2020-01-29 11:35:02 -05:00
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[[release-highlights-7.7.0]]
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== 7.7.0 release highlights
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++++
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<titleabbrev>7.7.0</titleabbrev>
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++++
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//NOTE: The notable-highlights tagged regions are re-used in the
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//Installation and Upgrade Guide
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2020-04-17 07:37:37 -04:00
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// tag::notable-highlights[]
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[float]
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=== Fixed index corruption on shrunk indices
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Applying deletes or updates on an index after it had been shrunk would likely
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corrupt the index. We advise users of Elasticsearch 6.x who opt in for soft
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deletes on some of their indices and all users of Elasticsearch 7.x to upgrade
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to 7.7 as soon as possible to no longer be subject to this corruption bug. In
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case upgrading in the near future is not an option, we recommend to completely
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stop using `_shrink` on read-write indices and to do a force-merge right after
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shrinking on read-only indices, which significantly reduces the likeliness of
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being affected by this bug in case deletes or updates get applied by mistake.
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This bug is fixed as of {es} 7.7.0. Low-level details can be found on the
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https://issues.apache.org/jira/browse/LUCENE-9300[corresponding issue].
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// end::notable-highlights[]
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2020-01-29 11:35:02 -05:00
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// tag::notable-highlights[]
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[discrete]
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2020-04-23 05:58:32 -04:00
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=== {transforms-cap} – now in GA!
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2020-01-29 11:35:02 -05:00
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2020-04-23 05:58:32 -04:00
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In 7.7, we move {transforms} from beta to general availability.
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{ref}/transforms.html[{transforms-cap}] enable you to pivot existing {es}
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indices using group-by and aggregations into a destination feature index, which
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provides opportunities for new insights and analytics. For example, you can use
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{transforms} to pivot your data into entity-centric indices that summarize the
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behavior of users or sessions or other entities in your data.
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{transforms-cap} now include support for cross-cluster search. Allowing you to
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create your destination feature index on a separate cluster from the source
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indices.
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Aggregation support has been expanded within {transforms} to include support for
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{ref}/search-aggregations-metrics-percentile-aggregation.html[multi-value (percentiles)]
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and
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{ref}/search-aggregations-bucket-filter-aggregation.html[filter aggregations].
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We also optimized the performance of the
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{ref}/search-aggregations-bucket-datehistogram-aggregation.html[date histogram aggregations].
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[discrete]
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=== Introducing multiclass {classification}
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{ml-docs}/dfa-classification.html[{classification-cap}] using multiple classes
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is now available in {dfanalytics}. {classification-cap} is a supervised {ml}
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technique which has been already available as a binary process in the previous
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release. Multiclass {classification} works well with up to 30 distinct
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categories.
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2020-01-29 11:35:02 -05:00
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// end::notable-highlights[]
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2020-04-23 05:58:32 -04:00
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// tag::notable-highlights[]
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[discrete]
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=== {feat-imp-cap} at {infer} time
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{feat-imp-cap} now can be calculated at {infer} time. This value provides
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further insight into the results of a {classification} or {regression} job and
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therefore helps interpret these results.
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// end::notable-highlights[]
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