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14.2. Mapping Entities to the Index Structure

14.2.1. Mapping an Entity
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All the metadata information required to index entities is described through annotations, so there is no need for XML mapping files. You can still use Hibernate mapping files for the basic Hibernate configuration, but the Hibernate Search specific configuration has to be expressed via annotations.
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14.2.1.1. Basic Mapping
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Lets start with the most commonly used annotations for mapping an entity.
The Lucene-based Query API uses the following common annotations to map entities:
  • @Indexed
  • @Field
  • @NumericField
  • @Id
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14.2.1.1.1. @Indexed
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Foremost we must declare a persistent class as indexable. This is done by annotating the class with @Indexed (all entities not annotated with @Indexed will be ignored by the indexing process):

Example 14.8. Making a class indexable with @Indexed

@Entity
@Indexed
public class Essay {
    ...
}
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You can optionally specify the index attribute of the @Indexed annotation to change the default name of the index.
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14.2.1.1.2. @Field
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For each property (or attribute) of your entity, you have the ability to describe how it will be indexed. The default (no annotation present) means that the property is ignored by the indexing process. @Field does declare a property as indexed and allows to configure several aspects of the indexing process by setting one or more of the following attributes:
  • name : describe under which name, the property should be stored in the Lucene Document. The default value is the property name (following the JavaBeans convention)
  • store : describe whether or not the property is stored in the Lucene index. You can store the value Store.YES (consuming more space in the index but allowing projection, see Section 14.3.1.10.5, “Projection”), store it in a compressed way Store.COMPRESS (this does consume more CPU), or avoid any storage Store.NO (this is the default value). When a property is stored, you can retrieve its original value from the Lucene Document. This is not related to whether the element is indexed or not.
  • index: describe whether the property is indexed or not. The different values are Index.NO (no indexing, ie cannot be found by a query), Index.YES (the element gets indexed and is searchable). The default value is Index.YES. Index.NO can be useful for cases where a property is not required to be searchable, but should be available for projection.

    Note

    Index.NO in combination with Analyze.YES or Norms.YES is not useful, since analyze and norms require the property to be indexed
  • analyze: determines whether the property is analyzed (Analyze.YES) or not (Analyze.NO). The default value is Analyze.YES.

    Note

    Whether or not you want to analyze a property depends on whether you wish to search the element as is, or by the words it contains. It make sense to analyze a text field, but probably not a date field.

    Note

    Fields used for sorting must not be analyzed.
  • norms: describes whether index time boosting information should be stored (Norms.YES) or not (Norms.NO). Not storing it can save a considerable amount of memory, but there won't be any index time boosting information available. The default value is Norms.YES.
  • termVector: describes collections of term-frequency pairs. This attribute enables the storing of the term vectors within the documents during indexing. The default value is TermVector.NO.
    The different values of this attribute are:
    Expand
    Value Definition
    TermVector.YES Store the term vectors of each document. This produces two synchronized arrays, one contains document terms and the other contains the term's frequency.
    TermVector.NO Do not store term vectors.
    TermVector.WITH_OFFSETS Store the term vector and token offset information. This is the same as TermVector.YES plus it contains the starting and ending offset position information for the terms.
    TermVector.WITH_POSITIONS Store the term vector and token position information. This is the same as TermVector.YES plus it contains the ordinal positions of each occurrence of a term in a document.
    TermVector.WITH_POSITION_OFFSETS Store the term vector, token position and offset information. This is a combination of the YES, WITH_OFFSETS and WITH_POSITIONS.
  • indexNullAs : Per default null values are ignored and not indexed. However, using indexNullAs you can specify a string which will be inserted as token for the null value. Per default this value is set to Field.DO_NOT_INDEX_NULL indicating that null values should not be indexed. You can set this value to Field.DEFAULT_NULL_TOKEN to indicate that a default null token should be used. This default null token can be specified in the configuration using hibernate.search.default_null_token. If this property is not set and you specify Field.DEFAULT_NULL_TOKEN the string "_null_" will be used as default.

    Note

    When the indexNullAs parameter is used it is important to use the same token in the search query to search for null values. It is also advisable to use this feature only with un-analyzed fields (analyze=Analyze.NO).

    Warning

    When implementing a custom FieldBridge or TwoWayFieldBridge it is up to the developer to handle the indexing of null values (see JavaDocs of LuceneOptions.indexNullAs()).
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14.2.1.1.3. @NumericField
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There is a companion annotation to @Field called @NumericField that can be specified in the same scope as @Field or @DocumentId. It can be specified for Integer, Long, Float, and Double properties. At index time the value will be indexed using a Trie structure. When a property is indexed as numeric field, it enables efficient range query and sorting, orders of magnitude faster than doing the same query on standard @Field properties. The @NumericField annotation accept the following parameters:
Expand
Value Definition
forField (Optional) Specify the name of the related @Field that will be indexed as numeric. It's only mandatory when the property contains more than a @Field declaration
precisionStep (Optional) Change the way that the Trie structure is stored in the index. Smaller precisionSteps lead to more disk space usage and faster range and sort queries. Larger values lead to less space used and range query performance more close to the range query in normal @Fields. Default value is 4.
@NumericField supports only Double, Long, Integer and Float. It is not possible to take any advantage from similar functionality in Lucene for the other numeric types, so remaining types should use the string encoding via the default or custom TwoWayFieldBridge.
It is possible to use a custom NumericFieldBridge assuming you can deal with the approximation during type transformation:

Example 14.9. Defining a custom NumericFieldBridge

public class BigDecimalNumericFieldBridge extends NumericFieldBridge {
   private static final BigDecimal storeFactor = BigDecimal.valueOf(100);

