Path parameters

• job_id string Required

  Identifier for the job.

Responses

• 200 application/json
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  • allow_lazy_open boolean Required
  • analysis_config object Required

    Additional properties are allowed.

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    • bucket_span string Required

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • categorization_analyzer string | object

      One of:

      _types:CategorizationAnalyzer string _types:CategorizationAnalyzerDefinition object

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      • char_filter array

        One or more character filters. In addition to the built-in character filters, other plugins can provide more character filters. If this property is not specified, no character filters are applied prior to categorization. If you are customizing some other aspect of the analyzer and you need to achieve the equivalent of categorization_filters (which are not permitted when some other aspect of the analyzer is customized), add them here as pattern replace character filters.

        External documentation
      • filter array

        One or more token filters. In addition to the built-in token filters, other plugins can provide more token filters. If this property is not specified, no token filters are applied prior to categorization.

        External documentation

      • tokenizer object | string

        The name or definition of the tokenizer to use after character filters are applied. This property is compulsory if categorization_analyzer is specified as an object. Machine learning provides a tokenizer called ml_standard that tokenizes in a way that has been determined to produce good categorization results on a variety of log file formats for logs in English. If you want to use that tokenizer but change the character or token filters, specify "tokenizer": "ml_standard" in your categorization_analyzer. Additionally, the ml_classic tokenizer is available, which tokenizes in the same way as the non-customizable tokenizer in old versions of the product (before 6.2). ml_classic was the default categorization tokenizer in versions 6.2 to 7.13, so if you need categorization identical to the default for jobs created in these versions, specify "tokenizer": "ml_classic" in your categorization_analyzer.

        One of:

        object-1 object string-2 string

        Additional properties are allowed.

        Tokenizer reference

        Tokenizer reference
    • categorization_field_name string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • categorization_filters array[string]

      If categorization_field_name is specified, you can also define optional filters. This property expects an array of regular expressions. The expressions are used to filter out matching sequences from the categorization field values.

    • detectors array[object] Required

      An array of detector configuration objects. Detector configuration objects specify which data fields a job analyzes. They also specify which analytical functions are used. You can specify multiple detectors for a job.

      Hide detectors attributes Show detectors attributes object

      • by_field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • custom_rules array[object]

        An array of custom rule objects, which enable you to customize the way detectors operate. For example, a rule may dictate to the detector conditions under which results should be skipped. Kibana refers to custom rules as job rules.

        Hide custom_rules attributes Show custom_rules attributes object

        • actions array[string]

          The set of actions to be triggered when the rule applies. If more than one action is specified the effects of all actions are combined.

          Values are skip_result or skip_model_update.

        • conditions array[object]

          An array of numeric conditions when the rule applies. A rule must either have a non-empty scope or at least one condition. Multiple conditions are combined together with a logical AND.

        • scope object

          A scope of series where the rule applies. A rule must either have a non-empty scope or at least one condition. By default, the scope includes all series. Scoping is allowed for any of the fields that are also specified in by_field_name, over_field_name, or partition_field_name.

      • detector_description string

        A description of the detector.

      • detector_index number

        A unique identifier for the detector. This identifier is based on the order of the detectors in the analysis_config, starting at zero.

      • exclude_frequent string

        Values are all, none, by, or over.

      • field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • function string Required

        The analysis function that is used. For example, count, rare, mean, min, max, and sum.

      • over_field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • partition_field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • use_null boolean

        Defines whether a new series is used as the null series when there is no value for the by or partition fields.

    • influencers array[string] Required

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • model_prune_window string

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • latency string

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • multivariate_by_fields boolean

      This functionality is reserved for internal use. It is not supported for use in customer environments and is not subject to the support SLA of official GA features. If set to true, the analysis will automatically find correlations between metrics for a given by field value and report anomalies when those correlations cease to hold.

    • per_partition_categorization object

      Additional properties are allowed.

      Hide per_partition_categorization attributes Show per_partition_categorization attributes object

      • enabled boolean

        To enable this setting, you must also set the partition_field_name property to the same value in every detector that uses the keyword mlcategory. Otherwise, job creation fails.

      • stop_on_warn boolean

        This setting can be set to true only if per-partition categorization is enabled. If true, both categorization and subsequent anomaly detection stops for partitions where the categorization status changes to warn. This setting makes it viable to have a job where it is expected that categorization works well for some partitions but not others; you do not pay the cost of bad categorization forever in the partitions where it works badly.

    • summary_count_field_name string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

  • analysis_limits object Required

    Additional properties are allowed.

    Hide analysis_limits attributes Show analysis_limits attributes object

    • categorization_examples_limit number

      The maximum number of examples stored per category in memory and in the results data store. If you increase this value, more examples are available, however it requires that you have more storage available. If you set this value to 0, no examples are stored. NOTE: The categorization_examples_limit applies only to analysis that uses categorization.

    • model_memory_limit string

      The approximate maximum amount of memory resources that are required for analytical processing. Once this limit is approached, data pruning becomes more aggressive. Upon exceeding this limit, new entities are not modeled. If the xpack.ml.max_model_memory_limit setting has a value greater than 0 and less than 1024mb, that value is used instead of the default. The default value is relatively small to ensure that high resource usage is a conscious decision. If you have jobs that are expected to analyze high cardinality fields, you will likely need to use a higher value. If you specify a number instead of a string, the units are assumed to be MiB. Specifying a string is recommended for clarity. If you specify a byte size unit of b or kb and the number does not equate to a discrete number of megabytes, it is rounded down to the closest MiB. The minimum valid value is 1 MiB. If you specify a value less than 1 MiB, an error occurs. If you specify a value for the xpack.ml.max_model_memory_limit setting, an error occurs when you try to create jobs that have model_memory_limit values greater than that setting value.

