1. In the Drools perspective, right-click the project and select Properties.

    The project properties dialog opens.

  2. Navigate and select the Drools category.
  3. Check the Enable project specific settings checkbox and select the appropriate runtime from the drop-down box.

    If you click the Configure workspace settings…​ link, the workspace preferences showing the currently installed Drools runtimes opens. You can add new runtimes there if required. If you uncheck the Enable project specific settings checkbox, it uses the default runtime as defined in your global preferences.

  4. Click OK.

9.2.4. Configuring the Red Hat JBoss BRMS Server

Red Hat JBoss Developer Studio can be configured to run the Red Hat JBoss BRMS\BPM Suite Server.

Configuring the Server

  1. Open the Drools view by clicking WindowOpen PerspectiveOther and then Drools. Click OK.
  2. Add the Server view by clicking WindowShow ViewOther…​ and then ServerServers.
  3. Open the server menu by right clicking the Servers panel. Click NewServer to add a new server.
  4. Define the server by selecting JBoss Enterprise MiddlewareJBoss Enterprise Application Platform 6.1+, and click Next.
  5. Click JBoss EAP 6.4 Runtime and select Create new runtime (next page). Click Next.
  6. Set the home directory by clicking Browse. Navigate to and select the installation directory for Red Hat JBoss EAP 6.4 that has Red Hat JBoss BPM Suite installed.
  7. Provide a name for the server in the Name field, make sure that the configuration file is set, and click Finish.

9.3. Exploring Red Hat JBoss BRMS Application

A BRMS project typically comprises the following:

  • Facts, which are a set of java class files, often POJOs.
  • Rules, which operate on the facts.
  • Drools library (JAR files) for executing the rules.

Red Hat JBoss Developer Studio helps you generate the getter and setter methods for attributes automatically. When you create a BRMS or a BPM Suite project, the following directories are generated:

  • src/main/java that stores the class files (facts).
  • src/main/resources/rules that stores the .drl files (rules).
  • src/main/resources/process that stores the .bpmn files (processes).

9.4. Creating a Red Hat JBoss BRMS Project

To create a new Red Hat JBoss BRMS project in the Drools perspective, do the following:

Procedure: Creating New Red Hat JBoss Developer Studio Project

  1. In the main menu, click FileNewProject.
  2. Click DroolsDrools Project and click Next.
  3. For now, choose the second option. Red Hat JBoss Developer Studio will create a project with a Red Hat JBoss BPM Suite example. Click Next.
  4. Enter a name for the project into the Project name: text box and click Finish.

To test the project:

  1. Navigate to the src/main/java directory and expand the com.sample package.
  2. Right click the desired Java class and click Run AsJava Application.

    The output will be displayed on the console tab.

If you checked the default artifacts checkboxes in the Drools Project wizard, you can see the newly created Drools project in the Package Explorer accordingly containing:

  • A sample rule Sample.drl in the src/main/resources/rules directory.
  • A sample process Sample.bpmn in the src/main/resources/process directory.
  • A sample decision table Sample.xls in the src/main/resources/dtables directory.
  • An example DroolsTest.java Java class in the src/main/java directory to execute the rules in the Drools engine in the com.sample package.
  • An example ProcessTest.java Java class in the src/main/java directory to execute the rules in the Drools engine in the com.sample package.
  • An example DecisionTableTest.java Java class in the src/main/java directory to execute the rules in the Drools engine in the com.sample package.

9.5. Using Textual Rule Editor

In the Package Explorer, you can double-click your existing rule file to open it on a textual rule editor or choose FileNewRule Resource to create a new rule on the textual editor. The textual rule editor has a pattern of a normal text editor and this is where you modify and manage your rules.

The textual rule editor works on files that have a .drl (or .rule) extension. Usually these contain related rules, but it is also possible to have rules in individual files, grouped by being in the same package namespace. These DRL files are plain text files. Even if your rule group is using a domain specific language (DSL), the rules are still stored as plain text. This allows easy management of rules and versions.

Textual editor provides features like:

  • Content assistance: The pop-up content assistance helps you quickly create rule attributes such as functions, import statements, and package declarations. You can invoke pop-up content assistance by pressing Ctrl+Space.
  • Code folding: Code Folding allows you to hide and show sections of a file use the icons with minus and plus on the left vertical line of the editor.
  • Sysnchronization with outline view: The text editor is in sync with the structure of the rules in the outline view as soon as you save your rules. The outline view provides a quick way of navigating around rules by name, or even in a file containing hundreds of rules. The items are sorted alphabetically by default.

9.6. Red Hat JBoss BRMS Views

You can alternate between these views when modifying rules:

Working Memory View
Shows all elements in the Red Hat JBoss BRMS working memory.
Agenda View
Shows all elements on the agenda. For each rule on the agenda, the rule name and bound variables are shown.
Global Data View
Shows all global data currently defined in the Red Hat JBoss BRMS working memory.
Audit View
Can be used to display audit logs containing events that were logged during the execution of a rules engine, in tree form.
Rete View

This shows you the current Rete Network for your DRL file. You display it by clicking on the tab "Rete Tree" at the bottom of the DRL Editor window. With the Rete Network visualization being open, you can use drag-and-drop on individual nodes to arrange optimal network overview. You may also select multiple nodes by dragging a rectangle over them so the entire group can be moved around.

Note

The Rete view works only in projects where the rule builder is set in the project´s properties. For other projects, you can use a workaround. Set up a Red Hat JBoss BRMS project next to your current project and transfer the libraries and the DRLs you want to inspect with the Rete view. Click on the right tab below in the DRL Editor, then click Generate Rete View.

Kie Navigator View
Shows you the contents of your Red Hat JBoss BPM Suite projects on your container. See chapter Kie Navigator of the Red Hat JBoss BPM Suite Getting Started Guide for more information.

9.7. Debugging Rules

Drools breakpoints are only enabled if you debug your application as a Drools Application. To do this you should perform one of two actions:

  • Select the main class of your application. Right-click on it and select Debug AsDrools Application.
  • Alternatively, select Debug AsDebug Configuration to open a new dialog window for creating, managing and running debug configurations.

    Select the Drools Application item in the left tree and click New launch configuration (leftmost icon in the toolbar above the tree). This will create a new configuration with a number of the properties already filled in based on main class you selected in the beginning. All properties shown here are the same as any standard Java program.

    Note

    Remember to change the name of your debug configuration to something meaningful.

    1. Click the Debug button on the bottom to start debugging your application.
    2. After enabling the debugging, the application starts executing and will halt if any breakpoint is encountered. This can be a Drools rule breakpoint, or any other standard Java breakpoint. Whenever a Drools rule breakpoint is encountered, the corresponding .drl file is opened and the active line is highlighted. The Variables view also contains all rule parameters and their value. You can then use the default Java debug actions to decide what to do next (resume, terminate, step over, and others). The debug views can also be used to determine the contents of the working memory and agenda at that time as well (the current executing working memory is automatically shown).

9.7.1. Creating Breakpoints

Create breakpoints to help monitor rules that have been executed. Instead of waiting for the result to appear at the end of the process, you can inspect the details of the execution at each breakpoint you set. This is useful for debugging and ensuring rules are executed as expected.

  1. To create breakpoints in the Package Explorer view or Navigator view of the Red Hat JBoss BRMS perspective, double-click the selected .drl file to open it in the editor.
  2. You can add and remove rule breakpoints in the .drl files in two ways:

    • Double-click the rule in the Rule editor at the line where you want to add a breakpoint. A breakpoint can be removed by double-clicking the rule once more.

      Note

      Rule breakpoints can only be created in the consequence of a rule. Double-clicking on a line where no breakpoint is allowed does nothing.

    • Right-click the ruler. Select the Toggle Breakpoint action in the context menu. Choosing this action adds a breakpoint at the selected line or remove it if there is one already.
  3. The Debug perspective contains a Breakpoints view which can be used to see all defined breakpoints, get their properties, enable/disable and remove them. You can switch to it by clicking WindowPerspectiveOthersDebug.

Part III. All About Processes

Chapter 10. Getting Started with Processes

JBoss Business Process Management System is a light-weight, open-source, flexible Business Process Management (BPM) Suite that allows you to create, execute, and monitor business processes throughout their life cycle. The business processes allow you to model your business goals. They describe the steps that need to be executed to achieve those goals. It depicts the order of these goals in a flow chart. The business processes greatly improve the visibility and agility of your business logic.

Red Hat JBoss BPM Suite creates the bridge between business analysts, developers and end users by offering process management features and tools in a way that both business users and developers like. The life cycle of Business processes includes authoring, deployment, process management and task lists, and dashboards and reporting.

