[ML] Add _cat/ml/anomaly_detectors API (#51364)
This commit is contained in:
Benjamin Trent
GitHub
parent
a29deecbda
commit
bf53ca3380
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@ -83,6 +83,30 @@ public class ForecastStats implements ToXContentObject, Writeable {
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return this;
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}
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public long getTotal() {
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return total;
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}
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public long getForecastedJobs() {
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return forecastedJobs;
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}
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public StatsAccumulator getMemoryStats() {
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return memoryStats;
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}
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public StatsAccumulator getRecordStats() {
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return recordStats;
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}
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public StatsAccumulator getRuntimeStats() {
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return runtimeStats;
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}
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public CountAccumulator getStatusCounts() {
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return statusCounts;
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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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@ -252,6 +252,7 @@ import org.elasticsearch.xpack.ml.rest.calendar.RestGetCalendarsAction;
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import org.elasticsearch.xpack.ml.rest.calendar.RestPostCalendarEventAction;
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import org.elasticsearch.xpack.ml.rest.calendar.RestPutCalendarAction;
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import org.elasticsearch.xpack.ml.rest.calendar.RestPutCalendarJobAction;
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import org.elasticsearch.xpack.ml.rest.cat.RestCatJobsAction;
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import org.elasticsearch.xpack.ml.rest.datafeeds.RestDeleteDatafeedAction;
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import org.elasticsearch.xpack.ml.rest.datafeeds.RestGetDatafeedStatsAction;
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import org.elasticsearch.xpack.ml.rest.datafeeds.RestGetDatafeedsAction;
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@ -777,7 +778,9 @@ public class MachineLearning extends Plugin implements ActionPlugin, AnalysisPlu
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new RestGetTrainedModelsAction(restController),
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new RestDeleteTrainedModelAction(restController),
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new RestGetTrainedModelsStatsAction(restController),
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new RestPutTrainedModelAction(restController)
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new RestPutTrainedModelAction(restController),
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// CAT Handlers
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new RestCatJobsAction(restController)
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);
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}
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@ -0,0 +1,378 @@
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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.ml.rest.cat;
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import org.elasticsearch.client.node.NodeClient;
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import org.elasticsearch.cluster.metadata.MetaData;
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import org.elasticsearch.cluster.node.DiscoveryNode;
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import org.elasticsearch.common.Strings;
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import org.elasticsearch.common.Table;
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import org.elasticsearch.common.unit.ByteSizeValue;
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import org.elasticsearch.common.unit.TimeValue;
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import org.elasticsearch.rest.RestController;
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import org.elasticsearch.rest.RestRequest;
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import org.elasticsearch.rest.RestResponse;
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import org.elasticsearch.rest.action.RestResponseListener;
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import org.elasticsearch.rest.action.cat.AbstractCatAction;
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import org.elasticsearch.rest.action.cat.RestTable;
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import org.elasticsearch.xpack.core.ml.action.GetJobsStatsAction;
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import org.elasticsearch.xpack.core.ml.job.config.Job;
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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.job.process.autodetect.state.TimingStats;
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import org.elasticsearch.xpack.core.ml.stats.ForecastStats;
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import static org.elasticsearch.rest.RestRequest.Method.GET;
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public class RestCatJobsAction extends AbstractCatAction {
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public RestCatJobsAction(RestController controller) {
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controller.registerHandler(GET, "_cat/ml/anomaly_detectors/{" + Job.ID.getPreferredName() + "}", this);
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controller.registerHandler(GET, "_cat/ml/anomaly_detectors", this);
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}
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@Override
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public String getName() {
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return "cat_ml_get_jobs_action";
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}
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@Override
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protected RestChannelConsumer doCatRequest(RestRequest restRequest, NodeClient client) {
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String jobId = restRequest.param(Job.ID.getPreferredName());
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if (Strings.isNullOrEmpty(jobId)) {
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jobId = MetaData.ALL;
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}
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GetJobsStatsAction.Request request = new GetJobsStatsAction.Request(jobId);
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request.setAllowNoJobs(restRequest.paramAsBoolean(GetJobsStatsAction.Request.ALLOW_NO_JOBS.getPreferredName(),
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request.allowNoJobs()));
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return channel -> client.execute(GetJobsStatsAction.INSTANCE,
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request,
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new RestResponseListener<GetJobsStatsAction.Response>(channel) {
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@Override
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public RestResponse buildResponse(GetJobsStatsAction.Response getJobStatsResponse) throws Exception {
