mirror of https://github.com/apache/lucene.git
LUCENE-6224: package.html -> package-info.java (just o.a.l.search initially)
git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/trunk@1658001 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Robert Muir
parent
77bf475f97
commit
270487d618
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@ -1904,7 +1904,7 @@ ${ant.project.name}.test.dependencies=${test.classpath.list}
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</target>
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<target name="-ecj-resolve" unless="ecj.loaded" depends="ivy-availability-check,ivy-configure" if="ecj-javadoc-lint.supported">
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<ivy:cachepath organisation="org.eclipse.jdt.core.compiler" module="ecj" revision="4.4"
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<ivy:cachepath organisation="org.eclipse.jdt.core.compiler" module="ecj" revision="4.4.1"
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inline="true" conf="master" type="jar" pathid="ecj.classpath" />
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<componentdef classname="org.eclipse.jdt.core.JDTCompilerAdapter"
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classpathref="ecj.classpath" name="ecj-component"/>
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@ -1920,21 +1920,29 @@ ${ant.project.name}.test.dependencies=${test.classpath.list}
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<element name="nested" implicit="yes" optional="yes"/>
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<sequential>
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<!-- hack: we can tell ECJ not to create classfiles, but it still creates
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package-info.class files. so redirect output to a tempdir -->
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<tempfile property="ecj.trash.out" destdir="${java.io.tmpdir}" prefix="ecj"/>
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<mkdir dir="${ecj.trash.out}"/>
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<javac
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includeAntRuntime="@{includeantruntime}"
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encoding="${build.encoding}"
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srcdir="@{srcdir}"
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destdir="${ecj.trash.out}"
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source="@{javac.source}"
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target="@{javac.source}"
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taskname="ecj-lint">
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<ecj-component/>
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<nested/>
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<!-- hack: we can't disable classfile creation right now, because we need
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to specify a destination for buggy package-info.class files
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<compilerarg value="-d"/>
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<compilerarg value="none"/>
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<compilerarg value="none"/> -->
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<compilerarg value="-enableJavadoc"/>
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<compilerarg value="-properties"/>
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<compilerarg value="@{configuration}"/>
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</javac>
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<delete dir="${ecj.trash.out}"/>
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</sequential>
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</macrodef>
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@ -0,0 +1,579 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/**
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* Code to search indices.
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*
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* <h2>Table Of Contents</h2>
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* <p>
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* <ol>
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* <li><a href="#search">Search Basics</a></li>
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* <li><a href="#query">The Query Classes</a></li>
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* <li><a href="#scoring">Scoring: Introduction</a></li>
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* <li><a href="#scoringBasics">Scoring: Basics</a></li>
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* <li><a href="#changingScoring">Changing the Scoring</a></li>
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* <li><a href="#algorithm">Appendix: Search Algorithm</a></li>
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* </ol>
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* </p>
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*
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*
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* <a name="search"></a>
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* <h2>Search Basics</h2>
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* <p>
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* Lucene offers a wide variety of {@link org.apache.lucene.search.Query} implementations, most of which are in
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* this package, its subpackages ({@link org.apache.lucene.search.spans spans}, {@link org.apache.lucene.search.payloads payloads}),
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* or the <a href="{@docRoot}/../queries/overview-summary.html">queries module</a>. These implementations can be combined in a wide
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* variety of ways to provide complex querying capabilities along with information about where matches took place in the document
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* collection. The <a href="#query">Query Classes</a> section below highlights some of the more important Query classes. For details
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* on implementing your own Query class, see <a href="#customQueriesExpert">Custom Queries -- Expert Level</a> below.
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* </p>
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* <p>
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* To perform a search, applications usually call {@link
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* org.apache.lucene.search.IndexSearcher#search(Query,int)} or {@link
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* org.apache.lucene.search.IndexSearcher#search(Query,Filter,int)}.
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* </p>
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* <p>
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* Once a Query has been created and submitted to the {@link org.apache.lucene.search.IndexSearcher IndexSearcher}, the scoring
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* process begins. After some infrastructure setup, control finally passes to the {@link org.apache.lucene.search.Weight Weight}
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* implementation and its {@link org.apache.lucene.search.Scorer Scorer} or {@link org.apache.lucene.search.BulkScorer BulkScore}
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* instances. See the <a href="#algorithm">Algorithm</a> section for more notes on the process.
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* </p>
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* <!-- FILL IN MORE HERE -->
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* <!-- TODO: this page over-links the same things too many times -->
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* </p>
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*
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*
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* <a name="query"></a>
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* <h2>Query Classes</h2>
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* <h3>
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* {@link org.apache.lucene.search.TermQuery TermQuery}
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* </h3>
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*
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* <p>Of the various implementations of
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* {@link org.apache.lucene.search.Query Query}, the
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* {@link org.apache.lucene.search.TermQuery TermQuery}
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* is the easiest to understand and the most often used in applications. A
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* {@link org.apache.lucene.search.TermQuery TermQuery} matches all the documents that contain the
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* specified
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* {@link org.apache.lucene.index.Term Term},
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* which is a word that occurs in a certain
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* {@link org.apache.lucene.document.Field Field}.
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* Thus, a {@link org.apache.lucene.search.TermQuery TermQuery} identifies and scores all
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* {@link org.apache.lucene.document.Document Document}s that have a
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* {@link org.apache.lucene.document.Field Field} with the specified string in it.
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* Constructing a {@link org.apache.lucene.search.TermQuery TermQuery}
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* is as simple as:
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* <pre class="prettyprint">
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* TermQuery tq = new TermQuery(new Term("fieldName", "term"));
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* </pre>In this example, the {@link org.apache.lucene.search.Query Query} identifies all
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* {@link org.apache.lucene.document.Document Document}s that have the
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* {@link org.apache.lucene.document.Field Field} named <tt>"fieldName"</tt>
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* containing the word <tt>"term"</tt>.
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* </p>
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* <h3>
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* {@link org.apache.lucene.search.BooleanQuery BooleanQuery}
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* </h3>
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*
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* <p>Things start to get interesting when one combines multiple
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* {@link org.apache.lucene.search.TermQuery TermQuery} instances into a
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* {@link org.apache.lucene.search.BooleanQuery BooleanQuery}.
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* A {@link org.apache.lucene.search.BooleanQuery BooleanQuery} contains multiple
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* {@link org.apache.lucene.search.BooleanClause BooleanClause}s,
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* where each clause contains a sub-query ({@link org.apache.lucene.search.Query Query}
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* instance) and an operator (from
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* {@link org.apache.lucene.search.BooleanClause.Occur BooleanClause.Occur})
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* describing how that sub-query is combined with the other clauses:
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* <ol>
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*
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* <li><p>{@link org.apache.lucene.search.BooleanClause.Occur#SHOULD SHOULD} — Use this operator when a clause can occur in the result set, but is not required.
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* If a query is made up of all SHOULD clauses, then every document in the result
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* set matches at least one of these clauses.</p></li>
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*
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* <li><p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST MUST} — Use this operator when a clause is required to occur in the result set. Every
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* document in the result set will match
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* all such clauses.</p></li>
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*
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* <li><p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST_NOT MUST NOT} — Use this operator when a
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* clause must not occur in the result set. No
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* document in the result set will match
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* any such clauses.</p></li>
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* </ol>
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* Boolean queries are constructed by adding two or more
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* {@link org.apache.lucene.search.BooleanClause BooleanClause}
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* instances. If too many clauses are added, a {@link org.apache.lucene.search.BooleanQuery.TooManyClauses TooManyClauses}
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* exception will be thrown during searching. This most often occurs
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* when a {@link org.apache.lucene.search.Query Query}
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* is rewritten into a {@link org.apache.lucene.search.BooleanQuery BooleanQuery} with many
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* {@link org.apache.lucene.search.TermQuery TermQuery} clauses,
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* for example by {@link org.apache.lucene.search.WildcardQuery WildcardQuery}.
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* The default setting for the maximum number
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* of clauses 1024, but this can be changed via the
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* static method {@link org.apache.lucene.search.BooleanQuery#setMaxClauseCount(int)}.
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* </p>
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*
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* <h3>Phrases</h3>
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*
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* <p>Another common search is to find documents containing certain phrases. This
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* is handled three different ways:
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* <ol>
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* <li>
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* <p>{@link org.apache.lucene.search.PhraseQuery PhraseQuery}
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* — Matches a sequence of
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* {@link org.apache.lucene.index.Term Term}s.
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* {@link org.apache.lucene.search.PhraseQuery PhraseQuery} uses a slop factor to determine
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* how many positions may occur between any two terms in the phrase and still be considered a match.