10.1. The Red Hat JBoss BPM Suite Engine

The core of Red Hat JBoss BPM Suite is a light-weight, extensible workflow engine called the BPM Suite engine in BPMN 2.0 format, written in pure Java that allows you to execute business processes. It can run in any Java environment, embedded in your application or as a service. It has the following features:

  • Solid, stable core engine for executing your process instances.
  • Native support for the latest BPMN 2.0 specification for modeling and executing business processes.
  • Strong focus on performance and scalability.
  • Light-weight. You can deploy it on almost any device that supports a simple Java Runtime Environment. It does not require any web container at all.
  • Pluggable persistence with a default JPA implementation (Optional).
  • Pluggable transaction support with a default JTA implementation.
  • Implemented as a generic process engine, so it can be extended to support new node types or other process languages.
  • Listeners to be notified of various events.
  • Ability to migrate running process instances to a new version of their process definition.

10.2. Integrating BPM Suite Engine With Other Services

The Red Hat JBoss BPM Suite engine can be integrated with a few independent core services such as:

The human task service
The human task service helps manage human tasks when human actors need to participate in the process. It is fully pluggable and the default implementation is based on the WS-HumanTask specification and manages the life cycle of the tasks, task lists, task forms, and some more advanced features like escalation, delegation, and rule-based assignments.
The history log
The history log stores all information about the execution of all the processes in the engine. This is necessary if you need access to historic information as runtime persistence only stores the current state of all active process instances. The history log can be used to store all current and historic states of active and completed process instances. It can be used to query for any information related to the execution of process instances, for monitoring, and analysis.

Chapter 11. Working with Processes

11.1. BPMN 2.0 Notation

11.1.1. Business Process Model and Notation (BPMN) 2.0 Specification

The Business Process Model and Notation (BPMN) 2.0 specification defines a standard for graphically representing a business process; it includes execution semantics for the defined elements and an XML format to store and share process definitions.

The table below shows the supported elements of the BPMN 2.0 specification and includes some additional elements and attributes.

definitions
Supported attributesSupported elementsExtension attributesExtension elements
 

BPMNDiagram, itemDefinition, signal, process, relationship*

  
process
Supported attributesSupported elementsExtension attributesExtension elements

processType, isExecutable, name, id

property, laneSet, flowElement

packageName, adHoc, version

import, global

sequenceFlow
Supported attributesSupported elementsExtension attributesExtension elements

sourceRef, targetRef, isImmediate, name, id

conditionExpression

priority

 
interface
Supported attributesSupported elementsExtension attributesExtension elements

name, id

operation

  
operation
Supported attributesSupported elementsExtension attributesExtension elements

name, id

inMessageRef

  
laneSet
Supported attributesSupported elementsExtension attributesExtension elements
 

lane

  
lane
Supported attributesSupported elementsExtension attributesExtension elements

name, id

flowNodeRef

  
import
Supported attributesSupported elementsExtension attributesExtension elements
 

name

  
global
Supported attributesSupported elementsExtension attributesExtension elements
 

identifier, type

  

* Used for extension elements for BPMN2, such as simulation data.

BPMN 2.0 Supported Elements and Attributes (Events)
startEvent
Supported attributesSupported elementsExtension attributesExtension elements

name, id

dataOutput, dataOutputAssociation, outputSet, eventDefinition

x, y, width, height

 
endEvent
Supported attributesSupported elementsExtension attributesExtension elements

name, id

dataInput, dataInputAssociation, inputSet, eventDefinition

x, y, width, height

 
intermediateCatchEvent
Supported attributesSupported elementsExtension attributesExtension elements

name, id

dataOutput, dataOutputAssociation, outputSet, eventDefinition

x, y, width, height

 
intermediateThrowEvent
Supported attributesSupported elementsExtension attributesExtension elements

name, id

dataInput, dataInputAssociation, inputSet, eventDefinition

x, y, width, height

 
boundaryEvent
Supported attributesSupported elementsExtension attributesExtension elements

cancelActivity, attachedToRef, name, id

eventDefinition

x, y, width, height

 
terminateEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements
    
compensateEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements

activityRef

documentation, extensionElements

  
conditionalEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements
 

condition

  
errorEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements

errorRef

   
error
Supported attributesSupported elementsExtension attributesExtension elements

errorCode, id

   
escalationEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements

escalationRef

   
escalation
Supported attributesSupported elementsExtension attributesExtension elements

escalationCode, id

   
messageEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements

messageRef

   
message
Supported attributesSupported elementsExtension attributesExtension elements

itemRef, id

   
signalEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements

signalRef

   
timerEventDefinition
Supported attributesSupported elementsExtension attributesExtension elements
 

timeCycle, timeDuration

  
BPMN 2.0 Supported Elements and Attributes (Activities)
task
Supported attributesSupported elementsExtension attributesExtension elements

name, id

ioSpecification, dataInputAssociation, dataOutputAssociation

taskName, x, y, width, height

 
scriptTask
Supported attributesSupported elementsExtension attributesExtension elements

scriptFormat, name, id

script

x, y, width, height

 
script
Supported attributesSupported elementsExtension attributesExtension elements
 

text[mixed content]

  
userTask
Supported attributesSupported elementsExtension attributesExtension elements

name, id

ioSpecification, dataInputAssociation, dataOutputAssociation, resourceRole

x, y, width, height

onEntry-script, onExit-script

potentialOwner
Supported attributesSupported elementsExtension attributesExtension elements
 

resourceAssignmentExpression

  
resourceAssignmentExpression
Supported attributesSupported elementsExtension attributesExtension elements
 

expression

  
businessRuleTask
Supported attributesSupported elementsExtension attributesExtension elements

name, id

 

x, y, width, height, ruleFlowGroup

onEntry-script, onExit-script

manualTask
Supported attributesSupported elementsExtension attributesExtension elements

name, id

 

x, y, width, height

onEntry-script, onExit-script

sendTask
Supported attributesSupported elementsExtension attributesExtension elements

messageRef, name, id

ioSpecification, dataInputAssociation

x, y, width, height

onEntry-script, onExit-script

receiveTask
Supported attributesSupported elementsExtension attributesExtension elements

messageRef, name, id

ioSpecification, dataOutputAssociation

x, y, width, height

onEntry-script, onExit-script

serviceTask
Supported attributesSupported elementsExtension attributesExtension elements

operationRef, name, id

ioSpecification, dataInputAssociation, dataOutputAssociation

x, y, width, height

onEntry-script, onExit-script

subProcess
Supported attributesSupported elementsExtension attributesExtension elements

name, id

flowElement, property, loopCharacteristics

x, y, width, height

 
adHocSubProcess
Supported attributesSupported elementsExtension attributesExtension elements

cancelRemainingInstances, name, id

completionCondition, flowElement, property

x, y, width, height

 
callActivity
Supported attributesSupported elementsExtension attributesExtension elements

calledElement, name, id

ioSpecification, dataInputAssociation, dataOutputAssociation

x, y, width, height, waitForCompletion, independent

onEntry-script, onExit-script

multiInstanceLoopCharacteristics
Supported attributesSupported elementsExtension attributesExtension elements
 

loopDataInputRef, inputDataItem

  
onEntry-script
Supported attributesSupported elementsExtension attributesExtension elements

scriptFormat

 

script

 
onExit-script
Supported attributesSupported elementsExtension attributesExtension elements

scriptFormat

 

script

 
BPMN 2.0 Supported Elements and Attributes (Gateways)
parallelGateway
Supported attributesSupported elementsExtension attributesExtension elements

gatewayDirection, name, id

 

x, y, width, height

 
eventBasedGateway
Supported attributesSupported elementsExtension attributesExtension elements

gatewayDirection, name, id

 

x, y, width, height

 
exclusiveGateway
Supported attributesSupported elementsExtension attributesExtension elements

default, gatewayDirection, name, id

 

x, y, width, height

 
inclusiveGateway
Supported attributesSupported elementsExtension attributesExtension elements

default, gatewayDirection, name, id

 

x, y, width, height

 
BPMN 2.0 Supported Elements and Attributes (Data)
property
Supported attributesSupported elementsExtension attributesExtension elements

itemSubjectRef, id

   
dataObject
Supported attributesSupported elementsExtension attributesExtension elements

itemSubjectRef, id

   
itemDefinition
Supported attributesSupported elementsExtension attributesExtension elements

structureRef, id

   
signal
Supported attributesSupported elementsExtension attributesExtension elements

name, id

   
ioSpecification
Supported attributesSupported elementsExtension attributesExtension elements
 

dataInput, dataOutput, inputSet, outputSet

  
dataInput
Supported attributesSupported elementsExtension attributesExtension elements

name, id

   
dataInputAssociation
Supported attributesSupported elementsExtension attributesExtension elements
 

sourceRef, targetRef, assignment

  
dataOutput
Supported attributesSupported elementsExtension attributesExtension elements

name, id

   
dataOutputAssociation
Supported attributesSupported elementsExtension attributesExtension elements
 

sourceRef, targetRef, assignment

  
inputSet
Supported attributesSupported elementsExtension attributesExtension elements
 

dataInputRefs

  
outputSet
Supported attributesSupported elementsExtension attributesExtension elements
 

dataOutputRefs

  
assignment
Supported attributesSupported elementsExtension attributesExtension elements
 

from, to

  
formalExpression
Supported attributesSupported elementsExtension attributesExtension elements

language

text[mixed content]

