Add indexing speed improvement to the 7.10 release highlights (#63621)
Add indexing speed improvement to the 7.10 release highlights Co-authored-by: James Rodewig <40268737+jrodewig@users.noreply.github.com>
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@ -25,6 +25,19 @@ Other versions:
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// tag::notable-highlights[]
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// tag::notable-highlights[]
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[discrete]
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[discrete]
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[[indexing-speed-improvement]]
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=== Indexing speed improvement
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{es} 7.10 improves indexing speed by up to 20%. We've reduced the coordination
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needed to add entries to the <<index-modules-translog,transaction log>>. This
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reduction allows for more concurrency and increases the transaction log buffer
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size from `8KB` to `1MB`. However, performance gains are lower for
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full-text search and other analysis-intensive use cases. The heavier the
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indexing chain, the lower the gains, so indexing chains that involve many
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fields, ingest pipelines or full-text indexing will see lower gains.
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[discrete]
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[[more-space-efficient-indices]]
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=== More space-efficient indices
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=== More space-efficient indices
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{es} 7.10 depends on Apache Lucene 8.7, which introduces higher compression of
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{es} 7.10 depends on Apache Lucene 8.7, which introduces higher compression of
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@ -40,12 +53,11 @@ Elasticsearch offers the ability to configure the <<index-codec,`index.codec`>>
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setting to tell Elasticsearch how aggressively to compress stored fields. Both
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setting to tell Elasticsearch how aggressively to compress stored fields. Both
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supported values `default` and `best_compression` will get better compression
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supported values `default` and `best_compression` will get better compression
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with this change.
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with this change.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[discrete]
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[discrete]
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[[data-tier-formalization]]
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[[data-tier-formalization]]
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=== Data tiers
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=== Data tiers
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7.10 introduces the concept of formalized data tiers within Elasticsearch. <<data-tiers,Data tiers>>
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7.10 introduces the concept of formalized data tiers within Elasticsearch. <<data-tiers,Data tiers>>
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are a simple, integrated approach that gives users control over optimizing for cost,
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are a simple, integrated approach that gives users control over optimizing for cost,
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performance, and breadth/depth of data. Prior to this formalization, many users configured their own
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performance, and breadth/depth of data. Prior to this formalization, many users configured their own
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