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* http://www.apache.org/licenses/LICENSE-2.0
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/**
* Code to search indices.
*
* <h2>Table Of Contents</h2>
*
* <ol>
* <li><a href="#search">Search Basics</a>
* <li><a href="#query">The Query Classes</a>
* <li><a href="#scoring">Scoring: Introduction</a>
* <li><a href="#scoringBasics">Scoring: Basics</a>
* <li><a href="#changingScoring">Changing the Scoring</a>
* <li><a href="#algorithm">Appendix: Search Algorithm</a>
* </ol>
*
* <a id="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 subpackage ({@link org.apache.lucene.search.spans spans}), 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>To perform a search, applications usually call {@link
* org.apache.lucene.search.IndexSearcher#search(Query,int)}.
*
* <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 BulkScorer} instances. See the <a
* href="#algorithm">Algorithm</a> section for more notes on the process.
* <!-- FILL IN MORE HERE -->
* <!-- TODO: this page over-links the same things too many times -->
* <a id="query"></a>
*
* <h2>Query Classes</h2>
*
* <h3>{@link org.apache.lucene.search.TermQuery TermQuery} </h3>
*
* <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 <code>"fieldName"</code> containing the word <code>
* "term"</code>.
*
* <h3>{@link org.apache.lucene.search.BooleanQuery BooleanQuery} </h3>
*
* <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} &mdash; 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.
* <li>
* <p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST MUST} &mdash; Use this operator
* when a clause is required to occur in the result set and should contribute to the score.
* Every document in the result set will match all such clauses.
* <li>
* <p>{@link org.apache.lucene.search.BooleanClause.Occur#FILTER FILTER} &mdash; Use this
* operator when a clause is required to occur in the result set but should not contribute to
* the score. Every document in the result set will match all such clauses.
* <li>
* <p>{@link org.apache.lucene.search.BooleanClause.Occur#MUST_NOT MUST NOT} &mdash; Use this
* operator when a clause must not occur in the result set. No document in the result set will
* match any such clauses.
* </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.IndexSearcher.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 is 1024, but this can be changed via the static method {@link
* org.apache.lucene.search.IndexSearcher#setMaxClauseCount(int)}.
*
* <h3>Phrases</h3>
*
* <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} &mdash; 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.
* <li>
* <p>{@link org.apache.lucene.search.MultiPhraseQuery MultiPhraseQuery} &mdash; 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>
* <p>{@link org.apache.lucene.search.spans.SpanNearQuery SpanNearQuery} &mdash; 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.
* </ol>
*
* <h3>{@link org.apache.lucene.search.PointRangeQuery PointRangeQuery} </h3>
*
* <p>The {@link org.apache.lucene.search.PointRangeQuery PointRangeQuery} matches all documents
* that occur in a numeric range. For PointRangeQuery to work, you must index the values using a one
* of the numeric fields ({@link org.apache.lucene.document.IntPoint IntPoint}, {@link
* org.apache.lucene.document.LongPoint LongPoint}, {@link org.apache.lucene.document.FloatPoint
* FloatPoint}, or {@link org.apache.lucene.document.DoublePoint DoublePoint}).
*
* <h3>{@link org.apache.lucene.search.PrefixQuery PrefixQuery}, {@link
* org.apache.lucene.search.WildcardQuery WildcardQuery}, {@link
* org.apache.lucene.search.RegexpQuery RegexpQuery} </h3>
*
* <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 <code>*</code> (matches 0 or more
* characters) and <code>?</code> (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 <code>*</code> and
* <code>?</code>, 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.
*
* <h3>{@link org.apache.lucene.search.FuzzyQuery FuzzyQuery} </h3>
*
* <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_distance">Levenshtein distance</a>. This type of
* query can be useful when accounting for spelling variations in the collection.
*
* <p><a id="scoring"></a>
*
* <h2>Scoring &mdash; 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 <code>java-user@lucene.apache.org</code> 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>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>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><a href="http://en.wikipedia.org/wiki/Probabilistic_relevance_model">Probabilistic
* 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><a href="http://en.wikipedia.org/wiki/Language_model">Language models</a>
* </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>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 id="scoringBasics"></a>
*
* <h2>Scoring &mdash; 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.
*
* <h3>Fields and Documents</h3>
*
* <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.
*
* <h3>Score Boosting</h3>
*
* <p>Lucene allows influencing the score contribution of various parts of the query by wrapping
* with {@link org.apache.lucene.search.BoostQuery}. <a id="changingScoring"></a>
*
* <h2>Changing Scoring &mdash; Similarity</h2>
*
* <h3>Changing the scoring formula</h3>
*
* <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>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>Finally, you can extend the low level {@link org.apache.lucene.search.similarities.Similarity
* Similarity} directly to implement a new retrieval model.
*
* <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.