  
BPMN 2.0 Supported Elements and Attributes (BPMNDI)
BPMNDiagram
Supported attributesSupported elementsExtension attributesExtension elements
 

BPMNPlane

  
BPMNPlane
Supported attributesSupported elementsExtension attributesExtension elements

bpmnElement

BPMNEdge, BPMNShape

  
BPMNShape
Supported attributesSupported elementsExtension attributesExtension elements

bpmnElement

Bounds

  
BPMNEdge
Supported attributesSupported elementsExtension attributesExtension elements

bpmnElement

waypoint

  
Bounds
Supported attributesSupported elementsExtension attributesExtension elements

x, y, width, height

   
waypoint
Supported attributesSupported elementsExtension attributesExtension elements

x, y

   

11.1.2. BPMN 2.0 Process Example

Here is a BPMN 2.0 process that prints out a "Hello World" statement when the process is started:

<?xml version="1.0" encoding="UTF-8"?>
<definitions id="Definition"
             targetNamespace="http://www.jboss.org/drools"
             typeLanguage="http://www.java.com/javaTypes"
             expressionLanguage="http://www.mvel.org/2.0"
             xmlns="http://www.omg.org/spec/BPMN/20100524/MODEL"
             xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
             xsi:schemaLocation="http://www.omg.org/spec/BPMN/20100524/MODEL BPMN20.xsd"
             xmlns:bpmndi="http://www.omg.org/spec/BPMN/20100524/DI"
             xmlns:dc="http://www.omg.org/spec/DD/20100524/DC"
             xmlns:di="http://www.omg.org/spec/DD/20100524/DI"
             xmlns:tns="http://www.jboss.org/drools">

  <process processType="Private" isExecutable="true" id="com.sample.bpmn.hello" name="Hello World" >

    <!-- nodes -->
    <scriptTask id="_2" name="Hello" >
      <script>System.out.println("Hello World");</script>
    </scriptTask>
    <startEvent id="_1" />
    <endEvent id="_3" >
        <terminateEventDefinition/>
    </endEvent>

    <!-- connections -->
    <sequenceFlow id="_1-_2" sourceRef="_1" targetRef="_2" />
    <sequenceFlow id="_2-_3" sourceRef="_2" targetRef="_3" />

  </process>

  <bpmndi:BPMNDiagram>
    <bpmndi:BPMNPlane bpmnElement="com.sample.bpmn.hello" >
      <bpmndi:BPMNShape bpmnElement="_2" >
        <dc:Bounds x="96" y="16" width="80" height="48" />
      </bpmndi:BPMNShape>
      <bpmndi:BPMNShape bpmnElement="_1" >
        <dc:Bounds x="30" y="22" width="36" height="36" />
      </bpmndi:BPMNShape>
      <bpmndi:BPMNShape bpmnElement="_3" >
        <dc:Bounds x="210" y="22" width="36" height="36" />
      </bpmndi:BPMNShape>
      <bpmndi:BPMNEdge bpmnElement="_1-_2" >
        <di:waypoint x="66" y="40" />
        <di:waypoint x="96" y="40" />
      </bpmndi:BPMNEdge>
      <bpmndi:BPMNEdge bpmnElement="_2-_3" >
        <di:waypoint x="176" y="40" />
        <di:waypoint x="210" y="40" />
      </bpmndi:BPMNEdge>
    </bpmndi:BPMNPlane>
  </bpmndi:BPMNDiagram>

</definitions>

11.1.3. Supported Elements and Attributes in BPMN 2.0 Specification

Red Hat JBoss BPM Suite 6 does not implement all elements and attributes as defined in the BPMN 2.0 specification. However, we do support significant node types that you can use inside executable processes. This includes almost all elements and attributes as defined in the Common Executable subclass of the BPMN 2.0 specification, extended with some additional elements and attributes we believe are valuable in that context as well. The full set of elements and attributes that are supported can be found below, but it includes elements like:

Flow Objects
  • Events

    • Start Event (None, Conditional, Signal, Message, Timer)
    • End Event (None, Terminate, Error, Escalation, Signal, Message, Compensation)
    • Intermediate Catch Event (Signal, Timer, Conditional, Message)
    • Intermediate Throw Event (None, Signal, Escalation, Message, Compensation)
    • Non-interrupting Boundary Event (Escalation, Signal, Timer, Conditional, Message)
    • Interrupting Boundary Event (Escalation, Error, Signal, Timer, Conditional, Message, Compensation)
  • Activities

    • Script Task
    • Task
    • Service Task
    • User Task
    • Business Rule Task
    • Manual Task
    • Send Task
    • Receive Task
    • Reusable Sub-Process (Call Activity)
    • Embedded Sub-Process
    • Event Sub-Process
    • Ad-Hoc Sub-Process
    • Data-Object
  • Gateways

    • Diverging

      • Exclusive
      • Inclusive
      • Parallel
      • Event-Based
    • Converging

      • Exclusive
      • Inclusive
      • Parallel
  • Lanes
Data
  • Java type language
  • Process properties
  • Embedded Sub-Process properties
  • Activity properties
Connecting Objects
  • Sequence flow

11.1.4. Loading and Executing a BPMN2 Process Into Repository

The following example shows how you can load a BPMN2 process into your knowledge base:

import org.kie.api.KieServices;
import org.kie.api.builder.KieRepository;
import org.kie.api.builder.KieFileSystem;
import org.kie.api.builder.KieBuilder;
import org.kie.internal.io.ResourceFactory;
import org.kie.api.runtime.KieContainer;
import org.kie.api.KieBase;
...
KieServices kServices = KieServices.Factory.get();
KieRepository kRepository = kServices.getRepository();
KieFileSystem kFileSystem = kServices.newKieFileSystem();

kFileSystem.write(ResourceFactory.newClassPathResource("MyProcess.bpmn"));

KieBuilder kBuilder = kServices.newKieBuilder(kFileSystem);
kBuilder.buildAll();

KieContainer kContainer = kServices.newKieContainer(kRepository.getDefaultReleaseId());
KieBase kBase = kContainer.getKieBase();

For a list of Maven dependencies, see example Embedded jBPM Engine Dependencies.

11.2. What Comprises a Business Process

A business process is a graph that describes the order in which a series of steps need to be executed using a flow chart. A process consists of a collection of nodes that are linked to each other using connections. Each of the nodes represents one step in the overall process, while the connections specify how to transition from one node to the other. A large selection of predefined node types have been defined.

A typical process consists of the following parts:

  • The header part that comprises global elements such as the name of the process, imports, and variables.
  • The nodes section that contains all the different nodes that are part of the process.
  • The connections section that links these nodes to each other to create a flow chart.

Figure 11.1. A Business Process

This image shows the steps of "self evaluation" through the project manager and HR manager.

Processes can be created with the following methods:

  • Using the Business Central or Red Hat JBoss Developer Studio with BPMN2 modeler.
  • As an XML file, according to the XML process format as defined in the XML Schema Definition in the BPMN 2.0 specification.
  • By directly creating a process using the Process API.
Note

The Red Hat JBoss Developer Studio Process editor has been deprecated in favor of BPMN2 Modeler for process modeling as it is not being developed any more. However, you can still use it for limited number of supported elements.

11.2.1. Process Nodes

Executable processes consist of different types of nodes which are connected to each other. The BPMN 2.0 specification defines three main types of nodes:

Events
Event elements represent a particular event that occurs or can occur during process runtime.
Activities
Activities represent relatively atomic pieces of work that need to be performed as part of the process execution.
Gateways
Gateways represent forking or merging of workflows during process execution.

11.2.2. Process Properties

Every process has the following properties:

  • ID: The unique ID of the process.
  • Name: The display name of the process.
  • Version: The version number of the process.
  • Package: The package (namespace) the process is defined in.
  • Variables (optional): Variables to store data during the execution of your process.
  • Swimlanes: Swimlanes used in the process for assigning human tasks.

