Chapter 1. Getting started

Welcome to Hibernate Search. The following chapter will guide you through the initial steps required to integrate Hibernate Search into an existing Hibernate enabled application. In case you are a Hibernate new timer we recommend you start here.

1.1. System Requirements

Table 1.1. System requirements

Java Runtime	A JDK or JRE version 6 or greater. You can download a Java Runtime for Windows/Linux/Solaris here. If using Java version 7 make sure you avoid builds 0 and 1: those versions contained an optimisation bug which would be triggered by Lucene. Hibernate Search 3.x was compatible with Java version 5.
Hibernate Search	`hibernate-search-4.0.0.Final.jar` and all runtime dependencies. You can get the jar artifacts either from the `dist/lib` directory of the Hibernate Search distribution or you can download them from the JBoss maven repository.
Hibernate Core	This instructions have been tested against Hibernate 4.0. You will need `hibernate-core-4.0.0.CR6.jar` and its transitive dependencies (either from the distribution bundle or the maven repository).
JPA 2	Even though Hibernate Search can be used without JPA annotations the following instructions will use them for basic entity configuration (@Entity, @Id, @OneToMany,...). This part of the configuration could also be expressed in xml or code. Hibernate Search, however, has also its own set of annotations (@Indexed, @DocumentId, @Field,...) for which there exists so far no XML based alternative; a better option is the Section 4.6, “Programmatic API”.

1.2. Using Maven

The Hibernate Search artifacts can be found in Maven's central repository but are released first in the JBoss maven repository. So it's not a requirement but we recommend to add this repository to your settings.xml file (see also Maven Getting Started for more details).

This is all you need to add to your pom.xml to get started:

Example 1.1. Maven artifact identifier for Hibernate Search


<dependency>

   <groupId>org.hibernate</groupId>

   <artifactId>hibernate-search</artifactId>

   <version>4.0.0.Final</version>

</dependency>

Example 1.2. Optional Maven dependencies for Hibernate Search


<dependency>

<!-- If using JPA (2), add: -->

<dependency>

   <groupId>org.hibernate</groupId>

   <artifactId>hibernate-entitymanager</artifactId>

   <version>4.0.0.CR6</version>

</dependency>

<!-- Additional Analyzers: -->

<dependency>

   <groupId>org.hibernate</groupId>

   <artifactId>hibernate-search-analyzers</artifactId>

   <version>4.0.0.Final</version>

</dependency>

<!-- Infinispan integration: -->

<dependency>

   <groupId>org.hibernate</groupId>

   <artifactId>hibernate-search-infinispan</artifactId>

   <version>4.0.0.Final</version>

</dependency>

Only the hibernate-search dependency is mandatory. hibernate-entitymanager is only required if you want to use Hibernate Search in conjunction with JPA.

To use hibernate-search-infinispan, adding the JBoss Maven repository is mandatory, because it contains the needed Infinispan dependencies which are currently not mirrored by central.

1.2.1. Using a Maven Archetype

Using a Maven Archetype it is possible to generate a Maven project from scratch, already containing the basic configuration files and some sample code and tests. Most development environments integrating maven support a graphical option to do this; the groupId is org.hibernate and the artifactId is hibernate-search-quickstart

Example 1.3. Generating a sample project using the Maven Archetype

mvn archetype:generate                                 \
   -DarchetypeGroupId=org.hibernate                    \
   -DarchetypeArtifactId=hibernate-search-quickstart   \
   -DarchetypeVersion=4.0.0.Final                      \
   -DarchetypeRepository=http://repository.jboss.org/nexus/content/groups/public-jboss/

1.3. Configuration

Once you have downloaded and added all required dependencies to your application you have to add a couple of properties to your hibernate configuration file. If you are using Hibernate directly this can be done in hibernate.properties or hibernate.cfg.xml. If you are using Hibernate via JPA you can also add the properties to persistence.xml. The good news is that for standard use most properties offer a sensible default. An example persistence.xml configuration could look like this:

Example 1.4. Basic configuration options to be added to hibernate.properties, hibernate.cfg.xml or persistence.xml


...

