lucene/sandbox/src/java/org/apache/lucene/search/CombinedFieldQuery.java - solr - Git at Google

 /*
  * 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.
  */
 package org.apache.lucene.search;

 import java.io.IOException;
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.Collections;
 import java.util.HashMap;
 import java.util.HashSet;
 import java.util.List;
 import java.util.Map;
 import java.util.Set;
 import java.util.TreeMap;
 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.TermState;
 import org.apache.lucene.index.TermStates;
 import org.apache.lucene.index.TermsEnum;
 import org.apache.lucene.search.BooleanClause;
 import org.apache.lucene.search.BooleanQuery;
 import org.apache.lucene.search.CollectionStatistics;
 import org.apache.lucene.search.DisiPriorityQueue;
 import org.apache.lucene.search.DisiWrapper;
 import org.apache.lucene.search.DisjunctionDISIApproximation;
 import org.apache.lucene.search.DocIdSetIterator;
 import org.apache.lucene.search.Explanation;
 import org.apache.lucene.search.IndexSearcher;
 import org.apache.lucene.search.LeafSimScorer;
 import org.apache.lucene.search.Matches;
 import org.apache.lucene.search.Query;
 import org.apache.lucene.search.QueryVisitor;
 import org.apache.lucene.search.ScoreMode;
 import org.apache.lucene.search.Scorer;
 import org.apache.lucene.search.SynonymQuery;
 import org.apache.lucene.search.TermQuery;
 import org.apache.lucene.search.TermScorer;
 import org.apache.lucene.search.TermStatistics;
 import org.apache.lucene.search.Weight;
 import org.apache.lucene.search.similarities.BM25Similarity;
 import org.apache.lucene.search.similarities.DFRSimilarity;
 import org.apache.lucene.search.similarities.Similarity;
 import org.apache.lucene.search.similarities.SimilarityBase;
 import org.apache.lucene.util.Accountable;
 import org.apache.lucene.util.BytesRef;
 import org.apache.lucene.util.RamUsageEstimator;
 import org.apache.lucene.util.SmallFloat;

 /**
  * A {@link Query} that treats multiple fields as a single stream and scores terms as if you had
  * indexed them as a single term in a single field.
  *
  * <p>The query works as follows:
  *
  * <ol>
  *   <li>Given a list of fields and weights, it pretends there is a synthetic combined field where
  *       all terms have been indexed. It computes new term and collection statistics for this
  *       combined field.
  *   <li>It uses a disjunction iterator and {@link IndexSearcher#getSimilarity} to score documents.
  * </ol>
  *
  * <p>In order for a similarity to be compatible, {@link Similarity#computeNorm} must be additive:
  * the norm of the combined field is the sum of norms for each individual field. The norms must also
  * be encoded using {@link SmallFloat#intToByte4}. These requirements hold for all similarities that
  * compute norms the same way as {@link SimilarityBase#computeNorm}, which includes {@link
  * BM25Similarity} and {@link DFRSimilarity}. Per-field similarities are not supported.
  *
  * <p>The scoring is based on BM25F's simple formula described in:
  * http://www.staff.city.ac.uk/~sb317/papers/foundations_bm25_review.pdf. This query implements the
  * same approach but allows other similarities besides {@link
  * org.apache.lucene.search.similarities.BM25Similarity}.
  *
  * @lucene.experimental
  */
 public final class CombinedFieldQuery extends Query implements Accountable {
   private static final long BASE_RAM_BYTES =
       RamUsageEstimator.shallowSizeOfInstance(CombinedFieldQuery.class);

   /** A builder for {@link CombinedFieldQuery}. */
   public static class Builder {
     private final Map<String, FieldAndWeight> fieldAndWeights = new HashMap<>();
     private final Set<BytesRef> termsSet = new HashSet<>();

     /**
      * Adds a field to this builder.
      *
      * @param field The field name.
      */
     public Builder addField(String field) {
       return addField(field, 1f);
     }

     /**
      * Adds a field to this builder.
      *
      * @param field The field name.
      * @param weight The weight associated to this field.
      */
     public Builder addField(String field, float weight) {
       if (weight < 1) {
         throw new IllegalArgumentException("weight must be greater or equal to 1");
       }
       fieldAndWeights.put(field, new FieldAndWeight(field, weight));
       return this;
     }