11.2.3. Defining Processes Using XML

You can create processes directly in XML format using the BPMN 2.0 specifications. The syntax of these XML processes is defined using the BPMN 2.0 XML Schema Definition.

The process XML file consists of:

The process element
This is the top part of the process XML that contains the definition of the different nodes and their properties. The process XML consist of exactly one <process> element. This element contains parameters related to the process (its type, name, ID, and package name), and consists of three subsections: a header section (where process-level information like variables, globals, imports, and lanes can be defined), a nodes section that defines each of the nodes in the process, and a connections section that contains the connections between all the nodes in the process.
The BPMNDiagram element
This is the lower part of the process XML that contains all graphical information, like the location of the nodes. In the nodes section, there is a specific element for each node, defining the various parameters and, possibly, sub-elements for that node type.

The following XML fragment shows a simple process that contains a sequence of a Start Event, a Script Task that prints "Hello World" to the console, and an End Event:

<?xml version="1.0" encoding="UTF-8"?>

<definitions
  id="Definition"
  targetNamespace="http://www.jboss.org/drools"
  typeLanguage="http://www.java.com/javaTypes"
  expressionLanguage="http://www.mvel.org/2.0"
  xmlns="http://www.omg.org/spec/BPMN/20100524/MODEL"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://www.omg.org/spec/BPMN/20100524/MODEL BPMN20.xsd"
  xmlns:g="http://www.jboss.org/drools/flow/gpd"
  xmlns:bpmndi="http://www.omg.org/spec/BPMN/20100524/DI"
  xmlns:dc="http://www.omg.org/spec/DD/20100524/DC"
  xmlns:di="http://www.omg.org/spec/DD/20100524/DI"
  xmlns:tns="http://www.jboss.org/drools">

  <process processType="Private" isExecutable="true" id="com.sample.hello" name="Hello Process">
    <!-- nodes -->
    <startEvent id="_1" name="Start" />

    <scriptTask id="_2" name="Hello">
      <script>System.out.println("Hello World");</script>
    </scriptTask>

    <endEvent id="_3" name="End" >
      <terminateEventDefinition/>
    </endEvent>

    <!-- connections -->

    <sequenceFlow id="_1-_2" sourceRef="_1" targetRef="_2" />
    <sequenceFlow id="_2-_3" sourceRef="_2" targetRef="_3" />
  </process>

  <bpmndi:BPMNDiagram>
    <bpmndi:BPMNPlane bpmnElement="com.sample.hello" >

      <bpmndi:BPMNShape bpmnElement="_1" >
        <dc:Bounds x="16" y="16" width="48" height="48" />
      </bpmndi:BPMNShape>

      <bpmndi:BPMNShape bpmnElement="_2" >
        <dc:Bounds x="96" y="16" width="80" height="48" />
      </bpmndi:BPMNShape>

      <bpmndi:BPMNShape bpmnElement="_3" >
        <dc:Bounds x="208" y="16" width="48" height="48" />
      </bpmndi:BPMNShape>

      <bpmndi:BPMNEdge bpmnElement="_1-_2" >
        <di:waypoint x="40" y="40" />
        <di:waypoint x="136" y="40" />
      </bpmndi:BPMNEdge>

      <bpmndi:BPMNEdge bpmnElement="_2-_3" >
        <di:waypoint x="136" y="40" />
        <di:waypoint x="232" y="40" />
      </bpmndi:BPMNEdge>

    </bpmndi:BPMNPlane>
  </bpmndi:BPMNDiagram>

</definitions>

11.3. Activities

An activity is an action performed inside a business process. Activities are classified based on the type of tasks they do:

Task
Use this activity type in your business process to implement a single task which can not be further broken into subtasks.
Subprocess
Use this activity type in your business process when you have a group of tasks to be processed in a sequential order in order to achieve a single result.

Each activity has one incoming and one outgoing connection.

11.3.1. Tasks

A task is an action that is executed inside a business process. Tasks can be of the following types:

Table 11.1. Types of Tasks in Object Library
TaskIconDescription

User

6607

Use the User task activity type in your business process when you require a human actor to execute your task.

  • The User task defines within it, the type of task that needs to be executed. You must pass the data that a human actor may require to execute this task as the content of the task.
  • The User task has one incoming and one outgoing connection. You can use the User tasks in combination with Swimlanes to assign multiple human tasks to similar human actors.

Send

6608

Use the Send task to send a message.

  • A Send task has a message associated with it.
  • When a Send task is activated, the message data is assigned to the data input property of the Send task. A Send task completes when this message is sent.

Receive

6609

Use the Receive task in your process when your process is relying on a specific message to continue.

  • When a Receive task receives the specified message, the data from the message is transferred to the Data Output property of the Receive task and the task completes.

Manual

6610

Use the Manual task when you require a task to be executed by a human actor that need not be managed by your process.

  • The difference between a Manual task and a User task is that a User task is executed in the context of the process, requires system interaction to accomplish the task, and are assigned to specific human actors. The Manual tasks on the other hand, execute without the need to interact with the system and not managed by the process.

Service

6611

Use the Service task in your business process for specifying the tasks use a service (such as a web service) that must execute outside the process engine.

  • The Service task may use any service such as email server, message logger, or any other automated service.
  • You can specify the required input parameters and expected results of this task in its properties. When the associated work is executed and specified result is received, the Service task completes.

Business Rule

6612

Use the Business Rule task when you want a set of rules to be executed as a task in your business process flow.

  • During the execution of your process flow, when the engine reaches the Business Rule task, all the rules associated with this task are fired and evaluated.
  • The DataInputSet and DataOutputSet properties define the input to the rule engine and the calculated output received from the rule engine respectively.
  • The set of rules that this task runs are defined in .drl format.
  • All the rules that belong to a Business Rule task must belong to a specific ruleflow group. You can assign a rule its ruleflow group using the ruleflow-group attribute in the header of the rule. So when a Business Rule task executes, all the rules that belong to the ruleflow-group specified in the ruleflow-group property of the task are executed.

Script

6613

Use the Script task in your business process when you want a script to be executed within the task.

  • A Script task has an associated action that contains the action code and the language that the action is written in.
  • When a Script task is reached in the process, it executes the action and then continues to the next node.
  • Use a Script task in your process to for modeling low level behavior such as manipulating variables. For a complex model, use a Service task.
  • Ensure that the script associated with a Script task is executed as soon as the task is reached in a business process. If that is not possible, use an asynchronous Service task instead.
  • Ensure that your script does not contact an external service as the process engine has no visibility of the external services that a script may call.
  • Ensure that any exception that your script may throw must be caught within the script itself.

None

6614

A None task type is an abstract undefined task type.

11.3.2. Subprocesses

A subprocess is a process within another process. When a parent process calls a child process (subprocess), the child process executes in a sequential manner and once complete, the execution control then transfers to the main parent process. Subprocess can be of the following types:

Table 11.2. Types of Subprocesses in Object Library
SubprocessIconDescription

Reusable

6615

Use the Reusable subprocess to invoke another process from the parent process.

The Reusable subprocess is independent from its parent process.

Multiple Instances

6616

Use the Multiple Instances subprocess when you want to execute the contained subprocess elements multiple number of times.

When the engine reaches a Multiple Instance subprocess in your process flow, the subprocess instances are executed in a sequential manner.

A Multiple Instances subprocess is completed when the condition specified in the MI completion condition property is satisfied.

Embedded

6617

Use the Embedded subprocess if you want a decomposable activity inside your process flow that encapsulates a part of your main process.

When you expand an Embedded subprocess, you can see a valid BPMN diagram inside that comprises a Start Event and at least one End Event.

An Embedded subprocess allows you to define local subprocess variables that are accessible to all elements inside this subprocess.

Ad-Hoc

6618

Use the Ad-Hoc subprocess when you want to execute activities inside your process, for which the execution order is irrelevant. An Ad-Hoc subprocess is a group of activities that have no required sequence relationships.

You can define a set of activities for this subprocess, but the sequence and number of performances for the activities is determined by the performers of the activities.

Use an Ad-Hoc subprocesses for example when executing a list of tasks that have no dependencies between them and can be executed in any order.

Event

6619

Use the Event subprocess in your process flow when you want to handle events that occur within the boundary of a subprocess. This subprocess becomes active when its start event gets triggered.

The Event subprocess differs from the other subprocess as they are not a part of the regular process flow and occur only in the context of a subprocess.

An Event subprocess can be interrupting or non-interrupting. The interrupting Event subprocess interrupts the parent process unlike the non-interrupting Event subprocess.

Note

Only the Reusable subprocess can contain Swimlanes.

