Body

• config object
  Hide config attributes Show config attributes object

  • source object Required
    Hide source attributes Show source attributes object

    • index string | array[string] Required
    • query object
      Hide query attributes Show query attributes object

      • bool object
        Hide bool attributes Show bool attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string

        • filter object | array[object]

          The clause (query) must appear in matching documents. However, unlike must, the score of the query will be ignored.

          One of:

          query_dsl:QueryContainer object array-2 array[object]

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string

        • must object | array[object]

          The clause (query) must appear in matching documents and will contribute to the score.

          One of:

          query_dsl:QueryContainer object array-2 array[object]

        • must_not object | array[object]

          The clause (query) must not appear in the matching documents. Because scoring is ignored, a score of 0 is returned for all documents.

          One of:

          query_dsl:QueryContainer object array-2 array[object]

        • should object | array[object]

          The clause (query) should appear in the matching document.

          One of:

          query_dsl:QueryContainer object array-2 array[object]
      • boosting object
        Hide boosting attributes Show boosting attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • negative_boost number Required

          Floating point number between 0 and 1.0 used to decrease the relevance scores of documents matching the negative query.

        • negative object Required
        • positive object Required
      • common object Deprecated
      • combined_fields object
        Hide combined_fields attributes Show combined_fields attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • fields array[string] Required

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

        • query string Required

          Text to search for in the provided fields. The combined_fields query analyzes the provided text before performing a search.

        • auto_generate_synonyms_phrase_query boolean

          If true, match phrase queries are automatically created for multi-term synonyms.

        • operator string

          Values are or or and.

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string
        • zero_terms_query string

          Values are none or all.

      • constant_score object
        Hide constant_score attributes Show constant_score attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • filter object Required
      • dis_max object
        Hide dis_max attributes Show dis_max attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • queries array[object] Required

          One or more query clauses. Returned documents must match one or more of these queries. If a document matches multiple queries, Elasticsearch uses the highest relevance score.
        • tie_breaker number

          Floating point number between 0 and 1.0 used to increase the relevance scores of documents matching multiple query clauses.

      • distance_feature object

        One of:

        query_dsl:UntypedDistanceFeatureQuery object query_dsl:GeoDistanceFeatureQuery object query_dsl:DateDistanceFeatureQuery object
      • exists object
        Hide exists attributes Show exists attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

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

      • function_score object
        Hide function_score attributes Show function_score attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • boost_mode string

          Values are multiply, replace, sum, avg, max, or min.

        • functions array[object]

          One or more functions that compute a new score for each document returned by the query.

        • max_boost number

          Restricts the new score to not exceed the provided limit.

        • min_score number

          Excludes documents that do not meet the provided score threshold.

        • query object
        • score_mode string

          Values are multiply, sum, avg, first, max, or min.

      • fuzzy object

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

      • geo_bounding_box object
        Hide geo_bounding_box attributes Show geo_bounding_box attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • type string

          Values are memory or indexed.

        • validation_method string

          Values are coerce, ignore_malformed, or strict.

        • ignore_unmapped boolean

          Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.

      • geo_distance object
        Hide geo_distance attributes Show geo_distance attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • distance string Required
        • distance_type string

          Values are arc or plane.

        • validation_method string

          Values are coerce, ignore_malformed, or strict.

        • ignore_unmapped boolean

          Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.

      • geo_polygon object
        Hide geo_polygon attributes Show geo_polygon attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • validation_method string

          Values are coerce, ignore_malformed, or strict.

        • ignore_unmapped boolean
      • geo_shape object
        Hide geo_shape attributes Show geo_shape attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • ignore_unmapped boolean

          Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.

      • has_child object
        Hide has_child attributes Show has_child attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • ignore_unmapped boolean

          Indicates whether to ignore an unmapped type and not return any documents instead of an error.

        • inner_hits object
          Hide inner_hits attributes Show inner_hits attributes object

          • name string
          • size number

            The maximum number of hits to return per inner_hits.

          • from number

            Inner hit starting document offset.