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* The slop is 0 by default, meaning the phrase must match exactly.</p>
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* </li>
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* <li>
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* <p>{@link org.apache.lucene.search.MultiPhraseQuery MultiPhraseQuery}
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* — A more general form of PhraseQuery that accepts multiple Terms
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* for a position in the phrase. For example, this can be used to perform phrase queries that also
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* incorporate synonyms.
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* </li>
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* <li>
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* <p>{@link org.apache.lucene.search.spans.SpanNearQuery SpanNearQuery}
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* — Matches a sequence of other
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* {@link org.apache.lucene.search.spans.SpanQuery SpanQuery}
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* instances. {@link org.apache.lucene.search.spans.SpanNearQuery SpanNearQuery} allows for
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* much more
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* complicated phrase queries since it is constructed from other
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* {@link org.apache.lucene.search.spans.SpanQuery SpanQuery}
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* instances, instead of only {@link org.apache.lucene.search.TermQuery TermQuery}
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* instances.</p>
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* </li>
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* </ol>
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* </p>
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*
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* <h3>
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* {@link org.apache.lucene.search.TermRangeQuery TermRangeQuery}
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* </h3>
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*
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* <p>The
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* {@link org.apache.lucene.search.TermRangeQuery TermRangeQuery}
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* matches all documents that occur in the
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* exclusive range of a lower
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* {@link org.apache.lucene.index.Term Term}
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* and an upper
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* {@link org.apache.lucene.index.Term Term}
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* according to {@link org.apache.lucene.util.BytesRef#compareTo BytesRef.compareTo()}. It is not intended
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* for numerical ranges; use {@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery} instead.
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*
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* For example, one could find all documents
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* that have terms beginning with the letters <tt>a</tt> through <tt>c</tt>.
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* </p>
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*
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* <h3>
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* {@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery}
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* </h3>
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*
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* <p>The
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* {@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery}
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* matches all documents that occur in a numeric range.
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* For NumericRangeQuery to work, you must index the values
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* using a one of the numeric fields ({@link org.apache.lucene.document.IntField IntField},
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* {@link org.apache.lucene.document.LongField LongField}, {@link org.apache.lucene.document.FloatField FloatField},
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* or {@link org.apache.lucene.document.DoubleField DoubleField}).
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* </p>
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*
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* <h3>
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* {@link org.apache.lucene.search.PrefixQuery PrefixQuery},
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* {@link org.apache.lucene.search.WildcardQuery WildcardQuery},
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* {@link org.apache.lucene.search.RegexpQuery RegexpQuery}
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* </h3>
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*
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* <p>While the
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* {@link org.apache.lucene.search.PrefixQuery PrefixQuery}
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* has a different implementation, it is essentially a special case of the
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* {@link org.apache.lucene.search.WildcardQuery WildcardQuery}.
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* The {@link org.apache.lucene.search.PrefixQuery PrefixQuery} allows an application
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* to identify all documents with terms that begin with a certain string. The
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* {@link org.apache.lucene.search.WildcardQuery WildcardQuery} generalizes this by allowing
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* for the use of <tt>*</tt> (matches 0 or more characters) and <tt>?</tt> (matches exactly one character) wildcards.
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* Note that the {@link org.apache.lucene.search.WildcardQuery WildcardQuery} can be quite slow. Also
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* note that
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* {@link org.apache.lucene.search.WildcardQuery WildcardQuery} should
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* not start with <tt>*</tt> and <tt>?</tt>, as these are extremely slow.
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* Some QueryParsers may not allow this by default, but provide a <code>setAllowLeadingWildcard</code> method
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* to remove that protection.
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* The {@link org.apache.lucene.search.RegexpQuery RegexpQuery} is even more general than WildcardQuery,
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* allowing an application to identify all documents with terms that match a regular expression pattern.
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* </p>
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* <h3>
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* {@link org.apache.lucene.search.FuzzyQuery FuzzyQuery}
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* </h3>
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*
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* <p>A
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* {@link org.apache.lucene.search.FuzzyQuery FuzzyQuery}
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* matches documents that contain terms similar to the specified term. Similarity is
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* determined using
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* <a href="http://en.wikipedia.org/wiki/Levenshtein">Levenshtein (edit) distance</a>.
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* This type of query can be useful when accounting for spelling variations in the collection.
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* </p>
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*
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*
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* <a name="scoring"></a>
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* <h2>Scoring — Introduction</h2>
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* <p>Lucene scoring is the heart of why we all love Lucene. It is blazingly fast and it hides
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* almost all of the complexity from the user. In a nutshell, it works. At least, that is,
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* until it doesn't work, or doesn't work as one would expect it to work. Then we are left
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* digging into Lucene internals or asking for help on
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* <a href="mailto:java-user@lucene.apache.org">java-user@lucene.apache.org</a> to figure out
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* why a document with five of our query terms scores lower than a different document with
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* only one of the query terms.
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* </p>
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* <p>While this document won't answer your specific scoring issues, it will, hopefully, point you
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* to the places that can help you figure out the <i>what</i> and <i>why</i> of Lucene scoring.
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* </p>
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* <p>Lucene scoring supports a number of pluggable information retrieval
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* <a href="http://en.wikipedia.org/wiki/Information_retrieval#Model_types">models</a>, including:
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* <ul>
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* <li><a href="http://en.wikipedia.org/wiki/Vector_Space_Model">Vector Space Model (VSM)</a></li>
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* <li><a href="http://en.wikipedia.org/wiki/Probabilistic_relevance_model">Probablistic Models</a> such as
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* <a href="http://en.wikipedia.org/wiki/Probabilistic_relevance_model_(BM25)">Okapi BM25</a> and
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* <a href="http://en.wikipedia.org/wiki/Divergence-from-randomness_model">DFR</a></li>
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* <li><a href="http://en.wikipedia.org/wiki/Language_model">Language models</a></li>
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* </ul>
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* These models can be plugged in via the {@link org.apache.lucene.search.similarities Similarity API},
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* and offer extension hooks and parameters for tuning. In general, Lucene first finds the documents
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* that need to be scored based on boolean logic in the Query specification, and then ranks this subset of
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* matching documents via the retrieval model. For some valuable references on VSM and IR in general refer to
|
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* <a href="http://wiki.apache.org/lucene-java/InformationRetrieval">Lucene Wiki IR references</a>.
|
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* </p>
|
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* <p>The rest of this document will cover <a href="#scoringBasics">Scoring basics</a> and explain how to
|
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* change your {@link org.apache.lucene.search.similarities.Similarity Similarity}. Next, it will cover
|
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* ways you can customize the lucene internals in
|
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* <a href="#customQueriesExpert">Custom Queries -- Expert Level</a>, which gives details on
|
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* implementing your own {@link org.apache.lucene.search.Query Query} class and related functionality.
|
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* Finally, we will finish up with some reference material in the <a href="#algorithm">Appendix</a>.
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* </p>
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*
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*
|
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* <a name="scoringBasics"></a>
|
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* <h2>Scoring — Basics</h2>
|
||||
* <p>Scoring is very much dependent on the way documents are indexed, so it is important to understand
|
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* indexing. (see <a href="{@docRoot}/overview-summary.html#overview_description">Lucene overview</a>
|
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* before continuing on with this section) Be sure to use the useful
|
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* {@link org.apache.lucene.search.IndexSearcher#explain(org.apache.lucene.search.Query, int) IndexSearcher.explain(Query, doc)}
|
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* to understand how the score for a certain matching document was
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* computed.
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*
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* <p>Generally, the Query determines which documents match (a binary
|
||||
* decision), while the Similarity determines how to assign scores to
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* the matching documents.
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*
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||||
* </p>
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* <h3>Fields and Documents</h3>
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* <p>In Lucene, the objects we are scoring are {@link org.apache.lucene.document.Document Document}s.
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* A Document is a collection of {@link org.apache.lucene.document.Field Field}s. Each Field has
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* {@link org.apache.lucene.document.FieldType semantics} about how it is created and stored
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* ({@link org.apache.lucene.document.FieldType#tokenized() tokenized},
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* {@link org.apache.lucene.document.FieldType#stored() stored}, etc). It is important to note that
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* Lucene scoring works on Fields and then combines the results to return Documents. This is
|
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* important because two Documents with the exact same content, but one having the content in two
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* Fields and the other in one Field may return different scores for the same query due to length
|
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* normalization.