<property name="hibernate.search.default.directory_provider" 

          value="filesystem"/> 



<property name="hibernate.search.default.indexBase" 

          value="/var/lucene/indexes"/> 

...

First you have to tell Hibernate Search which DirectoryProvider to use. This can be achieved by setting the hibernate.search.default.directory_provider property. Apache Lucene has the notion of a Directory to store the index files. Hibernate Search handles the initialization and configuration of a Lucene Directory instance via a DirectoryProvider. In this tutorial we will use a a directory provider storing the index in the file system. This will give us the ability to physically inspect the Lucene indexes created by Hibernate Search (eg via Luke). Once you have a working configuration you can start experimenting with other directory providers (see Section 3.3, “Directory configuration”). Next to the directory provider you also have to specify the default base directory for all indexes via hibernate.search.default.indexBase.

Lets assume that your application contains the Hibernate managed classes example.Book and example.Author and you want to add free text search capabilities to your application in order to search the books contained in your database.

Example 1.5. Example entities Book and Author before adding Hibernate Search specific annotations

package example;

...

@Entity

public class Book {


  @Id

  @GeneratedValue

  private Integer id; 


  private String title;  


  private String subtitle; 


  @ManyToMany 

  private Set<Author> authors = new HashSet<Author>();


  private Date publicationDate;

  

  public Book() {} 

  

  // standard getters/setters follow here

  ...

}

package example;

...

@Entity

public class Author {


  @Id

  @GeneratedValue

  private Integer id;


  private String name;


  public Author() {} 

 

  // standard getters/setters follow here

  ...

}

To achieve this you have to add a few annotations to the Book and Author class. The first annotation @Indexed marks Book as indexable. By design Hibernate Search needs to store an untokenized id in the index to ensure index unicity for a given entity. @DocumentId marks the property to use for this purpose and is in most cases the same as the database primary key. The @DocumentId annotation is optional in the case where an @Id annotation exists.

Next you have to mark the fields you want to make searchable. Let's start with title and subtitle and annotate both with @Field. The parameter index=Index.YES will ensure that the text will be indexed, while analyze=analyze.YES ensures that the text will be analyzed using the default Lucene analyzer. Usually, analyzing means chunking a sentence into individual words and potentially excluding common words like 'a' or 'the'. We will talk more about analyzers a little later on. The third parameter we specify within @Field, store=Store.NO, ensures that the actual data will not be stored in the index. Whether this data is stored in the index or not has nothing to do with the ability to search for it. From Lucene's perspective it is not necessary to keep the data once the index is created. The benefit of storing it is the ability to retrieve it via projections ( see Section 5.1.3.5, “Projection”).

Without projections, Hibernate Search will per default execute a Lucene query in order to find the database identifiers of the entities matching the query critera and use these identifiers to retrieve managed objects from the database. The decision for or against projection has to be made on a case to case basis. The default behaviour is recommended since it returns managed objects whereas projections only return object arrays.

Note that index=Index.YES, analyze=analyze.YES and store=Store.NO are the default values for these paramters and could be ommited.

After this short look under the hood let's go back to annotating the Book class. Another annotation we have not yet discussed is @DateBridge. This annotation is one of the built-in field bridges in Hibernate Search. The Lucene index is purely string based. For this reason Hibernate Search must convert the data types of the indexed fields to strings and vice versa. A range of predefined bridges are provided, including the DateBridge which will convert a java.util.Date into a String with the specified resolution. For more details see Section 4.4, “Bridges”.

This leaves us with @IndexedEmbedded. This annotation is used to index associated entities (@ManyToMany, @*ToOne, @Embedded and @ElementCollection) as part of the owning entity. This is needed since a Lucene index document is a flat data structure which does not know anything about object relations. To ensure that the authors' name will be searchable you have to make sure that the names are indexed as part of the book itself. On top of @IndexedEmbedded you will also have to mark all fields of the associated entity you want to have included in the index with @Indexed. For more details see Section 4.1.3, “Embedded and associated objects”.