          • collapse object
          • docvalue_fields array[object]
          • explain boolean
          • highlight
          • ignore_unmapped boolean
          • script_fields
          • seq_no_primary_term boolean
          • fields string | array[string]
          • sort
          • _source
          • stored_fields string | array[string]
          • track_scores boolean
          • version boolean
        • max_children number

          Maximum number of child documents that match the query allowed for a returned parent document. If the parent document exceeds this limit, it is excluded from the search results.

        • min_children number

          Minimum number of child documents that match the query required to match the query for a returned parent document. If the parent document does not meet this limit, it is excluded from the search results.

        • query object Required
        • score_mode string

          Values are none, avg, sum, max, or min.

        • type string Required
      • has_parent object
        Hide has_parent attributes Show has_parent attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • ignore_unmapped boolean

          Indicates whether to ignore an unmapped parent_type and not return any documents instead of an error. You can use this parameter to query multiple indices that may not contain the parent_type.

        • inner_hits object
          Hide inner_hits attributes Show inner_hits attributes object

          • name string
          • size number

            The maximum number of hits to return per inner_hits.

          • from number

            Inner hit starting document offset.

          • collapse object
          • docvalue_fields array[object]
          • explain boolean
          • highlight
          • ignore_unmapped boolean
          • script_fields
          • seq_no_primary_term boolean
          • fields string | array[string]
          • sort
          • _source
          • stored_fields string | array[string]
          • track_scores boolean
          • version boolean
        • parent_type string Required
        • query object Required
        • score boolean

          Indicates whether the relevance score of a matching parent document is aggregated into its child documents.

      • ids object
        Hide ids attributes Show ids attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string

        • values string | array[string]

          One of:

          _types:Id string _types:Ids array[string]
      • intervals object

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

      • knn object
        Hide knn attributes Show knn attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

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

        • query_vector array[number]
        • query_vector_builder object
          Hide query_vector_builder attribute Show query_vector_builder attribute object

          • text_embedding object
        • num_candidates number

          The number of nearest neighbor candidates to consider per shard

        • k number

          The final number of nearest neighbors to return as top hits

        • filter object | array[object]

          Filters for the kNN search query

          One of:

          query_dsl:QueryContainer object array-2 array[object]
        • similarity number

          The minimum similarity for a vector to be considered a match

      • match object

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

      • match_all object
        Hide match_all attributes Show match_all attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
      • 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_none object
        Hide match_none attributes Show match_none attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
      • 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.

      • more_like_this object
        Hide more_like_this attributes Show more_like_this attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • analyzer string

          The analyzer that is used to analyze the free form text. Defaults to the analyzer associated with the first field in fields.

        • boost_terms number

          Each term in the formed query could be further boosted by their tf-idf score. This sets the boost factor to use when using this feature. Defaults to deactivated (0).

        • fail_on_unsupported_field boolean

          Controls whether the query should fail (throw an exception) if any of the specified fields are not of the supported types (text or keyword).

        • fields array[string]

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

        • include boolean

          Specifies whether the input documents should also be included in the search results returned.

        • like array[string | object] Required
        • max_doc_freq number

          The maximum document frequency above which the terms are ignored from the input document.

        • max_query_terms number

          The maximum number of query terms that can be selected.

        • max_word_length number

          The maximum word length above which the terms are ignored. Defaults to unbounded (0).

        • min_doc_freq number

          The minimum document frequency below which the terms are ignored from the input document.

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string
        • min_term_freq number

          The minimum term frequency below which the terms are ignored from the input document.

        • min_word_length number

          The minimum word length below which the terms are ignored.

        • routing string

        • stop_words string | array[string]

          Language value, such as arabic or thai. Defaults to english. Each language value corresponds to a predefined list of stop words in Lucene. See Stop words by language for supported language values and their stop words. Also accepts an array of stop words.

          One of:

          analysis:StopWords string analysis:StopWords array[string]
        • unlike array[string | object]
        • version number
        • version_type string

          Values are internal, external, external_gte, or force.

      • multi_match object
        Hide multi_match attributes Show multi_match attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • analyzer string

          Analyzer used to convert the text in the query value into tokens.