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* </p>
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* <h3>Score Boosting</h3>
|
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* <p>Lucene allows influencing search results by "boosting" at different times:
|
||||
* <ul>
|
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* <li><b>Index-time boost</b> by calling
|
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* {@link org.apache.lucene.document.Field#setBoost(float) Field.setBoost()} before a document is
|
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* added to the index.</li>
|
||||
* <li><b>Query-time boost</b> by setting a boost on a query clause, calling
|
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* {@link org.apache.lucene.search.Query#setBoost(float) Query.setBoost()}.</li>
|
||||
* </ul>
|
||||
* </p>
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||||
* <p>Indexing time boosts are pre-processed for storage efficiency and written to
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* storage for a field as follows:
|
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* <ul>
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||||
* <li>All boosts of that field (i.e. all boosts under the same field name in that doc) are
|
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* multiplied.</li>
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||||
* <li>The boost is then encoded into a normalization value by the Similarity
|
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* object at index-time: {@link org.apache.lucene.search.similarities.Similarity#computeNorm computeNorm()}.
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||||
* The actual encoding depends upon the Similarity implementation, but note that most
|
||||
* use a lossy encoding (such as multiplying the boost with document length or similar, packed
|
||||
* into a single byte!).</li>
|
||||
* <li>Decoding of any index-time normalization values and integration into the document's score is also performed
|
||||
* at search time by the Similarity.</li>
|
||||
* </ul>
|
||||
* </p>
|
||||
*
|
||||
*
|
||||
* <a name="changingScoring"></a>
|
||||
* <h2>Changing Scoring — Similarity</h2>
|
||||
* <p>
|
||||
* Changing {@link org.apache.lucene.search.similarities.Similarity Similarity} is an easy way to
|
||||
* influence scoring, this is done at index-time with
|
||||
* {@link org.apache.lucene.index.IndexWriterConfig#setSimilarity(org.apache.lucene.search.similarities.Similarity)
|
||||
* IndexWriterConfig.setSimilarity(Similarity)} and at query-time with
|
||||
* {@link org.apache.lucene.search.IndexSearcher#setSimilarity(org.apache.lucene.search.similarities.Similarity)
|
||||
* IndexSearcher.setSimilarity(Similarity)}. Be sure to use the same
|
||||
* Similarity at query-time as at index-time (so that norms are
|
||||
* encoded/decoded correctly); Lucene makes no effort to verify this.
|
||||
* </p>
|
||||
* <p>
|
||||
* You can influence scoring by configuring a different built-in Similarity implementation, or by tweaking its
|
||||
* parameters, subclassing it to override behavior. Some implementations also offer a modular API which you can
|
||||
* extend by plugging in a different component (e.g. term frequency normalizer).
|
||||
* </p>
|
||||
* <p>
|
||||
* Finally, you can extend the low level {@link org.apache.lucene.search.similarities.Similarity Similarity} directly
|
||||
* to implement a new retrieval model, or to use external scoring factors particular to your application. For example,
|
||||
* a custom Similarity can access per-document values via {@link org.apache.lucene.index.NumericDocValues} and
|
||||
* integrate them into the score.
|
||||
* </p>
|
||||
* <p>
|
||||
* See the {@link org.apache.lucene.search.similarities} package documentation for information
|
||||
* on the built-in available scoring models and extending or changing Similarity.
|
||||
* </p>
|
||||
*
|
||||
*
|
||||
* <a name="customQueriesExpert"></a>
|
||||
* <h2>Custom Queries — Expert Level</h2>
|
||||
*
|
||||
* <p>Custom queries are an expert level task, so tread carefully and be prepared to share your code if
|
||||
* you want help.
|
||||
* </p>
|
||||
*
|
||||
* <p>With the warning out of the way, it is possible to change a lot more than just the Similarity
|
||||
* when it comes to matching and scoring in Lucene. Lucene's search is a complex mechanism that is grounded by
|
||||
* <span>three main classes</span>:
|
||||
* <ol>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Query Query} — The abstract object representation of the
|
||||
* user's information need.</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight Weight} — The internal interface representation of
|
||||
* the user's Query, so that Query objects may be reused.
|
||||
* This is global (across all segments of the index) and
|
||||
* generally will require global statistics (such as docFreq
|
||||
* for a given term across all segments).</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer Scorer} — An abstract class containing common
|
||||
* functionality for scoring. Provides both scoring and
|
||||
* explanation capabilities. This is created per-segment.</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.BulkScorer BulkScorer} — An abstract class that scores
|
||||
* a range of documents. A default implementation simply iterates through the hits from
|
||||
* {@link org.apache.lucene.search.Scorer Scorer}, but some queries such as
|
||||
* {@link org.apache.lucene.search.BooleanQuery BooleanQuery} have more efficient
|
||||
* implementations.</li>
|
||||
* </ol>
|
||||
* Details on each of these classes, and their children, can be found in the subsections below.
|
||||
* </p>
|
||||
* <h3>The Query Class</h3>
|
||||
* <p>In some sense, the
|
||||
* {@link org.apache.lucene.search.Query Query}
|
||||
* class is where it all begins. Without a Query, there would be
|
||||
* nothing to score. Furthermore, the Query class is the catalyst for the other scoring classes as it
|
||||
* is often responsible
|
||||
* for creating them or coordinating the functionality between them. The
|
||||
* {@link org.apache.lucene.search.Query Query} class has several methods that are important for
|
||||
* derived classes:
|
||||
* <ol>
|
||||
* <li>{@link org.apache.lucene.search.Query#createWeight(IndexSearcher,boolean) createWeight(IndexSearcher searcher,boolean)} — A
|
||||
* {@link org.apache.lucene.search.Weight Weight} is the internal representation of the
|
||||
* Query, so each Query implementation must
|
||||
* provide an implementation of Weight. See the subsection on <a
|
||||
* href="#weightClass">The Weight Interface</a> below for details on implementing the Weight
|
||||
* interface.</li>
|
||||
* <li>{@link org.apache.lucene.search.Query#rewrite(org.apache.lucene.index.IndexReader) rewrite(IndexReader reader)} — Rewrites queries into primitive queries. Primitive queries are:
|
||||
* {@link org.apache.lucene.search.TermQuery TermQuery},
|
||||
* {@link org.apache.lucene.search.BooleanQuery BooleanQuery}, <span
|
||||
* >and other queries that implement {@link org.apache.lucene.search.Query#createWeight(IndexSearcher,boolean) createWeight(IndexSearcher searcher,boolean)}</span></li>
|
||||
* </ol>
|
||||
* </p>
|
||||
* <a name="weightClass"></a>
|
||||
* <h3>The Weight Interface</h3>
|
||||
* <p>The
|
||||
* {@link org.apache.lucene.search.Weight Weight}
|
||||
* interface provides an internal representation of the Query so that it can be reused. Any
|
||||
* {@link org.apache.lucene.search.IndexSearcher IndexSearcher}
|
||||
* dependent state should be stored in the Weight implementation,
|
||||
* not in the Query class. The interface defines five methods that must be implemented:
|
||||
* <ol>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#getQuery getQuery()} — Pointer to the
|
||||
* Query that this Weight represents.</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#getValueForNormalization() getValueForNormalization()} —
|
||||
* A weight can return a floating point value to indicate its magnitude for query normalization. Typically
|
||||
* a weight such as TermWeight that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity}
|
||||
* will just defer to the Similarity's implementation:
|
||||
* {@link org.apache.lucene.search.similarities.Similarity.SimWeight#getValueForNormalization SimWeight#getValueForNormalization()}.
|
||||
* For example, with {@link org.apache.lucene.search.similarities.TFIDFSimilarity Lucene's classic vector-space formula}, this
|
||||
* is implemented as the sum of squared weights: <code>(idf * boost)<sup>2</sup></code></li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#normalize(float,float) normalize(float norm, float topLevelBoost)} —
|
||||
* Performs query normalization:
|
||||
* <ul>
|
||||
* <li><code>topLevelBoost</code>: A query-boost factor from any wrapping queries that should be multiplied into every
|
||||
* document's score. For example, a TermQuery that is wrapped within a BooleanQuery with a boost of <code>5</code> would
|
||||
* receive this value at this time. This allows the TermQuery (the leaf node in this case) to compute this up-front
|
||||
* a single time (e.g. by multiplying into the IDF), rather than for every document.</li>
|
||||
* <li><code>norm</code>: Passes in a a normalization factor which may
|
||||
* allow for comparing scores between queries.</li>
|
||||
* </ul>
|
||||
* Typically a weight such as TermWeight
|
||||
* that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity} will just defer to the Similarity's implementation:
|
||||
* {@link org.apache.lucene.search.similarities.Similarity.SimWeight#normalize SimWeight#normalize(float,float)}.</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#scorer scorer()} —
|
||||
* Construct a new {@link org.apache.lucene.search.Scorer Scorer} for this Weight. See <a href="#scorerClass">The Scorer Class</a>
|
||||
* below for help defining a Scorer. As the name implies, the Scorer is responsible for doing the actual scoring of documents
|
||||
* given the Query.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#bulkScorer bulkScorer()} —
|
||||
* Construct a new {@link org.apache.lucene.search.BulkScorer BulkScorer} for this Weight. See <a href="#bulkScorerClass">The BulkScorer Class</a>
|
||||
* below for help defining a BulkScorer. This is an optional method, and most queries do not implement it.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Weight#explain(org.apache.lucene.index.LeafReaderContext, int)
|
||||
* explain(LeafReaderContext context, int doc)} — Provide a means for explaining why a given document was
|
||||
* scored the way it was.
