Chapter 2. KIE sessions

A stateless KIE session is a session that does not use inference to make iterative changes to facts over time. In a stateless KIE session, data from a previous invocation of the KIE session (the previous session state) is discarded between session invocations, whereas in a stateful KIE session, that data is retained. A stateless KIE session behaves similarly to a function in that the results that it produces are determined by the contents of the KIE base and by the data that is passed into the KIE session for execution at a specific point in time. The KIE session has no memory of any data that was passed into the KIE session previously.

Stateless KIE sessions are commonly used for the following use cases:

For example, consider the following driver’s license data model and sample DRL rule:

public class Applicant {
  private String name;
  private int age;
  private boolean valid;
  // Getter and setter methods
}

package com.company.license

rule "Is of valid age"
when
  $a : Applicant(age < 18)
then
  $a.setValid(false);
end

The Is of valid age rule disqualifies any applicant younger than 18 years old. When the Applicant object is inserted into the decision engine, the decision engine evaluates the constraints for each rule and searches for a match. The "objectType" constraint is always implied, after which any number of explicit field constraints are evaluated. The variable $a is a binding variable that references the matched object in the rule consequence.

In this example, the sample rule and all other files in the ~/resources folder of the Red Hat Decision Manager project are built with the following code:

KieServices kieServices = KieServices.Factory.get();

KieContainer kContainer = kieServices.getKieClasspathContainer();

This code compiles all the rule files found on the class path and adds the result of this compilation, a KieModule object, in the KieContainer.

Finally, the StatelessKieSession object is instantiated from the KieContainer and is executed against specified data:

StatelessKieSession kSession = kContainer.newStatelessKieSession();

Applicant applicant = new Applicant("Mr John Smith", 16);

assertTrue(applicant.isValid());

ksession.execute(applicant);

assertFalse(applicant.isValid());

In a stateless KIE session configuration, the execute() call acts as a combination method that instantiates the KieSession object, adds all the user data and executes user commands, calls fireAllRules(), and then calls dispose(). Therefore, with a stateless KIE session, you do not need to call fireAllRules() or call dispose() after session invocation as you do with a stateful KIE session.

In this case, the specified applicant is under the age of 18, so the application is declined.

For a more complex use case, see the following example. This example uses a stateless KIE session and executes rules against an iterable list of objects, such as a collection.

public class Applicant {
  private String name;
  private int age;
  // Getter and setter methods
}

public class Application {
  private Date dateApplied;
  private boolean valid;
  // Getter and setter methods
}

package com.company.license

rule "Is of valid age"
when
  Applicant(age < 18)
  $a : Application()
then
  $a.setValid(false);
end

rule "Application was made this year"
when
  $a : Application(dateApplied > "01-jan-2009")
then
  $a.setValid(false);
end

StatelessKieSession ksession = kbase.newStatelessKnowledgeSession();
Applicant applicant = new Applicant("Mr John Smith", 16);
Application application = new Application();

assertTrue(application.isValid());
ksession.execute(Arrays.asList(new Object[] { application, applicant }));  1
assertFalse(application.isValid());

ksession.execute
  (CommandFactory.newInsertIterable(new Object[] { application, applicant }));  2

List<Command> cmds = new ArrayList<Command>();  3
cmds.add(CommandFactory.newInsert(new Person("Mr John Smith"), "mrSmith"));
cmds.add(CommandFactory.newInsert(new Person("Mr John Doe"), "mrDoe"));

BatchExecutionResults results = ksession.execute(CommandFactory.newBatchExecution(cmds));
assertEquals(new Person("Mr John Smith"), results.getValue("mrSmith"));

import org.kie.api.runtime.ExecutionResults;

// Set up a list of commands.
List cmds = new ArrayList();
cmds.add(CommandFactory.newSetGlobal("list1", new ArrayList(), true));
cmds.add(CommandFactory.newInsert(new Person("jon", 102), "person"));
cmds.add(CommandFactory.newQuery("Get People" "getPeople"));

// Execute the list.
ExecutionResults results = ksession.execute(CommandFactory.newBatchExecution(cmds));

// Retrieve the `ArrayList`.
results.getValue("list1");
// Retrieve the inserted `Person` fact.
results.getValue("person");
// Retrieve the query as a `QueryResults` instance.
results.getValue("Get People");

A stateful KIE session is a session that uses inference to make iterative changes to facts over time. In a stateful KIE session, data from a previous invocation of the KIE session (the previous session state) is retained between session invocations, whereas in a stateless KIE session, that data is discarded.

