org.elasticsearch.search.aggregations.bucket.terms.InternalSignificantTerms Maven / Gradle / Ivy
/*
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
* or more contributor license agreements. Licensed under the Elastic License
* 2.0 and the Server Side Public License, v 1; you may not use this file except
* in compliance with, at your election, the Elastic License 2.0 or the Server
* Side Public License, v 1.
*/
package org.elasticsearch.search.aggregations.bucket.terms;
import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.search.DocValueFormat;
import org.elasticsearch.search.aggregations.AggregationReduceContext;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.Aggregator;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.InternalAggregations;
import org.elasticsearch.search.aggregations.InternalMultiBucketAggregation;
import org.elasticsearch.search.aggregations.bucket.terms.heuristic.SignificanceHeuristic;
import org.elasticsearch.search.aggregations.support.SamplingContext;
import org.elasticsearch.xcontent.XContentBuilder;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Objects;
/**
* Result of the significant terms aggregation.
*/
public abstract class InternalSignificantTerms, B extends InternalSignificantTerms.Bucket>
extends InternalMultiBucketAggregation
implements
SignificantTerms {
public static final String SCORE = "score";
public static final String BG_COUNT = "bg_count";
@SuppressWarnings("PMD.ConstructorCallsOverridableMethod")
public abstract static class Bucket> extends InternalMultiBucketAggregation.InternalBucket
implements
SignificantTerms.Bucket {
/**
* Reads a bucket. Should be a constructor reference.
*/
@FunctionalInterface
public interface Reader> {
B read(StreamInput in, long subsetSize, long supersetSize, DocValueFormat format) throws IOException;
}
long subsetDf;
long subsetSize;
long supersetDf;
long supersetSize;
/**
* Ordinal of the bucket while it is being built. Not used after it is
* returned from {@link Aggregator#buildAggregations(long[])} and not
* serialized.
*/
transient long bucketOrd;
double score;
protected InternalAggregations aggregations;
final transient DocValueFormat format;
protected Bucket(
long subsetDf,
long subsetSize,
long supersetDf,
long supersetSize,
InternalAggregations aggregations,
DocValueFormat format
) {
this.subsetSize = subsetSize;
this.supersetSize = supersetSize;
this.subsetDf = subsetDf;
this.supersetDf = supersetDf;
this.aggregations = aggregations;
this.format = format;
}
/**
* Read from a stream.
*/
protected Bucket(StreamInput in, long subsetSize, long supersetSize, DocValueFormat format) {
this.subsetSize = subsetSize;
this.supersetSize = supersetSize;
this.format = format;
}
@Override
public long getSubsetDf() {
return subsetDf;
}
@Override
public long getSupersetDf() {
return supersetDf;
}
@Override
public long getSupersetSize() {
return supersetSize;
}
@Override
public long getSubsetSize() {
return subsetSize;
}
// TODO we should refactor to remove this, since buckets should be immutable after they are generated.
// This can lead to confusing bugs if the bucket is re-created (via createBucket() or similar) without
// the score
void updateScore(SignificanceHeuristic significanceHeuristic) {
score = significanceHeuristic.getScore(subsetDf, subsetSize, supersetDf, supersetSize);
}
@Override
public long getDocCount() {
return subsetDf;
}
@Override
public Aggregations getAggregations() {
return aggregations;
}
@Override
public double getSignificanceScore() {
return score;
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
Bucket that = (Bucket) o;
return Double.compare(that.score, score) == 0
&& Objects.equals(aggregations, that.aggregations)
&& Objects.equals(format, that.format);
}
@Override
public int hashCode() {
return Objects.hash(getClass(), aggregations, score, format);
}
@Override
public final XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
keyToXContent(builder);
builder.field(CommonFields.DOC_COUNT.getPreferredName(), getDocCount());
builder.field(SCORE, score);
builder.field(BG_COUNT, supersetDf);
aggregations.toXContentInternal(builder, params);
builder.endObject();
return builder;
}
protected abstract XContentBuilder keyToXContent(XContentBuilder builder) throws IOException;
}
protected final int requiredSize;
protected final long minDocCount;
protected InternalSignificantTerms(String name, int requiredSize, long minDocCount, Map metadata) {
super(name, metadata);
this.requiredSize = requiredSize;
this.minDocCount = minDocCount;
}
/**
* Read from a stream.
