co.elastic.clients.elasticsearch.ml.Anomaly Maven / Gradle / Ivy
Show all versions of elasticsearch-java Show documentation
/*
* Licensed to Elasticsearch B.V. under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch B.V. 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 co.elastic.clients.elasticsearch.ml;
import co.elastic.clients.json.JsonpDeserializable;
import co.elastic.clients.json.JsonpDeserializer;
import co.elastic.clients.json.JsonpMapper;
import co.elastic.clients.json.JsonpSerializable;
import co.elastic.clients.json.JsonpUtils;
import co.elastic.clients.json.ObjectBuilderDeserializer;
import co.elastic.clients.json.ObjectDeserializer;
import co.elastic.clients.util.ApiTypeHelper;
import co.elastic.clients.util.ObjectBuilder;
import co.elastic.clients.util.WithJsonObjectBuilderBase;
import jakarta.json.stream.JsonGenerator;
import java.lang.Boolean;
import java.lang.Double;
import java.lang.Integer;
import java.lang.Long;
import java.lang.String;
import java.util.List;
import java.util.Objects;
import java.util.function.Function;
import javax.annotation.Nullable;
//----------------------------------------------------------------
// THIS CODE IS GENERATED. MANUAL EDITS WILL BE LOST.
//----------------------------------------------------------------
//
// This code is generated from the Elasticsearch API specification
// at https://github.com/elastic/elasticsearch-specification
//
// Manual updates to this file will be lost when the code is
// re-generated.
//
// If you find a property that is missing or wrongly typed, please
// open an issue or a PR on the API specification repository.
//
//----------------------------------------------------------------
// typedef: ml._types.Anomaly
/**
*
* @see API
* specification
*/
@JsonpDeserializable
public class Anomaly implements JsonpSerializable {
private final List actual;
@Nullable
private final AnomalyExplanation anomalyScoreExplanation;
private final long bucketSpan;
@Nullable
private final String byFieldName;
@Nullable
private final String byFieldValue;
private final List causes;
private final int detectorIndex;
@Nullable
private final String fieldName;
@Nullable
private final String function;
@Nullable
private final String functionDescription;
@Nullable
private final GeoResults geoResults;
private final List influencers;
private final double initialRecordScore;
private final boolean isInterim;
private final String jobId;
@Nullable
private final String overFieldName;
@Nullable
private final String overFieldValue;
@Nullable
private final String partitionFieldName;
@Nullable
private final String partitionFieldValue;
private final double probability;
private final double recordScore;
private final String resultType;
private final long timestamp;
private final List typical;
// ---------------------------------------------------------------------------------------------
private Anomaly(Builder builder) {
this.actual = ApiTypeHelper.unmodifiable(builder.actual);
this.anomalyScoreExplanation = builder.anomalyScoreExplanation;
this.bucketSpan = ApiTypeHelper.requireNonNull(builder.bucketSpan, this, "bucketSpan");
this.byFieldName = builder.byFieldName;
this.byFieldValue = builder.byFieldValue;
this.causes = ApiTypeHelper.unmodifiable(builder.causes);
this.detectorIndex = ApiTypeHelper.requireNonNull(builder.detectorIndex, this, "detectorIndex");
this.fieldName = builder.fieldName;
this.function = builder.function;
this.functionDescription = builder.functionDescription;
this.geoResults = builder.geoResults;
this.influencers = ApiTypeHelper.unmodifiable(builder.influencers);
this.initialRecordScore = ApiTypeHelper.requireNonNull(builder.initialRecordScore, this, "initialRecordScore");
this.isInterim = ApiTypeHelper.requireNonNull(builder.isInterim, this, "isInterim");
this.jobId = ApiTypeHelper.requireNonNull(builder.jobId, this, "jobId");
this.overFieldName = builder.overFieldName;
this.overFieldValue = builder.overFieldValue;
this.partitionFieldName = builder.partitionFieldName;
this.partitionFieldValue = builder.partitionFieldValue;
this.probability = ApiTypeHelper.requireNonNull(builder.probability, this, "probability");
this.recordScore = ApiTypeHelper.requireNonNull(builder.recordScore, this, "recordScore");
this.resultType = ApiTypeHelper.requireNonNull(builder.resultType, this, "resultType");
this.timestamp = ApiTypeHelper.requireNonNull(builder.timestamp, this, "timestamp");
this.typical = ApiTypeHelper.unmodifiable(builder.typical);
}
public static Anomaly of(Function> fn) {
return fn.apply(new Builder()).build();
}
/**
* The actual value for the bucket.
