Multi Search API

The multi search API allows to execute several search requests within the same API. The endpoint for it is _msearch.

The format of the request is similar to the bulk API format and makes use of the newline delimited JSON (NDJSON) format. the structure is as follows (the structure is specifically optimized to reduce parsing if a specific search ends up redirected to another node):

header\n
body\n
header\n
body\n

NOTE: the final line of data must end with a newline character \n. Each newline character may be preceded by a carriage return \r. When sending requests to this endpoint the Content-Type header should be set to application/x-ndjson.

The header part includes which index / indices to search on, the search_type, preference, and routing. The body includes the typical search body request (including the query, aggregations, from, size, and so on). Here is an example:

$ cat requests
{"index" : "test"}
{"query" : {"match_all" : {}}, "from" : 0, "size" : 10}
{"index" : "test", "search_type" : "dfs_query_then_fetch"}
{"query" : {"match_all" : {}}}
{}
{"query" : {"match_all" : {}}}

{"query" : {"match_all" : {}}}
{"search_type" : "dfs_query_then_fetch"}
{"query" : {"match_all" : {}}}

$ curl -H "Content-Type: application/x-ndjson" -XGET localhost:9200/_msearch --data-binary "@requests"; echo

Note, the above includes an example of an empty header (can also be just without any content) which is supported as well.

The response returns a responses array, which includes the search response and status code for each search request matching its order in the original multi search request. If there was a complete failure for that specific search request, an object with error message and corresponding status code will be returned in place of the actual search response.

The endpoint allows to also search against an index/indices in the URI itself, in which case it will be used as the default unless explicitly defined otherwise in the header. For example:

GET twitter/_msearch
{}
{"query" : {"match_all" : {}}, "from" : 0, "size" : 10}
{}
{"query" : {"match_all" : {}}}
{"index" : "twitter2"}
{"query" : {"match_all" : {}}}

The above will execute the search against the twitter index for all the requests that don’t define an index, and the last one will be executed against the twitter2 index.

The search_type can be set in a similar manner to globally apply to all search requests.

The msearch’s max_concurrent_searches request parameter can be used to control the maximum number of concurrent searches the multi search api will execute. This default is based on the number of data nodes and the default search thread pool size.

The request parameter max_concurrent_shard_requests can be used to control the maximum number of concurrent shard requests the each sub search request will execute. This parameter should be used to protect a single request from overloading a cluster (e.g., a default request will hit all indices in a cluster which could cause shard request rejections if the number of shards per node is high). This default is based on the number of data nodes in the cluster but at most 256.In certain scenarios parallelism isn’t achieved through concurrent request such that this protection will result in poor performance. For instance in an environment where only a very low number of concurrent search requests are expected it might help to increase this value to a higher number.

See URL-based access control

Much like described in Search Template for the _search resource, _msearch also provides support for templates. Submit them like follows:

GET _msearch/template
{"index" : "twitter"}
{ "source" : "{ \"query\": { \"match\": { \"message\" : \"{{keywords}}\" } } } }", "params": { "query_type": "match", "keywords": "some message" } }
{"index" : "twitter"}
{ "source" : "{ \"query\": { \"match_{{template}}\": {} } }", "params": { "template": "all" } }

for inline templates.

You can also create search templates:

POST /_scripts/my_template_1
{
    "script": {
        "lang": "mustache",
        "source": {
            "query": {
                "match": {
                    "message": "{{query_string}}"
                }
            }
        }
    }
}

POST /_scripts/my_template_2
{
    "script": {
        "lang": "mustache",
        "source": {
            "query": {
                "term": {
                    "{{field}}": "{{value}}"
                }
            }
        }
    }
}

and later use them in a _msearch:

GET _msearch/template
{"index" : "main"}
{ "id": "my_template_1", "params": { "query_string": "some message" } }
{"index" : "main"}
{ "id": "my_template_2", "params": { "field": "user", "value": "test" } }