   @Override
   public void set(String name, Object value, Document document, LuceneOptions luceneOptions) {
      if ( value != null ) {
         BigDecimal decimalValue = (BigDecimal) value;
         Long indexedValue = Long.valueOf( decimalValue.multiply( storeFactor ).longValue() );
         luceneOptions.addNumericFieldToDocument( name, indexedValue, document );
      }
   }

    @Override
    public Object get(String name, Document document) {
        String fromLucene = document.get( name );
        BigDecimal storedBigDecimal = new BigDecimal( fromLucene );
        return storedBigDecimal.divide( storeFactor );
    }

}
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14.2.1.1.4. @Id
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Finally, the id (identifier) property of an entity is a special property used by Hibernate Search to ensure index uniqueness of a given entity. By design, an id must be stored and must not be tokenized. To mark a property as an index identifier, use the @DocumentId annotation. If you are using JPA and you have specified @Id you can omit @DocumentId. The chosen entity identifier will also be used as the document identifier.

Example 14.10. Specifying indexed properties

@Entity
@Indexed
public class Essay {
    ...

    @Id
    @DocumentId
    public Long getId() { return id; }

    @Field(name="Abstract", store=Store.YES)
    public String getSummary() { return summary; }

    @Lob
    @Field
    public String getText() { return text; }

    @Field @NumericField( precisionStep = 6)
    public float getGrade() { return grade; }
}
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Example 14.10, “Specifying indexed properties” defines an index with four fields: id , Abstract, text and grade . Note that by default the field name is not capitalized, following the JavaBean specification. The grade field is annotated as numeric with a slightly larger precision step than the default.
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14.2.1.2. Mapping Properties Multiple Times
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Sometimes you need to map a property multiple times per index, with slightly different indexing strategies. For example, sorting a query by field requires the field to be un-analyzed. To search by words on this property and still sort it, it needs to be indexed - once analyzed and once un-analyzed. @Fields allows you to achieve this goal.

Example 14.11. Using @Fields to map a property multiple times

@Entity
@Indexed(index = "Book" )
public class Book {
    @Fields( {
            @Field,
            @Field(name = "summary_forSort", analyze = Analyze.NO, store = Store.YES)
            } )
    public String getSummary() {
        return summary;
    }

    ...
}
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In this example the field summary is indexed twice, once as summary in a tokenized way, and once as summary_forSort in an untokenized way.
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14.2.1.3. Embedded and Associated Objects
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Associated objects as well as embedded objects can be indexed as part of the root entity index. This is useful if you expect to search a given entity based on properties of associated objects. In Example 14.12, “Indexing associations” the aim is to return places where the associated city is Atlanta (In the Lucene query parser language, it would translate into address.city:Atlanta). The place fields will be indexed in the Place index. The Place index documents will also contain the fields address.id, address.street, and address.city which you will be able to query.

Example 14.12. Indexing associations

@Entity
@Indexed
public class Place {
    @Id
    @GeneratedValue
    @DocumentId
    private Long id;

    @Field
    private String name;

    @OneToOne( cascade = { CascadeType.PERSIST, CascadeType.REMOVE } )
    @IndexedEmbedded
    private Address address;
    ....
}

@Entity
public class Address {
    @Id
    @GeneratedValue
    private Long id;

    @Field
    private String street;

    @Field
    private String city;

    @ContainedIn
    @OneToMany(mappedBy="address")
    private Set<Place> places;
    ...
}
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Because the data is denormalized in the Lucene index when using the @IndexedEmbedded technique, Hibernate Search must be aware of any change in the Place object and any change in the Address object to keep the index up to date. To ensure the Place Lucene document is updated when it's Address changes, mark the other side of the bidirectional relationship with @ContainedIn.

Note

@ContainedIn is useful on both associations pointing to entities and on embedded (collection of) objects.
To expand upon this, the following example demonstrates nesting @IndexedEmbedded.

Example 14.13. Nested usage of @IndexedEmbedded and @ContainedIn

@Entity
@Indexed
public class Place {
    @Id
    @GeneratedValue
    @DocumentId
    private Long id;

    @Field
    private String name;

    @OneToOne( cascade = { CascadeType.PERSIST, CascadeType.REMOVE } )
    @IndexedEmbedded
    private Address address;
    ....
}

@Entity
public class Address {
    @Id
    @GeneratedValue
    private Long id;

    @Field
    private String street;

    @Field
    private String city;

    @IndexedEmbedded(depth = 1, prefix = "ownedBy_")
    private Owner ownedBy;

    @ContainedIn
    @OneToMany(mappedBy="address")
    private Set<Place> places;
    ...
}

@Embeddable
public class Owner {
    @Field
    private String name;
   ...
}
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Any @*ToMany, @*ToOne and @Embedded attribute can be annotated with @IndexedEmbedded. The attributes of the associated class will then be added to the main entity index. In Example 14.13, “Nested usage of @IndexedEmbedded and @ContainedIn” the index will contain the following fields:
  • id
  • name
  • address.street
  • address.city
  • address.ownedBy_name
The default prefix is propertyName., following the traditional object navigation convention. You can override it using the prefix attribute as it is shown on the ownedBy property.