        • auto_generate_synonyms_phrase_query boolean

          If true, match phrase queries are automatically created for multi-term synonyms.

        • cutoff_frequency number Deprecated
        • fields string | array[string]

        • fuzziness string | number

          One of:

          _types:Fuzziness string _types:Fuzziness number
        • fuzzy_rewrite string
        • fuzzy_transpositions boolean

          If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba). Can be applied to the term subqueries constructed for all terms but the final term.

        • lenient boolean

          If true, format-based errors, such as providing a text query value for a numeric field, are ignored.

        • max_expansions number

          Maximum number of terms to which the query will expand.

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string
        • operator string

          Values are and, AND, or, or OR.

        • prefix_length number

          Number of beginning characters left unchanged for fuzzy matching.

        • query string Required

          Text, number, boolean value or date you wish to find in the provided field.

        • slop number

          Maximum number of positions allowed between matching tokens.

        • tie_breaker number

          Determines how scores for each per-term blended query and scores across groups are combined.

        • type string

          Values are best_fields, most_fields, cross_fields, phrase, phrase_prefix, or bool_prefix.

        • zero_terms_query string

          Values are all or none.

      • nested object
        Hide nested attributes Show nested attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • ignore_unmapped boolean

          Indicates whether to ignore an unmapped path and not return any documents instead of an error.

        • inner_hits object
          Hide inner_hits attributes Show inner_hits attributes object

          • name string
          • size number

            The maximum number of hits to return per inner_hits.

          • from number

            Inner hit starting document offset.

          • collapse object
          • docvalue_fields array[object]
          • explain boolean
          • highlight
          • ignore_unmapped boolean
          • script_fields
          • seq_no_primary_term boolean
          • fields string | array[string]
          • sort
          • _source
          • stored_fields string | array[string]
          • track_scores boolean
          • version boolean
        • path string Required

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

        • query object Required
        • score_mode string

          Values are none, avg, sum, max, or min.

      • parent_id object
        Hide parent_id attributes Show parent_id attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • id string
        • ignore_unmapped boolean

          Indicates whether to ignore an unmapped type and not return any documents instead of an error.

        • type string
      • percolate object
        Hide percolate attributes Show percolate attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • document object

          The source of the document being percolated.

        • documents array[object]

          An array of sources of the documents being percolated.
        • field string Required

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

        • id string
        • index string
        • name string

          The suffix used for the _percolator_document_slot field when multiple percolate queries are specified.

        • preference string

          Preference used to fetch document to percolate.

        • routing string
        • version number
      • pinned object
        Hide pinned attributes Show pinned attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • organic object Required
        • ids array[string]

          Document IDs listed in the order they are to appear in results. Required if docs is not specified.

        • docs array[object]

          Documents listed in the order they are to appear in results. Required if ids is not specified.

      • prefix object

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

      • query_string object
        Hide query_string attributes Show query_string attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • allow_leading_wildcard boolean

          If true, the wildcard characters * and ? are allowed as the first character of the query string.

        • analyzer string

          Analyzer used to convert text in the query string into tokens.

        • analyze_wildcard boolean

          If true, the query attempts to analyze wildcard terms in the query string.

        • auto_generate_synonyms_phrase_query boolean

          If true, match phrase queries are automatically created for multi-term synonyms.

        • default_field string

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

        • default_operator string

          Values are and, AND, or, or OR.

        • enable_position_increments boolean

          If true, enable position increments in queries constructed from a query_string search.

        • escape boolean
        • fields array[string]

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

        • fuzziness string | number

          One of:

          _types:Fuzziness string _types:Fuzziness number
        • fuzzy_max_expansions number

          Maximum number of terms to which the query expands for fuzzy matching.

        • fuzzy_prefix_length number

          Number of beginning characters left unchanged for fuzzy matching.

        • fuzzy_rewrite string
        • fuzzy_transpositions boolean

          If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba).

        • lenient boolean

          If true, format-based errors, such as providing a text value for a numeric field, are ignored.