|
||||
* Typically a weight such as TermWeight
|
||||
* that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity} will make use of the Similarity's implementation:
|
||||
* {@link org.apache.lucene.search.similarities.Similarity.SimScorer#explain(int, Explanation) SimScorer#explain(int doc, Explanation freq)}.
|
||||
* </li>
|
||||
* </li>
|
||||
* </ol>
|
||||
* </p>
|
||||
* <a name="scorerClass"></a>
|
||||
* <h3>The Scorer Class</h3>
|
||||
* <p>The
|
||||
* {@link org.apache.lucene.search.Scorer Scorer}
|
||||
* abstract class provides common scoring functionality for all Scorer implementations and
|
||||
* is the heart of the Lucene scoring process. The Scorer defines the following abstract (some of them are not
|
||||
* yet abstract, but will be in future versions and should be considered as such now) methods which
|
||||
* must be implemented (some of them inherited from {@link org.apache.lucene.search.DocIdSetIterator DocIdSetIterator}):
|
||||
* <ol>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#nextDoc nextDoc()} — Advances to the next
|
||||
* document that matches this Query, returning true if and only if there is another document that matches.</li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#docID docID()} — Returns the id of the
|
||||
* {@link org.apache.lucene.document.Document Document} that contains the match.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#score score()} — Return the score of the
|
||||
* current document. This value can be determined in any appropriate way for an application. For instance, the
|
||||
* {@link org.apache.lucene.search.TermScorer TermScorer} simply defers to the configured Similarity:
|
||||
* {@link org.apache.lucene.search.similarities.Similarity.SimScorer#score(int, float) SimScorer.score(int doc, float freq)}.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#freq freq()} — Returns the number of matches
|
||||
* for the current document. This value can be determined in any appropriate way for an application. For instance, the
|
||||
* {@link org.apache.lucene.search.TermScorer TermScorer} simply defers to the term frequency from the inverted index:
|
||||
* {@link org.apache.lucene.index.DocsEnum#freq DocsEnum.freq()}.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#advance advance()} — Skip ahead in
|
||||
* the document matches to the document whose id is greater than
|
||||
* or equal to the passed in value. In many instances, advance can be
|
||||
* implemented more efficiently than simply looping through all the matching documents until
|
||||
* the target document is identified.
|
||||
* </li>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.Scorer#getChildren getChildren()} — Returns any child subscorers
|
||||
* underneath this scorer. This allows for users to navigate the scorer hierarchy and receive more fine-grained
|
||||
* details on the scoring process.
|
||||
* </li>
|
||||
* </ol>
|
||||
* </p>
|
||||
* <a name="bulkScorerClass"></a>
|
||||
* <h3>The BulkScorer Class</h3>
|
||||
* <p>The
|
||||
* {@link org.apache.lucene.search.BulkScorer BulkScorer} scores a range of documents. There is only one
|
||||
* abstract method:
|
||||
* <ol>
|
||||
* <li>
|
||||
* {@link org.apache.lucene.search.BulkScorer#score(org.apache.lucene.search.LeafCollector,int,int) score(LeafCollector,int,int)} —
|
||||
* Score all documents up to but not including the specified max document.
|
||||
* </li>
|
||||
* </ol>
|
||||
* </p>
|
||||
* <h3>Why would I want to add my own Query?</h3>
|
||||
*
|
||||
* <p>In a nutshell, you want to add your own custom Query implementation when you think that Lucene's
|
||||
* aren't appropriate for the
|
||||
* task that you want to do. You might be doing some cutting edge research or you need more information
|
||||
* back
|
||||
* out of Lucene (similar to Doug adding SpanQuery functionality).</p>
|
||||
*
|
||||
* <!-- TODO: integrate this better, it's better served as an intro than an appendix -->
|
||||
*
|
||||
*
|
||||
* <a name="algorithm"></a>
|
||||
* <h2>Appendix: Search Algorithm</h2>
|
||||
* <p>This section is mostly notes on stepping through the Scoring process and serves as
|
||||
* fertilizer for the earlier sections.</p>
|
||||
* <p>In the typical search application, a {@link org.apache.lucene.search.Query Query}
|
||||
* is passed to the {@link org.apache.lucene.search.IndexSearcher IndexSearcher},
|
||||
* beginning the scoring process.</p>
|
||||
* <p>Once inside the IndexSearcher, a {@link org.apache.lucene.search.Collector Collector}
|
||||
* is used for the scoring and sorting of the search results.
|
||||
* These important objects are involved in a search:
|
||||
* <ol>
|
||||
* <li>The {@link org.apache.lucene.search.Weight Weight} object of the Query. The
|
||||
* Weight object is an internal representation of the Query that allows the Query
|
||||
* to be reused by the IndexSearcher.</li>
|
||||
* <li>The IndexSearcher that initiated the call.</li>
|
||||
* <li>A {@link org.apache.lucene.search.Filter Filter} for limiting the result set.
|
||||
* Note, the Filter may be null.</li>
|
||||
* <li>A {@link org.apache.lucene.search.Sort Sort} object for specifying how to sort
|
||||
* the results if the standard score-based sort method is not desired.</li>
|
||||
* </ol>
|
||||
* </p>
|
||||
* <p>Assuming we are not sorting (since sorting doesn't affect the raw Lucene score),
|
||||
* we call one of the search methods of the IndexSearcher, passing in the
|
||||
* {@link org.apache.lucene.search.Weight Weight} object created by
|
||||
* {@link org.apache.lucene.search.IndexSearcher#createNormalizedWeight(org.apache.lucene.search.Query,boolean)
|
||||
* IndexSearcher.createNormalizedWeight(Query,boolean)},
|
||||
* {@link org.apache.lucene.search.Filter Filter} and the number of results we want.
|
||||
* This method returns a {@link org.apache.lucene.search.TopDocs TopDocs} object,
|
||||
* which is an internal collection of search results. The IndexSearcher creates
|
||||
* a {@link org.apache.lucene.search.TopScoreDocCollector TopScoreDocCollector} and
|
||||
* passes it along with the Weight, Filter to another expert search method (for
|
||||
* more on the {@link org.apache.lucene.search.Collector Collector} mechanism,
|
||||
* see {@link org.apache.lucene.search.IndexSearcher IndexSearcher}). The TopScoreDocCollector
|
||||
* uses a {@link org.apache.lucene.util.PriorityQueue PriorityQueue} to collect the
|
||||
* top results for the search.
|
||||
* </p>
|
||||
* <p>If a Filter is being used, some initial setup is done to determine which docs to include.
|
||||
* Otherwise, we ask the Weight for a {@link org.apache.lucene.search.Scorer Scorer} for each
|
||||
* {@link org.apache.lucene.index.IndexReader IndexReader} segment and proceed by calling
|
||||
* {@link org.apache.lucene.search.BulkScorer#score(org.apache.lucene.search.LeafCollector) BulkScorer.score(LeafCollector)}.
|
||||
* </p>
|
||||
* <p>At last, we are actually going to score some documents. The score method takes in the Collector
|
||||
* (most likely the TopScoreDocCollector or TopFieldCollector) and does its business.Of course, here
|
||||
* is where things get involved. The {@link org.apache.lucene.search.Scorer Scorer} that is returned
|
||||
* by the {@link org.apache.lucene.search.Weight Weight} object depends on what type of Query was
|
||||
* submitted. In most real world applications with multiple query terms, the
|
||||
* {@link org.apache.lucene.search.Scorer Scorer} is going to be a <code>BooleanScorer2</code> created
|
||||
* from {@link org.apache.lucene.search.BooleanWeight BooleanWeight} (see the section on
|
||||
* <a href="#customQueriesExpert">custom queries</a> for info on changing this).
|
||||
* </p>
|
||||
* <p>Assuming a BooleanScorer2, we first initialize the Coordinator, which is used to apply the coord()
|
||||
* factor. We then get a internal Scorer based on the required, optional and prohibited parts of the query.
