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* 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 org.apache.lucene.util.BytesRef;
import org.elasticsearch.Version;
import org.elasticsearch.common.bytes.BytesArray;
import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.common.text.BytesText;
import org.elasticsearch.common.text.Text;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.search.aggregations.AggregationStreams;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.InternalAggregations;
import org.elasticsearch.search.aggregations.bucket.BucketStreamContext;
import org.elasticsearch.search.aggregations.bucket.BucketStreams;
import org.elasticsearch.search.aggregations.bucket.significant.heuristics.SignificanceHeuristic;
import org.elasticsearch.search.aggregations.bucket.significant.heuristics.SignificanceHeuristicStreams;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
/**
*
*/
public class SignificantStringTerms extends InternalSignificantTerms {
public static final InternalAggregation.Type TYPE = new Type("significant_terms", "sigsterms");
public static final AggregationStreams.Stream STREAM = new AggregationStreams.Stream() {
@Override
public SignificantStringTerms readResult(StreamInput in) throws IOException {
SignificantStringTerms buckets = new SignificantStringTerms();
buckets.readFrom(in);
return buckets;
}
};
private final static BucketStreams.Stream<Bucket> BUCKET_STREAM = new BucketStreams.Stream<Bucket>() {
@Override
public Bucket readResult(StreamInput in, BucketStreamContext context) throws IOException {
Bucket buckets = new Bucket((long) context.attributes().get("subsetSize"), (long) context.attributes().get("supersetSize"));
buckets.readFrom(in);
return buckets;
}
@Override
public BucketStreamContext getBucketStreamContext(Bucket bucket) {
BucketStreamContext context = new BucketStreamContext();
Map<String, Object> attributes = new HashMap<>();
attributes.put("subsetSize", bucket.subsetSize);
attributes.put("supersetSize", bucket.supersetSize);
context.attributes(attributes);
return context;
}
};
public static void registerStream() {
AggregationStreams.registerStream(STREAM, TYPE.stream());
BucketStreams.registerStream(BUCKET_STREAM, TYPE.stream());
}
public static void registerStreams() {
AggregationStreams.registerStream(STREAM, TYPE.stream());
}
public static class Bucket extends InternalSignificantTerms.Bucket {
BytesRef termBytes;
public Bucket(long subsetSize, long supersetSize) {
// for serialization
super(subsetSize, supersetSize);
}
public Bucket(BytesRef term, long subsetDf, long subsetSize, long supersetDf, long supersetSize, InternalAggregations aggregations) {
super(subsetDf, subsetSize, supersetDf, supersetSize, aggregations);
this.termBytes = term;
}
@Override
public Text getKeyAsText() {
return new BytesText(new BytesArray(termBytes));
}
@Override
public Number getKeyAsNumber() {
// this method is needed for scripted numeric aggregations
return Double.parseDouble(termBytes.utf8ToString());
}
@Override
int compareTerm(SignificantTerms.Bucket other) {
return BytesRef.getUTF8SortedAsUnicodeComparator().compare(termBytes, ((Bucket) other).termBytes);
}
@Override
public String getKey() {
return termBytes.utf8ToString();
}
@Override
Bucket newBucket(long subsetDf, long subsetSize, long supersetDf, long supersetSize, InternalAggregations aggregations) {
return new Bucket(termBytes, subsetDf, subsetSize, supersetDf, supersetSize, aggregations);
}
@Override
public void readFrom(StreamInput in) throws IOException {
termBytes = in.readBytesRef();
subsetDf = in.readVLong();
supersetDf = in.readVLong();
aggregations = InternalAggregations.readAggregations(in);
}
@Override
public void writeTo(StreamOutput out) throws IOException {
out.writeBytesRef(termBytes);
out.writeVLong(subsetDf);
out.writeVLong(supersetDf);
aggregations.writeTo(out);
}
@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.utf8Field(CommonFields.KEY, termBytes);
builder.field(CommonFields.DOC_COUNT, getDocCount());
builder.field("score", score);
builder.field("bg_count", supersetDf);
aggregations.toXContentInternal(builder, params);
builder.endObject();
return builder;
}
}
SignificantStringTerms() {} // for serialization
public SignificantStringTerms(long subsetSize, long supersetSize, String name, int requiredSize,
long minDocCount, SignificanceHeuristic significanceHeuristic, List<InternalSignificantTerms.Bucket> buckets, Map<String, Object> metaData) {
super(subsetSize, supersetSize, name, requiredSize, minDocCount, significanceHeuristic, buckets, metaData);
}
@Override
public Type type() {
return TYPE;
}
@Override
InternalSignificantTerms newAggregation(long subsetSize, long supersetSize,
List<InternalSignificantTerms.Bucket> buckets) {
return new SignificantStringTerms(subsetSize, supersetSize, getName(), requiredSize, minDocCount, significanceHeuristic, buckets, getMetaData());
}
@Override
protected void doReadFrom(StreamInput in) throws IOException {
this.requiredSize = readSize(in);
this.minDocCount = in.readVLong();
this.subsetSize = in.readVLong();
this.supersetSize = in.readVLong();
significanceHeuristic = SignificanceHeuristicStreams.read(in);
int size = in.readVInt();
List<InternalSignificantTerms.Bucket> buckets = new ArrayList<>(size);
for (int i = 0; i < size; i++) {
Bucket bucket = new Bucket(subsetSize, supersetSize);
bucket.readFrom(in);
bucket.updateScore(significanceHeuristic);
buckets.add(bucket);
}
this.buckets = buckets;
this.bucketMap = null;
}
@Override
protected void doWriteTo(StreamOutput out) throws IOException {
writeSize(requiredSize, out);
out.writeVLong(minDocCount);
out.writeVLong(subsetSize);
out.writeVLong(supersetSize);
if (out.getVersion().onOrAfter(Version.V_1_3_0)) {
significanceHeuristic.writeTo(out);
}
out.writeVInt(buckets.size());
for (InternalSignificantTerms.Bucket bucket : buckets) {
bucket.writeTo(out);
}
}
@Override
public XContentBuilder doXContentBody(XContentBuilder builder, Params params) throws IOException {
builder.field("doc_count", subsetSize);
builder.startArray(CommonFields.BUCKETS);
for (InternalSignificantTerms.Bucket bucket : buckets) {
//There is a condition (presumably when only one shard has a bucket?) where reduce is not called
// and I end up with buckets that contravene the user's min_doc_count criteria in my reducer
if (bucket.subsetDf >= minDocCount) {
bucket.toXContent(builder, params);
}
}
builder.endArray();
return builder;
}
}