本地英文版地址: ../en/indices-forcemerge.html
Force merge APIedit
Forces a merge on the shards of one or more indices.
POST /twitter/_forcemerge
Descriptionedit
Use the force merge API to force a merge on the shards of one or more indices. Merging reduces the number of segments in each shard by merging some of them together, and also frees up the space used by deleted documents. Merging normally happens automatically, but sometimes it is useful to trigger a merge manually.
Force merge should only be called against an index after you have finished writing to it. Force merge can cause very large (>5GB) segments to be produced, and if you continue to write to such an index then the automatic merge policy will never consider these segments for future merges until they mostly consist of deleted documents. This can cause very large segments to remain in the index which can result in increased disk usage and worse search performance.
Blocks during a force mergeedit
Calls to this API block until the merge is complete. If the client connection is lost before completion then the force merge process will continue in the background. Any new requests to force merge the same indices will also block until the ongoing force merge is complete.
Force merging multiple indicesedit
The force merge API can be applied to more than one index with a single call, or
even on _all the indices. Multi index operations are executed one shard at a
time per node. Force merge makes the storage for the shard being merged
temporarily increase, up to double its size in case max_num_segments parameter
is set to 1, as all segments need to be rewritten into a new one.
Path parametersedit
-
<index> -
(Optional, string) Comma-separated list or wildcard expression of index names used to limit the request.
To force merge all indices in the cluster, omit this parameter or use a value of
_allor*.
Query parametersedit
-
allow_no_indices -
(Optional, boolean) If
true, the request does not return an error if a wildcard expression or_allvalue retrieves only missing or closed indices.This parameter also applies to index aliases that point to a missing or closed index.
Defaults to
true. -
expand_wildcards -
(Optional, string) Controls what kind of indices that wildcard expressions can expand to. Multiple values are accepted when separated by a comma, as in
open,hidden. Valid values are:-
all - Expand to open and closed indices, including hidden indices.
-
open - Expand only to open indices.
-
closed - Expand only to closed indices.
-
hidden -
Expansion of wildcards will include hidden indices.
Must be combined with
open,closed, or both. -
none - Wildcard expressions are not accepted.
Defaults to
open. -
-
flush -
(Optional, boolean)
If
true, Elasticsearch performs a flush on the indices after the force merge. Defaults totrue. -
ignore_unavailable -
(Optional, boolean) If
true, missing or closed indices are not included in the response. Defaults tofalse. -
max_num_segments -
(Optional, integer) The number of segments to merge to. To fully merge the index, set it to
1.Defaults to checking if a merge needs to execute. If so, executes it.
-
only_expunge_deletes -
(Optional, boolean) If
true, only expunge segments containing document deletions. Defaults tofalse.In Lucene, a document is not deleted from a segment; just marked as deleted. During a merge, a new segment is created that does not contain those document deletions.
This parameter does not override the
index.merge.policy.expunge_deletes_allowedsetting.
Examplesedit
Force merge a specific indexedit
POST /twitter/_forcemerge
Force merge several indicesedit
POST /kimchy,elasticsearch/_forcemerge
Force merge all indicesedit
POST /_forcemerge
Time-based indicesedit
Force-merging is useful for time-based indices, particularly when using rollover. In these cases, each index only receives indexing traffic for a certain period of time. Once an index receive no more writes, its shards can be force-merged to a single segment.
POST /logs-000001/_forcemerge?max_num_segments=1
This can be a good idea because single-segment shards can sometimes use simpler and more efficient data structures to perform searches.