elasticsearch/docs/java-rest/high-level/document/term-vectors.asciidoc

--
:api: term-vectors
:request: TermVectorsRequest
:response: TermVectorsResponse
--

[id="{upid}-{api}"]
=== Term Vectors API

Term Vectors API returns information and statistics on terms in the fields
of a particular document. The document could be stored in the index or
artificially provided by the user.


[id="{upid}-{api}-request"]
==== Term Vectors Request

A +{request}+ expects an `index`, a `type` and an `id` to specify
a certain document, and fields for which the information is retrieved.

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-request]
--------------------------------------------------

Term vectors can also be generated for artificial documents, that is for
documents not present in the index:

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-request-artificial]
--------------------------------------------------
<1> An artificial document is provided as an `XContentBuilder` object,
the Elasticsearch built-in helper to generate JSON content.

===== Optional arguments

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-request-optional-arguments]
--------------------------------------------------
<1> Set `fieldStatistics` to `false` (default is `true`) to omit document count,
sum of document frequencies, sum of total term frequencies.
<2> Set `termStatistics` to `true` (default is `false`) to display
total term frequency and document frequency.
<3> Set `positions` to `false` (default is `true`) to omit the output of
positions.
<4> Set `offsets` to `false` (default is `true`) to omit the output of
offsets.
<5> Set `payloads` to `false` (default is `true`) to omit the output of
payloads.
<6> Set `filterSettings` to filter the terms that can be returned based
on their tf-idf scores.
<7> Set `perFieldAnalyzer` to specify  a different analyzer than
the one that the field has.
<8> Set `realtime` to `false` (default is `true`) to retrieve term vectors
near realtime.
<9> Set a routing parameter


include::../execution.asciidoc[]


[id="{upid}-{api}-response"]
==== TermVectorsResponse

The `TermVectorsResponse` contains the following information:

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-response]
--------------------------------------------------
<1> The index name of the document.
<2> The type name of the document.
<3> The id of the document.
<4> Indicates whether or not the document found.


===== Inspecting Term Vectors
If `TermVectorsResponse` contains non-null list of term vectors,
more information about them can be obtained using following:

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-term-vectors]
--------------------------------------------------
<1> The list of `TermVector` for the document
<2> The name of the current field
<3> Fields statistics for the current field - document count
<4> Fields statistics for the current field - sum of total term frequencies
<5> Fields statistics for the current field - sum of document frequencies
<6> Terms for the current field
<7> The name of the term
<8> Term frequency of the term
<9> Document frequency of the term
<10> Total term frequency of the term
<11> Score of the term
<12> Tokens of the term
<13> Position of the token
<14> Start offset of the token
<15> End offset of the token
<16> Payload of the token


[id="{upid}-{api}-response"]
==== TermVectorsResponse

The `TermVectorsResponse` contains the following information:

["source","java",subs="attributes,callouts,macros"]
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-response]
--------------------------------------------------
<1> The index name of the document.
<2> The type name of the document.
<3> The id of the document.
<4> Indicates whether or not the document found.
<5> Indicates whether or not there are term vectors for this document.
<6> The list of `TermVector` for the document
<7> The name of the current field
<8> Fields statistics for the current field - document count
<9> Fields statistics for the current field - sum of total term frequencies
<10> Fields statistics for the current field - sum of document frequencies
<11> Terms for the current field
<12> The name of the term
<13> Term frequency of the term
<14> Document frequency of the term
<15> Total term frequency of the term
<16> Score of the term
<17> Tokens of the term
<18> Position of the token
<19> Start offset of the token
<20> End offset of the token
<21> Payload of the token