*
* API name: {@code actual}
*/
public final List actual() {
return this.actual;
}
/**
* Information about the factors impacting the initial anomaly score.
*
* API name: {@code anomaly_score_explanation}
*/
@Nullable
public final AnomalyExplanation anomalyScoreExplanation() {
return this.anomalyScoreExplanation;
}
/**
* Required - The length of the bucket in seconds. This value matches the
* bucket_span that is specified in the job.
*
* API name: {@code bucket_span}
*/
public final long bucketSpan() {
return this.bucketSpan;
}
/**
* The field used to split the data. In particular, this property is used for
* analyzing the splits with respect to their own history. It is used for
* finding unusual values in the context of the split.
*
* API name: {@code by_field_name}
*/
@Nullable
public final String byFieldName() {
return this.byFieldName;
}
/**
* The value of by_field_name.
*
* API name: {@code by_field_value}
*/
@Nullable
public final String byFieldValue() {
return this.byFieldValue;
}
/**
* For population analysis, an over field must be specified in the detector.
* This property contains an array of anomaly records that are the causes for
* the anomaly that has been identified for the over field. This sub-resource
* contains the most anomalous records for the over_field_name. For
* scalability reasons, a maximum of the 10 most significant causes of the
* anomaly are returned. As part of the core analytical modeling, these
* low-level anomaly records are aggregated for their parent over field record.
* The causes resource contains similar elements to the record
* resource, namely actual, typical,
* geo_results.actual_point,
* geo_results.typical_point, *_field_name and
* *_field_value. Probability and scores are not applicable to
* causes.
*
* API name: {@code causes}
*/
public final List causes() {
return this.causes;
}
/**
* Required - A unique identifier for the detector.
*
* API name: {@code detector_index}
*/
public final int detectorIndex() {
return this.detectorIndex;
}
/**
* Certain functions require a field to operate on, for example,
* sum(). For those functions, this value is the name of the field
* to be analyzed.
*
* API name: {@code field_name}
*/
@Nullable
public final String fieldName() {
return this.fieldName;
}
/**
* The function in which the anomaly occurs, as specified in the detector
* configuration. For example, max.
*
* API name: {@code function}
*/
@Nullable
public final String function() {
return this.function;
}
/**
* The description of the function in which the anomaly occurs, as specified in
* the detector configuration.
*
* API name: {@code function_description}
*/
@Nullable
public final String functionDescription() {
return this.functionDescription;
}
/**
* If the detector function is lat_long, this object contains comma
* delimited strings for the latitude and longitude of the actual and typical
* values.
*
* API name: {@code geo_results}
*/
@Nullable
public final GeoResults geoResults() {
return this.geoResults;
}
/**
* If influencers were specified in the detector configuration, this array
* contains influencers that contributed to or were to blame for an anomaly.
*
* API name: {@code influencers}
*/
public final List influencers() {
return this.influencers;
}
/**
* Required - A normalized score between 0-100, which is based on the
* probability of the anomalousness of this record. This is the initial value
* that was calculated at the time the bucket was processed.
*
* API name: {@code initial_record_score}
*/
public final double initialRecordScore() {
return this.initialRecordScore;
}
/**
* Required - If true, this is an interim result. In other words, the results
* are calculated based on partial input data.
*
* API name: {@code is_interim}
*/
public final boolean isInterim() {
return this.isInterim;
}
/**
* Required - Identifier for the anomaly detection job.
*
* API name: {@code job_id}
*/
public final String jobId() {
return this.jobId;
}
/**
* The field used to split the data. In particular, this property is used for
* analyzing the splits with respect to the history of all splits. It is used
* for finding unusual values in the population of all splits.
*
* API name: {@code over_field_name}
*/
@Nullable
public final String overFieldName() {
return this.overFieldName;
}
/**
* The value of over_field_name.
*
* API name: {@code over_field_value}
*/
@Nullable
public final String overFieldValue() {
return this.overFieldValue;
}
/**
* The field used to segment the analysis. When you use this property, you have
* completely independent baselines for each value of this field.
*
* API name: {@code partition_field_name}
*/
@Nullable
public final String partitionFieldName() {
return this.partitionFieldName;
}
/**
* The value of partition_field_name.
*
* API name: {@code partition_field_value}
*/
@Nullable
public final String partitionFieldValue() {
return this.partitionFieldValue;
}
/**
* Required - The probability of the individual anomaly occurring, in the range
* 0 to 1. For example, 0.0000772031. This value can be held to a
* high precision of over 300 decimal places, so the record_score
* is provided as a human-readable and friendly interpretation of this.
