[role="xpack"] [testenv="platinum"] [[cat-anomaly-detectors]] === cat anomaly detectors API ++++ cat anomaly detectors ++++ Returns configuration and usage information about {anomaly-jobs}. [[cat-anomaly-detectors-request]] ==== {api-request-title} `GET /_cat/ml/anomaly_detectors/` + `GET /_cat/ml/anomaly_detectors` [[cat-anomaly-detectors-prereqs]] ==== {api-prereq-title} * If the {es} {security-features} are enabled, you must have `monitor_ml`, `monitor`, `manage_ml`, or `manage` cluster privileges to use this API. See <> and {ml-docs}/setup.html[Set up {ml-features}]. [[cat-anomaly-detectors-desc]] ==== {api-description-title} See {ml-docs}/ml-jobs.html[{anomaly-jobs-cap}]. NOTE: This API returns a maximum of 10,000 jobs. [[cat-anomaly-detectors-path-params]] ==== {api-path-parms-title} ``:: (Optional, string) include::{docdir}/ml/ml-shared.asciidoc[tag=job-id-anomaly-detection] [[cat-anomaly-detectors-query-params]] ==== {api-query-parms-title} `allow_no_jobs`:: (Optional, boolean) include::{docdir}/ml/ml-shared.asciidoc[tag=allow-no-jobs] include::{docdir}/rest-api/common-parms.asciidoc[tag=bytes] include::{docdir}/rest-api/common-parms.asciidoc[tag=http-format] include::{docdir}/rest-api/common-parms.asciidoc[tag=cat-h] + If you do not specify which columns to include, the API returns the default columns. If you explicitly specify one or more columns, it returns only the specified columns. + Valid columns are: `assignment_explanation`, `ae`::: include::{docdir}/ml/ml-shared.asciidoc[tag=assignment-explanation-anomaly-jobs] `buckets.count`, `bc`, `bucketsCount`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-count-anomaly-jobs] `buckets.time.exp_avg`, `btea`, `bucketsTimeExpAvg`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-time-exponential-average] `buckets.time.exp_avg_hour`, `bteah`, `bucketsTimeExpAvgHour`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-time-exponential-average-hour] `buckets.time.max`, `btmax`, `bucketsTimeMax`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-time-maximum] `buckets.time.min`, `btmin`, `bucketsTimeMin`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-time-minimum] `buckets.time.total`, `btt`, `bucketsTimeTotal`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-time-total] `data.buckets`, `db`, `dataBuckets`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-count] `data.earliest_record`, `der`, `dataEarliestRecord`::: include::{docdir}/ml/ml-shared.asciidoc[tag=earliest-record-timestamp] `data.empty_buckets`, `deb`, `dataEmptyBuckets`::: include::{docdir}/ml/ml-shared.asciidoc[tag=empty-bucket-count] `data.input_bytes`, `dib`, `dataInputBytes`::: include::{docdir}/ml/ml-shared.asciidoc[tag=input-bytes] `data.input_fields`, `dif`, `dataInputFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=input-field-count] `data.input_records`, `dir`, `dataInputRecords`::: include::{docdir}/ml/ml-shared.asciidoc[tag=input-record-count] `data.invalid_dates`, `did`, `dataInvalidDates`::: include::{docdir}/ml/ml-shared.asciidoc[tag=invalid-date-count] `data.last`, `dl`, `dataLast`::: include::{docdir}/ml/ml-shared.asciidoc[tag=last-data-time] `data.last_empty_bucket`, `dleb`, `dataLastEmptyBucket`::: include::{docdir}/ml/ml-shared.asciidoc[tag=latest-empty-bucket-timestamp] `data.last_sparse_bucket`, `dlsb`, `dataLastSparseBucket`::: include::{docdir}/ml/ml-shared.asciidoc[tag=latest-sparse-record-timestamp] `data.latest_record`, `dlr`, `dataLatestRecord`::: include::{docdir}/ml/ml-shared.asciidoc[tag=latest-record-timestamp] `data.missing_fields`, `dmf`, `dataMissingFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=missing-field-count] `data.out_of_order_timestamps`, `doot`, `dataOutOfOrderTimestamps`::: include::{docdir}/ml/ml-shared.asciidoc[tag=out-of-order-timestamp-count] `data.processed_fields`, `dpf`, `dataProcessedFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=processed-field-count] `data.processed_records`, `dpr`, `dataProcessedRecords`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=processed-record-count] `data.sparse_buckets`, `dsb`, `dataSparseBuckets`::: include::{docdir}/ml/ml-shared.asciidoc[tag=sparse-bucket-count] `forecasts.memory.avg`, `fmavg`, `forecastsMemoryAvg`::: The average memory usage in bytes for forecasts related to the {anomaly-job}. `forecasts.memory.max`, `fmmax`, `forecastsMemoryMax`::: The maximum memory usage in bytes for forecasts related to the {anomaly-job}. `forecasts.memory.min`, `fmmin`, `forecastsMemoryMin`::: The minimum memory usage in bytes for forecasts related to the {anomaly-job}. `forecasts.memory.total`, `fmt`, `forecastsMemoryTotal`::: The total memory usage in bytes for forecasts related to the {anomaly-job}. `forecasts.records.avg`, `fravg`, `forecastsRecordsAvg`::: The average number of `model_forecast` documents