11.4. Data

Throughout the execution of a process, data can be retrieved, stored, passed on, and used. To store runtime data during the execution of the process, process variables are used. A variable is defined with a name and a data type. A basic data type could include the following: boolean, int, String, or any kind of object subclass.

Variables can be defined inside a variable scope. The top-level scope is the variable scope of the process itself. Sub-scopes can be defined using a sub-process. Variables that are defined in a sub-scope are only accessible for nodes within that scope.

Whenever a variable is accessed, the process will search for the appropriate variable scope that defines the variable. Nesting variable scopes are allowed. A node will always search for a variable in its parent container; if the variable cannot be found, the node will look in the parent’s parent container, and so on, until the process instance itself is reached. If the variable cannot be found, a read access yields null, and a write access produces an error message. All of this occurs with the process continuing execution.

Variables can be used in the following ways:

  • Process-level variables can be set when starting a process by providing a map of parameters to the invocation of the startProcess method. These parameters will be set as variables on the process scope.
  • Script actions can access variables directly simply by using the name of the variable as a local parameter in their script. For example, if the process defines a variable of type "org.jbpm.Person" in the process, a script in the process could access this directly:

    // call method on the process variable "person"
    
    person.setAge(10);

    Changing the value of a variable in a script can be done through the knowledge context:

    kcontext.setVariable(variableName, value);
    Warning

    Do not create a script variable with the same name as a process variable. Otherwise, an error similar to the following error is thrown during the deployment of your application. In the following case, the variable person has been declared both in a script task and as a process variable.

    ERROR [org.drools.compiler.kie.builder.impl.AbstractKieModule] (default task-16) Unable to build KieBaseModel:defaultKieBase
    Process Compilation error : Process com.myteam.scripttask.ScriptTaskBP(ScriptTask.ScriptTaskBP)
    	com/myteam/scripttask/Process_com$u46$myteam$u46$scripttask$u46$ScriptTaskBP95786628.java (9:437) : Duplicate local variable person
  • Service tasks (and reusable sub-processes) can pass the value of process variables to the outside world (or another process instance) by mapping the variable to an outgoing parameter. For example, the parameter mapping of a service task could define that the value of the process variable x should be mapped to a task parameter y just before the service is invoked. You can also inject the value of the process variable into a hard-coded parameter String using #{expression}. For example, the description of a human task could be defined as the following:

    You need to contact person #{person.getName()}

    Where person is a process variable. This will replace this expression with the actual name of the person when the service needs to be invoked. Similar results of a service (or reusable sub-process) can also be copied back to a variable using result mapping.

  • Various other nodes can also access data. Event nodes, for example, can store the data associated to the event in a variable. Check the properties of the different node types for more information.

Finally, processes (and rules) have access to globals, for example, globally defined variables and data in the Knowledge Session. Globals are directly accessible in actions like variables. Globals need to be defined as part of the process before they can be used. Globals can be set using the following:

ksession.setGlobal(name, value)

Globals can also be set from inside process scripts using:

kcontext.getKieRuntime().setGlobal(name,value);.

11.5. Events

Events are triggers, which when occur, impact a business process. Events are classified as start events, end events, and intermediate events. A start event indicates the beginning of a business process. An end event indicates the completion of a business process. And intermediate events drive the flow of a business process. Every event has an event ID and a name. You can implement triggers for each of these event types to identify the conditions under which an event is triggered. If the conditions of the triggers are not met, the events are not initialized, and hence the process flow does not complete.

11.5.1. Start Events

A start event is a flow element in a business process that indicates the beginning of a business process flow. The execution of a business process starts at this node, so a process flow can only have one start event. A start event can have only one outgoing connection which connects to another node to take the process flow ahead. Start events are of the following types:

Table 11.3. Types of Start Events in Object Library
EventIconDescription

None

6620

Use the None start events when your processes do not need a trigger to be initialized.

  • You can use the start event if your process does not depend on any condition to begin.
  • The start event is mostly used to initialize a subprocess or a process that needs to trigger by default or the trigger for the process is irrelevant.

Message

6621

Use the Message start event when you require your process to start, on receiving a particular message.

  • You can have multiple Message start events in your process.
  • A single message can trigger multiple Message start events that instantiates multiple processes.

Timer

6622

Use the Timer start event when you require your process to initialize at a specific time, specific points in time, or after a specific time span.

  • The Timer start event is mostly used in cases where a waiting state is required, for example, in cases involving a Human Task.

Escalation

6623

Use the Escalation start event in your subprocesses when you require your subprocess to initialize as a response to an escalation.

  • An escalation is identified by an escalation object in the main process, which is inserted into the main process by an Escalation Intermediate event or/and Escalation end event. An Escalation Intermediate event or/and Escalation end event produce an escalation object, which can be consumed by an Escalation Start event or an Escalation intermediate catch event.
  • A process flow can have one or more Escalation start events and the process flow does not complete until all the escalation objects are caught and handled in subprocesses.

Conditional

6624

Use the Conditional start event to start a process instance based on a business condition.

  • A condition output is a Boolean value and when a condition is evaluated as true, the process flow is initialized.
  • You can have one or more Conditional start events in your business process.

Error

6625

Use the Error start event in a subprocess when you require your subprocess to trigger as a response to a specific error object.

  • An error object indicates an incorrect process ending and must be handled for the process flow to complete.
  • An error object is inserted into a business process by an Error end event and can be handled by a Error intermediate catch event, or Error start event depending on the scope of the error in a process flow.

Compensation

6626

Use the Compensation start event in a subprocess when you require to handle a compensation.

  • A compensation means undoing the results of an already completed action. Note that this is different than an error. An error suspends a process at the location where it occurs, however, a compensation compensates the results of an action the process has already committed and needs to be undone.
  • A Compensation start event starts a subprocess and is the target Activity of a Compensation intermediate event.

Signal

6627

Use the Signal start event to start a process instance based on specific signals received from other processes.

  • A signal is identified by a signal object. A signal object defines a unique reference ID that is unique in a session.
  • A signal object is inserted in a process by a throw signal intermediate event as an action of an activity.

11.5.2. End Events

An end event marks the end of a business process. Your business process may have more than one end event. An end event has one incoming connection and no outgoing connections. End events are of the following types:

Table 11.4. Types of End Events in Object Library
EventIconDescription

None

6628

Use the None error end event to mark the end of your process or a subprocess flow. Note that this does not influence the workflow of any parallel subprocesses.

Message

6629

Use the Message end event to end your process flow with a message to an element in another process. An intermediate catch message event or a start message event in another process can catch this message to further process the flow.

Escalation

6630

Use the Escalation end event to mark the end of a process as a result of which the case in hand is escalated. This event creates an escalation signal that further triggers the escalation process.

Error

6631

Use the Error end event in your process or subprocess to end the process in an error state and throw a named error, which can be caught by a Catching Intermediate event.

Cancel

6632

Use the Cancel end event to end your process as canceled. Note that if your process comprises any compensations, it completes them and then marks the process as canceled.

Compensation

6633

Use the Compensation end event to end the current process and trigger compensation as the final step.

Signal

6634

Use the Signal end event to end a process with a signal thrown to an element in one or more other processes. Another process can catch this signal using Catch intermediate events.

Terminate

6635

Use the Terminate end event to terminate the entire process instance immediately. Note that this terminates all the other parallel execution flows and cancels any running activities.

11.5.3. Intermediate Events

Intermediate events occur during the execution of a process flow, and they drive the flow of the process. Some specific situations in a process may trigger these intermediate events. Intermediate events can occur in a process with one or no incoming flow and an outgoing flow. Intermediate events can further be classified as:

  • Catching Intermediate Events;
  • Throwing Intermediate Events.
11.5.3.1. Catching Intermediate Events

Catching intermediate events comprises intermediate events which implement a response to specific indication of a situation from the main process workflow. Catching intermediate events are of the following types:

  • Message: Use the Message catching intermediate events in your process to implement a reaction to an arriving message. The message that this event is expected to react to, is specified in its properties. It executes the flow only when it receives the specific message.
  • Timer: Use the Timer intermediate event to delay the workflow execution until a specified point or duration. A Timer intermediate event has one incoming flow and one outgoing flow and its execution starts when the incoming flow transfers to the event. When placed on an activity boundary, the execution is triggered at the same time as the activity execution.
  • Escalation: Use the Escalation catching intermediate event in your process to consume an Escalation object. An Escalation catching intermediate event awaits a specific escalation object defined in its properties. Once it receives the object, it triggers execution of its outgoing flow.
  • Conditional: Use the Conditional intermediate event to execute a workflow when a specific business Boolean condition that it defines, evaluates to true. When placed in the process workflow, a Conditional intermediate event has one incoming flow and one outgoing flow and its execution starts when the incoming flow transfers to the event. When placed on an activity boundary, the execution is triggered at the same time as the activity execution. Note that if the event is non-interrupting, it triggers continuously while the condition is true.
  • Error: Use the Error catching intermediate event in your process to execute a workflow when it received a specific error object defined in its properties.
  • Compensation: Use the Compensation intermediate event to handle compensation in case of partially failed operations. A Compensation intermediate event is a boundary event that is attached to an activity in a transaction subprocess that may finish with a Compensation end event or a Cancel end event. The Compensation intermediate event must have one outgoing flow that connects to an activity that defines the compensation action needed to compensate for the action performed by the activity.
  • Signal: Use the Signal catching intermediate event to execute a workflow once a specified signal object defined in its properties is received from the main process or any other process.
11.5.3.2. Throwing Intermediate Events

