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/*
 * Licensed to Elasticsearch under one or more contributor
 * license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright
 * ownership. Elasticsearch 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.
 */

package org.elasticsearch.common.lucene.all;

import org.apache.lucene.analysis.payloads.PayloadHelper;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.index.PostingsEnum;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.TermContext;
import org.apache.lucene.index.TermState;
import org.apache.lucene.index.Terms;
import org.apache.lucene.index.TermsEnum;
import org.apache.lucene.search.CollectionStatistics;
import org.apache.lucene.search.DocIdSetIterator;
import org.apache.lucene.search.Explanation;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.MatchNoDocsQuery;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.Scorer;
import org.apache.lucene.search.TermQuery;
import org.apache.lucene.search.TermStatistics;
import org.apache.lucene.search.Weight;
import org.apache.lucene.search.similarities.Similarity;
import org.apache.lucene.search.similarities.Similarity.SimScorer;
import org.apache.lucene.search.similarities.Similarity.SimWeight;
import org.apache.lucene.util.BytesRef;
import org.apache.lucene.util.SmallFloat;

import java.io.IOException;
import java.util.Objects;
import java.util.Set;

/**
 * A term query that takes all payload boost values into account.
 * 

* It is like PayloadTermQuery with AveragePayloadFunction, except * unlike PayloadTermQuery, it doesn't plug into the similarity to * determine how the payload should be factored in, it just parses * the float and multiplies the average with the regular score. */ public final class AllTermQuery extends Query { private final Term term; public AllTermQuery(Term term) { this.term = term; } public Term getTerm() { return term; } @Override public boolean equals(Object obj) { if (sameClassAs(obj) == false) { return false; } return Objects.equals(term, ((AllTermQuery) obj).term); } @Override public int hashCode() { return 31 * classHash() + term.hashCode(); } @Override public Query rewrite(IndexReader reader) throws IOException { Query rewritten = super.rewrite(reader); if (rewritten != this) { return rewritten; } boolean fieldExists = false; boolean hasPayloads = false; for (LeafReaderContext context : reader.leaves()) { final Terms terms = context.reader().terms(term.field()); if (terms != null) { fieldExists = true; if (terms.hasPayloads()) { hasPayloads = true; break; } } } if (fieldExists == false) { return new MatchNoDocsQuery(); } if (hasPayloads == false) { return new TermQuery(term); } return this; } @Override public Weight createWeight(IndexSearcher searcher, boolean needsScores) throws IOException { if (needsScores == false) { return new TermQuery(term).createWeight(searcher, needsScores); } final TermContext termStates = TermContext.build(searcher.getTopReaderContext(), term); final CollectionStatistics collectionStats = searcher.collectionStatistics(term.field()); final TermStatistics termStats = searcher.termStatistics(term, termStates); final Similarity similarity = searcher.getSimilarity(needsScores); final SimWeight stats = similarity.computeWeight(collectionStats, termStats); return new Weight(this) { @Override public float getValueForNormalization() throws IOException { return stats.getValueForNormalization(); } @Override public void normalize(float norm, float topLevelBoost) { stats.normalize(norm, topLevelBoost); } @Override public void extractTerms(Set terms) { terms.add(term); } @Override public Explanation explain(LeafReaderContext context, int doc) throws IOException { AllTermScorer scorer = scorer(context); if (scorer != null) { int newDoc = scorer.iterator().advance(doc); if (newDoc == doc) { float score = scorer.score(); float freq = scorer.freq(); SimScorer docScorer = similarity.simScorer(stats, context); Explanation freqExplanation = Explanation.match(freq, "termFreq=" + freq); Explanation termScoreExplanation = docScorer.explain(doc, freqExplanation); Explanation payloadBoostExplanation = Explanation.match(scorer.payloadBoost(), "payloadBoost=" + scorer.payloadBoost()); return Explanation.match( score, "weight(" + getQuery() + " in " + doc + ") [" + similarity.getClass().getSimpleName() + "], product of:", termScoreExplanation, payloadBoostExplanation); } } return Explanation.noMatch("no matching term"); } @Override public AllTermScorer scorer(LeafReaderContext context) throws IOException { final Terms terms = context.reader().terms(term.field()); if (terms == null) { return null; } final TermsEnum termsEnum = terms.iterator(); if (termsEnum == null) { return null; } final TermState state = termStates.get(context.ord); if (state == null) { // Term does not exist in this segment return null; } termsEnum.seekExact(term.bytes(), state); PostingsEnum docs = termsEnum.postings(null, PostingsEnum.PAYLOADS); assert docs != null; return new AllTermScorer(this, docs, similarity.simScorer(stats, context)); } }; } private static class AllTermScorer extends Scorer { final PostingsEnum postings; final Similarity.SimScorer docScorer; int doc = -1; float payloadBoost; AllTermScorer(Weight weight, PostingsEnum postings, Similarity.SimScorer docScorer) { super(weight); this.postings = postings; this.docScorer = docScorer; } float payloadBoost() throws IOException { if (doc != docID()) { final int freq = postings.freq(); payloadBoost = 0; for (int i = 0; i < freq; ++i) { postings.nextPosition(); final BytesRef payload = postings.getPayload(); float boost; if (payload == null) { boost = 1; } else if (payload.length == 1) { boost = SmallFloat.byte315ToFloat(payload.bytes[payload.offset]); } else if (payload.length == 4) { // TODO: for bw compat only, remove this in 6.0 boost = PayloadHelper.decodeFloat(payload.bytes, payload.offset); } else { throw new IllegalStateException("Payloads are expected to have a length of 1 or 4 but got: " + payload); } payloadBoost += boost; } payloadBoost /= freq; doc = docID(); } return payloadBoost; } @Override public float score() throws IOException { return payloadBoost() * docScorer.score(postings.docID(), postings.freq()); } @Override public int freq() throws IOException { return postings.freq(); } @Override public int docID() { return postings.docID(); } @Override public DocIdSetIterator iterator() { return postings; } } @Override public String toString(String field) { return new TermQuery(term).toString(field); } }





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