     /** Adds a term to this builder. */
     public Builder addTerm(BytesRef term) {
       if (termsSet.size() > BooleanQuery.getMaxClauseCount()) {
         throw new BooleanQuery.TooManyClauses();
       }
       termsSet.add(term);
       return this;
     }

     /** Builds the {@link CombinedFieldQuery}. */
     public CombinedFieldQuery build() {
       int size = fieldAndWeights.size() * termsSet.size();
       if (size > BooleanQuery.getMaxClauseCount()) {
         throw new BooleanQuery.TooManyClauses();
       }
       BytesRef[] terms = termsSet.toArray(new BytesRef[0]);
       return new CombinedFieldQuery(new TreeMap<>(fieldAndWeights), terms);
     }
   }

   static class FieldAndWeight {
     final String field;
     final float weight;

     FieldAndWeight(String field, float weight) {
       this.field = field;
       this.weight = weight;
     }
   }

   // sorted map for fields.
   private final TreeMap<String, FieldAndWeight> fieldAndWeights;
   // array of terms, sorted.
   private final BytesRef terms[];
   // array of terms per field, sorted
   private final Term fieldTerms[];

   private final long ramBytesUsed;

   private CombinedFieldQuery(TreeMap<String, FieldAndWeight> fieldAndWeights, BytesRef[] terms) {
     this.fieldAndWeights = fieldAndWeights;
     this.terms = terms;
     int numFieldTerms = fieldAndWeights.size() * terms.length;
     if (numFieldTerms > BooleanQuery.getMaxClauseCount()) {
       throw new BooleanQuery.TooManyClauses();
     }
     this.fieldTerms = new Term[numFieldTerms];
     Arrays.sort(terms);
     int pos = 0;
     for (String field : fieldAndWeights.keySet()) {
       for (BytesRef term : terms) {
         fieldTerms[pos++] = new Term(field, term);
       }
     }

     this.ramBytesUsed =
         BASE_RAM_BYTES
             + RamUsageEstimator.sizeOfObject(fieldAndWeights)
             + RamUsageEstimator.sizeOfObject(fieldTerms)
             + RamUsageEstimator.sizeOfObject(terms);
   }

   public List<Term> getTerms() {
     return Collections.unmodifiableList(Arrays.asList(fieldTerms));
   }

   @Override
   public String toString(String field) {
     StringBuilder builder = new StringBuilder("CombinedFieldQuery((");
     int pos = 0;
     for (FieldAndWeight fieldWeight : fieldAndWeights.values()) {
       if (pos++ != 0) {
         builder.append(" ");
       }
       builder.append(fieldWeight.field);
       if (fieldWeight.weight != 1f) {
         builder.append("^");
         builder.append(fieldWeight.weight);
       }
     }
     builder.append(")(");
     pos = 0;
     for (BytesRef term : terms) {
       if (pos++ != 0) {
         builder.append(" ");
       }
       builder.append(term.utf8ToString());
     }
     builder.append("))");
     return builder.toString();
   }

   @Override
   public int hashCode() {
     return 31 * classHash() + Arrays.hashCode(terms);
   }

   @Override
   public boolean equals(Object other) {
     return sameClassAs(other) && Arrays.equals(terms, ((CombinedFieldQuery) other).terms);
   }

   @Override
   public long ramBytesUsed() {
     return ramBytesUsed;
   }

   @Override
   public Query rewrite(IndexReader reader) throws IOException {
     // optimize zero and single field cases
     if (terms.length == 0) {
       return new BooleanQuery.Builder().build();
     }
     // single field and one term
     if (fieldTerms.length == 1) {
       return new TermQuery(fieldTerms[0]);
     }
     // single field and multiple terms
     if (fieldAndWeights.size() == 1) {
       SynonymQuery.Builder builder = new SynonymQuery.Builder(fieldTerms[0].field());
       for (Term term : fieldTerms) {
         builder.addTerm(term);
       }
       return builder.build();
     }
     return this;
   }

