![]() ![]() Geo_shape: These are the fields which support points, lines, circles, polygons, multi-polygons etc.īucket aggregations don’t calculate metrics over fields like the metrics aggregations do, but instead, they create buckets of documents. Geo_point: These are the fields which support lat/ lon pairs The has_child query returns the matching parent documents, while the has_parent query returns the matching child documents. Has_child & has_parent queries: This query is used to retrieve the parent-child relationship between two document types within a single index. Using this query, you can query each object as an independent document. Nested query: This query is used for the documents containing nested type fields. Ī query that allows to modify the score of a sub-query with a script.Ī query that accepts other queries as json or yaml string.Ī query that promotes selected documents over others matching a given query. This query allows a script to act as a filter. This query finds queries that are stored as documents that match with the specified document.Ī query that computes scores based on the values of numeric features and is able to efficiently skip non-competitive hits. This query finds documents which are similar to the specified text, document, or collection of documents. It is able to efficiently skip non-competitive hits. Term-level queries : term, terms, range, exists, prefix, Wildcard, regex, Fuzzy(number of different), Terms Set QueryĪ query that computes scores based on the dynamically computed distances between the origin and documents' date, date_nanos, and geo_point fields. ![]() For expert users only.Ī simpler, more robust version of the query_string syntax suitable for exposing directly to users. Supports the compact Lucene query string syntax, allowing you to specify AND|OR|NOT conditions and multi-field search within a single query string. Matches over multiple fields as if they had been indexed into one combined field. The multi-field version of the match query. Like the match_phrase query, but does a wildcard search on the final word. Like the match query but used for matching exact phrases or word proximity matches. The standard query for performing full text queries, including fuzzy matching and phrase or proximity queries.Ĭreates a bool query that matches each term as a term query, except for the last term, which is matched as a prefix query įull text queries : Match, match phrase(exact match), multi match(search in multi fields)Ī full text query that allows fine-grained control of the ordering and proximity of matching terms. Percolator : Indexes queries written in Query DSL. ![]() Geo_shape Complex shapes, such as polygons. Rank_features Records numeric features to boost hits at query time. Rank_feature Records a numeric feature to boost hits at query time. Sparse_vector Records sparse vectors of float values. Search_as_you_type text-like type for as-you-type completion.ĭense_vector Records dense vectors of float values. Used for identifying named entities.Ĭompletion Used for auto-complete suggestions. Analyzed, unstructured text.Īnnotated-text Text containing special markup. Text fields The text family, including text and match_only_text. Histogram Pre-aggregated numerical values in the form of a histogram. Murmur3 Compute and stores hashes of values.Īggregate_metric_double Pre-aggregated metric values. Supports Semantic Versioning precedence rules. Range Range types, such as long_range, double_range, date_range, and ip_range. Join Defines a parent/child relationship for documents in the same index. Nested A JSON object that preserves the relationship between its subfields. Īlias Defines an alias for an existing field.įlattened An entire JSON object as a single field value. Numbers Numeric types, such as long and double, used to express amounts.ĭates: Date types, including date and date_nanos. Keywords The keyword family, including keyword, constant_keyword, and wildcard. More dynamic than SQL, as can have virtual fieldsīinary Binary value encoded as a Base64 string. Relationship can be done with Parent/child and Nested Term-vector: get detail info about document, tf, idf. The following example shows an index being refreshed This makes all operations performed since the last refresh available for the search. Refresh : The refresh API is responsible for refreshing one or more index explicitly. The following example shows an index being flushed Basically, its a process of releasing memory from the index by pushing the data to the index storage and clearing the internal transaction log. Searching: Simple, Query DSL, filtered, Phrase(exact combination),įlush : The flush API is responsible for flushing one or more indices through an API. Highlight(tell why and where match happened) Visualization, monitoring, beats : heartbeat(monitoring) and other beats, graphs Fuzzy query : good query for number of differences and other stuffsĮxplain : shows how it does to get that result ![]()
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