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return RestTable.buildResponse(buildTable(restRequest, getJobStatsResponse), channel);
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}
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});
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}
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@Override
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protected void documentation(StringBuilder sb) {
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sb.append("/_cat/ml/anomaly_detectors\n");
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sb.append("/_cat/ml/anomaly_detectors/{job_id}\n");
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}
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@Override
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protected Table getTableWithHeader(RestRequest request) {
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Table table = new Table();
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table.startHeaders();
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// Job Info
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table.addCell("id", TableColumnAttributeBuilder.builder().setDescription("the job_id").build());
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table.addCell("state", TableColumnAttributeBuilder.builder()
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.setDescription("the job state")
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.setAliases("s")
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.setTextAlignment(TableColumnAttributeBuilder.TextAlign.RIGHT)
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.build());
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table.addCell("opened_time",
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TableColumnAttributeBuilder.builder()
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.setDescription("the amount of time the job has been opened")
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.setAliases("ot")
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.setDisplayByDefault(false)
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.build());
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table.addCell("assignment_explanation",
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TableColumnAttributeBuilder.builder("why the job is or is not assigned to a node", false)
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.setAliases("ae")
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.build());
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// Data Counts
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table.addCell("data.processed_records",
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TableColumnAttributeBuilder.builder("number of processed records")
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.setAliases("dpr", "dataProcessedRecords")
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.build());
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table.addCell("data.processed_fields",
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TableColumnAttributeBuilder.builder("number of processed fields", false)
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.setAliases("dpr", "dataProcessedFields")
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.build());
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table.addCell("data.input_bytes",
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TableColumnAttributeBuilder.builder("total input bytes", false)
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.setAliases("dib", "dataInputBytes")
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.build());
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table.addCell("data.input_records",
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TableColumnAttributeBuilder.builder("total record count", false)
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.setAliases("dir", "dataInputRecords")
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.build());
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table.addCell("data.input_fields",
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TableColumnAttributeBuilder.builder("total field count", false)
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.setAliases("dif", "dataInputFields")
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.build());
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table.addCell("data.invalid_dates",
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TableColumnAttributeBuilder.builder("number of records with invalid dates", false)
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.setAliases("did", "dataInvalidDates")
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.build());
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table.addCell("data.missing_fields",
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TableColumnAttributeBuilder.builder("number of records with missing fields", false)
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.setAliases("dmf", "dataMissingFields")
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.build());
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table.addCell("data.out_of_order_timestamps",
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TableColumnAttributeBuilder.builder("number of records handled out of order", false)
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.setAliases("doot", "dataOutOfOrderTimestamps")
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.build());
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table.addCell("data.empty_buckets",
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TableColumnAttributeBuilder.builder("number of empty buckets", false)
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.setAliases("deb", "dataEmptyBuckets")
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.build());
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table.addCell("data.sparse_buckets",
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TableColumnAttributeBuilder.builder("number of sparse buckets", false)
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.setAliases("dsb", "dataSparseBuckets")
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.build());
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table.addCell("data.buckets",
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TableColumnAttributeBuilder.builder("total bucket count", false)
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.setAliases("db", "dataBuckets")
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.build());
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table.addCell("data.earliest_record",
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TableColumnAttributeBuilder.builder("earliest record time", false)
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.setAliases("der", "dataEarliestRecord")
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.build());
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table.addCell("data.latest_record",
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TableColumnAttributeBuilder.builder("latest record time", false)
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.setAliases("dlr", "dataLatestRecord")
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.build());
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table.addCell("data.last",
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TableColumnAttributeBuilder.builder("last time data was seen", false)
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.setAliases("dl", "dataLast")
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.build());
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table.addCell("data.last_empty_bucket",
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TableColumnAttributeBuilder.builder("last time an empty bucket occurred", false)
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.setAliases("dleb", "dataLastEmptyBucket")
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.build());
