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On top of the rules we ve just discussed, a two-way bridge targeted at supporting identifier properties must follow two additional rules:
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objectToString must generate a unique string representation of the identifier. Hibernate Search will search this string in the field named after the name parameter in the set method. This query retrieves the document from its entity s identifier property. The set method must add a field named name (a parameter of the method set), which indexes the objectToString value untokenized. A Lucene term query will be used to retrieve a document by its identifier.
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You ve just discovered the most flexible way to convert an object structure to a Lucene index and are now ready to face the Wild, Wild West of domain models. Custom bridges are the most popular extension point of Hibernate Search. While in most situations you won t need to use custom bridges, they ll soon become an essential tool for mapping exotic domain models. You might feel right now that this puts too much power in your hands, that you don t need such flexibility (and in a lot of cases you ll be right), but after reading chapters 6 and 7 on queries, you ll need to bend the index structure to suit your needs in order to make the most of your full-text queries. Bridges will be there for you.
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Until now, we have quite elegantly avoided talking about a very important aspect of domain models: relationships. Without relationships, you simply could not express queries involving more than one entity; you could not search for all authors whose name is Bernard (property Author.name) and who live in Atlanta (property Author.address.city). It s important to preserve in one way or another the concept of relationship in the index structure.
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Deep inside both the relational model and the object model lies the idea of relationship (or association) between entities. Both models allow you to navigate from one entity to an associated entity. Because associations are a native part of the model, it s possible to express queries that apply restrictions on associated objects. We ll call such queries correlated queries. Unfortunately in Lucene, queries on related documents cannot be expressed; the notion of relationship between documents has not been built into Lucene. Figure 4.2 shows the different concepts as they are represented in the object model, the relational model, and the index model. The main consequence for us is that we cannot express correlated queries. The reasoning behind Lucene s choice is interesting. Lucene is not a database; it is an index. Indexes typically sacrifice normalization, data precision, and query expressive-
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ness for performance. This is what we re asking them to do. Lucene, which is essentially an index technology, follows this rule. Hibernate Search works around this problem by denormalizing associations. Since a Lucene query takes only a single document into consideration to evaluate its relevance and has no notion of a document join or association, contrary to the object and relational models, Hibernate Search indexes the object graph into a single document. In figure 4.3, you can see that when the item entity is indexed, its associated director and actors are indexed in the same document. Each of the association s entity properties is indexed in the association s namespace. In our example, the director s name is indexed in director.name, which is exactly how we d express a navigation to the director s name of a given item in an expression language or in HQL.
Figure 4.3 Hibernate Search denormalizes associations to make them queryable. The information in an object graph is rendered in a flat form in a single Lucene document.
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