Note

The prefix cannot be set to the empty string.
The depth property is necessary when the object graph contains a cyclic dependency of classes (not instances). For example, if Owner points to Place. Hibernate Search will stop including Indexed embedded attributes after reaching the expected depth (or the object graph boundaries are reached). A class having a self reference is an example of cyclic dependency. In our example, because depth is set to 1, any @IndexedEmbedded attribute in Owner (if any) will be ignored.
Using @IndexedEmbedded for object associations allows you to express queries (using Lucene's query syntax) such as:
  • Return places where name contains JBoss and where address city is Atlanta. In Lucene query this would be 
    +name:jboss +address.city:atlanta
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  • Return places where name contains JBoss and where owner's name contain Joe. In Lucene query this would be 
    +name:jboss +address.ownedBy_name:joe
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This behavior mimics the relational join operation in a more efficient way (at the cost of data duplication). Remember that, out of the box, Lucene indexes have no notion of association, the join operation does not exist. It might help to keep the relational model normalized while benefiting from the full text index speed and feature richness.

Note

An associated object can itself (but does not have to) be @Indexed
When @IndexedEmbedded points to an entity, the association has to be directional and the other side has to be annotated @ContainedIn (as seen in the previous example). If not, Hibernate Search has no way to update the root index when the associated entity is updated (in our example, a Place index document has to be updated when the associated Address instance is updated).
Sometimes, the object type annotated by @IndexedEmbedded is not the object type targeted by Hibernate and Hibernate Search. This is especially the case when interfaces are used in lieu of their implementation. For this reason you can override the object type targeted by Hibernate Search using the targetElement parameter.

Example 14.14. Using the targetElement property of @IndexedEmbedded

@Entity
@Indexed
public class Address {
    @Id
    @GeneratedValue
    @DocumentId
    private Long id;

    @Field
    private String street;

    @IndexedEmbedded(depth = 1, prefix = "ownedBy_", targetElement = Owner.class)
    @Target(Owner.class)
    private Person ownedBy;


    ...
}

@Embeddable
public class Owner implements Person { ... }
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14.2.1.4. Limiting Object Embedding to Specific Paths
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The @IndexedEmbedded annotation provides also an attribute includePaths which can be used as an alternative to depth, or be combined with it.
When using only depth all indexed fields of the embedded type will be added recursively at the same depth. This makes it harder to select only a specific path without adding all other fields as well, which might not be needed.
To avoid unnecessarily loading and indexing entities you can specify exactly which paths are needed. A typical application might need different depths for different paths, or in other words it might need to specify paths explicitly, as shown in Example 14.15, “Using the includePaths property of @IndexedEmbedded”

Example 14.15. Using the includePaths property of @IndexedEmbedded

@Entity
@Indexed
public class Person {

   @Id
   public int getId() {
      return id;
   }

   @Field
   public String getName() {
      return name;
   }

   @Field
   public String getSurname() {
      return surname;
   }

   @OneToMany
   @IndexedEmbedded(includePaths = { "name" })
   public Set<Person> getParents() {
      return parents;
   }

   @ContainedIn
   @ManyToOne
   public Human getChild() {
      return child;
   }

    ...//other fields omitted
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Using a mapping as in Example 14.15, “Using the includePaths property of @IndexedEmbedded”, you would be able to search on a Person by name and/or surname, and/or the name of the parent. It will not index the surname of the parent, so searching on parent's surnames will not be possible but speeds up indexing, saves space and improve overall performance.
The @IndexedEmbeddedincludePaths will include the specified paths in addition to what you would index normally specifying a limited value for depth. When using includePaths, and leaving depth undefined, behavior is equivalent to setting depth=0: only the included paths are indexed.

Example 14.16. Using the includePaths property of @IndexedEmbedded

@Entity
@Indexed
public class Human {

   @Id
   public int getId() {
      return id;
   }

   @Field
   public String getName() {
      return name;
   }

   @Field
   public String getSurname() {
      return surname;
   }

   @OneToMany
   @IndexedEmbedded(depth = 2, includePaths = { "parents.parents.name" })
   public Set<Human> getParents() {
      return parents;
   }

   @ContainedIn
   @ManyToOne
   public Human getChild() {
      return child;
   }

    ...//other fields omitted
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In Example 14.16, “Using the includePaths property of @IndexedEmbedded”, every human will have its name and surname attributes indexed. The name and surname of parents will also be indexed, recursively up to second line because of the depth attribute. It will be possible to search by name or surname, of the person directly, his parents or of his grand parents. Beyond the second level, we will in addition index one more level but only the name, not the surname.
This results in the following fields in the index:
  • id - as primary key
  • _hibernate_class - stores entity type
  • name - as direct field
  • surname - as direct field
  • parents.name - as embedded field at depth 1
  • parents.surname - as embedded field at depth 1
  • parents.parents.name - as embedded field at depth 2
  • parents.parents.surname - as embedded field at depth 2
  • parents.parents.parents.name - as additional path as specified by includePaths. The first parents. is inferred from the field name, the remaining path is the attribute of includePaths
Having explicit control of the indexed paths might be easier if you are designing your application by defining the needed queries first, as at that point you might know exactly which fields you need, and which other fields are unnecessary to implement your use case.
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14.2.2. Boosting
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Lucene has the notion of boosting which allows you to give certain documents or fields more or less importance than others. Lucene differentiates between index and search time boosting. The following sections show you how you can achieve index time boosting using Hibernate Search.
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14.2.2.1. Static Index Time Boosting
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To define a static boost value for an indexed class or property you can use the @Boost annotation. You can use this annotation within @Field or specify it directly on method or class level.

Example 14.17. Different ways of using @Boost

@Entity
@Indexed
@Boost(1.7f)
public class Essay {
    ...

