Search Optionsedit

A few optional query-string parameters can influence the search process.


The preference parameter allows you to control which shards or nodes are used to handle the search request. It accepts values such as _primary, _primary_first, _local, _only_node:xyz, _prefer_node:xyz, and _shards:2,3, which are explained in detail on the search preference documentation page.

However, the most generally useful value is some arbitrary string, to avoid the bouncing results problem.


By default, the coordinating node waits to receive a response from all shards. If one node is having trouble, it could slow down the response to all search requests.

The timeout parameter tells the coordinating node how long it should wait before giving up and just returning the results that it already has. It can be better to return some results than none at all.

The response to a search request will indicate whether the search timed out and how many shards responded successfully:

    "timed_out":     true,  
    "_shards": {
       "total":      5,
       "successful": 4,
       "failed":     1 

The search request timed out.

One shard out of five failed to respond in time.

If all copies of a shard fail for other reasons—perhaps because of a hardware failure—this will also be reflected in the _shards section of the response.


In Routing a Document to a Shard, we explained how a custom routing parameter could be provided at index time to ensure that all related documents, such as the documents belonging to a single user, are stored on a single shard. At search time, instead of searching on all the shards of an index, you can specify one or more routing values to limit the search to just those shards:

GET /_search?routing=user_1,user2

This technique comes in handy when designing very large search systems, and we discuss it in detail in Designing for Scale.


While query_then_fetch is the default search type, other search types can be specified for particular purposes, for example:

GET /_search?search_type=count
The count search type has only a query phase. It can be used when you don’t need search results, just a document count or aggregations on documents matching the query.
The query_and_fetch search type combines the query and fetch phases into a single step. This is an internal optimization that is used when a search request targets a single shard only, such as when a routing value has been specified. While you can choose to use this search type manually, it is almost never useful to do so.
dfs_query_then_fetch and dfs_query_and_fetch
The dfs search types have a prequery phase that fetches the term frequencies from all involved shards in order to calculate global term frequencies. We discuss this further in Relevance Is Broken!.
The scan search type is used in conjunction with the scroll API to retrieve large numbers of results efficiently. It does this by disabling sorting. We discuss scan-and-scroll in the next section.