        • max_determinized_states number

          Maximum number of automaton states required for the query.

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string
        • phrase_slop number

          Maximum number of positions allowed between matching tokens for phrases.

        • query string Required

          Query string you wish to parse and use for search.

        • quote_analyzer string

          Analyzer used to convert quoted text in the query string into tokens. For quoted text, this parameter overrides the analyzer specified in the analyzer parameter.

        • quote_field_suffix string

          Suffix appended to quoted text in the query string. You can use this suffix to use a different analysis method for exact matches.

        • rewrite string
        • tie_breaker number

          How to combine the queries generated from the individual search terms in the resulting dis_max query.

        • time_zone string
        • type string

          Values are best_fields, most_fields, cross_fields, phrase, phrase_prefix, or bool_prefix.

      • range object

        Returns documents that contain terms within a provided range.

      • rank_feature object
        Hide rank_feature attributes Show rank_feature attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

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

        • saturation object
        • log object
        • linear object
        • sigmoid object
      • regexp object

        Returns documents that contain terms matching a regular expression.

      • rule object
        Hide rule attributes Show rule attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • organic object Required
        • ruleset_ids array[string] Required
        • match_criteria object Required
      • script object
        Hide script attributes Show script attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • script object Required
          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.

          • lang
          • options object
      • script_score object
        Hide script_score attributes Show script_score attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • min_score number

          Documents with a score lower than this floating point number are excluded from the search results.

        • query object Required
        • script object Required
          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.

          • lang
          • options object
      • semantic object
        Hide semantic attributes Show semantic attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

          The field to query, which must be a semantic_text field type

        • query string Required

          The query text

      • shape object
        Hide shape attributes Show shape attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • ignore_unmapped boolean

          When set to true the query ignores an unmapped field and will not match any documents.

      • simple_query_string object
        Hide simple_query_string attributes Show simple_query_string attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • analyzer string

          Analyzer used to convert text in the query string into tokens.

        • analyze_wildcard boolean

          If true, the query attempts to analyze wildcard terms in the query string.

        • auto_generate_synonyms_phrase_query boolean

          If true, the parser creates a match_phrase query for each multi-position token.

        • default_operator string

          Values are and, AND, or, or OR.

        • fields array[string]

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

        • flags
        • fuzzy_max_expansions number

          Maximum number of terms to which the query expands for fuzzy matching.

        • fuzzy_prefix_length number

          Number of beginning characters left unchanged for fuzzy matching.

        • fuzzy_transpositions boolean

          If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba).

        • lenient boolean

          If true, format-based errors, such as providing a text value for a numeric field, are ignored.

        • minimum_should_match number | string

          The minimum number of terms that should match as integer, percentage or range

          One of:

          _types:MinimumShouldMatch number _types:MinimumShouldMatch string
        • query string Required

          Query string in the simple query string syntax you wish to parse and use for search.

        • quote_field_suffix string

          Suffix appended to quoted text in the query string.

      • span_containing object
        Hide span_containing attributes Show span_containing attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • big object Required
          Hide big attributes Show big attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
        • little object Required
          Hide little attributes Show little attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
      • span_field_masking object
        Hide span_field_masking attributes Show span_field_masking attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

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

        • query object Required
          Hide query attributes Show query attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
      • span_first object
        Hide span_first attributes Show span_first attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • end number Required

          Controls the maximum end position permitted in a match.

        • match object Required
          Hide match attributes Show match attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
      • span_multi object
        Hide span_multi attributes Show span_multi attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • match object Required
      • span_near object
        Hide span_near attributes Show span_near attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • clauses array[object] Required

          Array of one or more other span type queries.
        • in_order boolean

          Controls whether matches are required to be in-order.

        • slop number

          Controls the maximum number of intervening unmatched positions permitted.

      • span_not object
        Hide span_not attributes Show span_not attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • dist number

          The number of tokens from within the include span that can’t have overlap with the exclude span. Equivalent to setting both pre and post.

        • exclude object Required
          Hide exclude attributes Show exclude attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
        • include object Required
          Hide include attributes Show include attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
        • post number

          The number of tokens after the include span that can’t have overlap with the exclude span.

