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* 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.search.aggregations.bucket.significant;
import com.google.common.collect.Maps;
import org.elasticsearch.common.io.stream.Streamable;
import org.elasticsearch.common.xcontent.ToXContent;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.InternalAggregations;
import org.elasticsearch.search.aggregations.bucket.significant.heuristics.SignificanceHeuristic;
import java.util.*;
/**
*
*/
public abstract class InternalSignificantTerms extends InternalAggregation implements SignificantTerms, ToXContent, Streamable {
protected SignificanceHeuristic significanceHeuristic;
protected int requiredSize;
protected long minDocCount;
protected List<Bucket> buckets;
protected Map<String, Bucket> bucketMap;
protected long subsetSize;
protected long supersetSize;
protected InternalSignificantTerms() {} // for serialization
@SuppressWarnings("PMD.ConstructorCallsOverridableMethod")
public static abstract class Bucket extends SignificantTerms.Bucket {
long bucketOrd;
protected InternalAggregations aggregations;
double score;
protected Bucket(long subsetSize, long supersetSize) {
// for serialization
super(subsetSize, supersetSize);
}
protected Bucket(long subsetDf, long subsetSize, long supersetDf, long supersetSize, InternalAggregations aggregations) {
super(subsetDf, subsetSize, supersetDf, supersetSize);
this.aggregations = aggregations;
}
@Override
public long getSubsetDf() {
return subsetDf;
}
@Override
public long getSupersetDf() {
return supersetDf;
}
@Override
public long getSupersetSize() {
return supersetSize;
}
@Override
public long getSubsetSize() {
return subsetSize;
}
public void updateScore(SignificanceHeuristic significanceHeuristic) {
score = significanceHeuristic.getScore(subsetDf, subsetSize, supersetDf, supersetSize);
}
@Override
public long getDocCount() {
return subsetDf;
}
@Override
public Aggregations getAggregations() {
return aggregations;
}
public Bucket reduce(List<? extends Bucket> buckets, ReduceContext context) {
long subsetDf = 0;
long supersetDf = 0;
List<InternalAggregations> aggregationsList = new ArrayList<>(buckets.size());
for (Bucket bucket : buckets) {
subsetDf += bucket.subsetDf;
supersetDf += bucket.supersetDf;
aggregationsList.add(bucket.aggregations);
}
InternalAggregations aggs = InternalAggregations.reduce(aggregationsList, context);
return newBucket(subsetDf, subsetSize, supersetDf, supersetSize, aggs);
}
abstract Bucket newBucket(long subsetDf, long subsetSize, long supersetDf, long supersetSize, InternalAggregations aggregations);
@Override
public double getSignificanceScore() {
return score;
}
}
protected InternalSignificantTerms(long subsetSize, long supersetSize, String name, int requiredSize, long minDocCount, SignificanceHeuristic significanceHeuristic, List<Bucket> buckets, Map<String, Object> metaData) {
super(name, metaData);
this.requiredSize = requiredSize;
this.minDocCount = minDocCount;
this.buckets = buckets;
this.subsetSize = subsetSize;
this.supersetSize = supersetSize;
this.significanceHeuristic = significanceHeuristic;
}
@Override
public Iterator<SignificantTerms.Bucket> iterator() {
Object o = buckets.iterator();
return (Iterator<SignificantTerms.Bucket>) o;
}
@Override
public List<SignificantTerms.Bucket> getBuckets() {
Object o = buckets;
return (List<SignificantTerms.Bucket>) o;
}
@Override
public SignificantTerms.Bucket getBucketByKey(String term) {
if (bucketMap == null) {
bucketMap = Maps.newHashMapWithExpectedSize(buckets.size());
for (Bucket bucket : buckets) {
bucketMap.put(bucket.getKey(), bucket);
}
}
return bucketMap.get(term);
}
@Override
public InternalAggregation reduce(ReduceContext reduceContext) {
List<InternalAggregation> aggregations = reduceContext.aggregations();
long globalSubsetSize = 0;
long globalSupersetSize = 0;
// Compute the overall result set size and the corpus size using the
// top-level Aggregations from each shard
for (InternalAggregation aggregation : aggregations) {
InternalSignificantTerms terms = (InternalSignificantTerms) aggregation;
globalSubsetSize += terms.subsetSize;
globalSupersetSize += terms.supersetSize;
}
Map<String, List<InternalSignificantTerms.Bucket>> buckets = new HashMap<>();
for (InternalAggregation aggregation : aggregations) {
InternalSignificantTerms terms = (InternalSignificantTerms) aggregation;
for (Bucket bucket : terms.buckets) {
List<Bucket> existingBuckets = buckets.get(bucket.getKey());
if (existingBuckets == null) {
existingBuckets = new ArrayList<>(aggregations.size());
buckets.put(bucket.getKey(), existingBuckets);
}
// Adjust the buckets with the global stats representing the
// total size of the pots from which the stats are drawn
existingBuckets.add(bucket.newBucket(bucket.getSubsetDf(), globalSubsetSize, bucket.getSupersetDf(), globalSupersetSize, bucket.aggregations));
}
}
final int size = Math.min(requiredSize, buckets.size());
BucketSignificancePriorityQueue ordered = new BucketSignificancePriorityQueue(size);
for (Map.Entry<String, List<Bucket>> entry : buckets.entrySet()) {
List<Bucket> sameTermBuckets = entry.getValue();
final Bucket b = sameTermBuckets.get(0).reduce(sameTermBuckets, reduceContext);
b.updateScore(significanceHeuristic);
if ((b.score > 0) && (b.subsetDf >= minDocCount)) {
ordered.insertWithOverflow(b);
}
}
Bucket[] list = new Bucket[ordered.size()];
for (int i = ordered.size() - 1; i >= 0; i--) {
list[i] = (Bucket) ordered.pop();
}
return newAggregation(globalSubsetSize, globalSupersetSize, Arrays.asList(list));
}
abstract InternalSignificantTerms newAggregation(long subsetSize, long supersetSize, List<Bucket> buckets);
}