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table.addCell("data.last_sparse_bucket",
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TableColumnAttributeBuilder.builder("last time a sparse bucket occurred", false)
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.setAliases("dlsb", "dataLastSparseBucket")
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.build());
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// Model Size stats
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table.addCell("model.bytes",
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TableColumnAttributeBuilder.builder("model size").setAliases("mb", "modelBytes").build());
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table.addCell("model.memory_status",
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TableColumnAttributeBuilder.builder("current memory status")
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.setAliases("mms", "modelMemoryStatus")
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.setTextAlignment(TableColumnAttributeBuilder.TextAlign.RIGHT)
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.build());
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table.addCell("model.bytes_exceeded",
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TableColumnAttributeBuilder.builder("how much the model has exceeded the limit", false)
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.setAliases("mbe", "modelBytesExceeded")
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.build());
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table.addCell("model.memory_limit",
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TableColumnAttributeBuilder.builder("model memory limit", false)
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.setAliases("mml", "modelMemoryLimit")
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.build());
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table.addCell("model.by_fields",
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TableColumnAttributeBuilder.builder("count of 'by' fields", false)
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.setAliases("mbf", "modelByFields")
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.build());
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table.addCell("model.over_fields",
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TableColumnAttributeBuilder.builder("count of 'over' fields", false)
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.setAliases("mof", "modelOverFields")
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.build());
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table.addCell("model.partition_fields",
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TableColumnAttributeBuilder.builder("count of 'partition' fields", false)
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.setAliases("mpf", "modelPartitionFields")
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.build());
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table.addCell("model.bucket_allocation_failures",
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TableColumnAttributeBuilder.builder("number of bucket allocation failures", false)
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.setAliases("mbaf", "modelBucketAllocationFailures")
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.build());
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table.addCell("model.log_time",
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TableColumnAttributeBuilder.builder("when the model stats were gathered", false)
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.setAliases("mlt", "modelLogTime")
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.build());
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table.addCell("model.timestamp",
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TableColumnAttributeBuilder.builder("the time of the last record when the model stats were gathered", false)
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.setAliases("mt", "modelTimestamp")
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.build());
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// Forecast Stats
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table.addCell("forecast." + ForecastStats.Fields.TOTAL,
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TableColumnAttributeBuilder.builder("total number of forecasts").setAliases("ft", "forecastTotal").build());
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table.addCell("forecast.memory.min",
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TableColumnAttributeBuilder.builder("minimum memory used by forecasts", false)
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.setAliases("fmmin", "forecastMemoryMin")
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.build());
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table.addCell("forecast.memory.max",
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TableColumnAttributeBuilder.builder("maximum memory used by forecasts", false)
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.setAliases("fmmax", "forecastsMemoryMax")
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.build());
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table.addCell("forecast.memory.avg",
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TableColumnAttributeBuilder.builder("average memory used by forecasts", false)
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.setAliases("fmavg", "forecastMemoryAvg")
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.build());
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table.addCell("forecast.memory.total",
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TableColumnAttributeBuilder.builder("total memory used by all forecasts", false)
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.setAliases("fmt", "forecastMemoryTotal")
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.build());
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table.addCell("forecast." + ForecastStats.Fields.RECORDS + ".min",
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TableColumnAttributeBuilder.builder("minimum record count for forecasts", false)
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.setAliases("frmin", "forecastRecordsMin")
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.build());
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table.addCell("forecast." + ForecastStats.Fields.RECORDS + ".max",
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TableColumnAttributeBuilder.builder("maximum record count for forecasts", false)
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.setAliases("frmax", "forecastRecordsMax")
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.build());
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table.addCell("forecast." + ForecastStats.Fields.RECORDS + ".avg",
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TableColumnAttributeBuilder.builder("average record count for forecasts", false)
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.setAliases("fravg", "forecastRecordsAvg")
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.build());
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table.addCell("forecast." + ForecastStats.Fields.RECORDS + ".total",
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TableColumnAttributeBuilder.builder("total record count for all forecasts", false)
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.setAliases("frt", "forecastRecordsTotal")
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.build());
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table.addCell("forecast.time.min",
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TableColumnAttributeBuilder.builder("minimum runtime for forecasts", false)
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.setAliases("ftmin", "forecastTimeMin")
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.build());