These settings should be sufficient for now. For more details on entity mapping refer to Section 4.1, “Mapping an entity”.

Example 1.6. Example entities after adding Hibernate Search annotations

package example;

...

@Entity
@Indexed

public class Book {


  @Id

  @GeneratedValue

  private Integer id;

  

  @Field(index=Index.YES, analyze=Analyze.YES, store=Store.NO)

  private String title;

  

  @Field(index=Index.YES, analyze=Analyze.YES, store=Store.NO)

  private String subtitle; 
  @Field(index = Index.YES, analyze=Analyze.NO, store = Store.YES)
  @DateBridge(resolution = Resolution.DAY)

  private Date publicationDate;


  @IndexedEmbedded

  @ManyToMany 

  private Set<Author> authors = new HashSet<Author>();


  public Book() {

  } 

  

  // standard getters/setters follow here

  ... 

}

package example;

...

@Entity

public class Author {


  @Id

  @GeneratedValue

  private Integer id;


  @Field

  private String name;


  public Author() {

  } 

 

  // standard getters/setters follow here

  ...

}

1.4. Indexing

Hibernate Search will transparently index every entity persisted, updated or removed through Hibernate Core. However, you have to create an initial Lucene index for the data already present in your database. Once you have added the above properties and annotations it is time to trigger an initial batch index of your books. You can achieve this by using one of the following code snippets (see also Section 6.3, “Rebuilding the whole index”):

Example 1.7. Using Hibernate Session to index data

FullTextSession fullTextSession = Search.getFullTextSession(session);

fullTextSession.createIndexer().startAndWait();

Example 1.8. Using JPA to index data

EntityManager em = entityManagerFactory.createEntityManager();

FullTextEntityManager fullTextEntityManager = Search.getFullTextEntityManager(em);

fullTextEntityManager.createIndexer().startAndWait();

After executing the above code, you should be able to see a Lucene index under /var/lucene/indexes/example.Book. Go ahead an inspect this index with Luke. It will help you to understand how Hibernate Search works.

1.5. Searching

Now it is time to execute a first search. The general approach is to create a Lucene query (either via the Lucene API (Section 5.1.1, “Building a Lucene query using the Lucene API”) or via the Hibernate Search query DSL (Section 5.1.2, “Building a Lucene query with the Hibernate Search query DSL”)) and then wrap this query into a org.hibernate.Query in order to get all the functionality one is used to from the Hibernate API. The following code will prepare a query against the indexed fields, execute it and return a list of Books.

Example 1.9. Using Hibernate Session to create and execute a search

FullTextSession fullTextSession = Search.getFullTextSession(session);

Transaction tx = fullTextSession.beginTransaction();


// create native Lucene query unsing the query DSL

// alternatively you can write the Lucene query using the Lucene query parser

// or the Lucene programmatic API. The Hibernate Search DSL is recommended though

QueryBuilder qb = fullTextSession.getSearchFactory()

    .buildQueryBuilder().forEntity( Book.class ).get();

org.apache.lucene.search.Query query = qb

  .keyword()

  .onFields("title", "subtitle", "authors.name", "publicationDate")

  .matching("Java rocks!");

  .createQuery();


// wrap Lucene query in a org.hibernate.Query

org.hibernate.Query hibQuery = 

    fullTextSession.createFullTextQuery(query, Book.class);


// execute search

List result = hibQuery.list();

  

tx.commit();

session.close();

Example 1.10. Using JPA to create and execute a search

EntityManager em = entityManagerFactory.createEntityManager();

FullTextEntityManager fullTextEntityManager = 

    org.hibernate.search.jpa.Search.getFullTextEntityManager(em);

em.getTransaction().begin();


// create native Lucene query unsing the query DSL

// alternatively you can write the Lucene query using the Lucene query parser

// or the Lucene programmatic API. The Hibernate Search DSL is recommended though

QueryBuilder qb = fullTextEntityManager.getSearchFactory()

    .buildQueryBuilder().forEntity( Book.class ).get();

org.apache.lucene.search.Query query = qb

  .keyword()

  .onFields("title", "subtitle", "authors.name", "publicationDate")

  .matching("Java rocks!")