    @Id
    @DocumentId
    public Long getId() { return id; }

    @Field(name="Abstract", store=Store.YES, boost=@Boost(2f))
    @Boost(1.5f)
    public String getSummary() { return summary; }

    @Lob
    @Field(boost=@Boost(1.2f))
    public String getText() { return text; }

    @Field
    public String getISBN() { return isbn; }

}
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In Example 14.17, “Different ways of using @Boost”, Essay's probability to reach the top of the search list will be multiplied by 1.7. The summary field will be 3.0 (2 * 1.5, because @Field.boost and @Boost on a property are cumulative) more important than the isbn field. The text field will be 1.2 times more important than the isbn field. Note that this explanation is wrong in strictest terms, but it is simple and close enough to reality for all practical purposes.
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14.2.2.2. Dynamic Index Time Boosting
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The @Boost annotation used in Section 14.2.2.1, “Static Index Time Boosting” defines a static boost factor which is independent of the state of the indexed entity at runtime. However, there are usecases in which the boost factor may depend on the actual state of the entity. In this case you can use the @DynamicBoost annotation together with an accompanying custom BoostStrategy.

Example 14.18. Dynamic boost example

public enum PersonType {
    NORMAL,
    VIP
}

@Entity
@Indexed
@DynamicBoost(impl = VIPBoostStrategy.class)
public class Person {
    private PersonType type;   
    
    // ....
}

public class VIPBoostStrategy implements BoostStrategy {
    public float defineBoost(Object value) {
        Person person = ( Person ) value;
        if ( person.getType().equals( PersonType.VIP ) ) {
            return 2.0f;
        }
        else {
            return 1.0f;
        }
    }
}
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In Example 14.18, “Dynamic boost example” a dynamic boost is defined on class level specifying VIPBoostStrategy as implementation of the BoostStrategy interface to be used at indexing time. You can place the @DynamicBoost either at class or field level. Depending on the placement of the annotation either the whole entity is passed to the defineBoost method or just the annotated field/property value. It's up to you to cast the passed object to the correct type. In the example all indexed values of a VIP person would be double as important as the values of a normal person.

Note

The specified BoostStrategy implementation must define a public no-arg constructor.
Of course you can mix and match @Boost and @DynamicBoost annotations in your entity. All defined boost factors are cumulative.
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14.2.3. Analysis
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Analysis is the process of converting text into single terms (words) and can be considered as one of the key features of a full-text search engine. Lucene uses the concept of Analyzers to control this process. In the following section we cover the multiple ways Hibernate Search offers to configure the analyzers.
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14.2.3.1. Default Analyzer and Analyzer by Class
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The default analyzer class used to index tokenized fields is configurable through the hibernate.search.analyzer property. The default value for this property is org.apache.lucene.analysis.standard.StandardAnalyzer.
You can also define the analyzer class per entity, property and even per @Field (useful when multiple fields are indexed from a single property).

Example 14.19. Different ways of using @Analyzer

@Entity
@Indexed
@Analyzer(impl = EntityAnalyzer.class)
public class MyEntity {
    @Id
    @GeneratedValue
    @DocumentId
    private Integer id;

    @Field
    private String name;

    @Field
    @Analyzer(impl = PropertyAnalyzer.class)
    private String summary;

    @Field( analyzer = @Analyzer(impl = FieldAnalyzer.class )
    private String body;

    ...
}
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In this example, EntityAnalyzer is used to index tokenized property (name), except summary and body which are indexed with PropertyAnalyzer and FieldAnalyzer respectively.

Warning

Mixing different analyzers in the same entity is most of the time a bad practice. It makes query building more complex and results less predictable (for the novice), especially if you are using a QueryParser (which uses the same analyzer for the whole query). As a rule of thumb, for any given field the same analyzer should be used for indexing and querying.
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14.2.3.2. Named Analyzers
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Analyzers can become quite complex to deal with. For this reason introduces Hibernate Search the notion of analyzer definitions. An analyzer definition can be reused by many @Analyzer declarations and is composed of:
  • a name: the unique string used to refer to the definition
  • a list of char filters: each char filter is responsible to pre-process input characters before the tokenization. Char filters can add, change, or remove characters; one common usage is for characters normalization
  • a tokenizer: responsible for tokenizing the input stream into individual words
  • a list of filters: each filter is responsible to remove, modify, or sometimes even add words into the stream provided by the tokenizer
This separation of tasks - a list of char filters, and a tokenizer followed by a list of filters - allows for easy reuse of each individual component and let you build your customized analyzer in a very flexible way (like Lego). Generally speaking the char filters do some pre-processing in the character input, then the Tokenizer starts the tokenizing process by turning the character input into tokens which are then further processed by the TokenFilters. Hibernate Search supports this infrastructure by utilizing the Solr analyzer framework.

Note

Some of the analyzers and filters will require additional dependencies. For example to use the snowball stemmer you have to also include the lucene-snowball jar and for the PhoneticFilterFactory you need the commons-codec jar. Your distribution of Hibernate Search provides these dependencies in its lib/optional directory.
When using Maven all required Solr dependencies are now defined as dependencies of the artifact org.hibernate:hibernate-search-analyzers; add the following dependency : 
<dependency>
   <groupId>org.hibernate</groupId>
   <artifactId>hibernate-search-analyzers</artifactId>
   <version>4.6.0.Final-redhat-2</version>
   <scope>provided</scope>
<dependency>
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Let's review a concrete example now - Example 14.20, “@AnalyzerDef and the Solr framework”. First a char filter is defined by its factory. In our example, a mapping char filter is used, and will replace characters in the input based on the rules specified in the mapping file. Next a tokenizer is defined. This example uses the standard tokenizer. Last but not least, a list of filters is defined by their factories. In our example, the StopFilter filter is built reading the dedicated words property file. The filter is also expected to ignore case.