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table.addCell("forecast.time.max",
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TableColumnAttributeBuilder.builder("maximum run time for forecasts", false)
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.setAliases("ftmax", "forecastTimeMax")
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.build());
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table.addCell("forecast.time.avg",
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TableColumnAttributeBuilder.builder("average runtime for all forecasts (milliseconds)", false)
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.setAliases("ftavg", "forecastTimeAvg")
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.build());
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table.addCell("forecast.time.total",
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TableColumnAttributeBuilder.builder("total runtime for all forecasts", false)
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.setAliases("ftt", "forecastTimeTotal").build());
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//Node info
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table.addCell("node.id",
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TableColumnAttributeBuilder.builder("id of the assigned node", false)
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.setAliases("ni", "nodeId")
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.build());
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table.addCell("node.name",
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TableColumnAttributeBuilder.builder("name of the assigned node", false)
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.setAliases("nn", "nodeName")
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.build());
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table.addCell("node.ephemeral_id",
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TableColumnAttributeBuilder.builder("ephemeral id of the assigned node", false)
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.setAliases("ne", "nodeEphemeralId")
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.build());
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table.addCell("node.address",
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TableColumnAttributeBuilder.builder("network address of the assigned node", false)
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.setAliases("na", "nodeAddress")
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.build());
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//Timing Stats
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table.addCell("bucket.count",
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TableColumnAttributeBuilder.builder("bucket count")
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.setAliases("bc", "bucketCount")
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.build());
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table.addCell("bucket.time.total",
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TableColumnAttributeBuilder.builder("total bucket processing time", false)
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.setAliases("btt", "bucketTimeTotal")
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.build());
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table.addCell("bucket.time.min",
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TableColumnAttributeBuilder.builder("minimum bucket processing time", false)
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.setAliases("btmin", "bucketTimeMin")
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.build());
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table.addCell("bucket.time.max",
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TableColumnAttributeBuilder.builder("maximum bucket processing time", false)
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.setAliases("btmax", "bucketTimeMax")
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.build());
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table.addCell("bucket.time.exp_avg",
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TableColumnAttributeBuilder.builder("exponential average bucket processing time (milliseconds)", false)
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.setAliases("btea", "bucketTimeExpAvg")
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.build());
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table.addCell("bucket.time.exp_avg_hour",
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TableColumnAttributeBuilder.builder("exponential average bucket processing time by hour (milliseconds)", false)
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.setAliases("bteah", "bucketTimeExpAvgHour")
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.build());
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table.endHeaders();
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return table;
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}
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private Table buildTable(RestRequest request, GetJobsStatsAction.Response jobStats) {
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Table table = getTableWithHeader(request);
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jobStats.getResponse().results().forEach(job -> {
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table.startRow();
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table.addCell(job.getJobId());
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table.addCell(job.getState().value());
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table.addCell(job.getOpenTime());
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table.addCell(job.getAssignmentExplanation());
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DataCounts dataCounts = job.getDataCounts();
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table.addCell(dataCounts.getProcessedRecordCount());
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table.addCell(dataCounts.getProcessedFieldCount());
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table.addCell(new ByteSizeValue(dataCounts.getInputBytes()));
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table.addCell(dataCounts.getInputRecordCount());
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table.addCell(dataCounts.getInputFieldCount());
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table.addCell(dataCounts.getInvalidDateCount());
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table.addCell(dataCounts.getMissingFieldCount());
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table.addCell(dataCounts.getOutOfOrderTimeStampCount());
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table.addCell(dataCounts.getEmptyBucketCount());
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table.addCell(dataCounts.getSparseBucketCount());
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table.addCell(dataCounts.getBucketCount());
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table.addCell(dataCounts.getEarliestRecordTimeStamp());
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table.addCell(dataCounts.getLatestRecordTimeStamp());
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table.addCell(dataCounts.getLastDataTimeStamp());
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table.addCell(dataCounts.getLatestEmptyBucketTimeStamp());
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table.addCell(dataCounts.getLatestSparseBucketTimeStamp());
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ModelSizeStats modelSizeStats = job.getModelSizeStats();
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table.addCell(modelSizeStats == null ? null : new ByteSizeValue(modelSizeStats.getModelBytes()));
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getMemoryStatus().toString());
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table.addCell(modelSizeStats == null || modelSizeStats.getModelBytesExceeded() == null ?
