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Hendrik Muhs
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[ML] Return statistics about forecasts as part of the jobsstats and usage API (#31647)
This change adds stats about forecasts, to the jobstats api as well as xpack/_usage. The following information is collected: _xpack/ml/anomaly_detectors/{jobid|_all}/_stats: - total number of forecasts - memory statistics (mean/min/max) - runtime statistics - record statistics - counts by status _xpack/usage - collected by job status as well as overall (_all): - total number of forecasts - number of jobs that have at least 1 forecast - memory, runtime, record statistics - counts by status Fixes #31395
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‎x-pack/docs/en/rest-api/ml/jobcounts.asciidoc‎

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@@ -20,6 +20,10 @@ progress of a job.
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(object) An object that provides information about the size and contents of the model.
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See <<ml-modelsizestats,model size stats objects>>
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`forecasts_stats`::
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(object) An object that provides statistical information about forecasts
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of this job. See <<ml-forecastsstats, forecasts stats objects>>
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`node`::
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(object) For open jobs only, contains information about the node where the
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job runs. See <<ml-stats-node,node object>>.
@@ -177,6 +181,33 @@ NOTE: The `over` field values are counted separately for each detector and parti
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`timestamp`::
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(date) The timestamp of the `model_size_stats` according to the timestamp of the data.
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[float]
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[[ml-forecastsstats]]
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==== Forecasts Stats Objects
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The `forecasts_stats` object shows statistics about forecasts. It has the following properties:
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`total`::
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(long) The number of forecasts currently available for this model.
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`forecasted_jobs`::
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(long) The number of jobs that have at least one forecast.
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`memory_bytes`::
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(object) Statistics about the memory usage: minimum, maximum, average and total.
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`records`::
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(object) Statistics about the number of forecast records: minimum, maximum, average and total.
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`processing_time_ms`::
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(object) Statistics about the forecast runtime in milliseconds: minimum, maximum, average and total.
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`status`::
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(object) Counts per forecast status, for example: {"finished" : 2}.
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NOTE: `memory_bytes`, `records`, `processing_time_ms` and `status` require at least 1 forecast, otherwise
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these fields are ommitted.
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[float]
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[[ml-stats-node]]
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==== Node Objects

‎x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/MachineLearningFeatureSetUsage.java‎

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@@ -22,6 +22,7 @@ public class MachineLearningFeatureSetUsage extends XPackFeatureSet.Usage {
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public static final String DATAFEEDS_FIELD = "datafeeds";
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public static final String COUNT = "count";
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public static final String DETECTORS = "detectors";
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public static final String FORECASTS = "forecasts";
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public static final String MODEL_SIZE = "model_size";
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private final Map<String, Object> jobsUsage;

‎x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/action/GetJobsStatsAction.java‎

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import org.elasticsearch.xpack.core.ml.job.config.JobState;
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import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.DataCounts;
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import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSizeStats;
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import org.elasticsearch.xpack.core.ml.stats.ForecastStats;
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import org.elasticsearch.xpack.core.ml.utils.ExceptionsHelper;
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import java.io.IOException;
@@ -46,6 +47,7 @@ public class GetJobsStatsAction extends Action<GetJobsStatsAction.Response> {
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private static final String DATA_COUNTS = "data_counts";
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private static final String MODEL_SIZE_STATS = "model_size_stats";
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private static final String FORECASTS_STATS = "forecasts_stats";
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private static final String STATE = "state";
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private static final String NODE = "node";
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@@ -154,18 +156,22 @@ public static class JobStats implements ToXContentObject, Writeable {
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@Nullable
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private ModelSizeStats modelSizeStats;
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@Nullable
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private ForecastStats forecastStats;
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@Nullable
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private TimeValue openTime;
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private JobState state;
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@Nullable
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private DiscoveryNode node;
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@Nullable
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private String assignmentExplanation;
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public JobStats(String jobId, DataCounts dataCounts, @Nullable ModelSizeStats modelSizeStats, JobState state,
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@Nullable DiscoveryNode node, @Nullable String assignmentExplanation, @Nullable TimeValue opentime) {
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public JobStats(String jobId, DataCounts dataCounts, @Nullable ModelSizeStats modelSizeStats,
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@Nullable ForecastStats forecastStats, JobState state, @Nullable DiscoveryNode node,
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@Nullable String assignmentExplanation, @Nullable TimeValue opentime) {
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this.jobId = Objects.requireNonNull(jobId);
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this.dataCounts = Objects.requireNonNull(dataCounts);
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this.modelSizeStats = modelSizeStats;
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this.forecastStats = forecastStats;
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this.state = Objects.requireNonNull(state);
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this.node = node;
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this.assignmentExplanation = assignmentExplanation;
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node = in.readOptionalWriteable(DiscoveryNode::new);
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assignmentExplanation = in.readOptionalString();
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openTime = in.readOptionalTimeValue();
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if (in.getVersion().onOrAfter(Version.V_6_4_0)) {
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forecastStats = in.readOptionalWriteable(ForecastStats::new);
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}
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}
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public String getJobId() {
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public ModelSizeStats getModelSizeStats() {
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return modelSizeStats;
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}
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public ForecastStats getForecastStats() {
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return forecastStats;
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}
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public JobState getState() {
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return state;
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if (modelSizeStats != null) {
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builder.field(MODEL_SIZE_STATS, modelSizeStats);
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}
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if (forecastStats != null) {
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builder.field(FORECASTS_STATS, forecastStats);
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}
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builder.field(STATE, state.toString());
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if (node != null) {
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builder.startObject(NODE);
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out.writeOptionalWriteable(node);
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out.writeOptionalString(assignmentExplanation);
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out.writeOptionalTimeValue(openTime);
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if (out.getVersion().onOrAfter(Version.V_6_4_0)) {
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out.writeOptionalWriteable(forecastStats);
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}
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}
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@Override
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public int hashCode() {
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return Objects.hash(jobId, dataCounts, modelSizeStats, state, node, assignmentExplanation, openTime);
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return Objects.hash(jobId, dataCounts, modelSizeStats, forecastStats, state, node, assignmentExplanation, openTime);
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}
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@Override
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return Objects.equals(jobId, other.jobId)
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&& Objects.equals(this.dataCounts, other.dataCounts)
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&& Objects.equals(this.modelSizeStats, other.modelSizeStats)
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&& Objects.equals(this.forecastStats, other.forecastStats)
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&& Objects.equals(this.state, other.state)
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&& Objects.equals(this.node, other.node)
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&& Objects.equals(this.assignmentExplanation, other.assignmentExplanation)