|
||||
* Using this internal Scorer, the BooleanScorer2 then proceeds into a while loop based on the
|
||||
* {@link org.apache.lucene.search.Scorer#nextDoc Scorer.nextDoc()} method. The nextDoc() method advances
|
||||
* to the next document matching the query. This is an abstract method in the Scorer class and is thus
|
||||
* overridden by all derived implementations. If you have a simple OR query your internal Scorer is most
|
||||
* likely a DisjunctionSumScorer, which essentially combines the scorers from the sub scorers of the OR'd terms.</p>
|
||||
*/
|
||||
package org.apache.lucene.search;
|
||||
|
|
@ -1,583 +0,0 @@
|
|||
<!doctype html public "-//w3c//dtd html 4.0 transitional//en">
|
||||
<!--
|
||||
Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
contributor license agreements. See the NOTICE file distributed with
|
||||
this work for additional information regarding copyright ownership.
|
||||
The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
(the "License"); you may not use this file except in compliance with
|
||||
the License. You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
|
||||
</head>
|
||||
<body>
|
||||
Code to search indices.
|
||||
|
||||
<h2>Table Of Contents</h2>
|
||||
<p>
|
||||
<ol>
|
||||
<li><a href="#search">Search Basics</a></li>
|
||||
<li><a href="#query">The Query Classes</a></li>
|
||||
<li><a href="#scoring">Scoring: Introduction</a></li>
|
||||
<li><a href="#scoringBasics">Scoring: Basics</a></li>
|
||||
<li><a href="#changingScoring">Changing the Scoring</a></li>
|
||||
<li><a href="#algorithm">Appendix: Search Algorithm</a></li>
|
||||
</ol>
|
||||
</p>
|
||||
|
||||
|
||||
<a name="search"></a>
|
||||
<h2>Search Basics</h2>
|
||||
<p>
|
||||
Lucene offers a wide variety of {@link org.apache.lucene.search.Query} implementations, most of which are in
|
||||
this package, its subpackages ({@link org.apache.lucene.search.spans spans}, {@link org.apache.lucene.search.payloads payloads}),
|
||||
or the <a href="{@docRoot}/../queries/overview-summary.html">queries module</a>. These implementations can be combined in a wide
|
||||
variety of ways to provide complex querying capabilities along with information about where matches took place in the document
|
||||
collection. The <a href="#query">Query Classes</a> section below highlights some of the more important Query classes. For details
|
||||
on implementing your own Query class, see <a href="#customQueriesExpert">Custom Queries -- Expert Level</a> below.
|
||||
</p>
|
||||
<p>
|
||||
To perform a search, applications usually call {@link
|
||||
org.apache.lucene.search.IndexSearcher#search(Query,int)} or {@link
|
||||
org.apache.lucene.search.IndexSearcher#search(Query,Filter,int)}.
|
||||
</p>
|
||||
<p>
|
||||
Once a Query has been created and submitted to the {@link org.apache.lucene.search.IndexSearcher IndexSearcher}, the scoring
|
||||
process begins. After some infrastructure setup, control finally passes to the {@link org.apache.lucene.search.Weight Weight}
|
||||
implementation and its {@link org.apache.lucene.search.Scorer Scorer} or {@link org.apache.lucene.search.BulkScorer BulkScore}
|
||||
instances. See the <a href="#algorithm">Algorithm</a> section for more notes on the process.
|
||||
</p>
|
||||
<!-- FILL IN MORE HERE -->
|
||||
<!-- TODO: this page over-links the same things too many times -->
|
||||
</p>
|
||||
|
||||
|
||||
<a name="query"></a>
|
||||
<h2>Query Classes</h2>
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery}
|
||||
</h4>
|
||||
|
||||
<p>Of the various implementations of
|
||||
{@link org.apache.lucene.search.Query Query}, the
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery}
|
||||
is the easiest to understand and the most often used in applications. A
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery} matches all the documents that contain the
|
||||
specified
|
||||
{@link org.apache.lucene.index.Term Term},
|
||||
which is a word that occurs in a certain
|
||||
{@link org.apache.lucene.document.Field Field}.
|
||||
Thus, a {@link org.apache.lucene.search.TermQuery TermQuery} identifies and scores all
|
||||
{@link org.apache.lucene.document.Document Document}s that have a
|
||||
{@link org.apache.lucene.document.Field Field} with the specified string in it.
|
||||
Constructing a {@link org.apache.lucene.search.TermQuery TermQuery}
|
||||
is as simple as:
|
||||
<pre class="prettyprint">
|
||||
TermQuery tq = new TermQuery(new Term("fieldName", "term"));
|
||||
</pre>In this example, the {@link org.apache.lucene.search.Query Query} identifies all
|
||||
{@link org.apache.lucene.document.Document Document}s that have the
|
||||
{@link org.apache.lucene.document.Field Field} named <tt>"fieldName"</tt>
|
||||
containing the word <tt>"term"</tt>.
|
||||
</p>
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.BooleanQuery BooleanQuery}
|
||||
</h4>
|
||||
|
||||
<p>Things start to get interesting when one combines multiple
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery} instances into a
|
||||
{@link org.apache.lucene.search.BooleanQuery BooleanQuery}.
|
||||
A {@link org.apache.lucene.search.BooleanQuery BooleanQuery} contains multiple
|
||||
{@link org.apache.lucene.search.BooleanClause BooleanClause}s,
|
||||
where each clause contains a sub-query ({@link org.apache.lucene.search.Query Query}
|
||||
instance) and an operator (from
|
||||
{@link org.apache.lucene.search.BooleanClause.Occur BooleanClause.Occur})
|
||||
describing how that sub-query is combined with the other clauses:
|
||||
<ol>
|
||||
|
||||
<li><p>{@link org.apache.lucene.search.BooleanClause.Occur#SHOULD SHOULD} — Use this operator when a clause can occur in the result set, but is not required.
|
||||
If a query is made up of all SHOULD clauses, then every document in the result
|
||||
set matches at least one of these clauses.</p></li>
|
||||
|
||||
<li><p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST MUST} — Use this operator when a clause is required to occur in the result set. Every
|
||||
document in the result set will match
|
||||
all such clauses.</p></li>
|
||||
|
||||
<li><p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST_NOT MUST NOT} — Use this operator when a
|
||||
clause must not occur in the result set. No
|
||||
document in the result set will match
|
||||
any such clauses.</p></li>
|
||||
</ol>
|
||||
Boolean queries are constructed by adding two or more
|
||||
{@link org.apache.lucene.search.BooleanClause BooleanClause}
|
||||
instances. If too many clauses are added, a {@link org.apache.lucene.search.BooleanQuery.TooManyClauses TooManyClauses}
|
||||
exception will be thrown during searching. This most often occurs
|
||||
when a {@link org.apache.lucene.search.Query Query}
|
||||
is rewritten into a {@link org.apache.lucene.search.BooleanQuery BooleanQuery} with many
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery} clauses,
|
||||
for example by {@link org.apache.lucene.search.WildcardQuery WildcardQuery}.
|
||||
The default setting for the maximum number
|
||||
of clauses 1024, but this can be changed via the
|
||||
static method {@link org.apache.lucene.search.BooleanQuery#setMaxClauseCount(int)}.
|
||||
</p>
|
||||
|
||||
<h4>Phrases</h4>
|
||||
|
||||
<p>Another common search is to find documents containing certain phrases. This
|
||||
is handled three different ways:
|
||||
<ol>
|
||||
<li>
|
||||
<p>{@link org.apache.lucene.search.PhraseQuery PhraseQuery}
|
||||
— Matches a sequence of
|
||||
{@link org.apache.lucene.index.Term Term}s.
|
||||
{@link org.apache.lucene.search.PhraseQuery PhraseQuery} uses a slop factor to determine
|
||||
how many positions may occur between any two terms in the phrase and still be considered a match.
|
||||
The slop is 0 by default, meaning the phrase must match exactly.</p>
|
||||
</li>
|
||||
<li>
|
||||
<p>{@link org.apache.lucene.search.MultiPhraseQuery MultiPhraseQuery}
|
||||
— A more general form of PhraseQuery that accepts multiple Terms
|
||||
for a position in the phrase. For example, this can be used to perform phrase queries that also
|
||||
incorporate synonyms.
