Class MemoryIndex
- java.lang.Object
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- org.apache.lucene.index.memory.MemoryIndex
 
 
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public class MemoryIndex extends java.lang.ObjectHigh-performance single-document main memory Apache Lucene fulltext search index.Overview
This class is a replacement/substitute for a large subset ofRAMDirectoryfunctionality. It is designed to enable maximum efficiency for on-the-fly matchmaking combining structured and fuzzy fulltext search in realtime streaming applications such as Nux XQuery based XML message queues, publish-subscribe systems for Blogs/newsfeeds, text chat, data acquisition and distribution systems, application level routers, firewalls, classifiers, etc. Rather than targeting fulltext search of infrequent queries over huge persistent data archives (historic search), this class targets fulltext search of huge numbers of queries over comparatively small transient realtime data (prospective search). For example as infloat score = search(String text, Query query)
Each instance can hold at most one Lucene "document", with a document containing zero or more "fields", each field having a name and a fulltext value. The fulltext value is tokenized (split and transformed) into zero or more index terms (aka words) on
addField(), according to the policy implemented by an Analyzer. For example, Lucene analyzers can split on whitespace, normalize to lower case for case insensitivity, ignore common terms with little discriminatory value such as "he", "in", "and" (stop words), reduce the terms to their natural linguistic root form such as "fishing" being reduced to "fish" (stemming), resolve synonyms/inflexions/thesauri (upon indexing and/or querying), etc. For details, see Lucene Analyzer Intro.Arbitrary Lucene queries can be run against this class - see Lucene Query Syntax as well as Query Parser Rules. Note that a Lucene query selects on the field names and associated (indexed) tokenized terms, not on the original fulltext(s) - the latter are not stored but rather thrown away immediately after tokenization.
For some interesting background information on search technology, see Bob Wyman's Prospective Search, Jim Gray's A Call to Arms - Custom subscriptions, and Tim Bray's On Search, the Series.
Example Usage
Analyzer analyzer = new SimpleAnalyzer(version); MemoryIndex index = new MemoryIndex(); index.addField("content", "Readings about Salmons and other select Alaska fishing Manuals", analyzer); index.addField("author", "Tales of James", analyzer); QueryParser parser = new QueryParser(version, "content", analyzer); float score = index.search(parser.parse("+author:james +salmon~ +fish* manual~")); if (score > 0.0f) { System.out.println("it's a match"); } else { System.out.println("no match found"); } System.out.println("indexData=" + index.toString());Example XQuery Usage
(: An XQuery that finds all books authored by James that have something to do with "salmon fishing manuals", sorted by relevance :) declare namespace lucene = "java:nux.xom.pool.FullTextUtil"; declare variable $query := "+salmon~ +fish* manual~"; (: any arbitrary Lucene query can go here :) for $book in /books/book[author="James" and lucene:match(abstract, $query) > 0.0] let $score := lucene:match($book/abstract, $query) order by $score descending return $book
No thread safety guarantees
An instance can be queried multiple times with the same or different queries, but an instance is not thread-safe. If desired use idioms such as:MemoryIndex index = ... synchronized (index) { // read and/or write index (i.e. add fields and/or query) }Performance Notes
Internally there's a new data structure geared towards efficient indexing and searching, plus the necessary support code to seamlessly plug into the Lucene framework.This class performs very well for very small texts (e.g. 10 chars) as well as for large texts (e.g. 10 MB) and everything in between. Typically, it is about 10-100 times faster than
RAMDirectory. Note thatRAMDirectoryhas particularly large efficiency overheads for small to medium sized texts, both in time and space. Indexing a field with N tokens takes O(N) in the best case, and O(N logN) in the worst case. Memory consumption is probably larger than forRAMDirectory.Example throughput of many simple term queries over a single MemoryIndex: ~500000 queries/sec on a MacBook Pro, jdk 1.5.0_06, server VM. As always, your mileage may vary.
If you're curious about the whereabouts of bottlenecks, run java 1.5 with the non-perturbing '-server -agentlib:hprof=cpu=samples,depth=10' flags, then study the trace log and correlate its hotspot trailer with its call stack headers (see hprof tracing ).
 