‎x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/stats/CountAccumulator.java‎

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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License;
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* you may not use this file except in compliance with the Elastic License.
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*/
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package org.elasticsearch.xpack.core.ml.stats;
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import org.elasticsearch.common.io.stream.StreamInput;
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import org.elasticsearch.common.io.stream.StreamOutput;
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import org.elasticsearch.common.io.stream.Writeable;
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import org.elasticsearch.search.aggregations.bucket.terms.StringTerms;
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import java.io.IOException;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.Objects;
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import java.util.Map.Entry;
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import java.util.stream.Collectors;
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import java.util.stream.Stream;
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/**
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* An accumulator for simple counts where statistical measures
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* are not of interest.
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*/
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public class CountAccumulator implements Writeable {
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private Map<String, Long> counts;
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public CountAccumulator() {
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this.counts = new HashMap<String, Long>();
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}
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private CountAccumulator(Map<String, Long> counts) {
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this.counts = counts;
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}
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public CountAccumulator(StreamInput in) throws IOException {
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this.counts = in.readMap(StreamInput::readString, StreamInput::readLong);
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}
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public void merge(CountAccumulator other) {
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counts = Stream.of(counts, other.counts).flatMap(m -> m.entrySet().stream())
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.collect(Collectors.toMap(Entry::getKey, Entry::getValue, (x, y) -> x + y));
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}
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public void add(String key, Long count) {
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counts.put(key, counts.getOrDefault(key, 0L) + count);
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}
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public Map<String, Long> asMap() {
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return counts;
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}
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public static CountAccumulator fromTermsAggregation(StringTerms termsAggregation) {
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return new CountAccumulator(termsAggregation.getBuckets().stream()
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.collect(Collectors.toMap(bucket -> bucket.getKeyAsString(), bucket -> bucket.getDocCount())));
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}
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public void writeTo(StreamOutput out) throws IOException {
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out.writeMap(counts, StreamOutput::writeString, StreamOutput::writeLong);
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}
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@Override
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public int hashCode() {
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return Objects.hash(counts);
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}
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@Override
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public boolean equals(Object obj) {
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if (obj == null) {
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return false;
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}
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if (getClass() != obj.getClass()) {
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return false;
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}
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CountAccumulator other = (CountAccumulator) obj;
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return Objects.equals(counts, other.counts);
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}
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}

‎x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/stats/ForecastStats.java‎