Throwing intermediate events comprises events which produce a specified trigger in the form of a message, escalation, or signal, to drive the flow of a process. Throwing intermediate events are of the following types:

  • Message: Use the Message throw intermediate event to produce and send a message to a communication partner (such as an element in another process). Once it sends a message, the process execution continues.
  • Escalation: Use the Escalation throw intermediate event to produce an escalation object. Once it creates an escalation object, the process execution continues. The escalation object can be consumed by an Escalation start event or an Escalation intermediate catch event, which is looking for this specific escalation object.
  • Signal: Use the Signal throwing intermediate events to produces a signal object. Once it creates a signal object, the process execution continues. The signal object is consumed by a Signal start event or a Signal catching intermediate event, which is looking for this specific signal object.

11.6. Gateways

"Gateways are used to control how Sequence Flows interact as they converge and diverge within a Process."[1]

Gateways are used to create or synchronize branches in the workflow using a set of conditions which is called the gating mechanism. Gateways are either converging (multiple flows into one flow) or diverging (one flow into multiple flows).

One Gateway cannot have multiple incoming and multiple outgoing flows.

Depending on the gating mechanism you want to apply, you can use the following types of gateways:

  • Parallel (AND): in a converging gateway, waits for all incoming flows. In a diverging gateway, takes all outgoing flows simultaneously.
  • Inclusive (OR): in a converging gateway, waits for all incoming flows whose condition evaluates to true. In a diverging gateway takes all outgoing flows whose condition evaluates to true.
  • Exclusive (XOR): in a converging gateway, only the first incoming flow whose condition evaluates to true is chosen. In a diverging gateway only one outgoing flow is chosen.
  • Event-based: used only in diverging gateways for reacting to events. See Section 11.6.1.1, “Event-Based Gateway”.
  • Data-based Exclusive: used in both diverging and converging gateways to make decisions based on available data. See Section 11.6.1.4, “Data-Based Exclusive Gateway”.

11.6.1. Gateway Types

11.6.1.1. Event-Based Gateway

"The Event-Based Gateway has pass-through semantics for a set of incoming branches (merging behavior). Exactly one of the outgoing branches is activated afterwards (branching behavior), depending on which of events of the Gateway configuration is first triggered."[2]

The Gateway is only diverging and allows you to react to possible events as opposed to the Data-based Exclusive Gateway, which reacts to the process data. It is the event that actually occurs that decides which outgoing flow is taken. As it provides the mechanism to react to exactly one of the possible events, it is exclusive, that is, only one outgoing flow is taken.

The Gateway might act as a start event, where the process is instantiated only if one the Intermediate Events connected to the Event-Based Gateway occurs.

11.6.1.2. Parallel Gateway

"A Parallel Gateway is used to synchronize (combine) parallel flows and to create parallel flows."[3]

Diverging
Once the incoming flow is taken, all outgoing flows are taken simultaneously.
Converging
The Gateway waits until all incoming flows have entered and only then triggers the outgoing flow.
11.6.1.3. Inclusive Gateway
Diverging

Once the incoming flow is taken, all outgoing flows whose condition evaluates to true are taken. Connections with lower priority numbers are triggered before triggering higher priority ones; priorities are evaluated but the BPMN2 specification doesn’t guarantee this. So for portability reasons it is recommended that you do not depend on this.

Important

Make sure that at least one of the outgoing flow evaluates to true at runtime; otherwise, the process instance terminates with a runtime exception.

Converging
The Gateway merges all incoming flows previously created by a diverging Inclusive Gateway; that is, it serves as a synchronizing entry point for the Inclusive Gateway branches.
Attributes
Default gate
The outgoing flow taken by default if no other flow can be taken.
11.6.1.4. Data-Based Exclusive Gateway
Diverging

The Gateway triggers exactly one outgoing flow: the flow with the constraint evaluated to true and the lowest priority is taken. After evaluating the constraints that are linked to the outgoing flows: the constraint with the lowest priority number that evaluates to true is selected.

Possible Runtime Exception

Make sure that at least one of the outgoing Flows evaluates to true at runtime: if no Flow can be taken, the execution returns a runtime exception.

Converging
The Gateway allows a workflow branch to continue to its outgoing flow as soon as it reaches the Gateway; that is, whenever one of the incoming flows triggers the Gateway, the workflow is sent to the outgoing flow of the Gateway; if it is triggered from more than one incoming connection, it triggers the next node for each trigger.
Attributes
Default gate
The outgoing flow taken by default if no other flow can be taken.


[1] Business Process Model and Notation (BPMN). Version 2.0, OMG Document Number: formal/2011-01-03 http://www.omg.org/spec/BPMN/2.0
[2] Business Process Model and Notation (BPMN). Version 2.0, OMG Document Number: formal/2011-01-03 http://www.omg.org/spec/BPMN/2.0
[3] Business Process Model and Notation (BPMN). Version 2.0, OMG Document Number: formal/2011-01-03 http://www.omg.org/spec/BPMN/2.0

11.7. Variables

Variables are elements that serve for storing a particular type of data during runtime. The type of data a variable contains is defined by its data type.

Just like any context data, every variable has its scope that defines its "visibility". An element, such as a process, subprocess, or task can only access variables in its own and parent contexts: variables defined in the element’s child elements cannot be accessed. Therefore, when an elements requires access to a variable on runtime, its own context is searched first. If the variable cannot be found directly in the element’s context, the immediate parent context is searched. The search continues to "level up" until the Process context is reached; in case of globals, the search is performed directly on the session container. If the variable cannot be found, a read access request returns null and a write access produces an error message, and the process continues its execution. Variables are searched for based on their ID.

In Red Hat JBoss BPM Suite, variables can live in the following contexts:

  • Session context: Globals are visible to all process instances and assets in the given session and are intended to be used primarily by business rules and by constrains. The are created dynamically by the rules or constrains.
  • Process context: Process variables are defined as properties in the BPMN2 definition file and are visible within the process instance. They are initialized at process creation and destroyed on process finish.
  • Element context: Local variables are available within their process element, such as an activity. They are initialized when the element context is initialized, that is, when the execution workflow enters the node and execution of the OnEntry action finished if applicable. They are destroyed when the element context is destroyed, that is, when the execution workflow leaves the element.

    Values of local variables can be mapped to global or process variables using the assignment mechanism (see Section 11.8, “Assignment”). This allows you to maintain relative independence of the parent element that accommodates the local variable. Such isolation may help prevent technical exceptions.

11.8. Assignment

The assignment mechanism allows you to assign a value to an object, such as a variable, before or after the particular element is executed.

When defining assignment on an activity element, the value assignment is performed either before or after activity execution. If the assignment defines mapping to a local variable, the time when the assignment is performed depends on whether the local variable is defined as an DataInput or DataOutput item.

For example, if you need to assign a task to a user whose ID is a process variable, use the assignment to map the variable to the parameter ActorId.

Assignment is defined in the Assignments property in case of activity elements and in the DataInputAssocations or DataOutputAssociations property in case of non-activity elements.

Data Types in Assignment

As parameters of the type String can make use of the assignment mechanism by applying the respective syntax directly in their value, #{userVariable}, assignment is rather intended for mapping of properties that are not of type String.

11.9. Action Scripts

Action scripts are pieces of code that define the Script property or an element’s interceptor action. Action scripts have access to global variables, process variables, and the predefined variable kcontext. Accordingly, kcontext is an instance of the ProcessContext interface. See the ProcessContext Javadoc for more information.

Currently, Java and MVEL are supported as dialects for action scripts definitions. MVEL accepts any valid Java code and additionally provides support for nested access to parameters. For example, the MVEL equivalent of Java call person.getName() is person.name.

Example 11.1. Sample Action Script

The following action script prints out the name of the person:

// Java dialect
System.out.println(person.getName());
// MVEL dialect
System.out.println(person.name);
Process Instance Action Scripts

Additionally, you can use action scripts to view information about process instances.