Example 14.20. @AnalyzerDef and the Solr framework

@AnalyzerDef(name="customanalyzer",
  charFilters = {
    @CharFilterDef(factory = MappingCharFilterFactory.class, params = {
      @Parameter(name = "mapping",
        value = "org/hibernate/search/test/analyzer/solr/mapping-chars.properties")
    })
  },
  tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class),
  filters = {
    @TokenFilterDef(factory = ISOLatin1AccentFilterFactory.class),
    @TokenFilterDef(factory = LowerCaseFilterFactory.class),
    @TokenFilterDef(factory = StopFilterFactory.class, params = {
      @Parameter(name="words",
        value= "org/hibernate/search/test/analyzer/solr/stoplist.properties" ),
      @Parameter(name="ignoreCase", value="true")
    })
})
public class Team {
    ...
}
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Note

Filters and char filters are applied in the order they are defined in the @AnalyzerDef annotation. Order matters!
Some tokenizers, token filters or char filters load resources like a configuration or metadata file. This is the case for the stop filter and the synonym filter. If the resource charset is not using the VM default, you can explicitly specify it by adding a resource_charset parameter.

Example 14.21. Use a specific charset to load the property file

@AnalyzerDef(name="customanalyzer",
  charFilters = {
    @CharFilterDef(factory = MappingCharFilterFactory.class, params = {
      @Parameter(name = "mapping",
        value = "org/hibernate/search/test/analyzer/solr/mapping-chars.properties")
    })
  },
  tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class),
  filters = {
    @TokenFilterDef(factory = ISOLatin1AccentFilterFactory.class),
    @TokenFilterDef(factory = LowerCaseFilterFactory.class),
    @TokenFilterDef(factory = StopFilterFactory.class, params = {
      @Parameter(name="words",
        value= "org/hibernate/search/test/analyzer/solr/stoplist.properties" ),
      @Parameter(name="resource_charset", value = "UTF-16BE"),
      @Parameter(name="ignoreCase", value="true")
  })
})
public class Team {
    ...
}
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Once defined, an analyzer definition can be reused by an @Analyzer declaration as seen in Example 14.22, “Referencing an analyzer by name”.

Example 14.22. Referencing an analyzer by name

@Entity
@Indexed
@AnalyzerDef(name="customanalyzer", ... )
public class Team {
    @Id
    @DocumentId
    @GeneratedValue
    private Integer id;

    @Field
    private String name;

    @Field
    private String location;

    @Field 
    @Analyzer(definition = "customanalyzer")
    private String description;
}
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Analyzer instances declared by @AnalyzerDef are also available by their name in the SearchFactory which is quite useful when building queries. 
Analyzer analyzer = fullTextSession.getSearchFactory().getAnalyzer("customanalyzer");
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Fields in queries must be analyzed with the same analyzer used to index the field so that they speak a common "language": the same tokens are reused between the query and the indexing process. This rule has some exceptions but is true most of the time. Respect it unless you know what you are doing.
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14.2.3.3. Available Analyzers
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Solr and Lucene come with a lot of useful default char filters, tokenizers, and filters. You can find a complete list of char filter factories, tokenizer factories and filter factories at http://wiki.apache.org/solr/AnalyzersTokenizersTokenFilters. Let's check a few of them.
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Table 14.1. Example of available char filters
Factory Description Parameters Additional dependencies
MappingCharFilterFactory Replaces one or more characters with one or more characters, based on mappings specified in the resource file
mapping: points to a resource file containing the mappings using the format:


                    "á" => "a"
                    "ñ" => "n"
                    "ø" => "o"

 none
HTMLStripCharFilterFactory Remove HTML standard tags, keeping the text none none
Expand
Table 14.2. Example of available tokenizers
Factory Description Parameters Additional dependencies
StandardTokenizerFactory Use the Lucene StandardTokenizer none none
HTMLStripCharFilterFactory Remove HTML tags, keep the text and pass it to a StandardTokenizer. none solr-core
PatternTokenizerFactory Breaks text at the specified regular expression pattern.
pattern: the regular expression to use for tokenizing
group: says which pattern group to extract into tokens
solr-core
Expand
Table 14.3. Examples of available filters
Factory Description Parameters Additional dependencies
StandardFilterFactory Remove dots from acronyms and 's from words none solr-core
LowerCaseFilterFactory Lowercases all words none solr-core
StopFilterFactory Remove words (tokens) matching a list of stop words
words: points to a resource file containing the stop words
ignoreCase: true if case should be ignored when comparing stop words, false otherwise
solr-core
SnowballPorterFilterFactory Reduces a word to it's root in a given language. (example: protect, protects, protection share the same root). Using such a filter allows searches matching related words. language: Danish, Dutch, English, Finnish, French, German, Italian, Norwegian, Portuguese, Russian, Spanish, Swedish and a few more solr-core
ISOLatin1AccentFilterFactory Remove accents for languages like French none solr-core
PhoneticFilterFactory Inserts phonetically similar tokens into the token stream
encoder: One of DoubleMetaphone, Metaphone, Soundex or RefinedSoundex
inject: true will add tokens to the stream, false will replace the existing token
maxCodeLength: sets the maximum length of the code to be generated. Supported only for Metaphone and DoubleMetaphone encodings
solr-core and commons-codec
CollationKeyFilterFactory Converts each token into its java.text.CollationKey, and then encodes the CollationKey with IndexableBinaryStringTools, to allow it to be stored as an index term. custom, language, country, variant, strength, decomposition
For more information, see Lucene's CollationKeyFilter javadocs
solr-core and commons-io
We recommend to check all the implementations of org.apache.solr.analysis.TokenizerFactory and org.apache.solr.analysis.TokenFilterFactory in your IDE to see the implementations available.
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14.2.3.4. Dynamic Analyzer Selection
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So far all the introduced ways to specify an analyzer were static. However, there are use cases where it is useful to select an analyzer depending on the current state of the entity to be indexed, for example in a multilingual applications. For an BlogEntry class for example the analyzer could depend on the language property of the entry. Depending on this property the correct language specific stemmer should be chosen to index the actual text.
To enable this dynamic analyzer selection Hibernate Search introduces the AnalyzerDiscriminator annotation. Example 14.23, “Usage of @AnalyzerDiscriminator” demonstrates the usage of this annotation.