*/
protected InternalSignificantTerms(StreamInput in) throws IOException {
super(in);
requiredSize = readSize(in);
minDocCount = in.readVLong();
}
protected final void doWriteTo(StreamOutput out) throws IOException {
writeSize(requiredSize, out);
out.writeVLong(minDocCount);
writeTermTypeInfoTo(out);
}
protected abstract void writeTermTypeInfoTo(StreamOutput out) throws IOException;
@Override
public abstract List getBuckets();
@Override
public InternalAggregation reduce(List aggregations, AggregationReduceContext reduceContext) {
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) {
@SuppressWarnings("unchecked")
InternalSignificantTerms terms = (InternalSignificantTerms) aggregation;
globalSubsetSize += terms.getSubsetSize();
globalSupersetSize += terms.getSupersetSize();
}
Map> buckets = new HashMap<>();
for (InternalAggregation aggregation : aggregations) {
@SuppressWarnings("unchecked")
InternalSignificantTerms terms = (InternalSignificantTerms) aggregation;
for (B bucket : terms.getBuckets()) {
List existingBuckets = buckets.get(bucket.getKeyAsString());
if (existingBuckets == null) {
existingBuckets = new ArrayList<>(aggregations.size());
buckets.put(bucket.getKeyAsString(), existingBuckets);
}
// Adjust the buckets with the global stats representing the
// total size of the pots from which the stats are drawn
existingBuckets.add(
createBucket(
bucket.getSubsetDf(),
globalSubsetSize,
bucket.getSupersetDf(),
globalSupersetSize,
bucket.aggregations,
bucket
)
);
}
}
SignificanceHeuristic heuristic = getSignificanceHeuristic().rewrite(reduceContext);
final int size = reduceContext.isFinalReduce() == false ? buckets.size() : Math.min(requiredSize, buckets.size());
BucketSignificancePriorityQueue ordered = new BucketSignificancePriorityQueue<>(size);
for (Map.Entry> entry : buckets.entrySet()) {
List sameTermBuckets = entry.getValue();
final B b = reduceBucket(sameTermBuckets, reduceContext);
b.updateScore(heuristic);
if (((b.score > 0) && (b.subsetDf >= minDocCount)) || reduceContext.isFinalReduce() == false) {
B removed = ordered.insertWithOverflow(b);
if (removed == null) {
reduceContext.consumeBucketsAndMaybeBreak(1);
} else {
reduceContext.consumeBucketsAndMaybeBreak(-countInnerBucket(removed));
}
} else {
reduceContext.consumeBucketsAndMaybeBreak(-countInnerBucket(b));
}
}
B[] list = createBucketsArray(ordered.size());
for (int i = ordered.size() - 1; i >= 0; i--) {
list[i] = ordered.pop();
}
return create(globalSubsetSize, globalSupersetSize, Arrays.asList(list));
}
@Override
public InternalAggregation finalizeSampling(SamplingContext samplingContext) {
long supersetSize = samplingContext.scaleUp(getSupersetSize());
long subsetSize = samplingContext.scaleUp(getSubsetSize());
return create(
subsetSize,
supersetSize,
getBuckets().stream()
.map(
b -> createBucket(
samplingContext.scaleUp(b.subsetDf),
subsetSize,
samplingContext.scaleUp(b.supersetDf),
supersetSize,
InternalAggregations.finalizeSampling(b.aggregations, samplingContext),
b
)
)
.toList()
);
}
@Override
protected B reduceBucket(List buckets, AggregationReduceContext context) {
assert buckets.size() > 0;
long subsetDf = 0;
long supersetDf = 0;
List aggregationsList = new ArrayList<>(buckets.size());
for (B bucket : buckets) {
subsetDf += bucket.subsetDf;
supersetDf += bucket.supersetDf;
aggregationsList.add(bucket.aggregations);
}
InternalAggregations aggs = InternalAggregations.reduce(aggregationsList, context);
return createBucket(subsetDf, buckets.get(0).subsetSize, supersetDf, buckets.get(0).supersetSize, aggs, buckets.get(0));
}
abstract B createBucket(
long subsetDf,
long subsetSize,
long supersetDf,
long supersetSize,
InternalAggregations aggregations,
B prototype
);
protected abstract A create(long subsetSize, long supersetSize, List buckets);
/**
* Create an array to hold some buckets. Used in collecting the results.
*/
protected abstract B[] createBucketsArray(int size);
protected abstract long getSubsetSize();
protected abstract long getSupersetSize();
protected abstract SignificanceHeuristic getSignificanceHeuristic();
@Override
public int hashCode() {
return Objects.hash(super.hashCode(), minDocCount, requiredSize);
}
@Override
public boolean equals(Object obj) {
if (this == obj) return true;
if (obj == null || getClass() != obj.getClass()) return false;
if (super.equals(obj) == false) return false;
InternalSignificantTerms that = (InternalSignificantTerms) obj;
return Objects.equals(minDocCount, that.minDocCount) && Objects.equals(requiredSize, that.requiredSize);
}
}