In order to enable full-text search on these relationships, you must denormalize the nested objects as dot-navigated fields in the Lucene Document objects. The data model in Lucene's Document class doesn't handle relationships through foreign key references, as a database does. You may notice a bidirectional many-to-one relationship between the Resume and User entities. The boost factor identified by gives more or less weight for the annotated property in Lucene index search, and affects the relevance scores of the search results. In contrast, if I had set store=Store.YES, the original Word documents would have been stored in and retrieved from the index. The attribute store=Store.NO indicates that the actual data (that is, the Word documents) will not be stored in the index therefore, that bean property will be returned through a separate SQL query as part of the Hibernate full-text search that returns the Resume entity objects. Bear in mind that you should not tokenize any primary key or natural key field. I choose the Lucene StandardAnalyzer for the sample application. Preprocessing involves removal of stop words, replacement of stemming words, and so on. Tokenizing is a critical step in indexing that preprocesses the source data before actual indexing takes place. The first attribute ensures that the text will be tokenized by a Lucene Analyzer. Two attributes of the annotation - index=Index.TOKENIZED and store=Store.NO - characterize Lucene indexing features, and so does the annotation. It is nearly effortless to build custom FieldBridges out of the existing Lucene DocumentHandlers. A wide variety of DocumentHandler implementations are available online for certain binary data types, including Word, Excel, PDF, HTML, and XML. The same concept exists in Lucene as DocumentHandler. I developed a custom FieldBridge WordDocHandlerBridge as part of the sample application to extract pure text from Word documents I used Apache POI, a Java API for accessing Microsoft Office files. Nevertheless, a byte array property in the Resume entity hosting Microsoft Word files requires special care. The built-in FieldBridges take care of all the built-in Java data types. A FieldBridge in Hibernate Search works as a data type converter in JSF or Spring that transforms any data type into text. Lucene indexing can't deal with any data type other than text strings thus, all bean properties to be indexed must be converted to their string representations. Hibernate Search uses that field internally to match a Lucene Document object to an entity instance. Most of the time, this ID is also a database primary key. Note that you don't have to index all of your JPA entity classes with Lucene, only those for which full-text search is required.Įven though a Lucene Document by itself doesn't enforce a unique key field, Hibernate Search requires you to specify a document ID field through a annotation. As discussed earlier, Lucene Document objects are the data unit for indexing and search as JPA entities in database persistence. More specifically, only bean properties annotated by are indexed as Fields in the Lucene Document objects. Hibernate Search implicitly matches an entity instance to a Lucene Document object. Any JPA entity class marked with the annotation is enabled for Lucene indexing, and is mapped to a unique Lucene index. A Maven 2 Hibernate plugin goal ( mvn hibernate3:hbm2ddl) outputs a SQL script from the annotated entity Java source files, and creates the corresponding database schema in the MySQL database.Īpart from the JPA annotations, the two entity classes are also marked with the new Hibernate Search annotations. The two persistence classes are annotated with the JPA tag, which declares that their nontranisent properties will be persisted to a relational database. Resume.java and User.java package =, mappedBy = Set resumes Two POJO persistence model classes, Resume.java and User.java, are defined in the sample application, as shown in Listing 1. In fact, its so easy, I'm going to show you how in 5 minutes!įor this simple case, we're going to create an in-memory index from some strings.I prefer to begin application programming with a persistence domain model. Lucene makes it easy to add full-text search capability to your application.
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