Example 14.23. Usage of @AnalyzerDiscriminator

@Entity
@Indexed
@AnalyzerDefs({
  @AnalyzerDef(name = "en",
    tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class),
    filters = {
      @TokenFilterDef(factory = LowerCaseFilterFactory.class),
      @TokenFilterDef(factory = EnglishPorterFilterFactory.class
      )
    }),
  @AnalyzerDef(name = "de",
    tokenizer = @TokenizerDef(factory = StandardTokenizerFactory.class),
    filters = {
      @TokenFilterDef(factory = LowerCaseFilterFactory.class),
      @TokenFilterDef(factory = GermanStemFilterFactory.class)
    })
})
public class BlogEntry {

    @Id
    @GeneratedValue
    @DocumentId
    private Integer id;

    @Field
    @AnalyzerDiscriminator(impl = LanguageDiscriminator.class)
    private String language;
    
    @Field
    private String text;
    
    private Set<BlogEntry> references;

    // standard getter/setter
    ...
}
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public class LanguageDiscriminator implements Discriminator {

    public String getAnalyzerDefinitionName(Object value, Object entity, String field) {
        if ( value == null || !( entity instanceof BlogEntry ) ) {
            return null;
        }
        return (String) value;

    }
}
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The prerequisite for using @AnalyzerDiscriminator is that all analyzers which are going to be used dynamically are predefined via @AnalyzerDef definitions. If this is the case, one can place the @AnalyzerDiscriminator annotation either on the class or on a specific property of the entity for which to dynamically select an analyzer. Via the impl parameter of the AnalyzerDiscriminator you specify a concrete implementation of the Discriminator interface. It is up to you to provide an implementation for this interface. The only method you have to implement is getAnalyzerDefinitionName() which gets called for each field added to the Lucene document. The entity which is getting indexed is also passed to the interface method. The value parameter is only set if the AnalyzerDiscriminator is placed on property level instead of class level. In this case the value represents the current value of this property.
An implementation of the Discriminator interface has to return the name of an existing analyzer definition or null if the default analyzer should not be overridden. Example 14.23, “Usage of @AnalyzerDiscriminator” assumes that the language parameter is either 'de' or 'en' which matches the specified names in the @AnalyzerDefs.
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14.2.3.5. Retrieving an Analyzer
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Retrieving an analyzer can be used when multiple analyzers have been used in a domain model, in order to benefit from stemming or phonetic approximation, etc. In this case, use the same analyzers to building a query. Alternatively, use the Hibernate Search query DSL, which selects the correct analyzer automatically. See Section 14.3.1.2, “Building a Lucene Query”
Whether you are using the Lucene programmatic API or the Lucene query parser, you can retrieve the scoped analyzer for a given entity. A scoped analyzer is an analyzer which applies the right analyzers depending on the field indexed. Remember, multiple analyzers can be defined on a given entity each one working on an individual field. A scoped analyzer unifies all these analyzers into a context-aware analyzer. While the theory seems a bit complex, using the right analyzer in a query is very easy.

Note

When you use programmatic mapping for a child entity, you can only see the fields defined by the child entity. Fields or methods inherited from a parent entity (annotated with @MappedSuperclass) are not configurable. To configure properties inherited from a parent entity, either override the property in the child entity or create a programmatic mapping for the parent entity. This mimics the usage of annotations where you cannot annotate a field or method of a parent entity unless it is redefined in the child entity.

Example 14.24. Using the scoped analyzer when building a full-text query

org.apache.lucene.queryParser.QueryParser parser = new QueryParser(
    "title", 
    fullTextSession.getSearchFactory().getAnalyzer( Song.class )
);

org.apache.lucene.search.Query luceneQuery = 
    parser.parse( "title:sky Or title_stemmed:diamond" );

org.hibernate.Query fullTextQuery = 
    fullTextSession.createFullTextQuery( luceneQuery, Song.class );

List result = fullTextQuery.list(); //return a list of managed objects
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In the example above, the song title is indexed in two fields: the standard analyzer is used in the field title and a stemming analyzer is used in the field title_stemmed. By using the analyzer provided by the search factory, the query uses the appropriate analyzer depending on the field targeted.

Note

You can also retrieve analyzers defined via @AnalyzerDef by their definition name using searchFactory.getAnalyzer(String).
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14.2.4. Bridges
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When discussing the basic mapping for an entity one important fact was so far disregarded. In Lucene all index fields have to be represented as strings. All entity properties annotated with @Field have to be converted to strings to be indexed. The reason we have not mentioned it so far is, that for most of your properties Hibernate Search does the translation job for you thanks to set of built-in bridges. However, in some cases you need a more fine grained control over the translation process.
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14.2.4.1. Built-in Bridges
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Hibernate Search comes bundled with a set of built-in bridges between a Java property type and its full text representation.
null
Per default null elements are not indexed. Lucene does not support null elements. However, in some situation it can be useful to insert a custom token representing the null value. See Section 14.2.1.1.2, “@Field” for more information.
java.lang.String
Strings are indexed as are
short, Short, integer, Integer, long, Long, float, Float, double, Double, BigInteger, BigDecimal
Numbers are converted into their string representation. Note that numbers cannot be compared by Lucene (that is, used in ranged queries) out of the box: they have to be padded.

