Multi termvectors API
editMulti termvectors API
editMulti termvectors API allows to get multiple termvectors at once. The documents from which to retrieve the term vectors are specified by an index, type and id. But the documents could also be artificially provided in the request itself.
The response includes a docs
array with all the fetched termvectors, each element having the structure
provided by the termvectors
API. Here is an example:
POST /_mtermvectors
{
"docs": [
{
"_index": "twitter",
"_type": "tweet",
"_id": "2",
"term_statistics": true
},
{
"_index": "twitter",
"_type": "tweet",
"_id": "1",
"fields": [
"message"
]
}
]
}
See the termvectors API for a description of possible parameters.
The _mtermvectors endpoint can also be used against an index (in which case it
is not required in the body):
POST /twitter/_mtermvectors
{
"docs": [
{
"_type": "tweet",
"_id": "2",
"fields": [
"message"
],
"term_statistics": true
},
{
"_type": "tweet",
"_id": "1"
}
]
}
And type:
POST /twitter/tweet/_mtermvectors
{
"docs": [
{
"_id": "2",
"fields": [
"message"
],
"term_statistics": true
},
{
"_id": "1"
}
]
}
If all requested documents are on same index and have same type and also the parameters are the same, the request can be simplified:
POST /twitter/tweet/_mtermvectors
{
"ids" : ["1", "2"],
"parameters": {
"fields": [
"message"
],
"term_statistics": true
}
}
Additionally, just like for the termvectors
API, term vectors could be generated for user provided documents. The mapping used is
determined by _index and _type.
POST /_mtermvectors
{
"docs": [
{
"_index": "twitter",
"_type": "tweet",
"doc" : {
"user" : "John Doe",
"message" : "twitter test test test"
}
},
{
"_index": "twitter",
"_type": "test",
"doc" : {
"user" : "Jane Doe",
"message" : "Another twitter test ..."
}
}
]
}