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Search Typeedit
There are different execution paths that can be done when executing a distributed search. The distributed search operation needs to be scattered to all the relevant shards and then all the results are gathered back. When doing scatter/gather type execution, there are several ways to do that, specifically with search engines.
One of the questions when executing a distributed search is how much results to retrieve from each shard. For example, if we have 10 shards, the 1st shard might hold the most relevant results from 0 till 10, with other shards results ranking below it. For this reason, when executing a request, we will need to get results from 0 till 10 from all shards, sort them, and then return the results if we want to insure correct results.
Another question, which relates to search engine, is the fact that each shard stands on its own. When a query is executed on a specific shard, it does not take into account term frequencies and other search engine information from the other shards. If we want to support accurate ranking, we would need to first execute the query against all shards and gather the relevant term frequencies, and then, based on it, execute the query.
Also, because of the need to sort the results, getting back a large
document set, or even scrolling it, while maintaing the correct sorting
behavior can be a very expensive operation. For large result set
scrolling without sorting, the scan search type (explained below) is
also available.
ElasticSearch is very flexible and allows to control the type of search to execute on a per search request basis. The type can be configured by setting the search_type parameter in the query string. The types are:
Query And Fetchedit
Parameter value: query_and_fetch.
The most naive (and possibly fastest) implementation is to simply
execute the query on all relevant shards and return the results. Each
shard returns size results. Since each shard already returns size
hits, this type actually returns size times number of shards results
back to the caller.
Query Then Fetchedit
Parameter value: query_then_fetch.
The query is executed against all shards, but only enough information is
returned (not the document content). The results are then sorted and
ranked, and based on it, only the relevant shards are asked for the
actual document content. The return number of hits is exactly as
specified in size, since they are the only ones that are fetched. This
is very handy when the index has a lot of shards (not replicas, shard id
groups).
This is the default setting, if you do not specify a search_type
in your request.
Dfs, Query And Fetchedit
Parameter value: dfs_query_and_fetch.
Same as "Query And Fetch", except for an initial scatter phase which goes and computes the distributed term frequencies for more accurate scoring.
Dfs, Query Then Fetchedit
Parameter value: dfs_query_then_fetch.
Same as "Query Then Fetch", except for an initial scatter phase which goes and computes the distributed term frequencies for more accurate scoring.
Countedit
Parameter value: count.
A special search type that returns the count that matched the search
request without any docs (represented in total_hits), and possibly,
including facets as well. In general, this is preferable to the count
API as it provides more options.
Scanedit
Parameter value: scan.
The scan search type allows to efficiently scroll a large result set.
It’s used first by executing a search request with scrolling and a
query:
curl -XGET 'localhost:9200/_search?search_type=scan&scroll=10m&size=50' -d '
{
"query" : {
"match_all" : {}
}
}
'
The scroll parameter controls the keep alive time of the scrolling
request and initiates the scrolling process. The timeout applies per
round trip (i.e. between the previous scan scroll request, to the next).
The response will include no hits, with two important results, the
total_hits will include the total hits that match the query, and the
scroll_id that allows to start the scroll process. From this stage,
the _search/scroll endpoint should be used to scroll the hits, feeding
the next scroll request with the previous search result scroll_id. For
example:
curl -XGET 'localhost:9200/_search/scroll?scroll=10m' -d 'c2NhbjsxOjBLMzdpWEtqU2IyZHlmVURPeFJOZnc7MzowSzM3aVhLalNiMmR5ZlVET3hSTmZ3OzU6MEszN2lYS2pTYjJkeWZVRE94Uk5mdzsyOjBLMzdpWEtqU2IyZHlmVURPeFJOZnc7NDowSzM3aVhLalNiMmR5ZlVET3hSTmZ3Ow=='
Scroll requests will include a number of hits equal to the size multiplied by the number of primary shards.
The "breaking" condition out of a scroll is when no hits has been returned. The total_hits will be maintained between scroll requests.
Note, scan search type does not support sorting (either on score or a field) or faceting.
Clear scroll apiedit
Added in 0.90.4.
Besides consuming the scroll search until no hits has been returned a scroll
search can also be aborted by deleting the scroll_id. This can be done via
the clear scroll api. When the scroll_id has been deleted all the
resources to keep the view open will be released. Example usage:
curl -XDELETE 'localhost:9200/_search/scroll/c2NhbjsxOjBLMzdpWEtqU2IyZHlmVURPeFJOZnc7MzowSzM3aVhLalNiMmR5ZlVET3hSTmZ3OzU6MEszN2lYS2pTYjJkeWZVRE94Uk5mdzsyOjBLMzdpWEtqU2IyZHlmVURPeFJOZnc7NDowSzM3aVhLalNiMmR5ZlVET3hSTmZ3Ow=='
Multiple scroll ids can be specified in a comma separated manner.
If all scroll ids need to be cleared the reserved _all value can used instead of an actual scroll_id:
curl -XDELETE 'localhost:9200/_search/scroll/_all'