Stateful KIE sessions are commonly used for the following use cases:

For example, consider the following fire alarm data model and sample DRL rules:

public class Room {
  private String name;
  // Getter and setter methods
}

public class Sprinkler {
  private Room room;
  private boolean on;
  // Getter and setter methods
}

public class Fire {
  private Room room;
  // Getter and setter methods
}

public class Alarm { }

rule "When there is a fire turn on the sprinkler"
when
  Fire($room : room)
  $sprinkler : Sprinkler(room == $room, on == false)
then
  modify($sprinkler) { setOn(true) };
  System.out.println("Turn on the sprinkler for room "+$room.getName());
end

rule "Raise the alarm when we have one or more fires"
when
    exists Fire()
then
    insert( new Alarm() );
    System.out.println( "Raise the alarm" );
end

rule "Cancel the alarm when all the fires have gone"
when
    not Fire()
    $alarm : Alarm()
then
    delete( $alarm );
    System.out.println( "Cancel the alarm" );
end


rule "Status output when things are ok"
when
    not Alarm()
    not Sprinkler( on == true )
then
    System.out.println( "Everything is ok" );
end

For the When there is a fire turn on the sprinkler rule, when a fire occurs, the instances of the Fire class are created for that room and inserted into the KIE session. The rule adds a constraint for the specific room matched in the Fire instance so that only the sprinkler for that room is checked. When this rule is executed, the sprinkler activates. The other sample rules determine when the alarm is activated or deactivated accordingly.

Whereas a stateless KIE session relies on standard Java syntax to modify a field, a stateful KIE session relies on the modify statement in rules to notify the decision engine of changes. The decision engine then reasons over the changes and assesses impact on subsequent rule executions. This process is part of the decision engine ability to use inference and truth maintenance and is essential in stateful KIE sessions.

In this example, the sample rules and all other files in the ~/resources folder of the Red Hat Decision Manager project are built with the following code:

KieServices kieServices = KieServices.Factory.get();
KieContainer kContainer = kieServices.getKieClasspathContainer();

This code compiles all the rule files found on the class path and adds the result of this compilation, a KieModule object, in the KieContainer.

Finally, the KieSession object is instantiated from the KieContainer and is executed against specified data:

KieSession ksession = kContainer.newKieSession();

String[] names = new String[]{"kitchen", "bedroom", "office", "livingroom"};
Map<String,Room> name2room = new HashMap<String,Room>();
for( String name: names ){
    Room room = new Room( name );
    name2room.put( name, room );
    ksession.insert( room );
    Sprinkler sprinkler = new Sprinkler( room );
    ksession.insert( sprinkler );
}

ksession.fireAllRules();

> Everything is ok

With the data added, the decision engine completes all pattern matching but no rules have been executed, so the configured verification message appears. As new data triggers rule conditions, the decision engine executes rules to activate the alarm and later to cancel the alarm that has been activated:

Fire kitchenFire = new Fire( name2room.get( "kitchen" ) );
Fire officeFire = new Fire( name2room.get( "office" ) );

FactHandle kitchenFireHandle = ksession.insert( kitchenFire );
FactHandle officeFireHandle = ksession.insert( officeFire );

ksession.fireAllRules();

> Raise the alarm
> Turn on the sprinkler for room kitchen
> Turn on the sprinkler for room office

ksession.delete( kitchenFireHandle );
ksession.delete( officeFireHandle );

ksession.fireAllRules();

> Cancel the alarm
> Turn off the sprinkler for room office
> Turn off the sprinkler for room kitchen
> Everything is ok

In this case, a reference is kept for the returned FactHandle object. A fact handle is an internal engine reference to the inserted instance and enables instances to be retracted or modified later.

As this example illustrates, the data and results from previous stateful KIE sessions (the activated alarm) affect the invocation of subsequent sessions (alarm cancellation).

In use cases with large amounts of KIE runtime data and high system activity, KIE sessions might be created and disposed very frequently. A high turnover of KIE sessions is not always time consuming, but when the turnover is repeated millions of times, the process can become a bottleneck and require substantial clean-up effort.

For these high-volume cases, you can use KIE session pools instead of many individual KIE sessions. To use a KIE session pool, you obtain a KIE session pool from a KIE container, define the initial number of KIE sessions in the pool, and create the KIE sessions from that pool as usual:

// Obtain a KIE session pool from the KIE container
KieContainerSessionsPool pool = kContainer.newKieSessionsPool(10);

// Create KIE sessions from the KIE session pool
KieSession kSession = pool.newKieSession();

In this example, the KIE session pool starts with 10 KIE sessions in it, but you can specify the number of KIE sessions that you need. This integer value is the number of KIE sessions that are only initially created in the pool. If required by the running application, the number of KIE sessions in the pool can dynamically grow beyond that value.

After you define a KIE session pool, the next time you use the KIE session as usual and call dispose() on it, the KIE session is reset and pushed back into the pool instead of being destroyed.

KIE session pools typically apply to stateful KIE sessions, but KIE session pools can also affect stateless KIE sessions that you reuse with multiple execute() calls. When you create a stateless KIE session directly from a KIE container, the KIE session continues to internally create a new KIE session for each execute() invocation. Conversely, when you create a stateless KIE session from a KIE session pool, the KIE session internally uses only the specific KIE sessions provided by the pool.

When you finish using a KIE session pool, you can call the shutdown() method on it to avoid memory leaks. Alternatively, you can call dispose() on the KIE container to shut down all the pools created from the KIE container.