*
* API name: {@code probability}
*/
public final double probability() {
return this.probability;
}
/**
* Required - A normalized score between 0-100, which is based on the
* probability of the anomalousness of this record. Unlike
* initial_record_score, this value will be updated by a
* re-normalization process as new data is analyzed.
*
* API name: {@code record_score}
*/
public final double recordScore() {
return this.recordScore;
}
/**
* Required - Internal. This is always set to record.
*
* API name: {@code result_type}
*/
public final String resultType() {
return this.resultType;
}
/**
* Required - The start time of the bucket for which these results were
* calculated.
*
* API name: {@code timestamp}
*/
public final long timestamp() {
return this.timestamp;
}
/**
* The typical value for the bucket, according to analytical modeling.
*
* API name: {@code typical}
*/
public final List typical() {
return this.typical;
}
/**
* Serialize this object to JSON.
*/
public void serialize(JsonGenerator generator, JsonpMapper mapper) {
generator.writeStartObject();
serializeInternal(generator, mapper);
generator.writeEnd();
}
protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
if (ApiTypeHelper.isDefined(this.actual)) {
generator.writeKey("actual");
generator.writeStartArray();
for (Double item0 : this.actual) {
generator.write(item0);
}
generator.writeEnd();
}
if (this.anomalyScoreExplanation != null) {
generator.writeKey("anomaly_score_explanation");
this.anomalyScoreExplanation.serialize(generator, mapper);
}
generator.writeKey("bucket_span");
generator.write(this.bucketSpan);
if (this.byFieldName != null) {
generator.writeKey("by_field_name");
generator.write(this.byFieldName);
}
if (this.byFieldValue != null) {
generator.writeKey("by_field_value");
generator.write(this.byFieldValue);
}
if (ApiTypeHelper.isDefined(this.causes)) {
generator.writeKey("causes");
generator.writeStartArray();
for (AnomalyCause item0 : this.causes) {
item0.serialize(generator, mapper);
}
generator.writeEnd();
}
generator.writeKey("detector_index");
generator.write(this.detectorIndex);
if (this.fieldName != null) {
generator.writeKey("field_name");
generator.write(this.fieldName);
}
if (this.function != null) {
generator.writeKey("function");
generator.write(this.function);
}
if (this.functionDescription != null) {
generator.writeKey("function_description");
generator.write(this.functionDescription);
}
if (this.geoResults != null) {
generator.writeKey("geo_results");
this.geoResults.serialize(generator, mapper);
}
if (ApiTypeHelper.isDefined(this.influencers)) {
generator.writeKey("influencers");
generator.writeStartArray();
for (Influence item0 : this.influencers) {
item0.serialize(generator, mapper);
}
generator.writeEnd();
}
generator.writeKey("initial_record_score");
generator.write(this.initialRecordScore);
generator.writeKey("is_interim");
generator.write(this.isInterim);
generator.writeKey("job_id");
generator.write(this.jobId);
if (this.overFieldName != null) {
generator.writeKey("over_field_name");
generator.write(this.overFieldName);
}
if (this.overFieldValue != null) {
generator.writeKey("over_field_value");
generator.write(this.overFieldValue);
}
if (this.partitionFieldName != null) {
generator.writeKey("partition_field_name");
generator.write(this.partitionFieldName);
}
if (this.partitionFieldValue != null) {
generator.writeKey("partition_field_value");
generator.write(this.partitionFieldValue);
}
generator.writeKey("probability");
generator.write(this.probability);
generator.writeKey("record_score");
generator.write(this.recordScore);
generator.writeKey("result_type");
generator.write(this.resultType);
generator.writeKey("timestamp");
generator.write(this.timestamp);
if (ApiTypeHelper.isDefined(this.typical)) {
generator.writeKey("typical");
generator.writeStartArray();
for (Double item0 : this.typical) {
generator.write(item0);
}
generator.writeEnd();
}
}
@Override
public String toString() {
return JsonpUtils.toString(this);
}
// ---------------------------------------------------------------------------------------------
/**
* Builder for {@link Anomaly}.