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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License;
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* you may not use this file except in compliance with the Elastic License.
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*/
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package org.elasticsearch.xpack.core.ml.stats;
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import org.elasticsearch.common.io.stream.StreamInput;
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import org.elasticsearch.common.io.stream.StreamOutput;
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import org.elasticsearch.common.io.stream.Writeable;
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import org.elasticsearch.common.xcontent.ToXContentObject;
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import org.elasticsearch.common.xcontent.XContentBuilder;
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import java.io.IOException;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.Objects;
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/**
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* A class to hold statistics about forecasts.
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*/
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public class ForecastStats implements ToXContentObject, Writeable {
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public static class Fields {
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public static final String TOTAL = "total";
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public static final String FORECASTED_JOBS = "forecasted_jobs";
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public static final String MEMORY = "memory_bytes";
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public static final String RUNTIME = "processing_time_ms";
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public static final String RECORDS = "records";
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public static final String STATUSES = "status";
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}
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private long total;
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private long forecastedJobs;
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private StatsAccumulator memoryStats;
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private StatsAccumulator recordStats;
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private StatsAccumulator runtimeStats;
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private CountAccumulator statusCounts;
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public ForecastStats() {
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this.total = 0;
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this.forecastedJobs = 0;
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this.memoryStats = new StatsAccumulator();
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this.recordStats = new StatsAccumulator();
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this.runtimeStats = new StatsAccumulator();
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this.statusCounts = new CountAccumulator();
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}
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/*
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* Construct ForecastStats for 1 job. Additional statistics can be added by merging other ForecastStats into it.
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*/
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public ForecastStats(long total, StatsAccumulator memoryStats, StatsAccumulator recordStats, StatsAccumulator runtimeStats,
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CountAccumulator statusCounts) {
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this.total = total;
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this.forecastedJobs = total > 0 ? 1 : 0;
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this.memoryStats = Objects.requireNonNull(memoryStats);
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this.recordStats = Objects.requireNonNull(recordStats);
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this.runtimeStats = Objects.requireNonNull(runtimeStats);
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this.statusCounts = Objects.requireNonNull(statusCounts);
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}
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public ForecastStats(StreamInput in) throws IOException {
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this.total = in.readLong();
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this.forecastedJobs = in.readLong();
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this.memoryStats = new StatsAccumulator(in);
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this.recordStats = new StatsAccumulator(in);
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this.runtimeStats = new StatsAccumulator(in);
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this.statusCounts = new CountAccumulator(in);
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}
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public ForecastStats merge(ForecastStats other) {
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if (other == null) {
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return this;
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}
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total += other.total;
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forecastedJobs += other.forecastedJobs;
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memoryStats.merge(other.memoryStats);
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recordStats.merge(other.recordStats);
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runtimeStats.merge(other.runtimeStats);
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statusCounts.merge(other.statusCounts);
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return this;
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}
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@Override
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public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
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builder.startObject();
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doXContentBody(builder, params);
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return builder.endObject();
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}
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public XContentBuilder doXContentBody(XContentBuilder builder, Params params) throws IOException {
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builder.field(Fields.TOTAL, total);
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builder.field(Fields.FORECASTED_JOBS, forecastedJobs);
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if (total > 0) {
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builder.field(Fields.MEMORY, memoryStats.asMap());
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builder.field(Fields.RECORDS, recordStats.asMap());
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builder.field(Fields.RUNTIME, runtimeStats.asMap());
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builder.field(Fields.STATUSES, statusCounts.asMap());
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}
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return builder;
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}
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public Map<String, Object> asMap() {
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Map<String, Object> map = new HashMap<>();
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map.put(Fields.TOTAL, total);
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map.put(Fields.FORECASTED_JOBS, forecastedJobs);
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if (total > 0) {
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map.put(Fields.MEMORY, memoryStats.asMap());
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map.put(Fields.RECORDS, recordStats.asMap());
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map.put(Fields.RUNTIME, runtimeStats.asMap());
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map.put(Fields.STATUSES, statusCounts.asMap());
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}
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return map;
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}
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@Override
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public void writeTo(StreamOutput out) throws IOException {
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out.writeLong(total);
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out.writeLong(forecastedJobs);
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memoryStats.writeTo(out);
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recordStats.writeTo(out);
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runtimeStats.writeTo(out);
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statusCounts.writeTo(out);
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}
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@Override
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public int hashCode() {
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return Objects.hash(total, forecastedJobs, memoryStats, recordStats, runtimeStats, statusCounts);
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}
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@Override
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public boolean equals(Object obj) {
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if (obj == null) {
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return false;
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}
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if (getClass() != obj.getClass()) {
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return false;
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}
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ForecastStats other = (ForecastStats) obj;
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return Objects.equals(total, other.total) && Objects.equals(forecastedJobs, other.forecastedJobs)
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&& Objects.equals(memoryStats, other.memoryStats) && Objects.equals(recordStats, other.recordStats)
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&& Objects.equals(runtimeStats, other.runtimeStats) && Objects.equals(statusCounts, other.statusCounts);
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}
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}

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