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Elasticsearch subproject :client:rest-high-level
/*
* 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.client.ml.job.results;
import org.elasticsearch.client.common.TimeUtil;
import org.elasticsearch.client.ml.job.config.Job;
import org.elasticsearch.xcontent.ConstructingObjectParser;
import org.elasticsearch.xcontent.ObjectParser.ValueType;
import org.elasticsearch.xcontent.ParseField;
import org.elasticsearch.xcontent.ToXContentObject;
import org.elasticsearch.xcontent.XContentBuilder;
import java.io.IOException;
import java.util.Date;
import java.util.Objects;
public class BucketInfluencer implements ToXContentObject {
/**
* Result type
*/
public static final String RESULT_TYPE_VALUE = "bucket_influencer";
public static final ParseField RESULT_TYPE_FIELD = new ParseField(RESULT_TYPE_VALUE);
/**
* Field names
*/
public static final ParseField INFLUENCER_FIELD_NAME = new ParseField("influencer_field_name");
public static final ParseField INITIAL_ANOMALY_SCORE = new ParseField("initial_anomaly_score");
public static final ParseField ANOMALY_SCORE = new ParseField("anomaly_score");
public static final ParseField RAW_ANOMALY_SCORE = new ParseField("raw_anomaly_score");
public static final ParseField PROBABILITY = new ParseField("probability");
public static final ParseField BUCKET_SPAN = new ParseField("bucket_span");
public static final ConstructingObjectParser PARSER = new ConstructingObjectParser<>(
RESULT_TYPE_FIELD.getPreferredName(),
true,
a -> new BucketInfluencer((String) a[0], (Date) a[1], (long) a[2])
);
static {
PARSER.declareString(ConstructingObjectParser.constructorArg(), Job.ID);
PARSER.declareField(
ConstructingObjectParser.constructorArg(),
(p) -> TimeUtil.parseTimeField(p, Result.TIMESTAMP.getPreferredName()),
Result.TIMESTAMP,
ValueType.VALUE
);
PARSER.declareLong(ConstructingObjectParser.constructorArg(), BUCKET_SPAN);
PARSER.declareString((bucketInfluencer, s) -> {}, Result.RESULT_TYPE);
PARSER.declareString(BucketInfluencer::setInfluencerFieldName, INFLUENCER_FIELD_NAME);
PARSER.declareDouble(BucketInfluencer::setInitialAnomalyScore, INITIAL_ANOMALY_SCORE);
PARSER.declareDouble(BucketInfluencer::setAnomalyScore, ANOMALY_SCORE);
PARSER.declareDouble(BucketInfluencer::setRawAnomalyScore, RAW_ANOMALY_SCORE);
PARSER.declareDouble(BucketInfluencer::setProbability, PROBABILITY);
PARSER.declareBoolean(BucketInfluencer::setIsInterim, Result.IS_INTERIM);
}
private final String jobId;
private String influenceField;
private double initialAnomalyScore;
private double anomalyScore;
private double rawAnomalyScore;
private double probability;
private boolean isInterim;
private final Date timestamp;
private final long bucketSpan;
BucketInfluencer(String jobId, Date timestamp, long bucketSpan) {
this.jobId = jobId;
this.timestamp = Objects.requireNonNull(timestamp);
this.bucketSpan = bucketSpan;
}
@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.field(Job.ID.getPreferredName(), jobId);
builder.field(Result.RESULT_TYPE.getPreferredName(), RESULT_TYPE_VALUE);
if (influenceField != null) {
builder.field(INFLUENCER_FIELD_NAME.getPreferredName(), influenceField);
}
builder.field(INITIAL_ANOMALY_SCORE.getPreferredName(), initialAnomalyScore);
builder.field(ANOMALY_SCORE.getPreferredName(), anomalyScore);
builder.field(RAW_ANOMALY_SCORE.getPreferredName(), rawAnomalyScore);
builder.field(PROBABILITY.getPreferredName(), probability);
builder.timeField(Result.TIMESTAMP.getPreferredName(), Result.TIMESTAMP.getPreferredName() + "_string", timestamp.getTime());
builder.field(BUCKET_SPAN.getPreferredName(), bucketSpan);
builder.field(Result.IS_INTERIM.getPreferredName(), isInterim);
builder.endObject();
return builder;
}
public String getJobId() {
return jobId;
}
public double getProbability() {
return probability;
}
void setProbability(double probability) {
this.probability = probability;
}
public String getInfluencerFieldName() {
return influenceField;
}
void setInfluencerFieldName(String fieldName) {
this.influenceField = fieldName;
}
public double getInitialAnomalyScore() {
return initialAnomalyScore;
}
void setInitialAnomalyScore(double influenceScore) {
this.initialAnomalyScore = influenceScore;
}
public double getAnomalyScore() {
return anomalyScore;
}
void setAnomalyScore(double score) {
anomalyScore = score;
}
public double getRawAnomalyScore() {
return rawAnomalyScore;
}
void setRawAnomalyScore(double score) {
rawAnomalyScore = score;
}
void setIsInterim(boolean isInterim) {
this.isInterim = isInterim;
}
public boolean isInterim() {
return isInterim;
}
public Date getTimestamp() {
return timestamp;
}
@Override
public int hashCode() {
return Objects.hash(
influenceField,
initialAnomalyScore,
anomalyScore,
rawAnomalyScore,
probability,
isInterim,
timestamp,
jobId,
bucketSpan
);
}
@Override
public boolean equals(Object obj) {
if (this == obj) {
return true;
}
if (obj == null) {
return false;
}
if (getClass() != obj.getClass()) {
return false;
}
BucketInfluencer other = (BucketInfluencer) obj;
return Objects.equals(influenceField, other.influenceField)
&& Double.compare(initialAnomalyScore, other.initialAnomalyScore) == 0
&& Double.compare(anomalyScore, other.anomalyScore) == 0
&& Double.compare(rawAnomalyScore, other.rawAnomalyScore) == 0
&& Double.compare(probability, other.probability) == 0
&& Objects.equals(isInterim, other.isInterim)
&& Objects.equals(timestamp, other.timestamp)
&& Objects.equals(jobId, other.jobId)
&& bucketSpan == other.bucketSpan;
}
}
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