Note

Using a Range query has drawbacks, an alternative approach is to use a Filter query which will filter the result query to the appropriate range.
Hibernate Search also supports the use of a custom StringBridge as described in Section 14.2.4.2, “Custom Bridges”.
java.util.Date
Dates are stored as yyyyMMddHHmmssSSS in GMT time (200611072203012 for Nov 7th of 2006 4:03PM and 12ms EST). You shouldn't really bother with the internal format. What is important is that when using a TermRangeQuery, you should know that the dates have to be expressed in GMT time.
Usually, storing the date up to the millisecond is not necessary. @DateBridge defines the appropriate resolution you are willing to store in the index (@DateBridge(resolution=Resolution.DAY)). The date pattern will then be truncated accordingly. 
@Entity 
@Indexed
public class Meeting {
    @Field(analyze=Analyze.NO)
    @DateBridge(resolution=Resolution.MINUTE)
    private Date date;
    ...
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Warning

A Date whose resolution is lower than MILLISECOND cannot be a @DocumentId.

Important

The default Date bridge uses Lucene's DateTools to convert from and to String. This means that all dates are expressed in GMT time. If your requirements are to store dates in a fixed time zone you have to implement a custom date bridge. Make sure you understand the requirements of your applications regarding to date indexing and searching.
java.net.URI, java.net.URL
URI and URL are converted to their string representation.
java.lang.Class
Class are converted to their fully qualified class name. The thread context class loader is used when the class is rehydrated.
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14.2.4.2. Custom Bridges
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Sometimes, the built-in bridges of Hibernate Search do not cover some of your property types, or the String representation used by the bridge does not meet your requirements. The following paragraphs describe several solutions to this problem.
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14.2.4.2.1. StringBridge
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The simplest custom solution is to give Hibernate Search an implementation of your expected Object to String bridge. To do so you need to implement the org.hibernate.search.bridge.StringBridge interface. All implementations have to be thread-safe as they are used concurrently.

Example 14.25. Custom StringBridge implementation

/**
 * Padding Integer bridge.
 * All numbers will be padded with 0 to match 5 digits
 *
 * @author Emmanuel Bernard
 */
public class PaddedIntegerBridge implements StringBridge {

    private int PADDING = 5;

    public String objectToString(Object object) {
        String rawInteger = ( (Integer) object ).toString();
        if (rawInteger.length() > PADDING) 
            throw new IllegalArgumentException( "Try to pad on a number too big" );
        StringBuilder paddedInteger = new StringBuilder( );
        for ( int padIndex = rawInteger.length() ; padIndex < PADDING ; padIndex++ ) {
            paddedInteger.append('0');
        }
        return paddedInteger.append( rawInteger ).toString();
    }
}
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Given the string bridge defined in Example 14.25, “Custom StringBridge implementation”, any property or field can use this bridge thanks to the @FieldBridge annotation: 
@FieldBridge(impl = PaddedIntegerBridge.class)
private Integer length;
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14.2.4.2.2. Parameterized Bridge
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Parameters can also be passed to the bridge implementation making it more flexible. Example 14.26, “Passing parameters to your bridge implementation” implements a ParameterizedBridge interface and parameters are passed through the @FieldBridge annotation.

Example 14.26. Passing parameters to your bridge implementation

public class PaddedIntegerBridge implements StringBridge, ParameterizedBridge {

    public static String PADDING_PROPERTY = "padding";
    private int padding = 5; //default

    public void setParameterValues(Map<String,String> parameters) {
        String padding = parameters.get( PADDING_PROPERTY );
        if (padding != null) this.padding = Integer.parseInt( padding );
    }

    public String objectToString(Object object) {
        String rawInteger = ( (Integer) object ).toString();
        if (rawInteger.length() > padding) 
            throw new IllegalArgumentException( "Try to pad on a number too big" );
        StringBuilder paddedInteger = new StringBuilder( );
        for ( int padIndex = rawInteger.length() ; padIndex < padding ; padIndex++ ) {
            paddedInteger.append('0');
        }
        return paddedInteger.append( rawInteger ).toString();
    }
}


//property
@FieldBridge(impl = PaddedIntegerBridge.class,
             params = @Parameter(name="padding", value="10")
            )
private Integer length;
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The ParameterizedBridge interface can be implemented by StringBridge, TwoWayStringBridge, FieldBridge implementations.
All implementations have to be thread-safe, but the parameters are set during initialization and no special care is required at this stage.
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14.2.4.2.3. Type Aware Bridge
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It is sometimes useful to get the type the bridge is applied on:
  • the return type of the property for field/getter-level bridges.
  • the class type for class-level bridges.
An example is a bridge that deals with enums in a custom fashion but needs to access the actual enum type. Any bridge implementing AppliedOnTypeAwareBridge will get the type the bridge is applied on injected. Like parameters, the type injected needs no particular care with regard to thread-safety.
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14.2.4.2.4. Two-Way Bridge
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If you expect to use your bridge implementation on an id property (that is, annotated with @DocumentId ), you need to use a slightly extended version of StringBridge named TwoWayStringBridge. Hibernate Search needs to read the string representation of the identifier and generate the object out of it. There is no difference in the way the @FieldBridge annotation is used.