*/
public static class Builder extends WithJsonObjectBuilderBase implements ObjectBuilder {
@Nullable
private List actual;
@Nullable
private AnomalyExplanation anomalyScoreExplanation;
private Long bucketSpan;
@Nullable
private String byFieldName;
@Nullable
private String byFieldValue;
@Nullable
private List causes;
private Integer detectorIndex;
@Nullable
private String fieldName;
@Nullable
private String function;
@Nullable
private String functionDescription;
@Nullable
private GeoResults geoResults;
@Nullable
private List influencers;
private Double initialRecordScore;
private Boolean isInterim;
private String jobId;
@Nullable
private String overFieldName;
@Nullable
private String overFieldValue;
@Nullable
private String partitionFieldName;
@Nullable
private String partitionFieldValue;
private Double probability;
private Double recordScore;
private String resultType;
private Long timestamp;
@Nullable
private List typical;
/**
* The actual value for the bucket.
*
* API name: {@code actual}
*
* Adds all elements of list to actual.
*/
public final Builder actual(List list) {
this.actual = _listAddAll(this.actual, list);
return this;
}
/**
* The actual value for the bucket.
*
* API name: {@code actual}
*
* Adds one or more values to actual.
*/
public final Builder actual(Double value, Double... values) {
this.actual = _listAdd(this.actual, value, values);
return this;
}
/**
* Information about the factors impacting the initial anomaly score.
*
* API name: {@code anomaly_score_explanation}
*/
public final Builder anomalyScoreExplanation(@Nullable AnomalyExplanation value) {
this.anomalyScoreExplanation = value;
return this;
}
/**
* Information about the factors impacting the initial anomaly score.
*
* API name: {@code anomaly_score_explanation}
*/
public final Builder anomalyScoreExplanation(
Function> fn) {
return this.anomalyScoreExplanation(fn.apply(new AnomalyExplanation.Builder()).build());
}
/**
* Required - The length of the bucket in seconds. This value matches the
* bucket_span that is specified in the job.
*
* API name: {@code bucket_span}
*/
public final Builder bucketSpan(long value) {
this.bucketSpan = value;
return this;
}
/**
* The field used to split the data. In particular, this property is used for
* analyzing the splits with respect to their own history. It is used for
* finding unusual values in the context of the split.
*
* API name: {@code by_field_name}
*/
public final Builder byFieldName(@Nullable String value) {
this.byFieldName = value;
return this;
}
/**
* The value of by_field_name.
*
* API name: {@code by_field_value}
*/
public final Builder byFieldValue(@Nullable String value) {
this.byFieldValue = value;
return this;
}
/**
* For population analysis, an over field must be specified in the detector.
* This property contains an array of anomaly records that are the causes for
* the anomaly that has been identified for the over field. This sub-resource
* contains the most anomalous records for the over_field_name. For
* scalability reasons, a maximum of the 10 most significant causes of the
* anomaly are returned. As part of the core analytical modeling, these
* low-level anomaly records are aggregated for their parent over field record.
* The causes resource contains similar elements to the record
* resource, namely actual, typical,
* geo_results.actual_point,
* geo_results.typical_point, *_field_name and
* *_field_value. Probability and scores are not applicable to
* causes.
*
* API name: {@code causes}
*
* Adds all elements of list to causes.
*/
public final Builder causes(List list) {
this.causes = _listAddAll(this.causes, list);
return this;
}
/**
* For population analysis, an over field must be specified in the detector.
* This property contains an array of anomaly records that are the causes for
* the anomaly that has been identified for the over field. This sub-resource
* contains the most anomalous records for the over_field_name. For
* scalability reasons, a maximum of the 10 most significant causes of the
* anomaly are returned. As part of the core analytical modeling, these
* low-level anomaly records are aggregated for their parent over field record.
* The causes resource contains similar elements to the record
* resource, namely actual, typical,
* geo_results.actual_point,
* geo_results.typical_point, *_field_name and
* *_field_value. Probability and scores are not applicable to
* causes.
*
* API name: {@code causes}
*
* Adds one or more values to causes.
*/
public final Builder causes(AnomalyCause value, AnomalyCause... values) {
this.causes = _listAdd(this.causes, value, values);
return this;
}
/**
* For population analysis, an over field must be specified in the detector.
* This property contains an array of anomaly records that are the causes for
* the anomaly that has been identified for the over field. This sub-resource
* contains the most anomalous records for the over_field_name. For
* scalability reasons, a maximum of the 10 most significant causes of the
* anomaly are returned. As part of the core analytical modeling, these
* low-level anomaly records are aggregated for their parent over field record.
* The causes resource contains similar elements to the record
* resource, namely actual, typical,
* geo_results.actual_point,
* geo_results.typical_point, *_field_name and
* *_field_value. Probability and scores are not applicable to
* causes.
