Filters documents that have fields that match any of the provided terms (not analyzed). For example:
GET /_search
{
"query": {
"terms" : { "user" : ["kimchy", "elasticsearch"]}
}
}
Note
|
Highlighting terms queries is best-effort only, so terms of a terms
query might not be highlighted depending on the highlighter implementation that
is selected and on the number of terms in the terms query.
|
When it’s needed to specify a terms
filter with a lot of terms it can
be beneficial to fetch those term values from a document in an index. A
concrete example would be to filter tweets tweeted by your followers.
Potentially the amount of user ids specified in the terms filter can be
a lot. In this scenario it makes sense to use the terms filter’s terms
lookup mechanism.
The terms lookup mechanism supports the following options:
index
|
The index to fetch the term values from. |
type
|
The type to fetch the term values from. |
id
|
The id of the document to fetch the term values from. |
path
|
The field specified as path to fetch the actual values for the
|
routing
|
A custom routing value to be used when retrieving the external terms doc. |
The values for the terms
filter will be fetched from a field in a
document with the specified id in the specified type and index.
Internally a get request is executed to fetch the values from the
specified path. At the moment for this feature to work the _source
needs to be stored.
Also, consider using an index with a single shard and fully replicated across all nodes if the "reference" terms data is not large. The lookup terms filter will prefer to execute the get request on a local node if possible, reducing the need for networking.
Warning
|
Executing a Terms Query request with a lot of terms can be quite slow,
as each additional term demands extra processing and memory.
To safeguard against this, the maximum number of terms that can be used
in a Terms Query both directly or through lookup has been limited to 65536 .
This default maximum can be changed for a particular index with the index setting
index.max_terms_count .
|
At first we index the information for user with id 2, specifically, its followers, then index a tweet from user with id 1. Finally we search on all the tweets that match the followers of user 2.
PUT /users/_doc/2
{
"followers" : ["1", "3"]
}
PUT /tweets/_doc/1
{
"user" : "1"
}
GET /tweets/_search
{
"query" : {
"terms" : {
"user" : {
"index" : "users",
"type" : "_doc",
"id" : "2",
"path" : "followers"
}
}
}
}
The structure of the external terms document can also include an array of inner objects, for example:
PUT /users/_doc/2
{
"followers" : [
{
"id" : "1"
},
{
"id" : "2"
}
]
}
In which case, the lookup path will be followers.id
.