elasticsearch/docs/reference/search/multi-search.asciidoc

[[search-multi-search]]
== 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):

[source,js]
--------------------------------------------------
header\n
body\n
header\n
body\n
--------------------------------------------------
// NOTCONSOLE

*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:

[source,js]
--------------------------------------------------
$ 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" : {}}}
--------------------------------------------------
// NOTCONSOLE

[source,js]
--------------------------------------------------
$ curl -H "Content-Type: application/x-ndjson" -XGET localhost:9200/_msearch --data-binary "@requests"; echo
--------------------------------------------------
// NOTCONSOLE

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:

[source,js]
--------------------------------------------------
GET twitter/_msearch
{}
{"query" : {"match_all" : {}}, "from" : 0, "size" : 10}
{}
{"query" : {"match_all" : {}}}
{"index" : "twitter2"}
{"query" : {"match_all" : {}}}
--------------------------------------------------
// CONSOLE
// TEST[setup:twitter]

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.

[float]
[[msearch-security]]
=== Security

See <<url-access-control>>

[float]
[[template-msearch]]
=== Template support

Much like described in <<search-template>> for the _search resource, _msearch
also provides support for templates. Submit them like follows:

[source,js]
-----------------------------------------------
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" } }
-----------------------------------------------
// CONSOLE
// TEST[setup:twitter]

for inline templates.

You can also create search templates:

[source,js]
------------------------------------------
POST /_scripts/my_template_1
{
    "script": {
        "lang": "mustache",
        "source": {
            "query": {
                "match": {
                    "message": "{{query_string}}"
                }
            }
        }
    }
}
------------------------------------------
// CONSOLE
// TEST[setup:twitter]

[source,js]
------------------------------------------
POST /_scripts/my_template_2
{
    "script": {
        "lang": "mustache",
        "source": {
            "query": {
                "term": {
                    "{{field}}": "{{value}}"
                }
            }
        }
    }
}
------------------------------------------
// CONSOLE
// TEST[continued]

and later use them in a _msearch:

[source,js]
-----------------------------------------------
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" } }
-----------------------------------------------
// CONSOLE
// TEST[continued]