        • pre number

          The number of tokens before the include span that can’t have overlap with the exclude span.

      • span_or object
        Hide span_or attributes Show span_or attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • clauses array[object] Required

          Array of one or more other span type queries.
      • span_term object

        Matches spans containing a term.

      • span_within object
        Hide span_within attributes Show span_within attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • big object Required
          Hide big attributes Show big attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
        • little object Required
          Hide little attributes Show little attributes object

          • span_containing
          • span_field_masking
          • span_first
          • span_gap object

            Can only be used as a clause in a span_near query.

          • span_multi
          • span_near
          • span_not
          • span_or
          • span_term object

            The equivalent of the term query but for use with other span queries.

          • span_within
      • sparse_vector object
        Hide sparse_vector attributes Show sparse_vector attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • field string Required

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

        • query string

          The query text you want to use for search. If inference_id is specified, query must also be specified.

        • prune boolean

          Whether to perform pruning, omitting the non-significant tokens from the query to improve query performance. If prune is true but the pruning_config is not specified, pruning will occur but default values will be used. Default: false

        • pruning_config object
        • query_vector object

          Dictionary of precomputed sparse vectors and their associated weights. Only one of inference_id or query_vector may be supplied in a request.

        • inference_id string
      • 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 object
        Hide terms attributes Show terms attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
      • 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

        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

        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.

      • wrapper object
        Hide wrapper attributes Show wrapper attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • query string Required

          A base64 encoded query. The binary data format can be any of JSON, YAML, CBOR or SMILE encodings

      • type object
        Hide type attributes Show type attributes object

        • boost number

          Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.

        • _name string
        • value string Required
    • runtime_mappings object
      Hide runtime_mappings attributes Show runtime_mappings attributes object

      • Additional properties
      • fields object
        Hide fields attributes Show fields attributes object

        • Additional properties
        • 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
        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.

          Hide params attributes Show params attributes object

          • Additional properties
          • key object

        • lang string

          Any of:

          _types:ScriptLanguage string _types:ScriptLanguage string

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

          • Additional properties
          • key string
      • type string Required

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

    • _source object
      Hide _source attributes Show _source attributes object

      • includes array[string] Required

        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] Required

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

  • analysis object Required
    Hide analysis attributes Show analysis attributes object

    • classification object
      Hide classification attributes Show classification attributes object

      • alpha number

        Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This parameter affects loss calculations by acting as a multiplier of the tree depth. Higher alpha values result in shallower trees and faster training times. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to zero.

      • dependent_variable string Required

        Defines which field of the document is to be predicted. It must match one of the fields in the index being used to train. If this field is missing from a document, then that document will not be used for training, but a prediction with the trained model will be generated for it. It is also known as continuous target variable. For classification analysis, the data type of the field must be numeric (integer, short, long, byte), categorical (ip or keyword), or boolean. There must be no more than 30 different values in this field. For regression analysis, the data type of the field must be numeric.

      • downsample_factor number

        Advanced configuration option. Controls the fraction of data that is used to compute the derivatives of the loss function for tree training. A small value results in the use of a small fraction of the data. If this value is set to be less than 1, accuracy typically improves. However, too small a value may result in poor convergence for the ensemble and so require more trees. By default, this value is calculated during hyperparameter optimization. It must be greater than zero and less than or equal to 1.

      • early_stopping_enabled boolean

        Advanced configuration option. Specifies whether the training process should finish if it is not finding any better performing models. If disabled, the training process can take significantly longer and the chance of finding a better performing model is unremarkable.

      • eta number

        Advanced configuration option. The shrinkage applied to the weights. Smaller values result in larger forests which have a better generalization error. However, larger forests cause slower training. By default, this value is calculated during hyperparameter optimization. It must be a value between 0.001 and 1.

      • eta_growth_rate_per_tree number

        Advanced configuration option. Specifies the rate at which eta increases for each new tree that is added to the forest. For example, a rate of 1.05 increases eta by 5% for each extra tree. By default, this value is calculated during hyperparameter optimization. It must be between 0.5 and 2.

