mirror of https://github.com/apache/lucene.git
some javadoc comment improvements
PR: 31350 Submitted by: Paul Elschot git-svn-id: https://svn.apache.org/repos/asf/lucene/java/trunk@150590 13f79535-47bb-0310-9956-ffa450edef68
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@ -246,8 +246,9 @@ public final class Field implements Serializable {
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return f;
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}
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/** The name of the field (e.g., "date", "title", "body", ...)
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as an interned string. */
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/** Returns the name of the field as an interned string.
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* For example "date", "title", "body", ...
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*/
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public String name() { return name; }
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/** The value of the field as a String, or null. If null, the Reader value
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@ -496,7 +496,7 @@ public class QueryParser {
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/**
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* Returns a String where those characters that QueryParser
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* expects to be escaped are escaped, i.e. preceded by a <code>\</code>.
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* expects to be escaped are escaped by a preceding <code>\</code>.
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*/
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public static String escape(String s) {
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StringBuffer sb = new StringBuffer();
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@ -86,7 +86,7 @@ public final class FuzzyQuery extends MultiTermQuery {
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}
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/**
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* Returns the prefix length, i.e. the number of characters at the start
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* Returns the non-fuzzy prefix length. This is the number of characters at the start
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* of a term that must be identical (not fuzzy) to the query term if the query
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* is to match that term.
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*/
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@ -19,9 +19,9 @@ package org.apache.lucene.search;
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import java.io.IOException;
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/** Expert: Common scoring functionality for different types of queries.
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* <br>A <code>Scorer</code> iterates over all documents matching a query,
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* <br>A <code>Scorer</code> either iterates over documents matching a query,
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* or provides an explanation of the score for a query for a given document.
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* <br>Scores are computed using a given <code>Similarity</code> implementation.
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* <br>Document scores are computed using a given <code>Similarity</code> implementation.
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*/
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public abstract class Scorer {
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private Similarity similarity;
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@ -41,6 +41,7 @@ public abstract class Scorer {
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/** Scores and collects all matching documents.
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* @param hc The collector to which all matching documents are passed through
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* {@link HitCollector#collect(int, float)}.
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* <br>When this method is used the {@link #explain(int)} method should not be used.
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*/
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public void score(HitCollector hc) throws IOException {
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while (next()) {
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@ -67,6 +68,7 @@ public abstract class Scorer {
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/** Advances to the next document matching the query.
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* @return true iff there is another document matching the query.
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* <br>When this method is used the {@link #explain(int)} method should not be used.
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*/
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public abstract boolean next() throws IOException;
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@ -82,6 +84,7 @@ public abstract class Scorer {
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/** Skips to the first match beyond the current whose document number is
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* greater than or equal to a given target.
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* <br>When this method is used the {@link #explain(int)} method should not be used.
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* @param target The target document number.
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* @return true iff there is such a match.
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* <p>Behaves as if written: <pre>
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@ -92,14 +95,13 @@ public abstract class Scorer {
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* } while (target > doc());
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* return true;
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* }
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* </pre>
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* Most implementations are considerably more efficient than that.
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* </pre>Most implementations are considerably more efficient than that.
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*/
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public abstract boolean skipTo(int target) throws IOException;
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/** Returns an explanation of the score for a document.
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* <br>When this method is used, the {@link #next()} method
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* and the {@link #score(HitCollector)} method should not be used.
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* <br>When this method is used, the {@link #next()}, {@link #skipTo(int)} and
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* {@link #score(HitCollector)} methods should not be used.
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* @param doc The document number for the explanation.
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*/
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public abstract Explanation explain(int doc) throws IOException;
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@ -99,7 +99,7 @@ public abstract class Similarity {
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* @see #encodeNorm(float)
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*/
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public static float decodeNorm(byte b) {
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return NORM_TABLE[b & 0xFF];
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return NORM_TABLE[b & 0xFF]; // & 0xFF maps negative bytes to positive above 127
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}
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/** Returns a table for decoding normalization bytes.
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@ -21,13 +21,18 @@ import java.io.IOException;
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import org.apache.lucene.index.IndexReader;
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/** Expert: Calculate query weights and build query scorers.
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*
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* <p>A Weight is constructed by a query, given a Searcher ({@link
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* Query#createWeight(Searcher)}). The {@link #sumOfSquaredWeights()} method
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* is then called on the top-level query to compute the query normalization
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* factor {@link Similarity#queryNorm(float)}. This factor is then passed to
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* {@link #normalize(float)}. At this point the weighting is complete and a
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* scorer may be constructed by calling {@link #scorer(IndexReader)}.
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* <br>A <code>Weight</code> is used in the following way:
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* <ol>
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* <li>A <code>Weight</code> is constructed by a top-level query,
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* given a <code>Searcher</code> ({@link Query#createWeight(Searcher)}).
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* <li>The {@link #sumOfSquaredWeights()} method is called
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* on the <code>Weight</code> to compute
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* the query normalization factor {@link Similarity#queryNorm(float)}
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* of the query clauses contained in the query.
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* <li>The query normalization factor is passed to {@link #normalize(float)}.
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* At this point the weighting is complete.
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* <li>A <code>Scorer</code> is constructed by {@link #scorer(IndexReader)}.
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* </ol>
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*/
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public interface Weight extends java.io.Serializable {
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/** The query that this concerns. */
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