Example 14.27. Implementing a TwoWayStringBridge usable for id properties

public class PaddedIntegerBridge implements TwoWayStringBridge, ParameterizedBridge {

    public static String PADDING_PROPERTY = "padding";
    private int padding = 5; //default

    public void setParameterValues(Map parameters) {
        Object padding = parameters.get( PADDING_PROPERTY );
        if (padding != null) this.padding = (Integer) padding;
    }

    public String objectToString(Object object) {
        String rawInteger = ( (Integer) object ).toString();
        if (rawInteger.length() > padding) 
            throw new IllegalArgumentException( "Try to pad on a number too big" );
        StringBuilder paddedInteger = new StringBuilder( );
        for ( int padIndex = rawInteger.length() ; padIndex < padding ; padIndex++ ) {
            paddedInteger.append('0');
        }
        return paddedInteger.append( rawInteger ).toString();
    }

    public Object stringToObject(String stringValue) {
        return new Integer(stringValue);
    }
}


//id property
@DocumentId
@FieldBridge(impl = PaddedIntegerBridge.class,
             params = @Parameter(name="padding", value="10") 
private Integer id;
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Important

It is important for the two-way process to be idempotent (ie object = stringToObject( objectToString( object ) ) ).
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14.2.4.2.5. FieldBridge
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Some use cases require more than a simple object to string translation when mapping a property to a Lucene index. To give you the greatest possible flexibility you can also implement a bridge as a FieldBridge. This interface gives you a property value and let you map it the way you want in your Lucene Document. You can for example store a property in two different document fields. The interface is very similar in its concept to the Hibernate UserTypes.

Example 14.28. Implementing the FieldBridge Interface

/**
 * Store the date in 3 different fields - year, month, day - to ease Range Query per
 * year, month or day (eg get all the elements of December for the last 5 years).
 * @author Emmanuel Bernard
 */
public class DateSplitBridge implements FieldBridge {
    private final static TimeZone GMT = TimeZone.getTimeZone("GMT");

    public void set(String name, Object value, Document document, LuceneOptions luceneOptions) {
        Date date = (Date) value;
        Calendar cal = GregorianCalendar.getInstance(GMT);
        cal.setTime(date);
        int year = cal.get(Calendar.YEAR);
        int month = cal.get(Calendar.MONTH) + 1;
        int day = cal.get(Calendar.DAY_OF_MONTH);
  
        // set year
        luceneOptions.addFieldToDocument(
            name + ".year",
            String.valueOf( year ),
            document );
  
        // set month and pad it if needed
        luceneOptions.addFieldToDocument(
            name + ".month",
            month < 10 ? "0" : "" + String.valueOf( month ),
            document );
  
        // set day and pad it if needed
        luceneOptions.addFieldToDocument(
            name + ".day",
            day < 10 ? "0" : "" + String.valueOf( day ),
            document );
    }
}

//property
@FieldBridge(impl = DateSplitBridge.class)
private Date date;
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In Example 14.28, “Implementing the FieldBridge Interface” the fields are not added directly to Document. Instead the addition is delegated to the LuceneOptions helper; this helper will apply the options you have selected on @Field, like Store or TermVector, or apply the choosen @Boost value. It is especially useful to encapsulate the complexity of COMPRESS implementations. Even though it is recommended to delegate to LuceneOptions to add fields to the Document, nothing stops you from editing the Document directly and ignore the LuceneOptions in case you need to.

Note

Classes like LuceneOptions are created to shield your application from changes in Lucene API and simplify your code. Use them if you can, but if you need more flexibility you're not required to.
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14.2.4.2.6. ClassBridge
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It is sometimes useful to combine more than one property of a given entity and index this combination in a specific way into the Lucene index. The @ClassBridge and @ClassBridges annotations can be defined at the class level, as opposed to the property level. In this case the custom field bridge implementation receives the entity instance as the value parameter instead of a particular property. Though not shown in Example 14.29, “Implementing a class bridge”, @ClassBridge supports the termVector attribute discussed in section Section 14.2.1.1, “Basic Mapping”.

Example 14.29. Implementing a class bridge

@Entity
@Indexed
@ClassBridge(name="branchnetwork",
             store=Store.YES,
             impl = CatFieldsClassBridge.class,
             params = @Parameter( name="sepChar", value=" " ) )
public class Department {
    private int id;
    private String network;
    private String branchHead;
    private String branch;
    private Integer maxEmployees
    ...
}

public class CatFieldsClassBridge implements FieldBridge, ParameterizedBridge {
    private String sepChar;

    public void setParameterValues(Map parameters) {
        this.sepChar = (String) parameters.get( "sepChar" );
    }

    public void set( String name, Object value, Document document, LuceneOptions luceneOptions) {
        // In this particular class the name of the new field was passed
        // from the name field of the ClassBridge Annotation. This is not
        // a requirement. It just works that way in this instance. The
        // actual name could be supplied by hard coding it below.
        Department dep = (Department) value;
        String fieldValue1 = dep.getBranch();
        if ( fieldValue1 == null ) {
            fieldValue1 = "";
        }
        String fieldValue2 = dep.getNetwork();
        if ( fieldValue2 == null ) {
            fieldValue2 = "";
        }
        String fieldValue = fieldValue1 + sepChar + fieldValue2;
        Field field = new Field( name, fieldValue, luceneOptions.getStore(),
            luceneOptions.getIndex(), luceneOptions.getTermVector() );
        field.setBoost( luceneOptions.getBoost() );
        document.add( field );
   }
}
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In this example, the particular CatFieldsClassBridge is applied to the department instance, the field bridge then concatenate both branch and network and index the concatenation.
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