  .createQuery();


// wrap Lucene query in a javax.persistence.Query

javax.persistence.Query persistenceQuery = 

    fullTextEntityManager.createFullTextQuery(query, Book.class);


// execute search

List result = persistenceQuery.getResultList();


em.getTransaction().commit();

em.close();

1.6. Analyzer

Let's make things a little more interesting now. Assume that one of your indexed book entities has the title "Refactoring: Improving the Design of Existing Code" and you want to get hits for all of the following queries: "refactor", "refactors", "refactored" and "refactoring". In Lucene this can be achieved by choosing an analyzer class which applies word stemming during the indexing as well as the search process. Hibernate Search offers several ways to configure the analyzer to be used (see Section 4.3.1, “Default analyzer and analyzer by class”):

Setting the hibernate.search.analyzer property in the configuration file. The specified class will then be the default analyzer.
Setting the @Analyzer annotation at the entity level.
Setting the @Analyzer annotation at the field level.

When using the @Analyzer annotation one can either specify the fully qualified classname of the analyzer to use or one can refer to an analyzer definition defined by the @AnalyzerDef annotation. In the latter case the Solr analyzer framework with its factories approach is utilized. To find out more about the factory classes available you can either browse the Solr JavaDoc or read the corresponding section on the Solr Wiki.

In the example below a StandardTokenizerFactory is used followed by two filter factories, LowerCaseFilterFactory and SnowballPorterFilterFactory. The standard tokenizer splits words at punctuation characters and hyphens while keeping email addresses and internet hostnames intact. It is a good general purpose tokenizer. The lowercase filter lowercases the letters in each token whereas the snowball filter finally applies language specific stemming.

Generally, when using the Solr framework you have to start with a tokenizer followed by an arbitrary number of filters.

Example 1.11. Using @AnalyzerDef and the Solr framework to define and use an analyzer

@Entity

@Indexed
@AnalyzerDef(name = "customanalyzer",
  tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class),
  filters = {
    @TokenFilterDef(factory = LowerCaseFilterFactory.class),
    @TokenFilterDef(factory = SnowballPorterFilterFactory.class, params = {
      @Parameter(name = "language", value = "English")
    })
  })

public class Book {


  @Id

  @GeneratedValue

  @DocumentId

  private Integer id;

  

  @Field

  @Analyzer(definition = "customanalyzer")

  private String title;

  

  @Field

  @Analyzer(definition = "customanalyzer")

  private String subtitle; 


  @IndexedEmbedded

  @ManyToMany 

  private Set<Author> authors = new HashSet<Author>();
  @Field(index = Index.YES, analyze = Analyze.NO, store = Store.YES)

  @DateBridge(resolution = Resolution.DAY)

  private Date publicationDate;

  

  public Book() {

  } 

  

  // standard getters/setters follow here

  ... 

}

Using @AnalyzerDef only defines an Analyzer, you still have to apply it to entities and or properties using @Analyzer. Like in the above example the customanalyzer is defined but not applied on the entity: it's applied on the title and subtitle properties only. An analyzer definition is global, so you can define it on any entity and reuse the definition on other entities.

1.7. What's next

The above paragraphs helped you getting an overview of Hibernate Search. The next step after this tutorial is to get more familiar with the overall architecture of Hibernate Search (Chapter 2, Architecture) and explore the basic features in more detail. Two topics which were only briefly touched in this tutorial were analyzer configuration (Section 4.3.1, “Default analyzer and analyzer by class”) and field bridges (Section 4.4, “Bridges”). Both are important features required for more fine-grained indexing. More advanced topics cover clustering (Section 3.4.1, “JMS Master/Slave back end”, Section 3.3.1, “Infinispan Directory configuration”) and large index handling (Section 9.4, “Sharding indexes”).