*
* <h3>Integrating field values into the score</h3>
*
* <p>While similarities help score a document relatively to a query, it is also common for
* documents to hold features that measure the quality of a match. Such features are best integrated
* into the score by indexing a {@link org.apache.lucene.document.FeatureField FeatureField} with
* the document at index-time, and then combining the similarity score and the feature score using a
* linear combination. For instance the below query matches the same documents as {@code
* originalQuery} and computes scores as {@code similarityScore + 0.7 * featureScore}:
*
* <pre class="prettyprint">
* Query originalQuery = new BooleanQuery.Builder()
* .add(new TermQuery(new Term("body", "apache")), Occur.SHOULD)
* .add(new TermQuery(new Term("body", "lucene")), Occur.SHOULD)
* .build();
* Query featureQuery = FeatureField.newSaturationQuery("features", "pagerank");
* Query query = new BooleanQuery.Builder()
* .add(originalQuery, Occur.MUST)
* .add(new BoostQuery(featureQuery, 0.7f), Occur.SHOULD)
* .build();
* </pre>
*
* <p>A less efficient yet more flexible way of modifying scores is to index scoring features into
* doc-value fields and then combine them with the similarity score using a <a
* href="{@docRoot}/../queries/org/apache/lucene/queries/function/FunctionScoreQuery.html">FunctionScoreQuery</a>
* from the <a href="{@docRoot}/../queries/overview-summary.html">queries module</a>. For instance
* the below example shows how to compute scores as {@code similarityScore * Math.log(popularity)}
* using the <a href="{@docRoot}/../expressions/overview-summary.html">expressions module</a> and
* assuming that values for the {@code popularity} field have been set in a {@link
* org.apache.lucene.document.NumericDocValuesField NumericDocValuesField} at index time:
*
* <pre class="prettyprint">
* // compile an expression:
* Expression expr = JavascriptCompiler.compile("_score * ln(popularity)");
*
* // SimpleBindings just maps variables to SortField instances
* SimpleBindings bindings = new SimpleBindings();
* bindings.add(new SortField("_score", SortField.Type.SCORE));
* bindings.add(new SortField("popularity", SortField.Type.INT));
*
* // create a query that matches based on 'originalQuery' but
* // scores using expr
* Query query = new FunctionScoreQuery(
* originalQuery,
* expr.getDoubleValuesSource(bindings));
* </pre>
*
* <a id="customQueriesExpert"></a>
*
* <h2>Custom Queries &mdash; 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>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} &mdash; The abstract object representation of
* the user's information need.
* <li>{@link org.apache.lucene.search.Weight Weight} &mdash; A specialization of a Query for a
* given index. This typically associates a Query object with index statistics that are later
* used to compute document scores.
* <li>{@link org.apache.lucene.search.Scorer Scorer} &mdash; The core class of the scoring
* process: for a given segment, scorers return {@link
* org.apache.lucene.search.Scorer#iterator iterators} over matches and give a way to compute
* the {@link org.apache.lucene.search.Scorer#score score} of these matches.
* <li>{@link org.apache.lucene.search.BulkScorer BulkScorer} &mdash; 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.
* </ol>
*
* Details on each of these classes, and their children, can be found in the subsections below.
*
* <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,ScoreMode,float)
* createWeight(IndexSearcher searcher, ScoreMode scoreMode, float boost)} &mdash; 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>{@link org.apache.lucene.search.Query#rewrite(org.apache.lucene.index.IndexReader)
* rewrite(IndexReader reader)} &mdash; 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,ScoreMode,float)
* createWeight(IndexSearcher searcher,ScoreMode scoreMode, float boost)}</span>
* </ol>
*
* <a id="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 four main methods:
*
* <ol>
* <li>{@link org.apache.lucene.search.Weight#scorer scorer()} &mdash; 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>{@link org.apache.lucene.search.Weight#explain(org.apache.lucene.index.LeafReaderContext,
* int) explain(LeafReaderContext context, int doc)} &mdash; 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(Explanation, long)
* SimScorer#explain(Explanation freq, long norm)}.
* <li>{@link org.apache.lucene.search.Weight#matches matches(LeafReaderContext context, int doc)}
* &mdash; Give information about positions and offsets of matches. This is typically useful
* to implement highlighting.
* </ol>
*
* <a id="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 methods which must be implemented:
*
* <ol>
* <li>{@link org.apache.lucene.search.Scorer#iterator iterator()} &mdash; Return a {@link
* org.apache.lucene.search.DocIdSetIterator DocIdSetIterator} that can iterate over all
* document that matches this Query.
* <li>{@link org.apache.lucene.search.Scorer#docID docID()} &mdash; Returns the id of the {@link
* org.apache.lucene.document.Document Document} that contains the match.
* <li>{@link org.apache.lucene.search.Scorer#score score()} &mdash; 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(float, long)
* SimScorer.score(float freq, long norm)}.
* <li>{@link org.apache.lucene.search.Scorer#getChildren getChildren()} &mdash; 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.
* </ol>
*
* <a id="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,org.apache.lucene.util.Bits,int,int)
* score(LeafCollector,Bits,int,int)} &mdash; Score all documents up to but not including the
* specified max document.
* </ol>
*
* <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).
* <!-- TODO: integrate this better, it's better served as an intro than an appendix -->
* <a id="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>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>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>The IndexSearcher that initiated the call.
* <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.
* </ol>
*
* <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#createWeight(org.apache.lucene.search.Query,ScoreMode,float)
* IndexSearcher.createWeight(Query,ScoreMode,float)} 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 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>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>Assuming a BooleanScorer2, we 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.DocIdSetIterator#nextDoc
* DocIdSetIterator.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.
*/
package org.apache.lucene.search;