[[release-highlights-7.7.0]]
== 7.7.0 release highlights
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<titleabbrev>7.7.0</titleabbrev>
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//NOTE: The notable-highlights tagged regions are re-used in the
//Installation and Upgrade Guide

// tag::notable-highlights[]
[float]
=== Fixed index corruption on shrunk indices

Applying deletes or updates on an index after it had been shrunk would likely
corrupt the index. We advise users of Elasticsearch 6.x who opt in for soft
deletes on some of their indices and all users of Elasticsearch 7.x to upgrade
to 7.7 as soon as possible to no longer be subject to this corruption bug. In
case upgrading in the near future is not an option, we recommend to completely
stop using `_shrink` on read-write indices and to do a force-merge right after
shrinking on read-only indices, which significantly reduces the likeliness of
being affected by this bug in case deletes or updates get applied by mistake.
This bug is fixed as of {es} 7.7.0. Low-level details can be found on the
https://issues.apache.org/jira/browse/LUCENE-9300[corresponding issue].

// end::notable-highlights[]

// tag::notable-highlights[]
[discrete]
=== {transforms-cap} – now in GA!

In 7.7, we move {transforms} from beta to general availability.

{ref}/transforms.html[{transforms-cap}] enable you to pivot existing {es} 
indices using group-by and aggregations into a destination feature index, which 
provides opportunities for new insights and analytics. For example, you can use 
{transforms} to pivot your data into entity-centric indices that summarize the 
behavior of users or sessions or other entities in your data.

{transforms-cap} now include support for cross-cluster search. Allowing you to 
create your destination feature index on a separate cluster from the source 
indices. 

Aggregation support has been expanded within {transforms} to include support for 
{ref}/search-aggregations-metrics-percentile-aggregation.html[multi-value (percentiles)] 
and 
{ref}/search-aggregations-bucket-filter-aggregation.html[filter aggregations]. 
We also optimized the performance of the 
{ref}/search-aggregations-bucket-datehistogram-aggregation.html[date histogram aggregations].

// end::notable-highlights[]

// tag::notable-highlights[]
[discrete]
=== Introducing multiclass {classification}

{ml-docs}/dfa-classification.html[{classification-cap}] using multiple classes 
is now available in {dfanalytics}. {classification-cap} is a supervised {ml} 
technique which has been already available as a binary process in the previous 
release. Multiclass {classification} works well with up to 30 distinct 
categories.

// end::notable-highlights[]

// tag::notable-highlights[]
[discrete]
=== {feat-imp-cap} at {infer} time

{feat-imp-cap} now can be calculated at {infer} time. This value provides 
further insight into the results of a {classification} or {regression} job and 
therefore helps interpret these results.

// end::notable-highlights[]