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Getting started with Hibernate Search
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between an HQL query and a full-text query. This makes the migration from one strategy to the other very simple and targeted. Other than the fundamental mismatches, Hibernate Search doesn t require any specific configuration infrastructure as it integrates into the Hibernate Core configuration scheme and lifecycle. It doesn t require you to list all the indexed entities. We ve only started our exploration of Hibernate Search, but you can already feel that this tool focuses on ease of use, has a deep integration with the persistence services, and addresses the mismatch problems of integrating a full-text solution like Lucene into a domain model-centric application. Hopefully, you want to know more about Hibernate Search and explore more of its functionalities, and there s a lot more to explore. The next chapters of the book are all about making you an expert in Hibernate Search and helping you discover what it can solve for you!
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Part 2 Ending structural and synchronization mismatches
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n these next three chapters, you will discover how Hibernate Search indexes your objects. 3 covers the concept of mapping and how to mark an entity and its properties as indexed. 4, going deeper into the mapping concept, describes how to map relationships between entities and unexpected property types. 5 tells you where the index information is stored, when and how index operations are performed, and what control you have over them. This chapter also covers the notion of a text analyzer and its relationship to advanced search techniques such as recovering from typos, phonetic approximation, and searching by synonym. While reading these chapters, you will index your domain model and set up Hibernate Search to answer your searches.
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Mapping simple data structures
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This chapter covers
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Index mapping of an entity class and its identity property Index mapping of properties (built-in bridge, indexing strategy) Using an analyzer
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2 gave us a very brief introduction to data mapping. This chapter will explain in greater detail each basic mapping structure, the reasoning behind it, and more important, in which situation it is useful. You will learn how to declare an entity as indexable, which properties are indexed in this entity, and what kind of indexing strategy is used. But before that, let s see why mapping is required.
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Mapping simple data structures
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Why do we need mapping, again
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The world in which our primary data structure lives (the object-oriented domain model) has a completely different model than the index structure. Let s talk about a few of the differences highlighted by figure 3.1 and see how those contradictions can be solved. An object-oriented domain model in Java has a few notable characteristics:
It is polymorphic. A class can inherit the structure from a superclass. It has a strong type system. Each attribute of a class has a type that precisely represents the data. In particular, different data types aren t interchangeable. It has a rich and extensible type system. Types can be any of the many built-in types provided by the JRE or a custom one. Specifically, any program can define its own classes.
The Lucene index structure is much more monotonous. An entry is roughly structured as a map (a Document in Lucene terminology) containing key value string pairs. Each entry in the Lucene Document is called a Field, and the key is the Field name. Readers familiar with Lucene probably have noticed that this description oversimplifies the actual Lucene model, but it s nevertheless a good first-level approximation. We encourage the curious reader to grab Lucene in Action for more information. Let s highlight some differences with the object model: It is not typed. Everything is essentially a string. The type model is not extensible. It is not possible to define a custom Field type. It is not hierarchical. There is no relation between Lucene documents, in particular, no hierarchical relation. It is unstructured. Two different documents in the same index can contain different fields.
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