2019-12-02 10:43:36 -05:00
|
|
|
|
[[release-highlights-7.5.0]]
|
|
|
|
|
|
== 7.5.0 release highlights
|
|
|
|
|
|
++++
|
|
|
|
|
|
<titleabbrev>7.5.0</titleabbrev>
|
|
|
|
|
|
++++
|
|
|
|
|
|
|
|
|
|
|
|
//NOTE: The notable-highlights tagged regions are re-used in the
|
|
|
|
|
|
//Installation and Upgrade Guide
|
|
|
|
|
|
|
|
|
|
|
|
// tag::notable-highlights[]
|
|
|
|
|
|
[float]
|
|
|
|
|
|
==== Enrich processor
|
|
|
|
|
|
|
|
|
|
|
|
A new {ref}/enrich-processor.html[enrich ingest processor] has been added,
|
|
|
|
|
|
which can enrich documents with data from another index.
|
|
|
|
|
|
|
|
|
|
|
|
// end::notable-highlights[]
|
|
|
|
|
|
|
|
|
|
|
|
// tag::notable-highlights[]
|
|
|
|
|
|
[float]
|
|
|
|
|
|
==== Shape support in SQL
|
|
|
|
|
|
|
|
|
|
|
|
{ref}/xpack-sql.html[SQL] functionality that worked for geo_shape will
|
2020-04-02 09:18:28 -04:00
|
|
|
|
now work for the {ref}/shape.html[`shape`] field type introduced in 7.4.
|
2019-12-02 10:43:36 -05:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// end::notable-highlights[]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// tag::notable-highlights[]
|
|
|
|
|
|
[float]
|
|
|
|
|
|
==== Snapshot lifecycle management retention
|
|
|
|
|
|
|
|
|
|
|
|
There is a new {ref}/slm-retention.html[snapshot lifecycle management retention],
|
|
|
|
|
|
which allows you to delete older snapshots automatically through a custom
|
|
|
|
|
|
policy’s schedule.
|
|
|
|
|
|
|
|
|
|
|
|
// end::notable-highlights[]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// tag::notable-highlights[]
|
|
|
|
|
|
[float]
|
|
|
|
|
|
==== Pause {ccr}
|
|
|
|
|
|
|
|
|
|
|
|
New {ref}/ccr-post-pause-follow.html[pause] and
|
|
|
|
|
|
{ref}/ccr-post-pause-follow.html[resume] API endpoints for
|
|
|
|
|
|
{ref}/xpack-ccr.html[{ccr}] have been added, which enable you to temporarily
|
|
|
|
|
|
pause auto-follow patterns.
|
|
|
|
|
|
|
|
|
|
|
|
// end::notable-highlights[]
|
|
|
|
|
|
|
|
|
|
|
|
// tag::notable-highlights[]
|
|
|
|
|
|
[float]
|
|
|
|
|
|
==== {ml-cap} {classanalysis}
|
|
|
|
|
|
|
2019-12-20 13:01:19 -05:00
|
|
|
|
{ml-docs}/dfa-classification.html[{classanalysis-cap}] is a supervised {ml}
|
2019-12-02 10:43:36 -05:00
|
|
|
|
process for predicting a class or category of a given data point in a dataset.
|
|
|
|
|
|
For example, it can determine whether an email is spam or not.
|
|
|
|
|
|
{classification-cap} is for predicting discrete, categorical values, unlike
|
|
|
|
|
|
{reganalysis}, which predicts continuous, numerical values. 7.5.0 introduces
|
|
|
|
|
|
binary classification, which can label data points into two possible categories.
|
|
|
|
|
|
|
|
|
|
|
|
// end::notable-highlights[]
|
|
|
|
|
|
|