  • background_persist_interval string

    A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

  • create_time number

    Time unit for milliseconds

  • finished_time number

    Time unit for milliseconds

  • custom_settings object
    Hide custom_settings attribute Show custom_settings attribute object

    • * string Additional properties
  • daily_model_snapshot_retention_after_days number Required
  • data_description object Required

    Additional properties are allowed.

    Hide data_description attributes Show data_description attributes object

    • format string

      Only JSON format is supported at this time.

    • time_field string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • time_format string

      The time format, which can be epoch, epoch_ms, or a custom pattern. The value epoch refers to UNIX or Epoch time (the number of seconds since 1 Jan 1970). The value epoch_ms indicates that time is measured in milliseconds since the epoch. The epoch and epoch_ms time formats accept either integer or real values. Custom patterns must conform to the Java DateTimeFormatter class. When you use date-time formatting patterns, it is recommended that you provide the full date, time and time zone. For example: yyyy-MM-dd'T'HH:mm:ssX. If the pattern that you specify is not sufficient to produce a complete timestamp, job creation fails.

    • field_delimiter string
  • datafeed_config object

    Additional properties are allowed.

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    • aggregations object
    • authorization object

      Additional properties are allowed.

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      • api_key object

        Additional properties are allowed.

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        • id string Required

          The identifier for the API key.

        • name string Required

          The name of the API key.

      • roles array[string]

        If a user ID was used for the most recent update to the datafeed, its roles at the time of the update are listed in the response.

      • service_account string

        If a service account was used for the most recent update to the datafeed, the account name is listed in the response.

    • chunking_config object

      Additional properties are allowed.

      Hide chunking_config attributes Show chunking_config attributes object

      • mode string Required

        Values are auto, manual, or off.

      • time_span string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • datafeed_id string Required
    • frequency string

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • indices array[string] Required
    • indexes array[string]
    • job_id string Required
    • max_empty_searches number
    • query_delay string

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • script_fields object
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      • * object Additional properties

        Additional properties are allowed.

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        • script object Required

          Additional properties are allowed.

          Hide script attributes Show script attributes object

          • source string

            The script source.

          • id string
          • params object

            Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.

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            • * object Additional properties

              Additional properties are allowed.

          • lang string

            Any of:

            _types:ScriptLanguage string _types:ScriptLanguage string

            Values are painless, expression, mustache, or java.
          • options object
            Hide options attribute Show options attribute object

            • * string Additional properties
        • ignore_failure boolean
    • scroll_size number
    • delayed_data_check_config object Required

      Additional properties are allowed.

      Hide delayed_data_check_config attributes Show delayed_data_check_config attributes object

      • check_window string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • enabled boolean Required

        Specifies whether the datafeed periodically checks for delayed data.

    • runtime_mappings object
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      • * object Additional properties

        Additional properties are allowed.

        Hide * attributes Show * attributes object

        • fields object

          For type composite

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          • * object Additional properties

            Additional properties are allowed.

            Hide * attribute Show * attribute object

            • type string Required

              Values are boolean, composite, date, double, geo_point, ip, keyword, long, or lookup.

        • fetch_fields array[object]

          For type lookup

          Hide fetch_fields attributes Show fetch_fields attributes object

          • field string Required

            Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

          • format string
        • format string

          A custom format for date type runtime fields.

        • input_field string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • target_field string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • target_index string
        • script object

          Additional properties are allowed.

          Hide script attributes Show script attributes object

          • source string

            The script source.

          • id string
          • params object

            Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.

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            • * object Additional properties

              Additional properties are allowed.

          • lang string

            Any of:

            _types:ScriptLanguage string _types:ScriptLanguage string

            Values are painless, expression, mustache, or java.
          • options object
            Hide options attribute Show options attribute object

            • * string Additional properties
        • type string Required

          Values are boolean, composite, date, double, geo_point, ip, keyword, long, or lookup.

    • indices_options object

      Additional properties are allowed.

      Hide indices_options attributes Show indices_options attributes object

      • allow_no_indices boolean

        If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices. For example, a request targeting foo*,bar* returns an error if an index starts with foo but no index starts with bar.

      • expand_wildcards string | array[string]
      • ignore_unavailable boolean

        If true, missing or closed indices are not included in the response.

      • ignore_throttled boolean

        If true, concrete, expanded or aliased indices are ignored when frozen.

    • query object Required

      The Elasticsearch query domain-specific language (DSL). This value corresponds to the query object in an Elasticsearch search POST body. All the options that are supported by Elasticsearch can be used, as this object is passed verbatim to Elasticsearch. By default, this property has the following value: {"match_all": {"boost": 1}}.

      Additional properties are allowed.

      Query DSL
  • description string
  • groups array[string]
  • job_id string Required
  • job_type string Required
  • job_version string Required
  • model_plot_config object

    Additional properties are allowed.

    Hide model_plot_config attributes Show model_plot_config attributes object

    • annotations_enabled boolean

      If true, enables calculation and storage of the model change annotations for each entity that is being analyzed.

    • enabled boolean

      If true, enables calculation and storage of the model bounds for each entity that is being analyzed.

    • terms string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

  • model_snapshot_id string
  • model_snapshot_retention_days number Required
  • renormalization_window_days number
  • results_index_name string Required
  • results_retention_days number