*
* API name: {@code causes}
*
* Adds a value to causes using a builder lambda.
*/
public final Builder causes(Function> fn) {
return causes(fn.apply(new AnomalyCause.Builder()).build());
}
/**
* Required - A unique identifier for the detector.
*
* API name: {@code detector_index}
*/
public final Builder detectorIndex(int value) {
this.detectorIndex = value;
return this;
}
/**
* Certain functions require a field to operate on, for example,
* sum(). For those functions, this value is the name of the field
* to be analyzed.
*
* API name: {@code field_name}
*/
public final Builder fieldName(@Nullable String value) {
this.fieldName = value;
return this;
}
/**
* The function in which the anomaly occurs, as specified in the detector
* configuration. For example, max.
*
* API name: {@code function}
*/
public final Builder function(@Nullable String value) {
this.function = value;
return this;
}
/**
* The description of the function in which the anomaly occurs, as specified in
* the detector configuration.
*
* API name: {@code function_description}
*/
public final Builder functionDescription(@Nullable String value) {
this.functionDescription = value;
return this;
}
/**
* If the detector function is lat_long, this object contains comma
* delimited strings for the latitude and longitude of the actual and typical
* values.
*
* API name: {@code geo_results}
*/
public final Builder geoResults(@Nullable GeoResults value) {
this.geoResults = value;
return this;
}
/**
* If the detector function is lat_long, this object contains comma
* delimited strings for the latitude and longitude of the actual and typical
* values.
*
* API name: {@code geo_results}
*/
public final Builder geoResults(Function> fn) {
return this.geoResults(fn.apply(new GeoResults.Builder()).build());
}
/**
* If influencers were specified in the detector configuration, this array
* contains influencers that contributed to or were to blame for an anomaly.
*
* API name: {@code influencers}
*
* Adds all elements of list to influencers.
*/
public final Builder influencers(List list) {
this.influencers = _listAddAll(this.influencers, list);
return this;
}
/**
* If influencers were specified in the detector configuration, this array
* contains influencers that contributed to or were to blame for an anomaly.
*
* API name: {@code influencers}
*
* Adds one or more values to influencers.
*/
public final Builder influencers(Influence value, Influence... values) {
this.influencers = _listAdd(this.influencers, value, values);
return this;
}
/**
* If influencers were specified in the detector configuration, this array
* contains influencers that contributed to or were to blame for an anomaly.
*
* API name: {@code influencers}
*
* Adds a value to influencers using a builder lambda.
*/
public final Builder influencers(Function> fn) {
return influencers(fn.apply(new Influence.Builder()).build());
}
/**
* Required - A normalized score between 0-100, which is based on the
* probability of the anomalousness of this record. This is the initial value
* that was calculated at the time the bucket was processed.
*
* API name: {@code initial_record_score}
*/
public final Builder initialRecordScore(double value) {
this.initialRecordScore = value;
return this;
}
/**
* Required - If true, this is an interim result. In other words, the results
* are calculated based on partial input data.
*
* API name: {@code is_interim}
*/
public final Builder isInterim(boolean value) {
this.isInterim = value;
return this;
}
/**
* Required - Identifier for the anomaly detection job.
*
* API name: {@code job_id}
*/
public final Builder jobId(String value) {
this.jobId = value;
return this;
}
/**
* The field used to split the data. In particular, this property is used for
* analyzing the splits with respect to the history of all splits. It is used
* for finding unusual values in the population of all splits.
*
* API name: {@code over_field_name}
*/
public final Builder overFieldName(@Nullable String value) {
this.overFieldName = value;
return this;
}
/**
* The value of over_field_name.
*
* API name: {@code over_field_value}
*/
public final Builder overFieldValue(@Nullable String value) {
this.overFieldValue = value;
return this;
}
/**
* The field used to segment the analysis. When you use this property, you have
* completely independent baselines for each value of this field.
*
* API name: {@code partition_field_name}
*/
public final Builder partitionFieldName(@Nullable String value) {
this.partitionFieldName = value;
return this;
}
/**
* The value of partition_field_name.
*
* API name: {@code partition_field_value}
*/
public final Builder partitionFieldValue(@Nullable String value) {
this.partitionFieldValue = value;
return this;
}
/**
* Required - The probability of the individual anomaly occurring, in the range
* 0 to 1. For example, 0.0000772031. This value can be held to a
* high precision of over 300 decimal places, so the record_score
* is provided as a human-readable and friendly interpretation of this.
