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Filters in Lucene are implemented as a subclass of org.hibernate.lucene. search.Filter, whose main method takes an IndexReader and returns a DocIdSet (see listing 8.1). A DocIdSet is a structure that returns the ordered list of matching document ids via an iterator. The most common DocIdSet implementation (DocIdBitSet) uses a structure named BitSet to store the list of matching results. BitSet is a compact structure that returns true or false for a given Lucene Document id; false means the element is filtered out. A BitSet uses one bit per Document. If your index contains ten million Documents, the BitSet structure will require 1.2 MB of memory. The DocIdSet is computed and returned for an IndexReader instance.
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Lucene comes bundled with a faster implementation of the BitSet class but which exposes more of its internal state. If you re looking for performance, consider using OpenBitSet instead of BitSet. Likewise, if your filter returns a very small subset of matching (or nonmatching elements), or if your filter can determine the list of matching documents based on a very compact structure, consider writing your own DocIdSet. Your own implementation of DocIdSet can save memory.
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An IndexReader instance represents the state of the index at the instant the IndexReader is opened by Hibernate Search. For a given IndexReader instance, the list of Documents is fixed, and a Document cannot change its id number. The same DocIdSet can be returned for the same IndexReader instance provided that the filter conditions don t change. But a different IndexReader instance works potentially on a different set of Documents (either from a different index or simply because the index has changed and a new IndexReader has been opened). The DocIdSet then has to be rebuilt. Listing 8.1 shows the Filter superclass. Every filter subclasses it and implements the necessary logic.
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Filters: cross-cutting restrictions
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Listing 8.1
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The Filter superclass
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public abstract class Filter implements java.io.Serializable { /** * @return a DocIdSet that provides the documents which should be * permitted or prohibited in search results. Lucene Filter * @see DocIdBitSet contract */ public DocIdSet getDocIdSet(IndexReader reader) throws IOException; }
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Return the DocIdSet filter B for a given IndexReader instance.
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Filter used to return BitSet objects instead of DocIdSet objects. While you can still write your filters using the old method, the authors recommend against it. Your implementation will not be supported in Lucene 3.0.
Lucene comes with built-in Filter implementations, but you can implement your own strategy quite easily. We ll walk through a few practical examples in the next section, but now let s have a look at some of the built-in Filter implementations to become more familiar with the concept:
QueryWrapperFilter A Lucene query result defines the DocIdSet applied on subsequent filtered queries. RangeFilter The DocIdSet contains the id for all documents where a given field is within the range; the field must not be tokenized. CachingWrapperFilter Wraps a Filter implementation and caches the DocIdSet per IndexReader instance in a WeakHashMap. Don t use this implementation with Hibernate Search. Use a hard reference-based or at least a soft reference-based cache mechanism instead. Even better, use the Hibernate Search built-in cache mechanism.
If you intend to filter based on some data stored in the index, QueryWrapperFilter is one of your best and most flexible choices. Filtering is built on a Lucene query; building a query is now a familiar operation for us. One of the use cases is to apply a query to the result set of a previous query, allowing a user to refine the search. RangeFilter is an alternative approach to RangeQuery, as we discussed in chapter 7. It restricts results to documents that match a given range. RangeFilter doesn t suffer from the TooManyClauses exception syndrome, because range is applied after the Lucene query execution. Filters really shine from a performance point of view when they can be cached and reused, that is, when the filter DocIdSet is built once (or occasionally) and reused by many queries. As you ve seen previously, a cached DocIdSet is valid for only a given IndexReader instance. Practically, it means that you cannot cache a filter efficiently if too many updates occur on your index data.
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