Use the following commands to:

  • Return the ID of a process instance:

    System.out.println(kcontext.getProcessInstance().getId());
  • Return the parent process instance ID if a process instance has a parent:

    System.out.println(kcontext.getProcessInstance().getParentProcessInstanceId());
  • Return the ID of a process definition that is related to a process instance:

    System.out.println(kcontext.getProcessInstance().getProcessId());
  • Return the name of a process definition that is related to a process instance:

    System.out.println(kcontext.getProcessInstance().getProcessName());
  • Return the state of a process instance:

    System.out.println(kcontext.getProcessInstance().getState());

To set a process variable in an action script, use kcontext.setVariable("VARIABLE_NAME", "VALUE").

11.10. Constraints

There are two types of constraints in business processes: code constraints and rule constraints.

  • Code constraints are boolean expressions evaluated directly whenever they are reached; these constraints are written in either Java or MVEL. Both Java and MVEL code constraints have direct access to the globals and variables defined in the process.

    Here is an example of a valid Java code constraint, person being a variable in the process:

    return person.getAge() > 20;

    Here is an example of a valid MVEL code constraint, person being a variable in the process:

    return person.age > 20;
  • Rule constraints are equal to normal Drools rule conditions. They use the Drools Rule Language syntax to express complex constraints. These rules can, like any other rule, refer to data in the working memory. They can also refer to globals directly. Here is an example of a valid rule constraint:

    Person(age > 20)

    This tests for a person older than 20 in the working memory.

Rule constraints do not have direct access to variables defined inside the process. However, it is possible to refer to the current process instance inside a rule constraint by adding the process instance to the working memory and matching for the process instance in your rule constraint. Logic is included to make sure that a variable processInstance of type WorkflowProcessInstance will only match the current process instance and not other process instances in the working memory. Note, it is necessary to insert the process instance into the session. If it is necessary to update the process instance, use Java code or an on-entry, on-exit, or explicit action in the process. The following example of a rule constraint will search for a person with the same name as the value stored in the variable name of the process:

processInstance : WorkflowProcessInstance()
Person(name == (processInstance.getVariable("name")))
# add more constraints here ...

11.11. Timers

Timers wait for a predefined amount of time before triggering, once, or repeatedly. You can use timers to trigger certain logic after a certain period, or to repeat some action at regular intervals.

Configuring Timer with Delay and Period

A Timer node is set up with a delay and a period. The delay specifies the amount of time to wait after node activation before triggering the timer for the first time. The period defines the time between subsequent trigger activations. A period of 0 results in a one-shot timer. The (period and delay) expression must be of the form [#d][#h][#m][#s][#[ms]]. You can specify the amount of days, hours, minutes, seconds, and milliseconds. Milliseconds is the default value. For example, the expression 1h waits one hour before triggering the timer again.

Configuring Timer ISO-8601 Date Format

Since version 6, you can configure timers with valid ISO8601 date format that supports both one shot timers and repeatable timers. You can define timers as date and time representation, time duration or repeating intervals. For example:

Date - 2013-12-24T20:00:00.000+02:00 - fires exactly at Christmas Eve at 8PM
Duration - PT1S - fires once after 1 second
Repeatable intervals - R/PT1S - fires every second, no limit.
	Alternatively R5/PT1S fires 5 times every second
Configuring Timer with Process Variables

In addition to the above mentioned configuration options, you can specify timers using process variable that consists of string representation of either delay and period or ISO8601 date format. By specifying #{variable}, the engine dynamically extracts process variable and uses it as timer expression. The timer service is responsible for making sure that timers get triggered at the appropriate times. You can cancel timers so that they are no longer triggered. You can use timers in the following ways inside a process:

  • You can add a timer event to a process flow. The process activation starts the timer, and when it triggers, once or repeatedly, it activates the timer node’s successor. Subsequently, the outgoing connection of a timer with a positive period is triggered multiple times. Canceling a Timer node also cancels the associated timer, after which no more triggers occur.
  • You can associate timer with a sub-process or tasks as a boundary event.
Updating Timer Within a Running Process Instance

Sometimes a process requires the possibility to dynamically alter the timer period or delay without the need to restart the entire process workflow. In that case, an already scheduled timer can be rescheduled to meet the new requirements: for example to prolong or shorten the timer expiration time or change the delay, period, and repeat limit.

For this reason, jBPM offers a corresponding UpdateTimerCommand class which allows you to perform these several steps as an atomic operation. All of them are then done within the same transaction.

org.jbpm.process.instance.command.UpdateTimerCommand

It is supported to update the boundary timer events as well as the intermediate timer events.

You can reschedule the timer by specifying the two mandatory parameters and one of the three optional parameter sets of the UpdateTimerCommand class.

Both of the following two parameters are mandatory:

  • process instance ID (long);
  • timer node name (String).

Next, choose and configure one of the three following parameter sets:

  • delay (long);
  • period (long) and repeat limit (int);
  • delay, period, and repeat limit.

Example 11.2. Rescheduling Timer Event

// Start the process instance and record its ID:
long id = kieSession.startProcess(BOUNDARY_PROCESS_NAME).getId();

// Set the timer delay to 3 seconds:
kieSession.execute(new UpdateTimerCommand(id, BOUNDARY_TIMER_ATTACHED_TO_NAME, 3));

As you can notice, the rescheduling is performed using the kieSession executor to ensure execution within the same transaction.

Troubleshooting
Getting IllegalStateException Exception

The Intelligent Process Server uses EJB timer service by default for implementation of timer-based nodes. Consequently, the limitations described in the warning message here about Singleton strategy and CMT are valid for the out-of-the-box Intelligent Process Server setup. To resolve the issue:

  • Change the RuntimeManager strategy.
  • Disable the default EJB timer service for timer nodes by setting the system property org.kie.timer.ejb.disabled to true.
The Intelligent Process Server Throws InactiveTransactionException When Using Timers

When you deploy the Intelligent Process Server on Red Hat JBoss EAP 7 and configure a database for the EJB timer service, processes that require timers end in the InactiveTransactionException exception similar to the following:

WFLYEJB0018: Ignoring exception during setRollbackOnly: com.arjuna.ats.jta.exceptions.InactiveTransactionException: ARJUNA016102: The transaction is not active! Uid is ...

To resolve this issue:

  1. Update your Red Hat JBoss BPM Suite to version 6.4.2.
  2. Set the property org.jbpm.ejb.timer.tx to true.

    Note that the property is not available in previous versions of Red Hat JBoss BPM Suite. See chapter System Properties of Red Hat JBoss BPM Suite Administration and Configuration Guide for further information.

11.12. Multi-Threading

11.12.1. Multi-Threading

In the following text, we will refer to two types of "multi-threading": logical and technical. Technical multi-threading is what happens when multiple threads or processes are started on a computer, for example by a Java or C program. Logical multi-threading is what we see in a BPM process after the process reaches a parallel gateway. From a functional standpoint, the original process will then split into two processes that are executed in a parallel fashion.

The BPM engine supports logical multi-threading; for example, processes that include a parallel gateway are supported. We’ve chosen to implement logical multi-threading using one thread; accordingly, a BPM process that includes logical multi-threading will only be executed in one technical thread. The main reason for doing this is that multiple (technical) threads need to be be able to communicate state information with each other if they are working on the same process. This requirement brings with it a number of complications. While it might seem that multi-threading would bring performance benefits with it, the extra logic needed to make sure the different threads work together well means that this is not guaranteed. There is also the extra overhead incurred because we need to avoid race conditions and deadlocks.

11.12.2. Engine Execution

In general, the BPM engine executes actions in serial. For example, when the engine encounters a script task in a process, it will synchronously execute that script and wait for it to complete before continuing execution. Similarly, if a process encounters a parallel gateway, it will sequentially trigger each of the outgoing branches, one after the other. This is possible since execution is almost always instantaneous, meaning that it is extremely fast and produces almost no overhead. As a result, the user will usually not even notice this. Similarly, action scripts in a process are also synchronously executed, and the engine will wait for them to finish before continuing the process. For example, doing a Thread.sleep(…​) as part of a script will not make the engine continue execution elsewhere but will block the engine thread during that period.

The same principle applies to service tasks. When a service task is reached in a process, the engine will also invoke the handler of this service synchronously. The engine will wait for the completeWorkItem(…​) method to return before continuing execution. It is important that your service handler executes your service asynchronously if its execution is not instantaneous.