   @Override
   public void visit(QueryVisitor visitor) {
     Term[] selectedTerms =
         Arrays.stream(fieldTerms).filter(t -> visitor.acceptField(t.field())).toArray(Term[]::new);
     if (selectedTerms.length > 0) {
       QueryVisitor v = visitor.getSubVisitor(BooleanClause.Occur.SHOULD, this);
       v.consumeTerms(this, selectedTerms);
     }
   }

   private BooleanQuery rewriteToBoolean() {
     // rewrite to a simple disjunction if the score is not needed.
     BooleanQuery.Builder bq = new BooleanQuery.Builder();
     for (Term term : fieldTerms) {
       bq.add(new TermQuery(term), BooleanClause.Occur.SHOULD);
     }
     return bq.build();
   }

   @Override
   public Weight createWeight(IndexSearcher searcher, ScoreMode scoreMode, float boost)
       throws IOException {
     if (scoreMode.needsScores()) {
       return new CombinedFieldWeight(this, searcher, scoreMode, boost);
     } else {
       // rewrite to a simple disjunction if the score is not needed.
       Query bq = rewriteToBoolean();
       return searcher.rewrite(bq).createWeight(searcher, ScoreMode.COMPLETE_NO_SCORES, boost);
     }
   }

   class CombinedFieldWeight extends Weight {
     private final IndexSearcher searcher;
     private final TermStates termStates[];
     private final Similarity.SimScorer simWeight;

     CombinedFieldWeight(Query query, IndexSearcher searcher, ScoreMode scoreMode, float boost)
         throws IOException {
       super(query);
       assert scoreMode.needsScores();
       this.searcher = searcher;
       long docFreq = 0;
       long totalTermFreq = 0;
       termStates = new TermStates[fieldTerms.length];
       for (int i = 0; i < termStates.length; i++) {
         FieldAndWeight field = fieldAndWeights.get(fieldTerms[i].field());
         TermStates ts = TermStates.build(searcher.getTopReaderContext(), fieldTerms[i], true);
         termStates[i] = ts;
         if (ts.docFreq() > 0) {
           TermStatistics termStats =
               searcher.termStatistics(fieldTerms[i], ts.docFreq(), ts.totalTermFreq());
           docFreq = Math.max(termStats.docFreq(), docFreq);
           totalTermFreq += (double) field.weight * termStats.totalTermFreq();
         }
       }
       if (docFreq > 0) {
         CollectionStatistics pseudoCollectionStats = mergeCollectionStatistics(searcher);
         TermStatistics pseudoTermStatistics =
             new TermStatistics(new BytesRef("pseudo_term"), docFreq, Math.max(1, totalTermFreq));
         this.simWeight =
             searcher.getSimilarity().scorer(boost, pseudoCollectionStats, pseudoTermStatistics);
       } else {
         this.simWeight = null;
       }
     }

     private CollectionStatistics mergeCollectionStatistics(IndexSearcher searcher)
         throws IOException {
       long maxDoc = searcher.getIndexReader().maxDoc();
       long docCount = 0;
       long sumTotalTermFreq = 0;
       long sumDocFreq = 0;
       for (FieldAndWeight fieldWeight : fieldAndWeights.values()) {
         CollectionStatistics collectionStats = searcher.collectionStatistics(fieldWeight.field);
         if (collectionStats != null) {
           docCount = Math.max(collectionStats.docCount(), docCount);
           sumDocFreq = Math.max(collectionStats.sumDocFreq(), sumDocFreq);
           sumTotalTermFreq += (double) fieldWeight.weight * collectionStats.sumTotalTermFreq();
         }
       }

       return new CollectionStatistics(
           "pseudo_field", maxDoc, docCount, sumTotalTermFreq, sumDocFreq);
     }

     @Override
     public void extractTerms(Set<Term> termSet) {
       termSet.addAll(Arrays.asList(fieldTerms));
     }

     @Override
     public Matches matches(LeafReaderContext context, int doc) throws IOException {
       Weight weight =
           searcher.rewrite(rewriteToBoolean()).createWeight(searcher, ScoreMode.COMPLETE, 1f);
       return weight.matches(context, doc);
     }