written for forecasts related to the {anomaly-job}. `forecasts.records.max`, `frmax`, `forecastsRecordsMax`::: The maximum number of `model_forecast` documents written for forecasts related to the {anomaly-job}. `forecasts.records.min`, `frmin`, `forecastsRecordsMin`::: The minimum number of `model_forecast` documents written for forecasts related to the {anomaly-job}. `forecasts.records.total`, `frt`, `forecastsRecordsTotal`::: The total number of `model_forecast` documents written for forecasts related to the {anomaly-job}. `forecasts.time.avg`, `ftavg`, `forecastsTimeAvg`::: The average runtime in milliseconds for forecasts related to the {anomaly-job}. `forecasts.time.max`, `ftmax`, `forecastsTimeMax`::: The maximum runtime in milliseconds for forecasts related to the {anomaly-job}. `forecasts.time.min`, `ftmin`, `forecastsTimeMin`::: The minimum runtime in milliseconds for forecasts related to the {anomaly-job}. `forecasts.time.total`, `ftt`, `forecastsTimeTotal`::: The total runtime in milliseconds for forecasts related to the {anomaly-job}. `forecasts.total`, `ft`, `forecastsTotal`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=forecast-total] `id`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=job-id-anomaly-detection] `model.bucket_allocation_failures`, `mbaf`, `modelBucketAllocationFailures`::: include::{docdir}/ml/ml-shared.asciidoc[tag=bucket-allocation-failures-count] `model.by_fields`, `mbf`, `modelByFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=total-by-field-count] `model.bytes`, `mb`, `modelBytes`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=model-bytes] `model.bytes_exceeded`, `mbe`, `modelBytesExceeded`::: include::{docdir}/ml/ml-shared.asciidoc[tag=model-bytes-exceeded] `model.categorization_status`, `mcs`, `modelCategorizationStatus`::: include::{docdir}/ml/ml-shared.asciidoc[tag=categorization-status] `model.categorized_doc_count`, `mcdc`, `modelCategorizedDocCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=categorized-doc-count] `model.dead_category_count`, `mdcc`, `modelDeadCategoryCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=dead-category-count] `model.failed_category_count`, `mdcc`, `modelFailedCategoryCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=failed-category-count] `model.frequent_category_count`, `mfcc`, `modelFrequentCategoryCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=frequent-category-count] `model.log_time`, `mlt`, `modelLogTime`::: The timestamp when the model stats were gathered, according to server time. `model.memory_limit`, `mml`, `modelMemoryLimit`::: include::{docdir}/ml/ml-shared.asciidoc[tag=model-memory-limit-anomaly-jobs] `model.memory_status`, `mms`, `modelMemoryStatus`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=model-memory-status] `model.over_fields`, `mof`, `modelOverFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=total-over-field-count] `model.partition_fields`, `mpf`, `modelPartitionFields`::: include::{docdir}/ml/ml-shared.asciidoc[tag=total-partition-field-count] `model.rare_category_count`, `mrcc`, `modelRareCategoryCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=rare-category-count] `model.timestamp`, `mt`, `modelTimestamp`::: include::{docdir}/ml/ml-shared.asciidoc[tag=model-timestamp] `model.total_category_count`, `mtcc`, `modelTotalCategoryCount`::: include::{docdir}/ml/ml-shared.asciidoc[tag=total-category-count] `node.address`, `na`, `nodeAddress`::: The network address of the node. + include::{docdir}/ml/ml-shared.asciidoc[tag=node-jobs] `node.ephemeral_id`, `ne`, `nodeEphemeralId`::: The ephemeral ID of the node. + include::{docdir}/ml/ml-shared.asciidoc[tag=node-jobs] `node.id`, `ni`, `nodeId`::: The unique identifier of the node. + include::{docdir}/ml/ml-shared.asciidoc[tag=node-jobs] `node.name`, `nn`, `nodeName`::: The node name. + include::{docdir}/ml/ml-shared.asciidoc[tag=node-jobs] `opened_time`, `ot`::: include::{docdir}/ml/ml-shared.asciidoc[tag=open-time] `state`, `s`::: (Default) include::{docdir}/ml/ml-shared.asciidoc[tag=state-anomaly-job] include::{docdir}/rest-api/common-parms.asciidoc[tag=help] include::{docdir}/rest-api/common-parms.asciidoc[tag=cat-s] include::{docdir}/rest-api/common-parms.asciidoc[tag=time] include::{docdir}/rest-api/common-parms.asciidoc[tag=cat-v] [[cat-anomaly-detectors-example]] ==== {api-examples-title} [source,console] -------------------------------------------------- GET _cat/ml/anomaly_detectors?h=id,s,dpr,mb&v -------------------------------------------------- // TEST[skip:kibana sample data] [source,console-result] ---- id s dpr mb high_sum_total_sales closed 14022 1.5mb low_request_rate closed 1216 40.5kb response_code_rates closed 28146 132.7kb url_scanning closed 28146 501.6kb ---- // TESTRESPONSE[skip:kibana sample data]