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• config object

  A data frame analytics config as described in create data frame analytics jobs. Note that id and dest don’t need to be provided in the context of this API.

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  • source object Required
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    • index string | array[string] Required

      Index or indices on which to perform the analysis. It can be a single index or index pattern as well as an array of indices or patterns. NOTE: If your source indices contain documents with the same IDs, only the document that is indexed last appears in the destination index.

    • query object

      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": {}}.

      External documentation
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      • common object Deprecated
      • fuzzy object

        Returns documents that contain terms similar to the search term, as measured by a Levenshtein edit distance.

      • geo_grid object

        Matches geo_point and geo_shape values that intersect a grid cell from a GeoGrid aggregation.

      • intervals object

        Returns documents based on the order and proximity of matching terms.

      • match object

        Returns documents that match a provided text, number, date or boolean value. The provided text is analyzed before matching.

      • match_bool_prefix object

        Analyzes its input and constructs a bool query from the terms. Each term except the last is used in a term query. The last term is used in a prefix query.

      • match_phrase object

        Analyzes the text and creates a phrase query out of the analyzed text.

      • match_phrase_prefix object

        Returns documents that contain the words of a provided text, in the same order as provided. The last term of the provided text is treated as a prefix, matching any words that begin with that term.

      • prefix object

        Returns documents that contain a specific prefix in a provided field.

      • range object

        Returns documents that contain terms within a provided range.

      • regexp object

        Returns documents that contain terms matching a regular expression.

      • span_term object

        Matches spans containing a term.

      • term object

        Returns documents that contain an exact term in a provided field. To return a document, the query term must exactly match the queried field's value, including whitespace and capitalization.

      • terms_set object

        Returns documents that contain a minimum number of exact terms in a provided field. To return a document, a required number of terms must exactly match the field values, including whitespace and capitalization.

      • text_expansion object Deprecated Generally available; Added in 8.8.0

        Uses a natural language processing model to convert the query text into a list of token-weight pairs which are then used in a query against a sparse vector or rank features field.

      • weighted_tokens object Deprecated Generally available; Added in 8.13.0

        Supports returning text_expansion query results by sending in precomputed tokens with the query.

      • wildcard object

        Returns documents that contain terms matching a wildcard pattern.

    • runtime_mappings object

      Definitions of runtime fields that will become part of the mapping of the destination index.

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      • * object Additional properties
    • _source object

      Specify includes and/or `excludes patterns to select which fields will be present in the destination. Fields that are excluded cannot be included in the analysis.

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      • includes array[string]

        An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.

      • excludes array[string]

        An array of strings that defines the fields that will be included in the analysis.

  • analysis object Required
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    • classification object
    • outlier_detection object

      The configuration information necessary to perform outlier detection. NOTE: Advanced parameters are for fine-tuning classification analysis. They are set automatically by hyperparameter optimization to give the minimum validation error. It is highly recommended to use the default values unless you fully understand the function of these parameters.

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      • compute_feature_influence boolean

        Specifies whether the feature influence calculation is enabled.

        Default value is true.

      • feature_influence_threshold number

        The minimum outlier score that a document needs to have in order to calculate its feature influence score. Value range: 0-1.

        Default value is 0.1.

      • method string

        The method that outlier detection uses. Available methods are lof, ldof, distance_kth_nn, distance_knn, and ensemble. The default value is ensemble, which means that outlier detection uses an ensemble of different methods and normalises and combines their individual outlier scores to obtain the overall outlier score.

        Default value is ensemble.

      • n_neighbors number

        Defines the value for how many nearest neighbors each method of outlier detection uses to calculate its outlier score. When the value is not set, different values are used for different ensemble members. This default behavior helps improve the diversity in the ensemble; only override it if you are confident that the value you choose is appropriate for the data set.

      • outlier_fraction number

        The proportion of the data set that is assumed to be outlying prior to outlier detection. For example, 0.05 means it is assumed that 5% of values are real outliers and 95% are inliers.

      • standardization_enabled boolean

        If true, the following operation is performed on the columns before computing outlier scores: (x_i - mean(x_i)) / sd(x_i).

        Default value is true.

    • regression object
  • model_memory_limit string
  • max_num_threads number
  • analyzed_fields object
    Hide analyzed_fields attributes Show analyzed_fields attributes object

    • includes array[string]

      An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.

    • excludes array[string]

      An array of strings that defines the fields that will be included in the analysis.