     @Override
     public Explanation explain(LeafReaderContext context, int doc) throws IOException {
       Scorer scorer = scorer(context);
       if (scorer != null) {
         int newDoc = scorer.iterator().advance(doc);
         if (newDoc == doc) {
           final float freq;
           if (scorer instanceof CombinedFieldScorer) {
             freq = ((CombinedFieldScorer) scorer).freq();
           } else {
             assert scorer instanceof TermScorer;
             freq = ((TermScorer) scorer).freq();
           }
           final MultiNormsLeafSimScorer docScorer =
               new MultiNormsLeafSimScorer(
                   simWeight, context.reader(), fieldAndWeights.values(), true);
           Explanation freqExplanation = Explanation.match(freq, "termFreq=" + freq);
           Explanation scoreExplanation = docScorer.explain(doc, freqExplanation);
           return Explanation.match(
               scoreExplanation.getValue(),
               "weight(" + getQuery() + " in " + doc + "), result of:",
               scoreExplanation);
         }
       }
       return Explanation.noMatch("no matching term");
     }

     @Override
     public Scorer scorer(LeafReaderContext context) throws IOException {
       List<PostingsEnum> iterators = new ArrayList<>();
       List<FieldAndWeight> fields = new ArrayList<>();
       for (int i = 0; i < fieldTerms.length; i++) {
         TermState state = termStates[i].get(context);
         if (state != null) {
           TermsEnum termsEnum = context.reader().terms(fieldTerms[i].field()).iterator();
           termsEnum.seekExact(fieldTerms[i].bytes(), state);
           PostingsEnum postingsEnum = termsEnum.postings(null, PostingsEnum.FREQS);
           iterators.add(postingsEnum);
           fields.add(fieldAndWeights.get(fieldTerms[i].field()));
         }
       }

       if (iterators.isEmpty()) {
         return null;
       }

       // we must optimize this case (term not in segment), disjunctions require >= 2 subs
       if (iterators.size() == 1) {
         final LeafSimScorer scoringSimScorer =
             new LeafSimScorer(simWeight, context.reader(), fields.get(0).field, true);
         return new TermScorer(this, iterators.get(0), scoringSimScorer);
       }
       final MultiNormsLeafSimScorer scoringSimScorer =
           new MultiNormsLeafSimScorer(simWeight, context.reader(), fields, true);
       LeafSimScorer nonScoringSimScorer =
           new LeafSimScorer(simWeight, context.reader(), "pseudo_field", false);
       // we use termscorers + disjunction as an impl detail
       DisiPriorityQueue queue = new DisiPriorityQueue(iterators.size());
       for (int i = 0; i < iterators.size(); i++) {
         float weight = fields.get(i).weight;
         queue.add(
             new WeightedDisiWrapper(
                 new TermScorer(this, iterators.get(i), nonScoringSimScorer), weight));
       }
       // Even though it is called approximation, it is accurate since none of
       // the sub iterators are two-phase iterators.
       DocIdSetIterator iterator = new DisjunctionDISIApproximation(queue);
       return new CombinedFieldScorer(this, queue, iterator, scoringSimScorer);
     }

     @Override
     public boolean isCacheable(LeafReaderContext ctx) {
       return false;
     }
   }

   private static class WeightedDisiWrapper extends DisiWrapper {
     final float weight;

     WeightedDisiWrapper(Scorer scorer, float weight) {
       super(scorer);
       this.weight = weight;
     }

     float freq() throws IOException {
       return weight * ((PostingsEnum) iterator).freq();
     }
   }

   private static class CombinedFieldScorer extends Scorer {
     private final DisiPriorityQueue queue;
     private final DocIdSetIterator iterator;
     private final MultiNormsLeafSimScorer simScorer;

     CombinedFieldScorer(
         Weight weight,
         DisiPriorityQueue queue,
         DocIdSetIterator iterator,
         MultiNormsLeafSimScorer simScorer) {
       super(weight);
       this.queue = queue;
       this.iterator = iterator;
       this.simScorer = simScorer;
     }

     @Override
     public int docID() {
       return iterator.docID();
     }

     float freq() throws IOException {
       DisiWrapper w = queue.topList();
       float freq = ((WeightedDisiWrapper) w).freq();
       for (w = w.next; w != null; w = w.next) {
         freq += ((WeightedDisiWrapper) w).freq();
         if (freq < 0) { // overflow
           return Integer.MAX_VALUE;
         }
       }
       return freq;
     }

     @Override
     public float score() throws IOException {
       return simScorer.score(iterator.docID(), freq());
     }

     @Override
     public DocIdSetIterator iterator() {
       return iterator;
     }

