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Chapter 3. Querying remote caches
You can index and query remote caches on Data Grid Server.
3.1. Querying caches from Hot Rod Java clients 링크 복사링크가 클립보드에 복사되었습니다!
Data Grid lets you programmatically query remote caches from Java clients through the Hot Rod endpoint. This procedure explains how to index query a remote cache that stores Book instances.
Prerequisites
-
Add the ProtoStream processor to your
pom.xml.
Data Grid provides this processor for the @ProtoField annotations so you can generate Protobuf schemas and perform queries.
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>...</version>
<configuration>
<annotationProcessorPaths>
<annotationProcessorPath>
<groupId>org.infinispan.protostream</groupId>
<artifactId>protostream-processor</artifactId>
<version>...</version>
</annotationProcessorPath>
</annotationProcessorPaths>
</configuration>
</plugin>
</plugins>
</build>
Procedure
Add indexing annotations to your class, as in the following example:
Book.java
import org.infinispan.api.annotations.indexing.Basic; import org.infinispan.api.annotations.indexing.Indexed; import org.infinispan.api.annotations.indexing.Text; import org.infinispan.protostream.annotations.ProtoFactory; import org.infinispan.protostream.annotations.ProtoField; @Indexed public class Book { @Text @ProtoField(number = 1) final String title; @Text @ProtoField(number = 2) final String description; @Basic @ProtoField(number = 3, defaultValue = "0") final int publicationYear; @ProtoFactory Book(String title, String description, int publicationYear) { this.title = title; this.description = description; this.publicationYear = publicationYear; } // public Getter methods omitted for brevity }Implement the
SerializationContextInitializerinterface in a new class and then add the@ProtoSchemaannotation.-
Reference the class that includes the
@ProtoFieldannotations with theincludeClassesparameter. -
Define a name for the Protobuf schema that you generate and filesystem path with the
schemaFileNameandschemaFilePathparameters. Specify the package name for the Protobuf schema with the
schemaPackageNameparameter.RemoteQueryInitializer.java
import org.infinispan.protostream.SerializationContextInitializer; import org.infinispan.protostream.annotations.ProtoSchema; @ProtoSchema( includeClasses = { Book.class }, schemaFileName = "book.proto", schemaFilePath = "proto/", schemaPackageName = "book_sample") public interface RemoteQueryInitializer extends SerializationContextInitializer { }
-
Reference the class that includes the
Compile your project.
The code examples in this procedure generate a
proto/book.protoschema and anRemoteQueryInitializerImpl.javaimplementation of the annotatedBookclass.
Next steps
Create a remote cache that configures Data Grid to index your entities. For example, the following remote cache indexes the Book entity in the book.proto schema that you generated in the previous step:
<replicated-cache name="books">
<indexing>
<indexed-entities>
<indexed-entity>book_sample.Book</indexed-entity>
</indexed-entities>
</indexing>
</replicated-cache>
The following RemoteQuery class does the following:
-
Registers the
RemoteQueryInitializerImplserialization context with a Hot Rod Java client. -
Registers the Protobuf schema,
book.proto, with Data Grid Server. -
Adds two
Bookinstances to the remote cache. - Performs a full-text query that matches books by keywords in the title.
RemoteQuery.java
package org.infinispan;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.List;
import org.infinispan.client.hotrod.RemoteCache;
import org.infinispan.client.hotrod.RemoteCacheManager;
import org.infinispan.client.hotrod.Search;
import org.infinispan.client.hotrod.configuration.ConfigurationBuilder;
import org.infinispan.query.dsl.Query;
import org.infinispan.query.dsl.QueryFactory;
import org.infinispan.query.remote.client.ProtobufMetadataManagerConstants;
public class RemoteQuery {
public static void main(String[] args) throws Exception {
ConfigurationBuilder clientBuilder = new ConfigurationBuilder();
// RemoteQueryInitializerImpl is generated
clientBuilder.addServer().host("127.0.0.1").port(11222)
.security().authentication().username("user").password("user")
.addContextInitializers(new RemoteQueryInitializerImpl());
RemoteCacheManager remoteCacheManager = new RemoteCacheManager(clientBuilder.build());
// Grab the generated protobuf schema and registers in the server.
Path proto = Paths.get(RemoteQuery.class.getClassLoader()
.getResource("proto/book.proto").toURI());
String protoBufCacheName = ProtobufMetadataManagerConstants.PROTOBUF_METADATA_CACHE_NAME;
remoteCacheManager.getCache(protoBufCacheName).put("book.proto", Files.readString(proto));
// Obtain the 'books' remote cache
RemoteCache<Object, Object> remoteCache = remoteCacheManager.getCache("books");
// Add some Books
Book book1 = new Book("Infinispan in Action", "Learn Infinispan with using it", 2015);
Book book2 = new Book("Cloud-Native Applications with Java and Quarkus", "Build robust and reliable cloud applications", 2019);
remoteCache.put(1, book1);
remoteCache.put(2, book2);
// Execute a full-text query
Query<Book> query = remoteCache.query("FROM book_sample.Book WHERE title:'java'");
List<Book> list = query.execute().list(); // Voila! We have our book back from the cache!
