ElasticsearchMetricelasticsearch.index.operations.merge.size
Merge operation size bytesDimensions:None
Summary
Reports the cumulative size of data merged during segment consolidation operations. Merging combines smaller segments into larger ones to optimize search performance at the cost of I/O and CPU resources. Large merge sizes indicate significant compaction activity, which may trigger merge throttling (documented in the "Merge Throttling Write Amplification" insight) to prevent I/O saturation, requiring balance between merge efficiency and indexing throughput.
Interface Metrics (9)
Datadog
Dimensions:None
DatadogDimensions:None
OpenTelemetryDimensions:None
DatadogDimensions:None
DatadogDimensions:None
Sources
elasticsearch.merges.total.size.countgithub.com
indices_merges_total_size_bytes_totalgithub.com
elasticsearch_indices_merges_total_size_bytes_totalwww.dynatrace.com
elasticsearch.primaries.merges.current.sizegithub.com
elasticsearch.index.operations.merge.sizegithub.com
elasticsearch.merges.current.sizegithub.com
elasticsearch.merges.total.sizegithub.com
elasticsearch.primaries.merges.total.sizegithub.com
Technical Annotations (3)
Technical References (3)
ILMcomponentdownsamplingconceptforce mergecomponentRelated Insights (2)
Segment Merge Backlog Causing Query Slowdownwarning
Background segment merges consolidate small Lucene segments into larger ones, reducing file count. When merge rate cannot keep pace with segment creation, segment count explodes causing slow queries and increased memory usage.
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ILM force merge can be disabled in downsampling to reduce resource contentioninfo
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