     @Override
     public float getMaxScore(int upTo) throws IOException {
       return Float.POSITIVE_INFINITY;
     }
   }
 }
	/*
	* 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.
	*/
	package org.apache.lucene.search;

	import java.io.IOException;
	import java.util.ArrayList;
	import java.util.Arrays;
	import java.util.Collections;
	import java.util.HashMap;
	import java.util.HashSet;
	import java.util.List;
	import java.util.Map;
	import java.util.Set;
	import java.util.TreeMap;
	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.TermState;
	import org.apache.lucene.index.TermStates;
	import org.apache.lucene.index.TermsEnum;
	import org.apache.lucene.search.BooleanClause;
	import org.apache.lucene.search.BooleanQuery;
	import org.apache.lucene.search.CollectionStatistics;
	import org.apache.lucene.search.DisiPriorityQueue;
	import org.apache.lucene.search.DisiWrapper;
	import org.apache.lucene.search.DisjunctionDISIApproximation;
	import org.apache.lucene.search.DocIdSetIterator;
	import org.apache.lucene.search.Explanation;
	import org.apache.lucene.search.IndexSearcher;
	import org.apache.lucene.search.LeafSimScorer;
	import org.apache.lucene.search.Matches;
	import org.apache.lucene.search.Query;
	import org.apache.lucene.search.QueryVisitor;
	import org.apache.lucene.search.ScoreMode;
	import org.apache.lucene.search.Scorer;
	import org.apache.lucene.search.SynonymQuery;
	import org.apache.lucene.search.TermQuery;
	import org.apache.lucene.search.TermScorer;
	import org.apache.lucene.search.TermStatistics;
	import org.apache.lucene.search.Weight;
	import org.apache.lucene.search.similarities.BM25Similarity;
	import org.apache.lucene.search.similarities.DFRSimilarity;
	import org.apache.lucene.search.similarities.Similarity;
	import org.apache.lucene.search.similarities.SimilarityBase;
	import org.apache.lucene.util.Accountable;
	import org.apache.lucene.util.BytesRef;
	import org.apache.lucene.util.RamUsageEstimator;
	import org.apache.lucene.util.SmallFloat;

	/**
	* A {@link Query} that treats multiple fields as a single stream and scores terms as if you had
	* indexed them as a single term in a single field.
	*
	* <p>The query works as follows:
	*
	* <ol>
	* <li>Given a list of fields and weights, it pretends there is a synthetic combined field where
	* all terms have been indexed. It computes new term and collection statistics for this
	* combined field.
	* <li>It uses a disjunction iterator and {@link IndexSearcher#getSimilarity} to score documents.
	* </ol>
	*
	* <p>In order for a similarity to be compatible, {@link Similarity#computeNorm} must be additive:
	* the norm of the combined field is the sum of norms for each individual field. The norms must also
	* be encoded using {@link SmallFloat#intToByte4}. These requirements hold for all similarities that
	* compute norms the same way as {@link SimilarityBase#computeNorm}, which includes {@link
	* BM25Similarity} and {@link DFRSimilarity}. Per-field similarities are not supported.
	*
	* <p>The scoring is based on BM25F's simple formula described in:
	* http://www.staff.city.ac.uk/~sb317/papers/foundations_bm25_review.pdf. This query implements the
	* same approach but allows other similarities besides {@link
	* org.apache.lucene.search.similarities.BM25Similarity}.
	*
	* @lucene.experimental
	*/
	public final class CombinedFieldQuery extends Query implements Accountable {
	private static final long BASE_RAM_BYTES =
	RamUsageEstimator.shallowSizeOfInstance(CombinedFieldQuery.class);

	/** A builder for {@link CombinedFieldQuery}. */
	public static class Builder {
	private final Map<String, FieldAndWeight> fieldAndWeights = new HashMap<>();
	private final Set<BytesRef> termsSet = new HashSet<>();

	/**
	* Adds a field to this builder.
	*
	* @param field The field name.
	*/
	public Builder addField(String field) {
	return addField(field, 1f);
	}

	/**
	* Adds a field to this builder.
	*
	* @param field The field name.
	* @param weight The weight associated to this field.
	*/
	public Builder addField(String field, float weight) {
	if (weight < 1) {
	throw new IllegalArgumentException("weight must be greater or equal to 1");
	}
	fieldAndWeights.put(field, new FieldAndWeight(field, weight));
	return this;
	}