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null :
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new ByteSizeValue(modelSizeStats.getModelBytesExceeded()));
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table.addCell(modelSizeStats == null || modelSizeStats.getModelBytesMemoryLimit() == null ?
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null :
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new ByteSizeValue(modelSizeStats.getModelBytesMemoryLimit()));
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getTotalByFieldCount());
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getTotalOverFieldCount());
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getTotalPartitionFieldCount());
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getBucketAllocationFailuresCount());
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getLogTime());
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table.addCell(modelSizeStats == null ? null : modelSizeStats.getTimestamp());
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ForecastStats forecastStats = job.getForecastStats();
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boolean missingForecastStats = forecastStats == null || forecastStats.getTotal() <= 0L;
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table.addCell(forecastStats == null ? null : forecastStats.getTotal());
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table.addCell(missingForecastStats ? null : new ByteSizeValue((long)forecastStats.getMemoryStats().getMin()));
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table.addCell(missingForecastStats ? null : new ByteSizeValue((long)forecastStats.getMemoryStats().getMax()));
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table.addCell(missingForecastStats ? null : new ByteSizeValue(Math.round(forecastStats.getMemoryStats().getAvg())));
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table.addCell(missingForecastStats ? null : new ByteSizeValue((long)forecastStats.getMemoryStats().getTotal()));
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table.addCell(missingForecastStats ? null : forecastStats.getRecordStats().getMin());
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table.addCell(missingForecastStats ? null : forecastStats.getRecordStats().getMax());
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table.addCell(missingForecastStats ? null : forecastStats.getRecordStats().getAvg());
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table.addCell(missingForecastStats ? null : forecastStats.getRecordStats().getTotal());
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table.addCell(missingForecastStats ? null : TimeValue.timeValueMillis((long)forecastStats.getRuntimeStats().getMin()));
|
||||
table.addCell(missingForecastStats ? null : TimeValue.timeValueMillis((long)forecastStats.getRuntimeStats().getMax()));
|
||||
table.addCell(missingForecastStats ? null : forecastStats.getRuntimeStats().getAvg());
|
||||
table.addCell(missingForecastStats ? null : TimeValue.timeValueMillis((long)forecastStats.getRuntimeStats().getTotal()));
|
||||
|
||||
DiscoveryNode node = job.getNode();
|
||||
table.addCell(node == null ? null : node.getId());
|
||||
table.addCell(node == null ? null : node.getName());
|
||||
table.addCell(node == null ? null : node.getEphemeralId());
|
||||
table.addCell(node == null ? null : node.getAddress().toString());
|
||||
|
||||
TimingStats timingStats = job.getTimingStats();
|
||||
table.addCell(timingStats == null ? null : timingStats.getBucketCount());
|
||||
table.addCell(timingStats == null ? null : TimeValue.timeValueMillis((long)timingStats.getTotalBucketProcessingTimeMs()));
|
||||
table.addCell(timingStats == null || timingStats.getMinBucketProcessingTimeMs() == null ?
|
||||
null :
|
||||
TimeValue.timeValueMillis(timingStats.getMinBucketProcessingTimeMs().longValue()));
|
||||
table.addCell(timingStats == null || timingStats.getMaxBucketProcessingTimeMs() == null ?
|
||||
null :
|
||||
TimeValue.timeValueMillis(timingStats.getMaxBucketProcessingTimeMs().longValue()));
|
||||
table.addCell(timingStats == null ? null : timingStats.getExponentialAvgBucketProcessingTimeMs());
|
||||
table.addCell(timingStats == null ? null : timingStats.getExponentialAvgBucketProcessingTimePerHourMs());
|
||||
|
||||
table.endRow();
|
||||
});
|
||||
return table;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,139 @@
|
|||
/*
|
||||
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
|
||||
* or more contributor license agreements. Licensed under the Elastic License;
|
||||
* you may not use this file except in compliance with the Elastic License.