*
* API name: {@code probability}
*/
public final Builder probability(double value) {
this.probability = value;
return this;
}
/**
* Required - A normalized score between 0-100, which is based on the
* probability of the anomalousness of this record. Unlike
* initial_record_score, this value will be updated by a
* re-normalization process as new data is analyzed.
*
* API name: {@code record_score}
*/
public final Builder recordScore(double value) {
this.recordScore = value;
return this;
}
/**
* Required - Internal. This is always set to record.
*
* API name: {@code result_type}
*/
public final Builder resultType(String value) {
this.resultType = value;
return this;
}
/**
* Required - The start time of the bucket for which these results were
* calculated.
*
* API name: {@code timestamp}
*/
public final Builder timestamp(long value) {
this.timestamp = value;
return this;
}
/**
* The typical value for the bucket, according to analytical modeling.
*
* API name: {@code typical}
*
* Adds all elements of list to typical.
*/
public final Builder typical(List list) {
this.typical = _listAddAll(this.typical, list);
return this;
}
/**
* The typical value for the bucket, according to analytical modeling.
*
* API name: {@code typical}
*
* Adds one or more values to typical.
*/
public final Builder typical(Double value, Double... values) {
this.typical = _listAdd(this.typical, value, values);
return this;
}
@Override
protected Builder self() {
return this;
}
/**
* Builds a {@link Anomaly}.
*
* @throws NullPointerException
* if some of the required fields are null.
*/
public Anomaly build() {
_checkSingleUse();
return new Anomaly(this);
}
}
// ---------------------------------------------------------------------------------------------
/**
* Json deserializer for {@link Anomaly}
*/
public static final JsonpDeserializer _DESERIALIZER = ObjectBuilderDeserializer.lazy(Builder::new,
Anomaly::setupAnomalyDeserializer);
protected static void setupAnomalyDeserializer(ObjectDeserializer op) {
op.add(Builder::actual, JsonpDeserializer.arrayDeserializer(JsonpDeserializer.doubleDeserializer()), "actual");
op.add(Builder::anomalyScoreExplanation, AnomalyExplanation._DESERIALIZER, "anomaly_score_explanation");
op.add(Builder::bucketSpan, JsonpDeserializer.longDeserializer(), "bucket_span");
op.add(Builder::byFieldName, JsonpDeserializer.stringDeserializer(), "by_field_name");
op.add(Builder::byFieldValue, JsonpDeserializer.stringDeserializer(), "by_field_value");
op.add(Builder::causes, JsonpDeserializer.arrayDeserializer(AnomalyCause._DESERIALIZER), "causes");
op.add(Builder::detectorIndex, JsonpDeserializer.integerDeserializer(), "detector_index");
op.add(Builder::fieldName, JsonpDeserializer.stringDeserializer(), "field_name");
op.add(Builder::function, JsonpDeserializer.stringDeserializer(), "function");
op.add(Builder::functionDescription, JsonpDeserializer.stringDeserializer(), "function_description");
op.add(Builder::geoResults, GeoResults._DESERIALIZER, "geo_results");
op.add(Builder::influencers, JsonpDeserializer.arrayDeserializer(Influence._DESERIALIZER), "influencers");
op.add(Builder::initialRecordScore, JsonpDeserializer.doubleDeserializer(), "initial_record_score");
op.add(Builder::isInterim, JsonpDeserializer.booleanDeserializer(), "is_interim");
op.add(Builder::jobId, JsonpDeserializer.stringDeserializer(), "job_id");
op.add(Builder::overFieldName, JsonpDeserializer.stringDeserializer(), "over_field_name");
op.add(Builder::overFieldValue, JsonpDeserializer.stringDeserializer(), "over_field_value");
op.add(Builder::partitionFieldName, JsonpDeserializer.stringDeserializer(), "partition_field_name");
op.add(Builder::partitionFieldValue, JsonpDeserializer.stringDeserializer(), "partition_field_value");
op.add(Builder::probability, JsonpDeserializer.doubleDeserializer(), "probability");
op.add(Builder::recordScore, JsonpDeserializer.doubleDeserializer(), "record_score");
op.add(Builder::resultType, JsonpDeserializer.stringDeserializer(), "result_type");
op.add(Builder::timestamp, JsonpDeserializer.longDeserializer(), "timestamp");
op.add(Builder::typical, JsonpDeserializer.arrayDeserializer(JsonpDeserializer.doubleDeserializer()),
"typical");
}
}