}
}
3.2. Querying ProtoStream common types 링크 복사링크가 클립보드에 복사되었습니다!
Perform Ickle queries on caches that store data as ProtoStream common types such as BigInteger and BigDecimal.
Procedure
Add indexing annotations to your class, as in the following example:
@Indexed public class CalculusIndexed { @Basic @ProtoField(value = 1) public BigInteger getPurchases() { return purchases; } @Decimal // the scale is 2 by default @ProtoField(value = 2) public BigDecimal getProspect() { return prospect; } }Set the
dependsOnattribute toCommonTypes.classto indicate that the generated Protobuf schema can reference and useCommonTypestypes such asBigIntegerandBigDecimal:@ProtoSchema(includeClasses = CalculusIndexed.class, dependsOn = CommonTypes.class, schemaFilePath = "/protostream", schemaFileName = "calculus-indexed.proto", schemaPackageName = "lab.indexed") public interface CalculusIndexedSchema extends GeneratedSchema { }Perform queries:
Query<Product> query = cache.query("from lab.indexed.CalculusIndexed c where c.purchases > 9"); QueryResult<Product> result = query.execute(); // play with the result query = cache.query("from lab.indexed.CalculusIndexed c where c.prospect = 2.2"); result = query.execute(); // play with the result
3.3. Querying caches from Data Grid Console and CLI 링크 복사링크가 클립보드에 복사되었습니다!
Data Grid Console and the Data Grid Command Line Interface (CLI) let you query indexed and non-indexed remote caches. You can also use any HTTP client to index and query caches via the REST API.
This procedure explains how to index and query a remote cache that stores Person instances.
Prerequisites
- Have at least one running Data Grid Server instance.
- Have Data Grid credentials with create permissions.
Procedure
Add indexing annotations to your Protobuf schema, as in the following example:
package org.infinispan.example; /* @Indexed */ message Person { /* @Basic */ optional int32 id = 1; /* @Keyword(projectable = true) */ required string name = 2; /* @Keyword(projectable = true) */ required string surname = 3; /* @Basic(projectable = true, sortable = true) */ optional int32 age = 6; }From the Data Grid CLI, use the
schemacommand with the--upload=argument as follows:schema --upload=person.proto person.protoCreate a cache named people that uses ProtoStream encoding and configures Data Grid to index entities declared in your Protobuf schema.
The following cache indexes the
Personentity from the previous step:<distributed-cache name="people"> <encoding media-type="application/x-protostream"/> <indexing> <indexed-entities> <indexed-entity>org.infinispan.example.Person</indexed-entity> </indexed-entities> </indexing> </distributed-cache>From the CLI, use the
create cachecommand with the--file=argument as follows:create cache --file=people.xml peopleAdd entries to the cache.
To query a remote cache, it needs to contain some data. For this example procedure, create entries that use the following JSON values:
PersonOne
{ "_type":"org.infinispan.example.Person", "id":1, "name":"Person", "surname":"One", "age":44 }PersonTwo
{ "_type":"org.infinispan.example.Person", "id":2, "name":"Person", "surname":"Two", "age":27 }PersonThree
{ "_type":"org.infinispan.example.Person", "id":3, "name":"Person", "surname":"Three", "age":35 }From the CLI, use the
putcommand with the--file=argument to add each entry, as follows:put --encoding=application/json --file=personone.json persononeTipFrom Data Grid Console, you must select Custom Type for the Value content type field when you add values in JSON format with custom types .
Query your remote cache.
From the CLI, use the
querycommand from the context of the remote cache.query "from org.infinispan.example.Person p WHERE p.name='Person' ORDER BY p.age ASC"The query returns all entries with a name that matches
Personby age in ascending order.
3.4. Using analyzers with remote caches 링크 복사링크가 클립보드에 복사되었습니다!
Analyzers convert input data into terms that you can index and query. You specify analyzer definitions with the @Text annotation in your Java classes or directly in Protobuf schema.
Procedure
-
Annotate the property with the
@Textannotation to indicate that its value is analyzed. -
Use the
analyzerattribute to specify the desired analyzer that you want to use for indexing and searching.
Protobuf schema
/* @Indexed */
message TestEntity {
/* @Keyword(projectable = true) */
optional string id = 1;
/* @Text(projectable = true, analyzer = "simple") */
optional string name = 2;
}
Java classes
@Text(projectable = true, analyzer = "whitespace")
@ProtoField(value = 1)
private String id;
@Text(projectable = true, analyzer = "simple")
@ProtoField(value = 2)
private String description;
3.4.1. Default analyzer definitions 링크 복사링크가 클립보드에 복사되었습니다!
Data Grid provides a set of default analyzer definitions.
| Definition | Description |
|---|---|
|
| Splits text fields into tokens, treating whitespace and punctuation as delimiters. |
|
| Tokenizes input streams by delimiting at non-letters and then converting all letters to lowercase characters. Whitespace and non-letters are discarded. |
|
| Splits text streams on whitespace and returns sequences of non-whitespace characters as tokens. |
|
| Treats entire text fields as single tokens. |
|
| Stems English words using the Snowball Porter filter. |
|
| Generates n-gram tokens that are 3 grams in size by default. |
|
|
Splits text fields into larger size tokens than the |
|
| Converts all the letters of the text to lowercase characters, the text is not tokenized (normalizer). |
These analyzer definitions are based on Apache Lucene. For more information about tokenizers, filters, and CharFilters, see the Apache Lucene documentation.