|
||||
*/
|
||||
package org.elasticsearch.xpack.ml.rest.cat;
|
||||
|
||||
|
||||
import org.elasticsearch.common.Strings;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Locale;
|
||||
|
||||
/**
|
||||
* Helper to build {@link org.elasticsearch.rest.action.cat.RestTable} display attributes
|
||||
*/
|
||||
public final class TableColumnAttributeBuilder {
|
||||
|
||||
private static final String ATTR_DELIM = ";";
|
||||
private String aliases;
|
||||
private Boolean displayByDefault;
|
||||
private String description;
|
||||
private String textAlignment;
|
||||
private String sibling;
|
||||
|
||||
public static TableColumnAttributeBuilder builder() {
|
||||
return new TableColumnAttributeBuilder();
|
||||
}
|
||||
|
||||
public static TableColumnAttributeBuilder builder(String description) {
|
||||
return new TableColumnAttributeBuilder().setDescription(description);
|
||||
}
|
||||
|
||||
public static TableColumnAttributeBuilder builder(String description, boolean display) {
|
||||
return new TableColumnAttributeBuilder().setDescription(description).setDisplayByDefault(display);
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the various aliases available to this column
|
||||
*
|
||||
* The API consumer can supply one of these strings in the parameter flags instead of the full column name
|
||||
*
|
||||
* Default: no configured aliases
|
||||
* @param aliases Non-null array of strings
|
||||
*/
|
||||
public TableColumnAttributeBuilder setAliases(String... aliases) {
|
||||
this.aliases = Strings.arrayToCommaDelimitedString(aliases);
|
||||
return this;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether or not to display the column by default
|
||||
*
|
||||
* Default: true, always display the column
|
||||
* @param displayByDefault When false, the user must specify to display the column in the REST request
|
||||
*/
|
||||
public TableColumnAttributeBuilder setDisplayByDefault(Boolean displayByDefault) {
|
||||
this.displayByDefault = displayByDefault;
|
||||
return this;
|
||||
}
|
||||
|
||||
/**
|
||||
* Human readable description of the column. Consumed via the `help` REST call.
|
||||
*
|
||||
* Default: "not available"
|
||||
* @param description Human readable description
|
||||
*/
|
||||
public TableColumnAttributeBuilder setDescription(String description) {
|
||||
this.description = description;
|
||||
return this;
|
||||
}
|
||||
|
||||
/**
|
||||
* Text alignment for the column when building the table
|
||||
*
|
||||
* Default: {@link TextAlign#LEFT}
|
||||
* @param textAlignment The desired text alignment
|
||||
*/
|
||||
public TableColumnAttributeBuilder setTextAlignment(TextAlign textAlignment) {
|
||||
this.textAlignment = textAlignment.toString();
|
||||
return this;
|
||||
}
|
||||
|
||||
/**
|
||||
* The sibling column for this column
|
||||
*
|
||||
* If a normal column is included and the sibling is requested, then the sibling is included as well
|
||||
*
|
||||
* Example:
|
||||
*
|
||||
* Cat indices, requesting `pri` and wanting the `cs` columns (which have a sibling, pri.cs)
|
||||
*
|
||||
* {@code GET _cat/indices?pri&h=cs&v}
|
||||
*
|
||||
* ss pri.ss
|
||||
* 290kb 290kb
|
||||
* 230b 230b
|
||||
*
|
||||
* Default: No sibling
|
||||
* @param sibling The sibling column prefix
|
||||
*/
|
||||
public TableColumnAttributeBuilder setSibling(String sibling) {
|
||||
this.sibling = sibling;
|
||||