|
||||
</li>
|
||||
<li>
|
||||
<p>{@link org.apache.lucene.search.spans.SpanNearQuery SpanNearQuery}
|
||||
— Matches a sequence of other
|
||||
{@link org.apache.lucene.search.spans.SpanQuery SpanQuery}
|
||||
instances. {@link org.apache.lucene.search.spans.SpanNearQuery SpanNearQuery} allows for
|
||||
much more
|
||||
complicated phrase queries since it is constructed from other
|
||||
{@link org.apache.lucene.search.spans.SpanQuery SpanQuery}
|
||||
instances, instead of only {@link org.apache.lucene.search.TermQuery TermQuery}
|
||||
instances.</p>
|
||||
</li>
|
||||
</ol>
|
||||
</p>
|
||||
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.TermRangeQuery TermRangeQuery}
|
||||
</h4>
|
||||
|
||||
<p>The
|
||||
{@link org.apache.lucene.search.TermRangeQuery TermRangeQuery}
|
||||
matches all documents that occur in the
|
||||
exclusive range of a lower
|
||||
{@link org.apache.lucene.index.Term Term}
|
||||
and an upper
|
||||
{@link org.apache.lucene.index.Term Term}
|
||||
according to {@link org.apache.lucene.util.BytesRef#compareTo BytesRef.compareTo()}. It is not intended
|
||||
for numerical ranges; use {@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery} instead.
|
||||
|
||||
For example, one could find all documents
|
||||
that have terms beginning with the letters <tt>a</tt> through <tt>c</tt>.
|
||||
</p>
|
||||
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery}
|
||||
</h4>
|
||||
|
||||
<p>The
|
||||
{@link org.apache.lucene.search.NumericRangeQuery NumericRangeQuery}
|
||||
matches all documents that occur in a numeric range.
|
||||
For NumericRangeQuery to work, you must index the values
|
||||
using a one of the numeric fields ({@link org.apache.lucene.document.IntField IntField},
|
||||
{@link org.apache.lucene.document.LongField LongField}, {@link org.apache.lucene.document.FloatField FloatField},
|
||||
or {@link org.apache.lucene.document.DoubleField DoubleField}).
|
||||
</p>
|
||||
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.PrefixQuery PrefixQuery},
|
||||
{@link org.apache.lucene.search.WildcardQuery WildcardQuery},
|
||||
{@link org.apache.lucene.search.RegexpQuery RegexpQuery}
|
||||
</h4>
|
||||
|
||||
<p>While the
|
||||
{@link org.apache.lucene.search.PrefixQuery PrefixQuery}
|
||||
has a different implementation, it is essentially a special case of the
|
||||
{@link org.apache.lucene.search.WildcardQuery WildcardQuery}.
|
||||
The {@link org.apache.lucene.search.PrefixQuery PrefixQuery} allows an application
|
||||
to identify all documents with terms that begin with a certain string. The
|
||||
{@link org.apache.lucene.search.WildcardQuery WildcardQuery} generalizes this by allowing
|
||||
for the use of <tt>*</tt> (matches 0 or more characters) and <tt>?</tt> (matches exactly one character) wildcards.
|
||||
Note that the {@link org.apache.lucene.search.WildcardQuery WildcardQuery} can be quite slow. Also
|
||||
note that
|
||||
{@link org.apache.lucene.search.WildcardQuery WildcardQuery} should
|
||||
not start with <tt>*</tt> and <tt>?</tt>, as these are extremely slow.
|
||||
Some QueryParsers may not allow this by default, but provide a <code>setAllowLeadingWildcard</code> method
|
||||
to remove that protection.
|
||||
The {@link org.apache.lucene.search.RegexpQuery RegexpQuery} is even more general than WildcardQuery,
|
||||
allowing an application to identify all documents with terms that match a regular expression pattern.
|
||||
</p>
|
||||
<h4>
|
||||
{@link org.apache.lucene.search.FuzzyQuery FuzzyQuery}
|
||||
</h4>
|
||||
|
||||
<p>A
|
||||
{@link org.apache.lucene.search.FuzzyQuery FuzzyQuery}
|
||||
matches documents that contain terms similar to the specified term. Similarity is
|
||||
determined using
|
||||
<a href="http://en.wikipedia.org/wiki/Levenshtein">Levenshtein (edit) distance</a>.
|
||||
This type of query can be useful when accounting for spelling variations in the collection.
|
||||
</p>
|
||||
|
||||
|
||||
<a name="scoring"></a>
|
||||
<h2>Scoring — Introduction</h2>
|
||||
<p>Lucene scoring is the heart of why we all love Lucene. It is blazingly fast and it hides
|
||||
almost all of the complexity from the user. In a nutshell, it works. At least, that is,
|
||||
until it doesn't work, or doesn't work as one would expect it to work. Then we are left
|
||||
digging into Lucene internals or asking for help on
|
||||
<a href="mailto:java-user@lucene.apache.org">java-user@lucene.apache.org</a> to figure out
|
||||
why a document with five of our query terms scores lower than a different document with
|
||||
only one of the query terms.
|
||||
</p>
|
||||
<p>While this document won't answer your specific scoring issues, it will, hopefully, point you
|
||||
to the places that can help you figure out the <i>what</i> and <i>why</i> of Lucene scoring.
|
||||
</p>
|
||||
<p>Lucene scoring supports a number of pluggable information retrieval
|
||||
<a href="http://en.wikipedia.org/wiki/Information_retrieval#Model_types">models</a>, including:
|
||||
<ul>
|
||||
<li><a href="http://en.wikipedia.org/wiki/Vector_Space_Model">Vector Space Model (VSM)</a></li>
|
||||
<li><a href="http://en.wikipedia.org/wiki/Probabilistic_relevance_model">Probablistic Models</a> such as
|
||||
<a href="http://en.wikipedia.org/wiki/Probabilistic_relevance_model_(BM25)">Okapi BM25</a> and
|
||||
<a href="http://en.wikipedia.org/wiki/Divergence-from-randomness_model">DFR</a></li>
|
||||
<li><a href="http://en.wikipedia.org/wiki/Language_model">Language models</a></li>
|
||||
</ul>
|
||||
These models can be plugged in via the {@link org.apache.lucene.search.similarities Similarity API},
|
||||
and offer extension hooks and parameters for tuning. In general, Lucene first finds the documents
|
||||
that need to be scored based on boolean logic in the Query specification, and then ranks this subset of
|
||||
matching documents via the retrieval model. For some valuable references on VSM and IR in general refer to
|
||||
<a href="http://wiki.apache.org/lucene-java/InformationRetrieval">Lucene Wiki IR references</a>.
|
||||
</p>
|
||||
<p>The rest of this document will cover <a href="#scoringBasics">Scoring basics</a> and explain how to
|
||||
change your {@link org.apache.lucene.search.similarities.Similarity Similarity}. Next, it will cover
|
||||
ways you can customize the lucene internals in
|
||||
<a href="#customQueriesExpert">Custom Queries -- Expert Level</a>, which gives details on
|
||||
implementing your own {@link org.apache.lucene.search.Query Query} class and related functionality.
|
||||
Finally, we will finish up with some reference material in the <a href="#algorithm">Appendix</a>.
|
||||
</p>
|
||||
|
||||
|
||||
<a name="scoringBasics"></a>
|
||||
<h2>Scoring — Basics</h2>
|
||||
<p>Scoring is very much dependent on the way documents are indexed, so it is important to understand
|
||||
indexing. (see <a href="{@docRoot}/overview-summary.html#overview_description">Lucene overview</a>
|
||||
before continuing on with this section) Be sure to use the useful
|
||||
{@link org.apache.lucene.search.IndexSearcher#explain(org.apache.lucene.search.Query, int) IndexSearcher.explain(Query, doc)}
|
||||
to understand how the score for a certain matching document was
|
||||
computed.
|
||||
|
||||
<p>Generally, the Query determines which documents match (a binary
|
||||
decision), while the Similarity determines how to assign scores to
|
||||
the matching documents.
|
||||
|
||||
</p>
|
||||
<h4>Fields and Documents</h4>
|
||||
<p>In Lucene, the objects we are scoring are {@link org.apache.lucene.document.Document Document}s.
|
||||
A Document is a collection of {@link org.apache.lucene.document.Field Field}s. Each Field has
|
||||
{@link org.apache.lucene.document.FieldType semantics} about how it is created and stored
|
||||
({@link org.apache.lucene.document.FieldType#tokenized() tokenized},
|
||||
{@link org.apache.lucene.document.FieldType#stored() stored}, etc). It is important to note that
|
||||
Lucene scoring works on Fields and then combines the results to return Documents. This is
|
||||
important because two Documents with the exact same content, but one having the content in two
|
||||
Fields and the other in one Field may return different scores for the same query due to length
|
||||
normalization.