	/** Adds a term to this builder. */
	public Builder addTerm(BytesRef term) {
	if (termsSet.size() > BooleanQuery.getMaxClauseCount()) {
	throw new BooleanQuery.TooManyClauses();
	}
	termsSet.add(term);
	return this;
	}

	/** Builds the {@link CombinedFieldQuery}. */
	public CombinedFieldQuery build() {
	int size = fieldAndWeights.size() * termsSet.size();
	if (size > BooleanQuery.getMaxClauseCount()) {
	throw new BooleanQuery.TooManyClauses();
	}
	BytesRef[] terms = termsSet.toArray(new BytesRef[0]);
	return new CombinedFieldQuery(new TreeMap<>(fieldAndWeights), terms);
	}
	}

	static class FieldAndWeight {
	final String field;
	final float weight;

	FieldAndWeight(String field, float weight) {
	this.field = field;
	this.weight = weight;
	}
	}

	// sorted map for fields.
	private final TreeMap<String, FieldAndWeight> fieldAndWeights;
	// array of terms, sorted.
	private final BytesRef terms[];
	// array of terms per field, sorted
	private final Term fieldTerms[];

	private final long ramBytesUsed;

	private CombinedFieldQuery(TreeMap<String, FieldAndWeight> fieldAndWeights, BytesRef[] terms) {
	this.fieldAndWeights = fieldAndWeights;
	this.terms = terms;
	int numFieldTerms = fieldAndWeights.size() * terms.length;
	if (numFieldTerms > BooleanQuery.getMaxClauseCount()) {
	throw new BooleanQuery.TooManyClauses();
	}
	this.fieldTerms = new Term[numFieldTerms];
	Arrays.sort(terms);
	int pos = 0;
	for (String field : fieldAndWeights.keySet()) {
	for (BytesRef term : terms) {
	fieldTerms[pos++] = new Term(field, term);
	}
	}

	this.ramBytesUsed =
	BASE_RAM_BYTES
	+ RamUsageEstimator.sizeOfObject(fieldAndWeights)
	+ RamUsageEstimator.sizeOfObject(fieldTerms)
	+ RamUsageEstimator.sizeOfObject(terms);
	}

	public List<Term> getTerms() {
	return Collections.unmodifiableList(Arrays.asList(fieldTerms));
	}

	@Override
	public String toString(String field) {
	StringBuilder builder = new StringBuilder("CombinedFieldQuery((");
	int pos = 0;
	for (FieldAndWeight fieldWeight : fieldAndWeights.values()) {
	if (pos++ != 0) {
	builder.append(" ");
	}
	builder.append(fieldWeight.field);
	if (fieldWeight.weight != 1f) {
	builder.append("^");
	builder.append(fieldWeight.weight);
	}
	}
	builder.append(")(");
	pos = 0;
	for (BytesRef term : terms) {
	if (pos++ != 0) {
	builder.append(" ");
	}
	builder.append(term.utf8ToString());
	}
	builder.append("))");
	return builder.toString();
	}

	@Override
	public int hashCode() {
	return 31 * classHash() + Arrays.hashCode(terms);
	}

	@Override
	public boolean equals(Object other) {
	return sameClassAs(other) && Arrays.equals(terms, ((CombinedFieldQuery) other).terms);
	}

	@Override
	public long ramBytesUsed() {
	return ramBytesUsed;
	}

	@Override
	public Query rewrite(IndexReader reader) throws IOException {
	// optimize zero and single field cases
	if (terms.length == 0) {
	return new BooleanQuery.Builder().build();
	}
	// single field and one term
	if (fieldTerms.length == 1) {
	return new TermQuery(fieldTerms[0]);
	}
	// single field and multiple terms
	if (fieldAndWeights.size() == 1) {
	SynonymQuery.Builder builder = new SynonymQuery.Builder(fieldTerms[0].field());
	for (Term term : fieldTerms) {
	builder.addTerm(term);
	}
	return builder.build();
	}
	return this;
	}