return this;
|
||||
}
|
||||
|
||||
public String build() {
|
||||
List<String> attrs = new ArrayList<>();
|
||||
if (aliases != null) {
|
||||
attrs.add("alias:" + aliases);
|
||||
}
|
||||
if (displayByDefault != null) {
|
||||
attrs.add("default:" + displayByDefault.toString());
|
||||
}
|
||||
if (description != null) {
|
||||
attrs.add("desc:" + description);
|
||||
}
|
||||
if (textAlignment != null) {
|
||||
attrs.add("text-align:" + textAlignment);
|
||||
}
|
||||
if (sibling != null) {
|
||||
attrs.add("sibling:" + sibling);
|
||||
}
|
||||
return String.join(ATTR_DELIM, attrs);
|
||||
}
|
||||
|
||||
public enum TextAlign {
|
||||
LEFT,
|
||||
RIGHT,
|
||||
NONE;
|
||||
|
||||
@Override
|
||||
public String toString() {
|
||||
return name().toLowerCase(Locale.ROOT);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,89 @@
|
|||
{
|
||||
"cat.ml.jobs":{
|
||||
"documentation":{
|
||||
"url":"http://www.elastic.co/guide/en/elasticsearch/reference/current/ml-get-job-stats.html"
|
||||
},
|
||||
"stability":"stable",
|
||||
"url":{
|
||||
"paths":[
|
||||
{
|
||||
"path":"/_cat/ml/anomaly_detectors",
|
||||
"methods":[
|
||||
"GET"
|
||||
]
|
||||
},
|
||||
{
|
||||
"path":"/_cat/ml/anomaly_detectors/{job_id}",
|
||||
"methods":[
|
||||
"GET"
|
||||
],
|
||||
"parts":{
|
||||
"job_id":{
|
||||
"type":"string",
|
||||
"description":"The ID of the jobs stats to fetch"
|
||||
}
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
"params":{
|
||||
"allow_no_jobs":{
|
||||
"type":"boolean",
|
||||
"required":false,
|
||||
"description":"Whether to ignore if a wildcard expression matches no jobs. (This includes `_all` string or when no jobs have been specified)"
|
||||
},
|
||||
"bytes":{
|
||||
"type":"enum",
|
||||
"description":"The unit in which to display byte values",
|
||||
"options":[
|
||||
"b",
|
||||
"k",
|
||||
"kb",
|
||||
"m",
|
||||
"mb",
|
||||
"g",
|
||||
"gb",
|
||||
"t",
|
||||
"tb",
|
||||
"p",
|
||||
"pb"
|
||||
]
|
||||
},
|
||||
"format":{
|
||||
"type":"string",
|
||||
"description":"a short version of the Accept header, e.g. json, yaml"
|
||||
},
|
||||
"h":{
|
||||
"type":"list",
|
||||
"description":"Comma-separated list of column names to display"
|
||||
},
|
||||
"help":{
|
||||
"type":"boolean",
|
||||
"description":"Return help information",
|
||||
"default":false
|
||||
},
|
||||
"s":{
|
||||
"type":"list",
|
||||
"description":"Comma-separated list of column names or column aliases to sort by"
|
||||
},
|
||||
"time":{
|
||||
"type":"enum",
|
||||
"description":"The unit in which to display time values",
|
||||
"options":[
|
||||
"d (Days)",
|
||||
"h (Hours)",
|
||||
"m (Minutes)",
|
||||
"s (Seconds)",
|
||||
"ms (Milliseconds)",
|
||||
"micros (Microseconds)",
|
||||
"nanos (Nanoseconds)"
|
||||
]
|
||||
},
|
||||
"v":{
|
||||
"type":"boolean",
|
||||
"description":"Verbose mode. Display column headers",
|
||||
"default":false
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,113 @@
|
|||
setup:
|
||||
- skip:
|
||||
features: headers
|
||||
- do:
|
||||
headers:
|
||||
Authorization: "Basic eF9wYWNrX3Jlc3RfdXNlcjp4LXBhY2stdGVzdC1wYXNzd29yZA==" # run as x_pack_rest_user, i.e. the test setup superuser
|
||||
ml.put_job:
|
||||
job_id: job-stats-test
|
||||
body: >
|
||||
{
|
||||
"job_id":"job-stats-test",
|
||||
"description":"Analysis of response time by airline",
|
||||
"analysis_config" : {
|
||||
"bucket_span": "1h",
