OpenSearch/docs/reference/index-modules/merge.asciidoc

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[[index-modules-merge]]
== Merge
experimental[All of the settings exposed in the `merge` module are expert only and may be removed in the future]
A shard in elasticsearch is a Lucene index, and a Lucene index is broken
down into segments. Segments are internal storage elements in the index
where the index data is stored, and are immutable up to delete markers.
Segments are, periodically, merged into larger segments to keep the
index size at bay and expunge deletes.
Merges segments of approximately equal size, subject to an allowed
number of segments per tier. The merge policy is able to merge
non-adjacent segments, and separates how many segments are merged at once from how many
segments are allowed per tier. It also does not over-merge (i.e., cascade merges).
The merge policy has the following settings:
`index.merge.policy.expunge_deletes_allowed`::
When expungeDeletes is called, we only merge away a segment if its delete
percentage is over this threshold. Default is `10`.
`index.merge.policy.floor_segment`::
Segments smaller than this are "rounded up" to this size, i.e. treated as
equal (floor) size for merge selection. This is to prevent frequent
flushing of tiny segments, thus preventing a long tail in the index. Default
is `2mb`.
`index.merge.policy.max_merge_at_once`::
Maximum number of segments to be merged at a time during "normal" merging.
Default is `10`.
`index.merge.policy.max_merge_at_once_explicit`::
Maximum number of segments to be merged at a time, during optimize or
expungeDeletes. Default is `30`.
`index.merge.policy.max_merged_segment`::
Maximum sized segment to produce during normal merging (not explicit
optimize). This setting is approximate: the estimate of the merged segment
size is made by summing sizes of to-be-merged segments (compensating for
percent deleted docs). Default is `5gb`.
`index.merge.policy.segments_per_tier`::
Sets the allowed number of segments per tier. Smaller values mean more
merging but fewer segments. Default is `10`. Note, this value needs to be
>= than the `max_merge_at_once` otherwise you'll force too many merges to
occur.
`index.merge.policy.reclaim_deletes_weight`::
Controls how aggressively merges that reclaim more deletions are favored.
Higher values favor selecting merges that reclaim deletions. A value of
`0.0` means deletions don't impact merge selection. Defaults to `2.0`.
For normal merging, the policy first computes a "budget" of how many
segments are allowed to be in the index. If the index is over-budget,
then the policy sorts segments by decreasing size (proportionally considering percent
deletes), and then finds the least-cost merge. Merge cost is measured by
a combination of the "skew" of the merge (size of largest seg divided by
smallest seg), total merge size and pct deletes reclaimed, so that
merges with lower skew, smaller size and those reclaiming more deletes,
are favored.
If a merge will produce a segment that's larger than
`max_merged_segment` then the policy will merge fewer segments (down to
1 at once, if that one has deletions) to keep the segment size under
budget.
Note, this can mean that for large shards that holds many gigabytes of
data, the default of `max_merged_segment` (`5gb`) can cause for many
segments to be in an index, and causing searches to be slower. Use the
indices segments API to see the segments that an index has, and
possibly either increase the `max_merged_segment` or issue an optimize
call for the index (try and aim to issue it on a low traffic time).
[float]
[[scheduling]]
=== Scheduling
The merge scheduler (ConcurrentMergeScheduler) controls the execution of
merge operations once they are needed (according to the merge policy). Merges
run in separate threads, and when the maximum number of threads is reached,
further merges will wait until a merge thread becomes available. The merge
scheduler supports this setting:
`index.merge.scheduler.max_thread_count`::
The maximum number of threads that may be merging at once. Defaults to
`Math.max(1, Math.min(4, Runtime.getRuntime().availableProcessors() / 2))`
which works well for a good solid-state-disk (SSD). If your index is on
spinning platter drives instead, decrease this to 1.
`index.merge.scheduler.auto_throttle`::
If this is true (the default), then the merge scheduler will
rate-limit IO (writes) for merges to an adaptive value depending on
how many merges are requested over time. An application with a low
indexing rate that unluckily suddenly requires a large merge will see
that merge aggressively throttled, while an application doing heavy
indexing will see the throttle move higher to allow merges to keep up
with ongoing indexing. This is a dynamic setting (you can <<indices-update-settings,change it
at any time on a running index>>).