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Once the data is properly converted to the index and kept synchronized with the database, we need to think about doing what we planned from day one: finding information. The full-text search engine will return a list of matching documents through a Lucene-specific API. A document is essentially a map of field names and field values. The developer has two choices: Accept an untyped version of its domain model (the map) and adjust the code to deal with two different models depending on the search method (full-text versus SQL), or convert the document back to the domain model. In addition to having to write the code to convert the index data back into an object model, some problems will arise: The index needs to store the same amount of data as the database, potentially wasting Lucene performance. You also need to be sure that the text version of the data can be converted back into its original type. This system also needs to implement lazy loading.
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Lazy loading is a technique heavily used in ORMs to avoid loading too much information into memory. Without lazy loading, loading an object means loading the object and all its associated objects recursively. Provided that the entities have rich relationships, this could mean loading the whole database into memory. To avoid that, an ORM will load only the object or object graph up to a certain level. This level is defined statically or dynamically by the developer. If the program reaches one of the nonloaded associations, the ORM will load the needed object graph section transparently. Don't try this at home; you ll soon discover that lazy loading is a quite complex problem to solve! There s an additional inconvenience even if you manage to solve the lazy loading problem: Hibernate no longer takes care of the loaded objects. If the application changes one of those objects, how do you make sure the changes will be propagated to both the database and the index One last problem with this architecture is that you could end up having two instances of an object representing the same database row, one from Hibernate and one from Lucene, leading to synchronization hell. Which one has the correct information
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We ve shown in this chapter various strategies to provide search functionalities to an application and to help the user on his quest to access information. While categorization and a detailed search screen address some of the needs, the simple search box feature popularized by websites such as Google or Yahoo! has become increasingly important. Traditional relational database query solutions do not address efficiently (and sometimes not at all) search requirements when it comes to interaction with human demand. Full-text search technologies address those concerns by providing solutions to searching by relevance, searching by approximation, efficiently searching documents matching certain words, and so on. Full-text search opens a lot of doors that were not accessible by other technologies; it pushes the limits of the user experience by providing a seminatural way of expressing queries. Unfortunately, properly integrating a full-text search engine like Lucene into a classic Java architecture, whether it be SE (Standard Edition) or EE (Enterprise Edition), is not an easy task, and most people have to accept some inconsistency within their programmatic model (from the Java Persistence/Hibernate part and from the Lucene part). The authors believe that these problems are the major reasons for the lack of large-scale adoption of full-text search engines like Lucene by Java applications despite constant pressure by the customers. The price to pay is high enough that project leaders think twice before jumping. Fortunately, Hibernate Search addresses the three mismatches and makes using Hibernate and Lucene a pleasant experience in which developers can focus on the business value of a search instead of spending most of their time in boring conversions and infrastructure code. This sounds like the perfect time to be introduced to
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Hibernate Search! The next chapter will get you started with Hibernate Search in a pragmatic way, from the setup and configuration process to the mapping and querywriting process. While walking through this guide, you ll start to see how Hibernate Search addresses the three mismatches we introduced in this chapter.
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