      • feature_bag_fraction number

        Advanced configuration option. Defines the fraction of features that will be used when selecting a random bag for each candidate split. By default, this value is calculated during hyperparameter optimization.

      • feature_processors array[object]

        Advanced configuration option. A collection of feature preprocessors that modify one or more included fields. The analysis uses the resulting one or more features instead of the original document field. However, these features are ephemeral; they are not stored in the destination index. Multiple feature_processors entries can refer to the same document fields. Automatic categorical feature encoding still occurs for the fields that are unprocessed by a custom processor or that have categorical values. Use this property only if you want to override the automatic feature encoding of the specified fields.

        Hide feature_processors attributes Show feature_processors attributes object

        • frequency_encoding object
        • multi_encoding object
        • n_gram_encoding object
        • one_hot_encoding object
        • target_mean_encoding object
      • gamma number

        Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies a linear penalty associated with the size of individual trees in the forest. A high gamma value causes training to prefer small trees. A small gamma value results in larger individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.

      • lambda number

        Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies an L2 regularization term which applies to leaf weights of the individual trees in the forest. A high lambda value causes training to favor small leaf weights. This behavior makes the prediction function smoother at the expense of potentially not being able to capture relevant relationships between the features and the dependent variable. A small lambda value results in large individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.

      • max_optimization_rounds_per_hyperparameter number

        Advanced configuration option. A multiplier responsible for determining the maximum number of hyperparameter optimization steps in the Bayesian optimization procedure. The maximum number of steps is determined based on the number of undefined hyperparameters times the maximum optimization rounds per hyperparameter. By default, this value is calculated during hyperparameter optimization.

      • max_trees number

        Advanced configuration option. Defines the maximum number of decision trees in the forest. The maximum value is 2000. By default, this value is calculated during hyperparameter optimization.

      • num_top_feature_importance_values number

        Advanced configuration option. Specifies the maximum number of feature importance values per document to return. By default, no feature importance calculation occurs.

      • prediction_field_name string

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

      • randomize_seed number

        Defines the seed for the random generator that is used to pick training data. By default, it is randomly generated. Set it to a specific value to use the same training data each time you start a job (assuming other related parameters such as source and analyzed_fields are the same).

      • soft_tree_depth_limit number

        Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This soft limit combines with the soft_tree_depth_tolerance to penalize trees that exceed the specified depth; the regularized loss increases quickly beyond this depth. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.

      • soft_tree_depth_tolerance number

        Advanced configuration option. This option controls how quickly the regularized loss increases when the tree depth exceeds soft_tree_depth_limit. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.01.

      • training_percent string | number

        One of:

        _types:Percentage string _types:Percentage number
      • class_assignment_objective string
      • num_top_classes number

        Defines the number of categories for which the predicted probabilities are reported. It must be non-negative or -1. If it is -1 or greater than the total number of categories, probabilities are reported for all categories; if you have a large number of categories, there could be a significant effect on the size of your destination index. NOTE: To use the AUC ROC evaluation method, num_top_classes must be set to -1 or a value greater than or equal to the total number of categories.

    • outlier_detection object
      Hide outlier_detection attributes Show outlier_detection attributes object

      • compute_feature_influence boolean

        Specifies whether the feature influence calculation is enabled.

      • 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.

      • 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.

      • 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).

    • regression object
      Hide regression attributes Show regression attributes object

      • alpha number

        Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This parameter affects loss calculations by acting as a multiplier of the tree depth. Higher alpha values result in shallower trees and faster training times. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to zero.

      • dependent_variable string Required

        Defines which field of the document is to be predicted. It must match one of the fields in the index being used to train. If this field is missing from a document, then that document will not be used for training, but a prediction with the trained model will be generated for it. It is also known as continuous target variable. For classification analysis, the data type of the field must be numeric (integer, short, long, byte), categorical (ip or keyword), or boolean. There must be no more than 30 different values in this field. For regression analysis, the data type of the field must be numeric.

