103 lines
3.6 KiB
Plaintext
103 lines
3.6 KiB
Plaintext
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--
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:api: term-vectors
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:request: TermVectorsRequest
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:response: TermVectorsResponse
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--
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[id="{upid}-{api}"]
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=== Term Vectors API
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Term Vectors API returns information and statistics on terms in the fields
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of a particular document. The document could be stored in the index or
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artificially provided by the user.
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[id="{upid}-{api}-request"]
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==== Term Vectors Request
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A +{request}+ expects an `index`, a `type` and an `id` to specify
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a certain document, and fields for which the information is retrieved.
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-request]
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--------------------------------------------------
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Term vectors can also be generated for artificial documents, that is for
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documents not present in the index:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-request-artificial]
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--------------------------------------------------
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<1> An artificial document is provided as an `XContentBuilder` object,
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the Elasticsearch built-in helper to generate JSON content.
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===== Optional arguments
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-request-optional-arguments]
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--------------------------------------------------
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<1> Set `fieldStatistics` to `false` (default is `true`) to omit document count,
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sum of document frequencies, sum of total term frequencies.
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<2> Set `termStatistics` to `true` (default is `false`) to display
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total term frequency and document frequency.
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<3> Set `positions` to `false` (default is `true`) to omit the output of
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positions.
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<4> Set `offsets` to `false` (default is `true`) to omit the output of
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offsets.
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<5> Set `payloads` to `false` (default is `true`) to omit the output of
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payloads.
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<6> Set `filterSettings` to filter the terms that can be returned based
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on their tf-idf scores.
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<7> Set `perFieldAnalyzer` to specify a different analyzer than
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the one that the field has.
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<8> Set `realtime` to `false` (default is `true`) to retrieve term vectors
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near realtime.
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<9> Set a routing parameter
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include::../execution.asciidoc[]
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[id="{upid}-{api}-response"]
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==== TermVectorsResponse
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The `TermVectorsResponse` contains the following information:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-response]
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--------------------------------------------------
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<1> The index name of the document.
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<2> The type name of the document.
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<3> The id of the document.
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<4> Indicates whether or not the document found.
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===== Inspecting Term Vectors
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If `TermVectorsResponse` contains non-null list of term vectors,
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more information about them can be obtained using following:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-term-vectors]
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--------------------------------------------------
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<1> The list of `TermVector` for the document
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<2> The name of the current field
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<3> Fields statistics for the current field - document count
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<4> Fields statistics for the current field - sum of total term frequencies
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<5> Fields statistics for the current field - sum of document frequencies
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<6> Terms for the current field
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<7> The name of the term
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<8> Term frequency of the term
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<9> Document frequency of the term
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<10> Total term frequency of the term
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<11> Score of the term
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<12> Tokens of the term
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<13> Position of the token
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<14> Start offset of the token
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<15> End offset of the token
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<16> Payload of the token
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