102 lines
4.2 KiB
Plaintext
102 lines
4.2 KiB
Plaintext
[[release-highlights-7.2.0]]
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== 7.2.0 release highlights
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++++
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<titleabbrev>7.2.0</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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// tag::notable-highlights[]
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[discrete]
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==== {dataframes-cap}
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beta[] You can now transform your data with
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{stack-ov}/ml-dataframes.html[data frames]. There is a new {kib} wizard that
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guides you through the process of creating a {dataframe-transform} to pivot and
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summarize your data and store it in a new index. Alternatively, you can use
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{ref}/data-frame-apis.html[{dataframe} APIs] to preview, create, and manage
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the transforms.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[float]
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==== Closed indices are now replicated
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Elasticsearch 7.2.0 brings better support for closed indices by allowing
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shards of closed indices to be replicated.
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As soon as an index is closed, Elasticsearch takes care of safely tearing down
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the "opened" shards before reinitializing them as "closed" shards, which require
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fewer resources. Closed shards can later be promoted to primary shards or
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automatically recovered during {ref}/recovery.html[peer recovery]
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The data is also automatically replicated by the
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cluster to ensure that enough shard copies are safely kept around at all
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times (configurable with `index.number_of_replicas`).
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In addition to that, it is now possible to snapshot closed indices using
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the {ref}/modules-snapshots.html[Snapshot/Restore API]. To include a closed index
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when creating a snapshot on Elasticsearch 7.2+, the `expand_wildcards`
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parameter must be explicitly set to either `all` or `closed` .
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Note that only indices closed in Elasticsearch 7.2+ are automatically
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replicated. Indices closed on previous versions of Elasticsearch will
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remain non replicated unless they are opened and closed again in 7.2+.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[float]
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==== Geo features in SQL
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beta[] This release introduces the first set of geo features to SQL.
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The implementation is based on the OpenGIS® Implementation Standard for Geographic
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information - "Simple feature access". This is the current de-facto standard for GIS
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system implementation. This release includes a small subset of SQL option AKA ISO 19125-2.
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For this initial beta release, we added support for returning
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geo_shapes and geo_points as results, added support for a few geo functions
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(ST_AsText, ST_Distance, ST_GeometryType, ST_GeometryFromText, ST_X, ST_Y, and ST_Z)
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, and added a limited support for using geo_points in distance queries. For example:
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SELECT * FROM my_index WHERE ST_Distance(point, ST_WKTToSQL('point (10 20)')) < 20.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[float]
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==== OpenId Connect authentication realm
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This release introduces OpenId Connect as an authentication realm.
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Elasticsearch (with the assistance of Kibana or another web component) can now serve as an
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OpenID Connect Relying Party (RP). {es} supports the Authorization Code Grant and Implicit
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flows as described in http://ela.st/oidc-spec. It also supports consuming and verifying signed ID Tokens
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, RP initiated single sign on (SSO), 3rd party initiated SSO, and RP initiated single logout.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[float]
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==== Search as you type field mapping type
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The `search_as_you_type` field type is a text-like field optimized to
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provide out-of-the-box support for queries that serve an as-you-type completion
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use case. It creates a series of subfields that are analyzed to index terms
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that can be efficiently matched by a query that partially matches the entire
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indexed text value. Both prefix completion (i.e matching terms starting at the
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beginning of the input) and infix completion (i.e. matching terms at any
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position within the input) are supported.
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// end::notable-highlights[]
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// tag::notable-highlights[]
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[float]
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==== Distance Feature Query
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The `distance_feature` query is a specialized query that only works on `date`, `date_nanos`, or `geo_point`
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fields. The query boosts documents scores based on proximity to some given origin.
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For example, you can use this query to give higher scores to documents with dates
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closer to a certain date or locations closer to a certain location.
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// end::notable-highlights[]
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