|
||||
</p>
|
||||
<h4>Score Boosting</h4>
|
||||
<p>Lucene allows influencing search results by "boosting" at different times:
|
||||
<ul>
|
||||
<li><b>Index-time boost</b> by calling
|
||||
{@link org.apache.lucene.document.Field#setBoost(float) Field.setBoost()} before a document is
|
||||
added to the index.</li>
|
||||
<li><b>Query-time boost</b> by setting a boost on a query clause, calling
|
||||
{@link org.apache.lucene.search.Query#setBoost(float) Query.setBoost()}.</li>
|
||||
</ul>
|
||||
</p>
|
||||
<p>Indexing time boosts are pre-processed for storage efficiency and written to
|
||||
storage for a field as follows:
|
||||
<ul>
|
||||
<li>All boosts of that field (i.e. all boosts under the same field name in that doc) are
|
||||
multiplied.</li>
|
||||
<li>The boost is then encoded into a normalization value by the Similarity
|
||||
object at index-time: {@link org.apache.lucene.search.similarities.Similarity#computeNorm computeNorm()}.
|
||||
The actual encoding depends upon the Similarity implementation, but note that most
|
||||
use a lossy encoding (such as multiplying the boost with document length or similar, packed
|
||||
into a single byte!).</li>
|
||||
<li>Decoding of any index-time normalization values and integration into the document's score is also performed
|
||||
at search time by the Similarity.</li>
|
||||
</ul>
|
||||
</p>
|
||||
|
||||
|
||||
<a name="changingScoring"></a>
|
||||
<h2>Changing Scoring — Similarity</h2>
|
||||
<p>
|
||||
Changing {@link org.apache.lucene.search.similarities.Similarity Similarity} is an easy way to
|
||||
influence scoring, this is done at index-time with
|
||||
{@link org.apache.lucene.index.IndexWriterConfig#setSimilarity(org.apache.lucene.search.similarities.Similarity)
|
||||
IndexWriterConfig.setSimilarity(Similarity)} and at query-time with
|
||||
{@link org.apache.lucene.search.IndexSearcher#setSimilarity(org.apache.lucene.search.similarities.Similarity)
|
||||
IndexSearcher.setSimilarity(Similarity)}. Be sure to use the same
|
||||
Similarity at query-time as at index-time (so that norms are
|
||||
encoded/decoded correctly); Lucene makes no effort to verify this.
|
||||
</p>
|
||||
<p>
|
||||
You can influence scoring by configuring a different built-in Similarity implementation, or by tweaking its
|
||||
parameters, subclassing it to override behavior. Some implementations also offer a modular API which you can
|
||||
extend by plugging in a different component (e.g. term frequency normalizer).
|
||||
</p>
|
||||
<p>
|
||||
Finally, you can extend the low level {@link org.apache.lucene.search.similarities.Similarity Similarity} directly
|
||||
to implement a new retrieval model, or to use external scoring factors particular to your application. For example,
|
||||
a custom Similarity can access per-document values via {@link org.apache.lucene.index.NumericDocValues} and
|
||||
integrate them into the score.
|
||||
</p>
|
||||
<p>
|
||||
See the {@link org.apache.lucene.search.similarities} package documentation for information
|
||||
on the built-in available scoring models and extending or changing Similarity.
|
||||
</p>
|
||||
|
||||
|
||||
<a name="customQueriesExpert"></a>
|
||||
<h2>Custom Queries — Expert Level</h2>
|
||||
|
||||
<p>Custom queries are an expert level task, so tread carefully and be prepared to share your code if
|
||||
you want help.
|
||||
</p>
|
||||
|
||||
<p>With the warning out of the way, it is possible to change a lot more than just the Similarity
|
||||
when it comes to matching and scoring in Lucene. Lucene's search is a complex mechanism that is grounded by
|
||||
<span>three main classes</span>:
|
||||
<ol>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Query Query} — The abstract object representation of the
|
||||
user's information need.</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight Weight} — The internal interface representation of
|
||||
the user's Query, so that Query objects may be reused.
|
||||
This is global (across all segments of the index) and
|
||||
generally will require global statistics (such as docFreq
|
||||
for a given term across all segments).</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer Scorer} — An abstract class containing common
|
||||
functionality for scoring. Provides both scoring and
|
||||
explanation capabilities. This is created per-segment.</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.BulkScorer BulkScorer} — An abstract class that scores
|
||||
a range of documents. A default implementation simply iterates through the hits from
|
||||
{@link org.apache.lucene.search.Scorer Scorer}, but some queries such as
|
||||
{@link org.apache.lucene.search.BooleanQuery BooleanQuery} have more efficient
|
||||
implementations.</li>
|
||||
</ol>
|
||||
Details on each of these classes, and their children, can be found in the subsections below.
|
||||
</p>
|
||||
<h4>The Query Class</h4>
|
||||
<p>In some sense, the
|
||||
{@link org.apache.lucene.search.Query Query}
|
||||
class is where it all begins. Without a Query, there would be
|
||||
nothing to score. Furthermore, the Query class is the catalyst for the other scoring classes as it
|
||||
is often responsible
|
||||
for creating them or coordinating the functionality between them. The
|
||||
{@link org.apache.lucene.search.Query Query} class has several methods that are important for
|
||||
derived classes:
|
||||
<ol>
|
||||
<li>{@link org.apache.lucene.search.Query#createWeight(IndexSearcher,boolean) createWeight(IndexSearcher searcher,boolean)} — A
|
||||
{@link org.apache.lucene.search.Weight Weight} is the internal representation of the
|
||||
Query, so each Query implementation must
|
||||
provide an implementation of Weight. See the subsection on <a
|
||||
href="#weightClass">The Weight Interface</a> below for details on implementing the Weight
|
||||
interface.</li>
|
||||
<li>{@link org.apache.lucene.search.Query#rewrite(IndexReader) rewrite(IndexReader reader)} — Rewrites queries into primitive queries. Primitive queries are:
|
||||
{@link org.apache.lucene.search.TermQuery TermQuery},
|
||||
{@link org.apache.lucene.search.BooleanQuery BooleanQuery}, <span
|
||||
>and other queries that implement {@link org.apache.lucene.search.Query#createWeight(IndexSearcher,boolean) createWeight(IndexSearcher searcher,boolean)}</span></li>
|
||||
</ol>
|
||||
</p>
|
||||
<a name="weightClass"></a>
|
||||
<h4>The Weight Interface</h4>
|
||||
<p>The
|
||||
{@link org.apache.lucene.search.Weight Weight}
|
||||
interface provides an internal representation of the Query so that it can be reused. Any
|
||||
{@link org.apache.lucene.search.IndexSearcher IndexSearcher}
|
||||
dependent state should be stored in the Weight implementation,
|
||||
not in the Query class. The interface defines five methods that must be implemented:
|
||||
<ol>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#getQuery getQuery()} — Pointer to the
|
||||
Query that this Weight represents.</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#getValueForNormalization() getValueForNormalization()} —
|
||||
A weight can return a floating point value to indicate its magnitude for query normalization. Typically
|
||||
a weight such as TermWeight that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity}
|
||||
will just defer to the Similarity's implementation:
|
||||
{@link org.apache.lucene.search.similarities.Similarity.SimWeight#getValueForNormalization SimWeight#getValueForNormalization()}.
|
||||
For example, with {@link org.apache.lucene.search.similarities.TFIDFSimilarity Lucene's classic vector-space formula}, this
|
||||
is implemented as the sum of squared weights: <code>(idf * boost)<sup>2</sup></code></li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#normalize(float,float) normalize(float norm, float topLevelBoost)} —
|
||||
Performs query normalization:
|
||||
<ul>
|
||||
<li><code>topLevelBoost</code>: A query-boost factor from any wrapping queries that should be multiplied into every
|
||||
document's score. For example, a TermQuery that is wrapped within a BooleanQuery with a boost of <code>5</code> would
|
||||
receive this value at this time. This allows the TermQuery (the leaf node in this case) to compute this up-front
|
||||
a single time (e.g. by multiplying into the IDF), rather than for every document.</li>
|
||||
<li><code>norm</code>: Passes in a a normalization factor which may
|
||||
allow for comparing scores between queries.</li>
|
||||
</ul>
|
||||
Typically a weight such as TermWeight
|
||||
that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity} will just defer to the Similarity's implementation:
|
||||
{@link org.apache.lucene.search.similarities.Similarity.SimWeight#normalize SimWeight#normalize(float,float)}.</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#scorer scorer()} —
|
||||
Construct a new {@link org.apache.lucene.search.Scorer Scorer} for this Weight. See <a href="#scorerClass">The Scorer Class</a>
|
||||
below for help defining a Scorer. As the name implies, the Scorer is responsible for doing the actual scoring of documents
|
||||
given the Query.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#bulkScorer bulkScorer()} —
|
||||
Construct a new {@link org.apache.lucene.search.BulkScorer BulkScorer} for this Weight. See <a href="#bulkScorerClass">The BulkScorer Class</a>
|
||||
below for help defining a BulkScorer. This is an optional method, and most queries do not implement it.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Weight#explain(org.apache.lucene.index.LeafReaderContext, int)
|
||||
explain(LeafReaderContext context, int doc)} — Provide a means for explaining why a given document was
|
||||
scored the way it was.