3.4.2. Creating custom analyzer definitions 링크 복사링크가 클립보드에 복사되었습니다!
Create custom analyzer definitions and add them to your Data Grid Server installations.
Prerequisites
Stop Data Grid Server if it is running.
Data Grid Server loads classes at startup only.
Procedure
-
Implement the
ProgrammaticSearchMappingProviderAPI. Package your implementation in a JAR with the fully qualified class (FQN) in the following file:
META-INF/services/org.infinispan.query.spi.ProgrammaticSearchMappingProvider-
Copy your JAR file to the
server/libdirectory of your Data Grid Server installation. - Start Data Grid Server.
ProgrammaticSearchMappingProvider example
import org.apache.lucene.analysis.core.LowerCaseFilterFactory;
import org.apache.lucene.analysis.core.StopFilterFactory;
import org.apache.lucene.analysis.standard.StandardFilterFactory;
import org.apache.lucene.analysis.standard.StandardTokenizerFactory;
import org.hibernate.search.cfg.SearchMapping;
import org.infinispan.Cache;
import org.infinispan.query.spi.ProgrammaticSearchMappingProvider;
public final class MyAnalyzerProvider implements ProgrammaticSearchMappingProvider {
@Override
public void defineMappings(Cache cache, SearchMapping searchMapping) {
searchMapping
.analyzerDef("standard-with-stop", StandardTokenizerFactory.class)
.filter(StandardFilterFactory.class)
.filter(LowerCaseFilterFactory.class)
.filter(StopFilterFactory.class);
}
}
3.5. Queries by keys 링크 복사링크가 클립보드에 복사되었습니다!
You can define the key of a cache entry as Indexed type to index the key fields as well the value fields allowing the keys to be used in Ickle queries.
To define an Indexed key, specify the fully qualified name of the ProtocolBuffer message type to use as the key type in the keyEntity attribute of the @Indexed annotation.
This feature is available only with indexed remote queries.
Specify the keyEntity of an indexed entity
import org.infinispan.api.annotations.indexing.Basic;
import org.infinispan.api.annotations.indexing.Indexed;
import org.infinispan.api.annotations.indexing.Text;
import org.infinispan.protostream.GeneratedSchema;
import org.infinispan.protostream.annotations.ProtoFactory;
import org.infinispan.protostream.annotations.ProtoField;
import org.infinispan.protostream.annotations.ProtoSchema;
@Indexed(keyEntity = "model.StructureKey")
public class Structure {
private final String code;
private final String description;
private final Integer value;
@ProtoFactory
public Structure(String code, String description, Integer value) {
this.code = code;
this.description = description;
this.value = value;
}
@ProtoField(1)
@Basic
public String getCode() {
return code;
}
@ProtoField(2)
@Text
public String getDescription() {
return description;
}
@ProtoField(3)
@Basic
public Integer getValue() {
return value;
}
@ProtoSchema(includeClasses = { Structure.class, StructureKey.class }, schemaPackageName = "model")
public interface StructureSchema extends GeneratedSchema {
StructureSchema INSTANCE = new StructureSchemaImpl();
}
}
Define the key entity and its indexed fields
import org.infinispan.api.annotations.indexing.Basic;
import org.infinispan.api.annotations.indexing.Indexed;
import org.infinispan.api.annotations.indexing.Keyword;
import org.infinispan.protostream.annotations.ProtoFactory;
import org.infinispan.protostream.annotations.ProtoField;
@Indexed
public class StructureKey {
private String zone;
private Integer row;
private Integer column;
@ProtoFactory
public StructureKey(String zone, Integer row, Integer column) {
this.zone = zone;
this.row = row;
this.column = column;
}
@Keyword(projectable = true, sortable = true)
@ProtoField(1)
public String getZone() {
return zone;
}
@Basic(projectable = true, sortable = true)
@ProtoField(2)
public Integer getRow() {
return row;
}
@Basic(projectable = true, sortable = true)
@ProtoField(3)
public Integer getColumn() {
return column;
}
}
3.5.1. Key property name 링크 복사링크가 클립보드에 복사되었습니다!
By default, the key fields will be targeted using the property named key.
Use key properties in the Ickle queries
select s.key.column from model.Structure s where s.key.zone = 'z7'
If the value already has a property named key, the definition of the key entity could create a naming conflict with the properties. For this reason, and also in general, it is possible to change the name to assign as a prefix for the property keys changing the attribute keyPropertyName of the @Indexed annotation.
3.5.2. Key include depth 링크 복사링크가 클립보드에 복사되었습니다!
An entity key can have embedded entities. You can limit the depth for the embedded entity fields that are indexed by changing the attribute keyIncludeDepth, which defaults to 3.