BlendedTermQuery

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 * 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
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package org.apache.lucene.queries;

import org.apache.lucene.index.*;
import org.apache.lucene.search.*;

import java.io.IOException;
import java.util.Arrays;
import java.util.List;

/**
 */
public abstract class BlendedTermQuery extends Query {

    private final String term;
    private final String[] fields;
    private final float bias;

    public BlendedTermQuery(String[] fields, String term) {
        this(fields, term, 0.0f);
    }

    public BlendedTermQuery(String[] fields, String term, float bias) {
        if (fields == null) {
            throw new IllegalArgumentException("fields must not be null");
        }
        if (term == null) {
            throw new IllegalArgumentException("term must note be null");
        }
        this.fields = fields;
        this.bias = bias;
        this.term = term;
    }

    @Override
    public Query rewrite(IndexReader reader) throws IOException {
        IndexReaderContext context = reader.getContext();
        Term[] terms = new Term[fields.length];
        TermContext[] ctx = new TermContext[fields.length];
        for (int i = 0; i < terms.length; i++) {
            terms[i] = new Term(fields[i], term);
            ctx[i] = TermContext.build(context, terms[i]);
        }
        blend(ctx, reader.maxDoc());
        return topLevelQuery(terms, ctx);
    }

    protected abstract Query topLevelQuery(Term[] terms, TermContext[] ctx);

    protected void blend(TermContext[] contexts, int maxDoc) {
        long sum = 0;
        int numZeroDF = 0;
        for (TermContext ctx : contexts) {
            int df = ctx.docFreq();
            sum += df;
            if (df == 0) {
                numZeroDF++;
            }
        }
        if (sum == 0) {
            return; // we are done that term doesn't exist at all
        }
        final long avg = sum / (contexts.length - numZeroDF);

        for (int i = 0; i < contexts.length; i++) {
            int df = contexts[i].docFreq();
            if (df == 0) {
                continue;
            }
            long blendedIDF = avg + ((long) (bias * (df - avg)));
            contexts[i].setDocFreq((int) Math.min(maxDoc, blendedIDF));
            contexts[i] = adjustTTF(contexts[i]);
        }
    }

    private TermContext adjustTTF(TermContext termContext) {
        if (termContext.docFreq() > termContext.totalTermFreq()) {
            TermContext newTermContext = new TermContext(termContext.topReaderContext);
            List<AtomicReaderContext> leaves = termContext.topReaderContext.leaves();
            final int len;
            if (leaves == null) {
                len = 1;
            } else {
                len = leaves.size();
            }
            int df = termContext.docFreq();
            long ttf = Math.max(df, termContext.totalTermFreq());
            for (int i = 0; i < len; i++) {
                TermState termState = termContext.get(i);
                if (termState == null) {
                    continue;
                }
                newTermContext.register(termState, i, df, ttf);
                df = 0;
                ttf = 0;
            }
            return newTermContext;
        }
        return termContext;
    }

    @Override
    public String toString(String field) {
        return "blended(\"" + term + "\", fields: " + Arrays.toString(fields) + ")";

    }

    @Override
    public boolean equals(Object o) {
        if (this == o) return true;
        if (o == null || getClass() != o.getClass()) return false;
        if (!super.equals(o)) return false;

        BlendedTermQuery that = (BlendedTermQuery) o;

        if (Float.compare(that.bias, bias) != 0) return false;
        if (!Arrays.equals(fields, that.fields)) return false;
        if (!term.equals(that.term)) return false;

        return true;
    }

    @Override
    public int hashCode() {
        int result = super.hashCode();
        result = 31 * result + term.hashCode();
        result = 31 * result + Arrays.hashCode(fields);
        result = 31 * result + Float.floatToIntBits(bias);
        return result;
    }

    public static BlendedTermQuery booleanBlendedQuery(String[] fields, String term, float bias, final boolean disableCoord) {
        return new BlendedTermQuery(fields, term, bias) {
            protected Query topLevelQuery(Term[] terms, TermContext[] ctx) {
                BooleanQuery query = new BooleanQuery(disableCoord);
                for (int i = 0; i < terms.length; i++) {
                    query.add(new TermQuery(terms[i], ctx[i]), BooleanClause.Occur.SHOULD);
                }
                return query;
            }
        };
    }

    public static BlendedTermQuery dismaxBlendedQuery(String[] fields, String term, float bias, final float tieBreakerMultiplier ) {
        return new BlendedTermQuery(fields, term, bias) {
            protected Query topLevelQuery(Term[] terms, TermContext[] ctx) {
                DisjunctionMaxQuery query = new DisjunctionMaxQuery(tieBreakerMultiplier);
                for (int i = 0; i < terms.length; i++) {
                    query.add(new TermQuery(terms[i], ctx[i]));
                }
                return query;
            }
        };
    }
}