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| <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) createWeight(IndexSearcher searcher)} — 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) createWeight(IndexSearcher searcher)}</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(org.apache.lucene.index.AtomicReaderContext, org.apache.lucene.util.Bits) |
| scorer(AtomicReaderContext context, Bits acceptDocs)} — |
| 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(org.apache.lucene.index.AtomicReaderContext, boolean, org.apache.lucene.util.Bits) |
| scorer(AtomicReaderContext context, boolean scoreDocsInOrder, Bits acceptDocs)} — |
| 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.AtomicReaderContext, int) |
| explain(AtomicReaderContext 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) score(LeafCollector,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, its 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) |
| IndexSearcher.createNormalizedWeight(Query)}, |
| {@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.BooleanQuery.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> |