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Constructor Summary
Constructors Constructor Description MemoryIndex()Constructs an empty instance.MemoryIndex(boolean storeOffsets)Constructs an empty instance that can optionally store the start and end character offset of each token term in the text. 
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidaddField(java.lang.String fieldName, java.lang.String text, Analyzer analyzer)Convenience method; Tokenizes the given field text and adds the resulting terms to the index; Equivalent to adding an indexed non-keyword LuceneFieldthat is tokenized, not stored, termVectorStored with positions (or termVectorStored with positions and offsets),voidaddField(java.lang.String fieldName, TokenStream stream)Equivalent toaddField(fieldName, stream, 1.0f).voidaddField(java.lang.String fieldName, TokenStream stream, float boost)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField.voidaddField(java.lang.String fieldName, TokenStream stream, float boost, int positionIncrementGap)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField.voidaddField(java.lang.String fieldName, TokenStream stream, float boost, int positionIncrementGap, int offsetGap)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField.IndexSearchercreateSearcher()Creates and returns a searcher that can be used to execute arbitrary Lucene queries and to collect the resulting query results as hits.longgetMemorySize()Returns a reasonable approximation of the main memory [bytes] consumed by this instance.<T> TokenStreamkeywordTokenStream(java.util.Collection<T> keywords)Convenience method; Creates and returns a token stream that generates a token for each keyword in the given collection, "as is", without any transforming text analysis.voidreset()Resets theMemoryIndexto its initial state and recycles all internal buffers.floatsearch(Query query)Convenience method that efficiently returns the relevance score by matching this index against the given Lucene query expression.java.lang.StringtoString()Returns a String representation of the index data for debugging purposes. 
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Constructor Detail
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MemoryIndex
public MemoryIndex()
Constructs an empty instance. 
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MemoryIndex
public MemoryIndex(boolean storeOffsets)
Constructs an empty instance that can optionally store the start and end character offset of each token term in the text. This can be useful for highlighting of hit locations with the Lucene highlighter package. Protected until the highlighter package matures, so that this can actually be meaningfully integrated.- Parameters:
 storeOffsets- whether or not to store the start and end character offset of each token term in the text
 
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Method Detail
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addField
public void addField(java.lang.String fieldName, java.lang.String text, Analyzer analyzer)Convenience method; Tokenizes the given field text and adds the resulting terms to the index; Equivalent to adding an indexed non-keyword LuceneFieldthat is tokenized, not stored, termVectorStored with positions (or termVectorStored with positions and offsets),- Parameters:
 fieldName- a name to be associated with the texttext- the text to tokenize and index.analyzer- the analyzer to use for tokenization
 
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keywordTokenStream
public <T> TokenStream keywordTokenStream(java.util.Collection<T> keywords)
Convenience method; Creates and returns a token stream that generates a token for each keyword in the given collection, "as is", without any transforming text analysis. The resulting token stream can be fed intoaddField(String, TokenStream), perhaps wrapped into anotherTokenFilter, as desired.- Parameters:
 keywords- the keywords to generate tokens for- Returns:
 - the corresponding token stream
 
 
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addField
public void addField(java.lang.String fieldName, TokenStream stream)Equivalent toaddField(fieldName, stream, 1.0f).- Parameters:
 fieldName- a name to be associated with the textstream- the token stream to retrieve tokens from
 
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addField
public void addField(java.lang.String fieldName, TokenStream stream, float boost)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField. Finally closes the token stream. Note that untokenized keywords can be added with this method viakeywordTokenStream(Collection), the LuceneKeywordTokenizeror similar utilities.- Parameters:
 fieldName- a name to be associated with the textstream- the token stream to retrieve tokens from.boost- the boost factor for hits for this field- See Also:
 Field.setBoost(float)
 
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addField
public void addField(java.lang.String fieldName, TokenStream stream, float boost, int positionIncrementGap)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField. Finally closes the token stream. Note that untokenized keywords can be added with this method viakeywordTokenStream(Collection), the LuceneKeywordTokenizeror similar utilities.- Parameters:
 fieldName- a name to be associated with the textstream- the token stream to retrieve tokens from.boost- the boost factor for hits for this fieldpositionIncrementGap- the position increment gap if fields with the same name are added more than once- See Also:
 Field.setBoost(float)
 
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addField
public void addField(java.lang.String fieldName, TokenStream stream, float boost, int positionIncrementGap, int offsetGap)Iterates over the given token stream and adds the resulting terms to the index; Equivalent to adding a tokenized, indexed, termVectorStored, unstored, LuceneField. Finally closes the token stream. Note that untokenized keywords can be added with this method viakeywordTokenStream(Collection), the LuceneKeywordTokenizeror similar utilities.- Parameters:
 fieldName- a name to be associated with the textstream- the token stream to retrieve tokens from.boost- the boost factor for hits for this fieldpositionIncrementGap- the position increment gap if fields with the same name are added more than onceoffsetGap- the offset gap if fields with the same name are added more than once- See Also:
 Field.setBoost(float)
 
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createSearcher
public IndexSearcher createSearcher()
Creates and returns a searcher that can be used to execute arbitrary Lucene queries and to collect the resulting query results as hits.- Returns:
 - a searcher
 
 
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search
public float search(Query query)
Convenience method that efficiently returns the relevance score by matching this index against the given Lucene query expression.- Parameters:
 query- an arbitrary Lucene query to run against this index- Returns:
 - the relevance score of the matchmaking; A number in the range [0.0 .. 1.0], with 0.0 indicating no match. The higher the number the better the match.
 
 
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getMemorySize
public long getMemorySize()
Returns a reasonable approximation of the main memory [bytes] consumed by this instance. Useful for smart memory sensititive caches/pools.- Returns:
 - the main memory consumption
 
 
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toString
public java.lang.String toString()
Returns a String representation of the index data for debugging purposes.- Overrides:
 toStringin classjava.lang.Object- Returns:
 - the string representation
 
 
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reset
public void reset()
Resets theMemoryIndexto its initial state and recycles all internal buffers. 
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