Get multiple term vectors
You can specify existing documents by index and ID or provide artificial documents in the body of the request.
You can specify the index in the request body or request URI.
The response contains a docs
array with all the fetched termvectors.
Each element has the structure provided by the termvectors API.
Path parameters
-
Name of the index that contains the documents.
Query parameters
-
ids array[string]
A comma-separated list of documents ids. You must define ids as parameter or set "ids" or "docs" in the request body
-
fields string | array[string]
Comma-separated list or wildcard expressions of fields to include in the statistics. Used as the default list unless a specific field list is provided in the
completion_fields
orfielddata_fields
parameters. -
field_statistics boolean
If
true
, the response includes the document count, sum of document frequencies, and sum of total term frequencies. -
offsets boolean
If
true
, the response includes term offsets. -
payloads boolean
If
true
, the response includes term payloads. -
positions boolean
If
true
, the response includes term positions. -
preference string
Specifies the node or shard the operation should be performed on. Random by default.
-
realtime boolean
If true, the request is real-time as opposed to near-real-time.
-
routing string
Custom value used to route operations to a specific shard.
-
term_statistics boolean
If true, the response includes term frequency and document frequency.
-
version number
If
true
, returns the document version as part of a hit. -
version_type string
Specific version type.
Values are
internal
,external
,external_gte
, orforce
.
curl \
-X GET http://api.example.com/{index}/_mtermvectors \
-H "Content-Type: application/json" \
-d '{"docs":[{"_id":"string","_index":"string","doc":{},"fields":"string","field_statistics":true,"filter":{"max_doc_freq":42.0,"max_num_terms":42.0,"max_term_freq":42.0,"max_word_length":42.0,"min_doc_freq":42.0,"min_term_freq":42.0,"min_word_length":42.0},"offsets":true,"payloads":true,"positions":true,"routing":"string","term_statistics":true,"version":42.0,"version_type":"internal"}],"ids":["string"]}'
{
"docs": [
{
"_id": "string",
"_index": "string",
"doc": {},
"fields": "string",
"field_statistics": true,
"filter": {
"max_doc_freq": 42.0,
"max_num_terms": 42.0,
"max_term_freq": 42.0,
"max_word_length": 42.0,
"min_doc_freq": 42.0,
"min_term_freq": 42.0,
"min_word_length": 42.0
},
"offsets": true,
"payloads": true,
"positions": true,
"routing": "string",
"term_statistics": true,
"version": 42.0,
"version_type": "internal"
}
],
"ids": [
"string"
]
}
{
"docs": [
{
"_id": "string",
"_index": "string",
"_version": 42.0,
"took": 42.0,
"found": true,
"term_vectors": {
"additionalProperty1": {
"field_statistics": {
"doc_count": 42.0,
"sum_doc_freq": 42.0,
"sum_ttf": 42.0
},
"terms": {
"additionalProperty1": {},
"additionalProperty2": {}
}
},
"additionalProperty2": {
"field_statistics": {
"doc_count": 42.0,
"sum_doc_freq": 42.0,
"sum_ttf": 42.0
},
"terms": {
"additionalProperty1": {},
"additionalProperty2": {}
}
}
},
"error": {
"type": "string",
"reason": "string",
"stack_trace": "string",
"caused_by": {},
"root_cause": [
{}
],
"suppressed": [
{}
]
}
}
]
}