|
||||
"detectors" :[{"function":"metric","field_name":"responsetime","by_field_name":"airline"}]
|
||||
},
|
||||
"analysis_limits" : {
|
||||
"model_memory_limit": "10mb"
|
||||
},
|
||||
"data_description" : {
|
||||
"format":"xcontent",
|
||||
"time_field":"time",
|
||||
"time_format":"epoch"
|
||||
}
|
||||
}
|
||||
|
||||
- do:
|
||||
headers:
|
||||
Authorization: "Basic eF9wYWNrX3Jlc3RfdXNlcjp4LXBhY2stdGVzdC1wYXNzd29yZA==" # run as x_pack_rest_user, i.e. the test setup superuser
|
||||
ml.open_job:
|
||||
job_id: job-stats-test
|
||||
|
||||
- do:
|
||||
headers:
|
||||
Authorization: "Basic eF9wYWNrX3Jlc3RfdXNlcjp4LXBhY2stdGVzdC1wYXNzd29yZA==" # run as x_pack_rest_user, i.e. the test setup superuser
|
||||
ml.put_job:
|
||||
job_id: jobs-get-stats-datafeed-job
|
||||
body: >
|
||||
{
|
||||
"job_id":"jobs-get-stats-datafeed-job",
|
||||
"description":"A job with a datafeed",
|
||||
"analysis_config" : {
|
||||
"bucket_span": "1h",
|
||||
"detectors" :[{"function":"metric","field_name":"responsetime","by_field_name":"airline"}]
|
||||
},
|
||||
"analysis_limits" : {
|
||||
"model_memory_limit": "10mb"
|
||||
},
|
||||
"data_description" : {
|
||||
"format" : "xcontent",
|
||||
"time_field":"time",
|
||||
"time_format":"yyyy-MM-dd'T'HH:mm:ssX"
|
||||
}
|
||||
}
|
||||
- do:
|
||||
headers:
|
||||
Authorization: "Basic eF9wYWNrX3Jlc3RfdXNlcjp4LXBhY2stdGVzdC1wYXNzd29yZA==" # run as x_pack_rest_user, i.e. the test setup superuser
|
||||
ml.open_job:
|
||||
job_id: jobs-get-stats-datafeed-job
|
||||
|
||||
- do:
|
||||
headers:
|
||||
Authorization: "Basic eF9wYWNrX3Jlc3RfdXNlcjp4LXBhY2stdGVzdC1wYXNzd29yZA==" # run as x_pack_rest_user, i.e. the test setup superuser
|
||||
ml.put_datafeed:
|
||||
datafeed_id: datafeed-1
|
||||
body: >
|
||||
{
|
||||
"job_id":"jobs-get-stats-datafeed-job",
|
||||
"indexes":["farequote"]
|
||||
}
|
||||
|
||||
---
|
||||
"Test get job stats after uploading data prompting the creation of some stats":
|
||||
|
||||
- do:
|
||||
ml.post_data:
|
||||
job_id: job-stats-test
|
||||
body: >
|
||||
{"airline":"AAL","responsetime":"132.2046","time":"1403481600"}
|
||||
{"airline":"JZA","responsetime":"990.4628","time":"1403481600"}
|
||||
{"airline":"JZA","responsetime":"244.1276","time":"1403485200"}
|
||||
|
||||
- do:
|
||||
ml.flush_job:
|
||||
job_id: job-stats-test
|
||||
- match: { flushed: true }
|
||||
|
||||
- do:
|
||||
cat.ml.jobs:
|
||||
job_id: job-stats-test
|
||||
- match:
|
||||
$body: |
|
||||
/ #id state data.processed_records model.bytes model.memory_status forecast.total bucket.count
|
||||
^ (job\-stats\-test \s+ \w+ \s+ \d+ \s+ .*? \s+ \w+ \s+ \d+ \s+ \d+ \n)+ $/
|
||||
|
||||
- do:
|
||||
cat.ml.jobs:
|
||||
v: true
|
||||
job_id: job-stats-test
|
||||
- match:
|
||||
$body: |
|
||||
/^ id \s+ state \s+ data\.processed_records \s+ model\.bytes \s+ model\.memory_status \s+ forecast\.total \s+ bucket\.count \n
|
||||
(job\-stats\-test \s+ \w+ \s+ \d+ \s+ .*? \s+ \w+ \s+ \d+ \s+ \d+ \n)+ $/
|
||||
|
||||
- do:
|
||||
cat.ml.jobs:
|
||||
h: id,data.processed_records,data.processed_fields,data.input_bytes
|
||||
v: true
|
||||
- match:
|
||||
$body: |
|
||||
/^ id \s+ data\.processed_records \s+ data\.processed_fields \s+ data\.input_bytes \n
|
||||
(job\-stats\-test \s+ \d+ \s+ \d+ \s+ \w+ \n)+
|
||||
(jobs\-get\-stats\-datafeed\-job \s+ \d+ \s+ \d+ \s+ \w+ \n)+ $/
|
||||
Loading…
Reference in New Issue