	@Override
	public void visit(QueryVisitor visitor) {
	Term[] selectedTerms =
	Arrays.stream(fieldTerms).filter(t -> visitor.acceptField(t.field())).toArray(Term[]::new);
	if (selectedTerms.length > 0) {
	QueryVisitor v = visitor.getSubVisitor(BooleanClause.Occur.SHOULD, this);
	v.consumeTerms(this, selectedTerms);
	}
	}

	private BooleanQuery rewriteToBoolean() {
	// rewrite to a simple disjunction if the score is not needed.
	BooleanQuery.Builder bq = new BooleanQuery.Builder();
	for (Term term : fieldTerms) {
	bq.add(new TermQuery(term), BooleanClause.Occur.SHOULD);
	}
	return bq.build();
	}

	@Override
	public Weight createWeight(IndexSearcher searcher, ScoreMode scoreMode, float boost)
	throws IOException {
	if (scoreMode.needsScores()) {
	return new CombinedFieldWeight(this, searcher, scoreMode, boost);
	} else {
	// rewrite to a simple disjunction if the score is not needed.
	Query bq = rewriteToBoolean();
	return searcher.rewrite(bq).createWeight(searcher, ScoreMode.COMPLETE_NO_SCORES, boost);
	}
	}

	class CombinedFieldWeight extends Weight {
	private final IndexSearcher searcher;
	private final TermStates termStates[];
	private final Similarity.SimScorer simWeight;

	CombinedFieldWeight(Query query, IndexSearcher searcher, ScoreMode scoreMode, float boost)
	throws IOException {
	super(query);
	assert scoreMode.needsScores();
	this.searcher = searcher;
	long docFreq = 0;
	long totalTermFreq = 0;
	termStates = new TermStates[fieldTerms.length];
	for (int i = 0; i < termStates.length; i++) {
	FieldAndWeight field = fieldAndWeights.get(fieldTerms[i].field());
	TermStates ts = TermStates.build(searcher.getTopReaderContext(), fieldTerms[i], true);
	termStates[i] = ts;
	if (ts.docFreq() > 0) {
	TermStatistics termStats =
	searcher.termStatistics(fieldTerms[i], ts.docFreq(), ts.totalTermFreq());
	docFreq = Math.max(termStats.docFreq(), docFreq);
	totalTermFreq += (double) field.weight * termStats.totalTermFreq();
	}
	}
	if (docFreq > 0) {
	CollectionStatistics pseudoCollectionStats = mergeCollectionStatistics(searcher);
	TermStatistics pseudoTermStatistics =
	new TermStatistics(new BytesRef("pseudo_term"), docFreq, Math.max(1, totalTermFreq));
	this.simWeight =
	searcher.getSimilarity().scorer(boost, pseudoCollectionStats, pseudoTermStatistics);
	} else {
	this.simWeight = null;
	}
	}

	private CollectionStatistics mergeCollectionStatistics(IndexSearcher searcher)
	throws IOException {
	long maxDoc = searcher.getIndexReader().maxDoc();
	long docCount = 0;
	long sumTotalTermFreq = 0;
	long sumDocFreq = 0;
	for (FieldAndWeight fieldWeight : fieldAndWeights.values()) {
	CollectionStatistics collectionStats = searcher.collectionStatistics(fieldWeight.field);
	if (collectionStats != null) {
	docCount = Math.max(collectionStats.docCount(), docCount);
	sumDocFreq = Math.max(collectionStats.sumDocFreq(), sumDocFreq);
	sumTotalTermFreq += (double) fieldWeight.weight * collectionStats.sumTotalTermFreq();
	}
	}

	return new CollectionStatistics(
	"pseudo_field", maxDoc, docCount, sumTotalTermFreq, sumDocFreq);
	}

	@Override
	public void extractTerms(Set<Term> termSet) {
	termSet.addAll(Arrays.asList(fieldTerms));
	}

	@Override
	public Matches matches(LeafReaderContext context, int doc) throws IOException {
	Weight weight =
	searcher.rewrite(rewriteToBoolean()).createWeight(searcher, ScoreMode.COMPLETE, 1f);
	return weight.matches(context, doc);
	}