To implement an asynchronous service handler, implement the service in a new thread using the executeWorkItem() method in the work item handler that allows the process instance to continue its execution.

package documentation.wih.async;

import java.util.concurrent.TimeUnit;
import org.kie.api.runtime.process.WorkItem;
import org.kie.api.runtime.process.WorkItemHandler;
import org.kie.api.runtime.process.WorkItemManager;

public class MyServiceTaskHandler implements WorkItemHandler {
    private Thread asyncThread;
    public void executeWorkItem(final WorkItem workItem, final WorkItemManager manager) {

        asyncThread = new Thread(new Runnable() {
            public void run() {
                for (int i = 0; i < 10; i++) {
                    System.out.println("Hello number + " + i + " from async!");
                    waitASecond();
                }
            }
        });
        asyncThread.start();

        manager.completeWorkItem(workItem.getId(), null);
    }
    public void abortWorkItem(WorkItem workItem, WorkItemManager manager) {
        //asyncThread can't be aborted
    }
    private static void waitASecond() {
        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException ignored) {}
    }
}

An example of this would be a service task that invokes an external service. Since the delay in invoking this service remotely and waiting for the results might be too long, it might be a good idea to invoke this service asynchronously. This means that the handler will only invoke the service and will notify the engine later when the results are available. In the mean time, the process engine then continues execution of the process.

Human tasks are a typical example of a service that needs to be invoked asynchronously, as we don’t want the engine to wait until a human actor has responded to the request. The human task handler will only create a new task (on the task list of the assigned actor) when the human task node is triggered. The engine will then be able to continue execution on the rest of the process (if necessary), and the handler will notify the engine asynchronously when the user has completed the task.

11.12.3. Job Executor for Asynchronous Execution

In Red Hat JBoss BPM Suite, the Job Executor component integrates with the runtime engine for processing asynchronous tasks. You can delegate asynchronous execution operations, such as error handling, retry, cancellation, and history logging in a new thread (using custom implementation of WorkItemHandler) and use the Job Executor to handle these operations for you. The Job Executor provides an environment for background execution of commands, which are nothing but business logic encapsulated within a simple interface.

The custom tasks that the process engine delegates to the Job Executor runs as asynchronous WorkItemHandler. Red Hat JBoss BPM Suite provides AsyncWorkItemHandler that is backed by the Red Hat JBoss BPM Suite Job Executor. During the execution, the AsyncWorkItemHandler sets contextual data available inside the command. You can configure the AsyncWorkItemHandler class in two ways:

  • As a generic handler where you provide the command name as part of the work item parameters. In Business Central while modeling a process, if you need to execute some work item asynchronously: specify async as the value for the TaskName property, create a data input called CommandClass and assign the fully-qualified class name of this CommandClass as the data input.
  • As a specific handler which is created to handle a given type of work item, thus allowing you to register different instances of AsyncWorkItemHandler for different work items. Commands are most likely to be dedicated to a particular work item, which allows you to specify the CommandClass at registration time instead of requiring it at design time, as with the first approach. But this means that an additional CDI bean that implements WorkItemHandlerProducer interface needs to be provided and placed on the application classpath so that the CDI container can find it. When you are ready to model your process, set the value of the TaskName property to the one provided at registration time.

11.12.4. Using Job Executor in Embedded Mode

The Job Executor API is a public API and is available within kie-api (org.kie.api.executor). You can run your background processes asynchronously using the Job Executor from Business Central or outside the Business Central in embedded mode. To use the Job Executor in Business Central, see Section 11.12.6, “Using Job Executor in Business Central”. Perform the following steps to use the Job Executor in the embedded mode:

  1. Implement the Command interface.
  2. Transfer business data from the process engine to your Command implementation.
  3. Configure the Job Executor.
  4. Register the AsyncWorkItemHandler handler, which uses the Job Executor.
  5. Provide the execution results to the process engine.

Wrapping Business Logic with the Command Interface

The Job Executor contains the business logic to be executed and does not have any process runtime related information. The Job Executor works on instances of the Command interface. It receives data through the CommandContext object and returns results of the execution with ExecutionResults class:

package org.kie.api.executor;

import org.kie.api.executor.ExecutionResults;

public interface Command {
  public ExecutionResults execute(CommandContext ctx) throws Exception;
}

Here, ctx is the contextual data given by the executor service.

Since the Job Executor is decoupled from the runtime process engine and provides only the logic that is to be executed as a part of that command, it promotes reuse of already existing logic by wrapping it with Command implementation.

Transferring Business Data from the Process Engine to the Command Interface

The input data is transferred from the process engine to the command using the data transfer object CommandContext. It is important that the data CommandContext holds is serializable.

package org.kie.api.executor;

import java.io.Serializable;

public class CommandContext implements Serializable {

  private static final long serialVersionUID = -1440017934399413860L;
  private Map<String, Object> data;

  public CommandContext() {
    data  = new HashMap<String, Object>();
  }

  public CommandContext(Map<String, Object> data) {
    this.data = data;
  }

  public void setData(Map<String, Object> data) {
    this.data = data;
  }

  public Map<String, Object> getData() {
    return data;
  }

  public Object getData(String key) {
    return data.get(key);
  }

  public void setData(String key, Object value) {
    data.put(key, value);
  }

  public Set<String> keySet() {
    return data.keySet();
  }

  @Override
  public String toString() {
    return "CommandContext{" + "data=" + data + '}';
  }
}

CommandContext should provide the following:

  • businessKey: a unique identifier of the caller.
  • callbacks: the fully qualified classname (FQCN) of the CommandCallback instance to be called on command completion.

Configuring the Executor

The Job Executor API usage scenarios are identical when used from Business Central and when used outside of Business Central. See example Job Executor configuration options:

  1. In-memory Job Executor with optional configuration:

    import org.jbpm.executor.ExecutorServiceFactory;
    
    ..
    
    // Configuration of in-memory executor service.
    executorService = ExecutorServiceFactory.newExecutorService();
    
    // Set number of threads which will be used by executor - default is 1.
    executorService.setThreadPoolSize(1);
    
    // Sets interval at which executor threads are running in seconds - default is 3.
    executorService.setInterval(1);
    
    // Sets time unit of interval - default is SECONDS.
    executorService.setTimeunit(TimeUnit.SECONDS);
    
    // Number of retries in case of excepting during execution of command - default is 3.
    executorService.setRetries(1);
    
    executorService.init();
  2. Executor configuration using EntityManagerFactory to store jobs into a database:

    emf = Persistence.createEntityManagerFactory("org.jbpm.executor");
    
    // Configuration of database executor service.
    executorService = ExecutorServiceFactory.newExecutorService(emf);
    
    // Optional configuration is skipped.
    executorService.init();

Registering the AsyncWorkItemHandler Handler

The AsyncWorkItemHandler handler uses Job Executor for scheduling tasks. See the following code sample to register the AsyncWorkItemHandler handler:

import java.util.List;
import java.util.Map;

import org.kie.api.event.process.ProcessEventListener;
import org.kie.api.io.ResourceType;
import org.kie.api.runtime.KieSession;
import org.kie.api.runtime.manager.RuntimeEngine;
import org.kie.api.runtime.manager.RuntimeEnvironment;
import org.kie.api.runtime.manager.RuntimeEnvironmentBuilder;
import org.kie.api.runtime.manager.RuntimeManagerFactory;
import org.kie.api.runtime.process.ProcessInstance;
import org.kie.api.runtime.process.WorkItemHandler;
import org.kie.internal.io.ResourceFactory;
import org.kie.internal.runtime.manager.context.EmptyContext;
import org.jbpm.runtime.manager.impl.DefaultRegisterableItemsFactory;

...

 RuntimeEnvironment environment = RuntimeEnvironmentBuilder
  .Factory.get().newDefaultBuilder()
  .userGroupCallback(userGroupCallback)
  .addAsset(ResourceFactory.newClassPathResource
    ("BPMN2-ScriptTask.bpmn2"), ResourceType.BPMN2)
  .registerableItemsFactory(new DefaultRegisterableItemsFactory() {

    @Override
    public Map<String, WorkItemHandler> getWorkItemHandlers(RuntimeEngine runtime) {
      Map<String, WorkItemHandler> handlers = super.getWorkItemHandlers(runtime);
      handlers.put("async", new AsyncWorkItemHandler
        (executorService, "org.jbpm.executor.commands.PrintOutCommand"));
      return handlers;
    }

    @Override
    public List<ProcessEventListener> getProcessEventListeners( RuntimeEngine runtime) {
      List<ProcessEventListener> listeners = super.getProcessEventListeners(runtime);
      listeners.add(countDownListener);
      return listeners;
    }
  })

  .get();

manager = RuntimeManagerFactory.Factory.get().newSingletonRuntimeManager(environment);
assertNotNull(manager);

RuntimeEngine runtime =