      • downsample_factor number

        Advanced configuration option. Controls the fraction of data that is used to compute the derivatives of the loss function for tree training. A small value results in the use of a small fraction of the data. If this value is set to be less than 1, accuracy typically improves. However, too small a value may result in poor convergence for the ensemble and so require more trees. By default, this value is calculated during hyperparameter optimization. It must be greater than zero and less than or equal to 1.

      • early_stopping_enabled boolean

        Advanced configuration option. Specifies whether the training process should finish if it is not finding any better performing models. If disabled, the training process can take significantly longer and the chance of finding a better performing model is unremarkable.

      • eta number

        Advanced configuration option. The shrinkage applied to the weights. Smaller values result in larger forests which have a better generalization error. However, larger forests cause slower training. By default, this value is calculated during hyperparameter optimization. It must be a value between 0.001 and 1.

      • eta_growth_rate_per_tree number

        Advanced configuration option. Specifies the rate at which eta increases for each new tree that is added to the forest. For example, a rate of 1.05 increases eta by 5% for each extra tree. By default, this value is calculated during hyperparameter optimization. It must be between 0.5 and 2.

      • feature_bag_fraction number

        Advanced configuration option. Defines the fraction of features that will be used when selecting a random bag for each candidate split. By default, this value is calculated during hyperparameter optimization.

      • feature_processors array[object]

        Advanced configuration option. A collection of feature preprocessors that modify one or more included fields. The analysis uses the resulting one or more features instead of the original document field. However, these features are ephemeral; they are not stored in the destination index. Multiple feature_processors entries can refer to the same document fields. Automatic categorical feature encoding still occurs for the fields that are unprocessed by a custom processor or that have categorical values. Use this property only if you want to override the automatic feature encoding of the specified fields.

        Hide feature_processors attributes Show feature_processors attributes object

        • frequency_encoding object
        • multi_encoding object
        • n_gram_encoding object
        • one_hot_encoding object
        • target_mean_encoding object
      • gamma number

        Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies a linear penalty associated with the size of individual trees in the forest. A high gamma value causes training to prefer small trees. A small gamma value results in larger individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.

      • lambda number

        Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies an L2 regularization term which applies to leaf weights of the individual trees in the forest. A high lambda value causes training to favor small leaf weights. This behavior makes the prediction function smoother at the expense of potentially not being able to capture relevant relationships between the features and the dependent variable. A small lambda value results in large individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.

      • max_optimization_rounds_per_hyperparameter number

        Advanced configuration option. A multiplier responsible for determining the maximum number of hyperparameter optimization steps in the Bayesian optimization procedure. The maximum number of steps is determined based on the number of undefined hyperparameters times the maximum optimization rounds per hyperparameter. By default, this value is calculated during hyperparameter optimization.

      • max_trees number

        Advanced configuration option. Defines the maximum number of decision trees in the forest. The maximum value is 2000. By default, this value is calculated during hyperparameter optimization.

      • num_top_feature_importance_values number

        Advanced configuration option. Specifies the maximum number of feature importance values per document to return. By default, no feature importance calculation occurs.

      • prediction_field_name string

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

      • randomize_seed number

        Defines the seed for the random generator that is used to pick training data. By default, it is randomly generated. Set it to a specific value to use the same training data each time you start a job (assuming other related parameters such as source and analyzed_fields are the same).

      • soft_tree_depth_limit number

        Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This soft limit combines with the soft_tree_depth_tolerance to penalize trees that exceed the specified depth; the regularized loss increases quickly beyond this depth. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.

      • soft_tree_depth_tolerance number

        Advanced configuration option. This option controls how quickly the regularized loss increases when the tree depth exceeds soft_tree_depth_limit. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.01.

      • training_percent string | number

        One of:

        _types:Percentage string _types:Percentage number
      • loss_function string

        The loss function used during regression. Available options are mse (mean squared error), msle (mean squared logarithmic error), huber (Pseudo-Huber loss).

      • loss_function_parameter number

        A positive number that is used as a parameter to the loss_function.

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

    • includes array[string] Required

      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] Required

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