	@Override
	public Explanation explain(LeafReaderContext context, int doc) throws IOException {
	Scorer scorer = scorer(context);
	if (scorer != null) {
	int newDoc = scorer.iterator().advance(doc);
	if (newDoc == doc) {
	final float freq;
	if (scorer instanceof CombinedFieldScorer) {
	freq = ((CombinedFieldScorer) scorer).freq();
	} else {
	assert scorer instanceof TermScorer;
	freq = ((TermScorer) scorer).freq();
	}
	final MultiNormsLeafSimScorer docScorer =
	new MultiNormsLeafSimScorer(
	simWeight, context.reader(), fieldAndWeights.values(), true);
	Explanation freqExplanation = Explanation.match(freq, "termFreq=" + freq);
	Explanation scoreExplanation = docScorer.explain(doc, freqExplanation);
	return Explanation.match(
	scoreExplanation.getValue(),
	"weight(" + getQuery() + " in " + doc + "), result of:",
	scoreExplanation);
	}
	}
	return Explanation.noMatch("no matching term");
	}

	@Override
	public Scorer scorer(LeafReaderContext context) throws IOException {
	List<PostingsEnum> iterators = new ArrayList<>();
	List<FieldAndWeight> fields = new ArrayList<>();
	for (int i = 0; i < fieldTerms.length; i++) {
	TermState state = termStates[i].get(context);
	if (state != null) {
	TermsEnum termsEnum = context.reader().terms(fieldTerms[i].field()).iterator();
	termsEnum.seekExact(fieldTerms[i].bytes(), state);
	PostingsEnum postingsEnum = termsEnum.postings(null, PostingsEnum.FREQS);
	iterators.add(postingsEnum);
	fields.add(fieldAndWeights.get(fieldTerms[i].field()));
	}
	}

	if (iterators.isEmpty()) {
	return null;
	}

	// we must optimize this case (term not in segment), disjunctions require >= 2 subs
	if (iterators.size() == 1) {
	final LeafSimScorer scoringSimScorer =
	new LeafSimScorer(simWeight, context.reader(), fields.get(0).field, true);
	return new TermScorer(this, iterators.get(0), scoringSimScorer);
	}
	final MultiNormsLeafSimScorer scoringSimScorer =
	new MultiNormsLeafSimScorer(simWeight, context.reader(), fields, true);
	LeafSimScorer nonScoringSimScorer =
	new LeafSimScorer(simWeight, context.reader(), "pseudo_field", false);
	// we use termscorers + disjunction as an impl detail
	DisiPriorityQueue queue = new DisiPriorityQueue(iterators.size());
	for (int i = 0; i < iterators.size(); i++) {
	float weight = fields.get(i).weight;
	queue.add(
	new WeightedDisiWrapper(
	new TermScorer(this, iterators.get(i), nonScoringSimScorer), weight));
	}
	// Even though it is called approximation, it is accurate since none of
	// the sub iterators are two-phase iterators.
	DocIdSetIterator iterator = new DisjunctionDISIApproximation(queue);
	return new CombinedFieldScorer(this, queue, iterator, scoringSimScorer);
	}

	@Override
	public boolean isCacheable(LeafReaderContext ctx) {
	return false;
	}
	}

	private static class WeightedDisiWrapper extends DisiWrapper {
	final float weight;

	WeightedDisiWrapper(Scorer scorer, float weight) {
	super(scorer);
	this.weight = weight;
	}

	float freq() throws IOException {
	return weight * ((PostingsEnum) iterator).freq();
	}
	}

	private static class CombinedFieldScorer extends Scorer {
	private final DisiPriorityQueue queue;
	private final DocIdSetIterator iterator;
	private final MultiNormsLeafSimScorer simScorer;

	CombinedFieldScorer(
	Weight weight,
	DisiPriorityQueue queue,
	DocIdSetIterator iterator,
	MultiNormsLeafSimScorer simScorer) {
	super(weight);
	this.queue = queue;
	this.iterator = iterator;
	this.simScorer = simScorer;
	}

	@Override
	public int docID() {
	return iterator.docID();
	}

	float freq() throws IOException {
	DisiWrapper w = queue.topList();
	float freq = ((WeightedDisiWrapper) w).freq();
	for (w = w.next; w != null; w = w.next) {
	freq += ((WeightedDisiWrapper) w).freq();
	if (freq < 0) { // overflow
	return Integer.MAX_VALUE;
	}
	}
	return freq;
	}

	@Override
	public float score() throws IOException {
	return simScorer.score(iterator.docID(), freq());
	}

	@Override
	public DocIdSetIterator iterator() {
	return iterator;
	}

	@Override
	public float getMaxScore(int upTo) throws IOException {
	return Float.POSITIVE_INFINITY;
	}
	}
	}