|
||||
Typically a weight such as TermWeight
|
||||
that scores via a {@link org.apache.lucene.search.similarities.Similarity Similarity} will make use of the Similarity's implementation:
|
||||
{@link org.apache.lucene.search.similarities.Similarity.SimScorer#explain(int, Explanation) SimScorer#explain(int doc, Explanation freq)}.
|
||||
</li>
|
||||
</li>
|
||||
</ol>
|
||||
</p>
|
||||
<a name="scorerClass"></a>
|
||||
<h4>The Scorer Class</h4>
|
||||
<p>The
|
||||
{@link org.apache.lucene.search.Scorer Scorer}
|
||||
abstract class provides common scoring functionality for all Scorer implementations and
|
||||
is the heart of the Lucene scoring process. The Scorer defines the following abstract (some of them are not
|
||||
yet abstract, but will be in future versions and should be considered as such now) methods which
|
||||
must be implemented (some of them inherited from {@link org.apache.lucene.search.DocIdSetIterator DocIdSetIterator}):
|
||||
<ol>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#nextDoc nextDoc()} — Advances to the next
|
||||
document that matches this Query, returning true if and only if there is another document that matches.</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#docID docID()} — Returns the id of the
|
||||
{@link org.apache.lucene.document.Document Document} that contains the match.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#score score()} — Return the score of the
|
||||
current document. This value can be determined in any appropriate way for an application. For instance, the
|
||||
{@link org.apache.lucene.search.TermScorer TermScorer} simply defers to the configured Similarity:
|
||||
{@link org.apache.lucene.search.similarities.Similarity.SimScorer#score(int, float) SimScorer.score(int doc, float freq)}.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#freq freq()} — Returns the number of matches
|
||||
for the current document. This value can be determined in any appropriate way for an application. For instance, the
|
||||
{@link org.apache.lucene.search.TermScorer TermScorer} simply defers to the term frequency from the inverted index:
|
||||
{@link org.apache.lucene.index.DocsEnum#freq DocsEnum.freq()}.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#advance advance()} — Skip ahead in
|
||||
the document matches to the document whose id is greater than
|
||||
or equal to the passed in value. In many instances, advance can be
|
||||
implemented more efficiently than simply looping through all the matching documents until
|
||||
the target document is identified.
|
||||
</li>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.Scorer#getChildren getChildren()} — Returns any child subscorers
|
||||
underneath this scorer. This allows for users to navigate the scorer hierarchy and receive more fine-grained
|
||||
details on the scoring process.
|
||||
</li>
|
||||
</ol>
|
||||
</p>
|
||||
<a name="bulkScorerClass"></a>
|
||||
<h4>The BulkScorer Class</h4>
|
||||
<p>The
|
||||
{@link org.apache.lucene.search.BulkScorer BulkScorer} scores a range of documents. There is only one
|
||||
abstract method:
|
||||
<ol>
|
||||
<li>
|
||||
{@link org.apache.lucene.search.BulkScorer#score(org.apache.lucene.search.LeafCollector,int,int) score(LeafCollector,int,int)} —
|
||||
Score all documents up to but not including the specified max document.
|
||||
</li>
|
||||
</ol>
|
||||
</p>
|
||||
<h4>Why would I want to add my own Query?</h4>
|
||||
|
||||
<p>In a nutshell, you want to add your own custom Query implementation when you think that Lucene's
|
||||
aren't appropriate for the
|
||||
task that you want to do. You might be doing some cutting edge research or you need more information
|
||||
back
|
||||
out of Lucene (similar to Doug adding SpanQuery functionality).</p>
|
||||
|
||||
<!-- TODO: integrate this better, it's better served as an intro than an appendix -->
|
||||
|
||||
|
||||
<a name="algorithm"></a>
|
||||
<h2>Appendix: Search Algorithm</h2>
|
||||
<p>This section is mostly notes on stepping through the Scoring process and serves as
|
||||
fertilizer for the earlier sections.</p>
|
||||
<p>In the typical search application, a {@link org.apache.lucene.search.Query Query}
|
||||
is passed to the {@link org.apache.lucene.search.IndexSearcher IndexSearcher},
|
||||
beginning the scoring process.</p>
|
||||
<p>Once inside the IndexSearcher, a {@link org.apache.lucene.search.Collector Collector}
|
||||
is used for the scoring and sorting of the search results.
|
||||
These important objects are involved in a search:
|
||||
<ol>
|
||||
<li>The {@link org.apache.lucene.search.Weight Weight} object of the Query. The
|
||||
Weight object is an internal representation of the Query that allows the Query
|
||||
to be reused by the IndexSearcher.</li>
|
||||
<li>The IndexSearcher that initiated the call.</li>
|
||||
<li>A {@link org.apache.lucene.search.Filter Filter} for limiting the result set.
|
||||
Note, the Filter may be null.</li>
|
||||
<li>A {@link org.apache.lucene.search.Sort Sort} object for specifying how to sort
|
||||
the results if the standard score-based sort method is not desired.</li>
|
||||
</ol>
|
||||
</p>
|
||||
<p>Assuming we are not sorting (since sorting doesn't affect the raw Lucene score),
|
||||
we call one of the search methods of the IndexSearcher, passing in the
|
||||
{@link org.apache.lucene.search.Weight Weight} object created by
|
||||
{@link org.apache.lucene.search.IndexSearcher#createNormalizedWeight(org.apache.lucene.search.Query,boolean)
|
||||
IndexSearcher.createNormalizedWeight(Query,boolean)},
|
||||
{@link org.apache.lucene.search.Filter Filter} and the number of results we want.
|
||||
This method returns a {@link org.apache.lucene.search.TopDocs TopDocs} object,
|
||||
which is an internal collection of search results. The IndexSearcher creates
|
||||
a {@link org.apache.lucene.search.TopScoreDocCollector TopScoreDocCollector} and
|
||||
passes it along with the Weight, Filter to another expert search method (for
|
||||
more on the {@link org.apache.lucene.search.Collector Collector} mechanism,
|
||||
see {@link org.apache.lucene.search.IndexSearcher IndexSearcher}). The TopScoreDocCollector
|
||||
uses a {@link org.apache.lucene.util.PriorityQueue PriorityQueue} to collect the
|
||||
top results for the search.
|
||||
</p>
|
||||
<p>If a Filter is being used, some initial setup is done to determine which docs to include.
|
||||
Otherwise, we ask the Weight for a {@link org.apache.lucene.search.Scorer Scorer} for each
|
||||
{@link org.apache.lucene.index.IndexReader IndexReader} segment and proceed by calling
|
||||
{@link org.apache.lucene.search.BulkScorer#score(org.apache.lucene.search.LeafCollector) BulkScorer.score(LeafCollector)}.
|
||||
</p>
|
||||
<p>At last, we are actually going to score some documents. The score method takes in the Collector
|
||||
(most likely the TopScoreDocCollector or TopFieldCollector) and does its business.Of course, here
|
||||
is where things get involved. The {@link org.apache.lucene.search.Scorer Scorer} that is returned
|
||||
by the {@link org.apache.lucene.search.Weight Weight} object depends on what type of Query was
|
||||
submitted. In most real world applications with multiple query terms, the
|
||||
{@link org.apache.lucene.search.Scorer Scorer} is going to be a <code>BooleanScorer2</code> created
|
||||
from {@link org.apache.lucene.search.BooleanWeight BooleanWeight} (see the section on
|
||||
<a href="#customQueriesExpert">custom queries</a> for info on changing this).
|
||||
</p>
|
||||
<p>Assuming a BooleanScorer2, we first initialize the Coordinator, which is used to apply the coord()
|
||||
factor. We then get a internal Scorer based on the required, optional and prohibited parts of the query.
|
||||
Using this internal Scorer, the BooleanScorer2 then proceeds into a while loop based on the
|
||||
{@link org.apache.lucene.search.Scorer#nextDoc Scorer.nextDoc()} method. The nextDoc() method advances
|
||||
to the next document matching the query. This is an abstract method in the Scorer class and is thus
|
||||
overridden by all derived implementations. If you have a simple OR query your internal Scorer is most
|
||||
likely a DisjunctionSumScorer, which essentially combines the scorers from the sub scorers of the OR'd terms.</p>
|
||||
</body>
|
||||
</html>
|
||||
Loading…
Reference in New Issue