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