OpenSearch/docs/reference/release-notes/highlights-7.2.0.asciidoc

[[release-highlights-7.2.0]]
== 7.2.0 release highlights
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<titleabbrev>7.2.0</titleabbrev>
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//NOTE: The notable-highlights tagged regions are re-used in the
//Installation and Upgrade Guide

// tag::notable-highlights[]
[discrete]
==== {dataframes-cap}

beta[] You can now transform your data with
{ref}/transforms.html[data frames]. There is a new {kib} wizard that
guides you through the process of creating a {dataframe-transform} to pivot and
summarize your data and store it in a new index. Alternatively, you can use
{ref}/data-frame-apis.html[{dataframe} APIs] to preview, create, and manage
the transforms.

// end::notable-highlights[]

// tag::notable-highlights[]
[float]
==== Closed indices are now replicated

Elasticsearch 7.2.0 brings better support for closed indices by allowing
shards of closed indices to be replicated.
As soon as an index is closed, Elasticsearch takes care of safely tearing down
the "opened" shards before reinitializing them as "closed" shards, which require
fewer resources. Closed shards can later be promoted to primary shards or
automatically recovered during {ref}/recovery.html[peer recovery]
The data is also automatically replicated by the
cluster to ensure that enough shard copies are safely kept around at all
times (configurable with `index.number_of_replicas`).

In addition to that, it is now possible to snapshot closed indices using
the {ref}/modules-snapshots.html[Snapshot/Restore API]. To include a closed index
when creating a snapshot on Elasticsearch 7.2+, the `expand_wildcards`
parameter must be explicitly set to either `all` or `closed` .

Note that only indices closed in Elasticsearch 7.2+ are automatically
replicated. Indices closed on previous versions of Elasticsearch will
remain non replicated unless they are opened and closed again in 7.2+.

// end::notable-highlights[]

// tag::notable-highlights[]
[float]
==== Geo features in SQL
beta[] This release introduces the first set of geo features to SQL.
The implementation is based on the OpenGIS® Implementation Standard for Geographic
information - "Simple feature access". This is the current de-facto standard for GIS
system implementation. This release includes a small subset of SQL option AKA ISO 19125-2.

For this initial beta release, we added support for returning
geo_shapes and geo_points as results, added support for a few geo functions
(ST_AsText, ST_Distance, ST_GeometryType, ST_GeometryFromText, ST_X, ST_Y, and ST_Z)
, and added a limited support for using geo_points in distance queries. For example:
SELECT * FROM my_index WHERE ST_Distance(point, ST_WKTToSQL('point (10 20)')) < 20.

// end::notable-highlights[]

// tag::notable-highlights[]
[float]
==== OpenId Connect authentication realm

This release introduces OpenId Connect as an authentication realm.
Elasticsearch (with the assistance of Kibana or another web component) can now serve as an
OpenID Connect Relying Party (RP). {es} supports the Authorization Code Grant and Implicit
flows as described in http://ela.st/oidc-spec. It also supports consuming and verifying signed ID Tokens
, RP initiated single sign on (SSO), 3rd party initiated SSO, and RP initiated single logout.


// end::notable-highlights[]

// tag::notable-highlights[]
[float]
==== Search as you type field mapping type

The `search_as_you_type` field type is a text-like field optimized to
provide out-of-the-box support for queries that serve an as-you-type completion
use case. It creates a series of subfields that are analyzed to index terms
that can be efficiently matched by a query that partially matches the entire
indexed text value. Both prefix completion (i.e matching terms starting at the
beginning of the input) and infix completion (i.e. matching terms at any
position within the input) are supported.

// end::notable-highlights[]


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[float]
==== Distance Feature Query

The `distance_feature` query is a specialized query that only works on `date`, `date_nanos`, or `geo_point`
fields. The query boosts documents scores based on proximity to some given origin.
For example, you can use this query to give higher scores to documents with dates
closer to a certain date or locations closer to a certain location.

// end::notable-highlights[]