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 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 SerializationContextInitializer interface in a new class and then add the @AutoProtoSchemaBuilder annotation. Reference the class that includes the @ProtoField annotations with the includeClasses parameter. Define a name for the Protobuf schema that you generate and filesystem path with the schemaFileName and schemaFilePath parameters. Specify the package name for the Protobuf schema with the schemaPackageName parameter. RemoteQueryInitializer.java import org.infinispan.protostream.SerializationContextInitializer; import org.infinispan.protostream.annotations.AutoProtoSchemaBuilder; @AutoProtoSchemaBuilder( includeClasses = { Book.class }, schemaFileName = "book.proto", schemaFilePath = "proto/", schemaPackageName = "book_sample") public interface RemoteQueryInitializer extends SerializationContextInitializer { } Compile your project. The code examples in this procedure generate a proto/book.proto schema and an RemoteQueryInitializerImpl.java implementation of the annotated Book class. 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 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 RemoteQueryInitializerImpl serialization context with a Hot Rod Java client. Registers the Protobuf schema, book.proto , with Data Grid Server. Adds two Book instances 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 QueryFactory queryFactory = Search.getQueryFactory(remoteCache); Query<Book> query = queryFactory.create("FROM book_sample.Book WHERE title:'java'"); List<Book> list = query.execute().list(); // Voila! We have our book back from the cache! } } Additional resources Encoding Infinispan caches and marshalling data Encoding Data Grid caches and marshalling data: ProtoStream annotations 3.2. Querying ProtoStream common types 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 dependsOn attribute to CommonTypes.class to indicate that the generated Protobuf schema can reference and use CommonTypes types such as BigInteger and BigDecimal : @AutoProtoSchemaBuilder(includeClasses = CalculusIndexed.class, dependsOn = CommonTypes.class, schemaFilePath = "/protostream", schemaFileName = "calculus-indexed.proto", schemaPackageName = "lab.indexed") public interface CalculusIndexedSchema extends GeneratedSchema { } Perform queries: Additional resources ProtoStream Types Marshalling 3.3. Querying caches from Data Grid Console and CLI 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 schema command with the --upload= argument as follows: Create 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 Person entity from the 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 cache command with the --file= argument as follows: Add 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 put command with the --file= argument to add each entry, as follows: Tip From 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 query command from the context of the remote cache. The query returns all entries with a name that matches Person by age in ascending order. Additional resources Data Grid REST API 3.4. Using analyzers with remote caches 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 @Text annotation to indicate that its value is analyzed. Use the analyzer attribute 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 Data Grid provides a set of default analyzer definitions. Definition Description standard Splits text fields into tokens, treating whitespace and punctuation as delimiters. simple Tokenizes input streams by delimiting at non-letters and then converting all letters to lowercase characters. Whitespace and non-letters are discarded. whitespace Splits text streams on whitespace and returns sequences of non-whitespace characters as tokens. keyword Treats entire text fields as single tokens. stemmer Stems English words using the Snowball Porter filter. ngram Generates n-gram tokens that are 3 grams in size by default. filename Splits text fields into larger size tokens than the standard analyzer, treating whitespace as a delimiter and converts all letters to lowercase characters. lowercase 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. Additional resources Apache Lucene Documentation 3.4.2. Creating custom analyzer definitions 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 ProgrammaticSearchMappingProvider API. Package your implementation in a JAR with the fully qualified class (FQN) in the following file: Copy your JAR file to the server/lib directory 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); } }

Commands:
<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>
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 }
import org.infinispan.protostream.SerializationContextInitializer; import org.infinispan.protostream.annotations.AutoProtoSchemaBuilder; @AutoProtoSchemaBuilder( includeClasses = { Book.class }, schemaFileName = "book.proto", schemaFilePath = "proto/", schemaPackageName = "book_sample") public interface RemoteQueryInitializer extends SerializationContextInitializer { }
<replicated-cache name="books"> <indexing> <indexed-entities> <indexed-entity>book_sample.Book</indexed-entity> </indexed-entities> </indexing> </replicated-cache>
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 QueryFactory queryFactory = Search.getQueryFactory(remoteCache); Query<Book> query = queryFactory.create("FROM book_sample.Book WHERE title:'java'"); List<Book> list = query.execute().list(); // Voila! We have our book back from the cache! } }
@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; } }
@AutoProtoSchemaBuilder(includeClasses = CalculusIndexed.class, dependsOn = CommonTypes.class, schemaFilePath = "/protostream", schemaFileName = "calculus-indexed.proto", schemaPackageName = "lab.indexed") public interface CalculusIndexedSchema extends GeneratedSchema { }
Query<Product> query = queryFactory.create("from lab.indexed.CalculusIndexed c where c.purchases > 9"); QueryResult<Product> result = query.execute(); // play with the result query = queryFactory.create("from lab.indexed.CalculusIndexed c where c.prospect = 2.2"); result = query.execute(); // play with the result
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; }
schema --upload=person.proto person.proto
<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>
create cache --file=people.xml people
_type: org.infinispan.example.Person
id: 1
name: Person
surname: One
age: 44
_type: org.infinispan.example.Person
id: 2
name: Person
surname: Two
age: 27
_type: org.infinispan.example.Person
id: 3
name: Person
surname: Three
age: 35
put --encoding=application/json --file=personone.json personone
query "from org.infinispan.example.Person p WHERE p.name='Person' ORDER BY p.age ASC"
/* @Indexed */ message TestEntity { /* @Keyword(projectable = true) */ optional string id = 1; /* @Text(projectable = true, analyzer = "simple") */ optional string name = 2; }
@Text(projectable = true, analyzer = "whitespace") @ProtoField(value = 1) private String id; @Text(projectable = true, analyzer = "simple") @ProtoField(value = 2) private String description;
META-INF/services/org.infinispan.query.spi.ProgrammaticSearchMappingProvider
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); } }