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Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multi-tenancy-enabled, full-text search engine with an HTTP web interface and schemaless JSON documents. Elasticsearch is developed in Java and released as open source software under the Apache license. The official client is available in Java, . NET (C#), PHP, Python, Apache Groovy, Ruby, and many other languages are available.
After nearly three years, Elasticsearch 8 is officially released, and new features include
: 8.0 introduces some significant changes to the Elasticsearch REST APIs. While it’s important to update your application to accommodate these changes, finding and updating every API call after an upgrade can be painful and error-prone for developers. To make this process easier, Elasticsearch has added support for 7.x-compatible headers to the REST API. These optional header files let you make 7.x-compliant requests to an 8.0 cluster and receive a 7.x-compliant response.
While developers are still encouraged to update your applications to use native 8.0 requests and responses, the 7.x API compatible header file allows you to safely make these changes over a longer period of time.

Running Elasticsearch

without security exposes your cluster to any user who can send requests to Elasticsearch. In previous releases, you had to explicitly enable Elasticsearch’s security features, such as authentication, authorization, and network encryption (TLS). Starting with Elasticsearch 8.0, security features are enabled and configured by default when Elasticsearch is first launched.
At launch, Elasticsearch 8.0 generates a registration token that you can use to connect to Kibana instances or register other nodes in a secure Elasticsearch cluster without generating security certificates or updating YAML profiles. Simply use the generated registration token when you launch a new node or Kibana instance, and Elastic Stack handles all the security configuration for you.
Known issue:
  • if you install from an archive on arch64 platforms such as Linux ARM or macOS M1 Elasticsearch, then the Elastic user password and Kibana registration token are not automatically generated the first time the node is launched. After the node starts, you need to use the bin/elasticsearch-reset-password tool to generate the elastic password:

 
bin/elasticsearch-reset-password -u elastic
  • then, use bin/ The elasticsearch-create-enrollment-token tool creates a registration token for Kibana: bin/elasticsearch-create-enrollment-token –

s kibana
System indexes store configuration and internal data for Elastic features. In general, system indexes are reserved for internal use only for these features. While possible, direct access to or altering system indexes can cause instability and other problems.
Several changes have been made in Elasticsearch 8.0 to protect system indexes from direct access. To access the system index, the user must now have the allow_restricted_indices permission set to true.
The superuser role also no longer gives write access to the system index. Therefore, the built-in elastic superuser cannot alter the system index by default.
Thereafter, developers should use Kibana or related Elasticsearch APIs to manage data for a feature instead of accessing system indexes. If you access the system index directly, Elasticsearch returns a warning in the header of the API response and in the obsolete log.
Technical preview of the KNN search API is available in Elasticsearch 8.0. By using the dense_vector field, the k-nearest neighbor (KNN) search finds the k vectors closest to the query vector (this is measured by the similarity metric). KNN is commonly used to support recommendation engines and relevance rankings based on natural language processing (NLP) algorithms.
Previously, Elasticsearch only supported precise KNN search, using script_score with vector functions  Inquire. While this approach guarantees accurate results, it tends to result in slow searches and doesn’t scale well on large datasets. In exchange for slower indexing and imperfect accuracy, the new KNN search API lets you run approximate KNN searches faster on larger datasets.
This release updates the inverted index, which is an internal data structure that allows for more space-efficient encoding. This change will benefit the keyword, match_only_text field, and text field. In benchmarks using application logs, this shift reduced the index size of the message field (mapped to match_only_text) by 14.4%, resulting in a 3.5% reduction in disk footprint overall.
The new version optimizes the indexing speed of multi-dimensional points, which are used for geo_point and geo_shape and the internal data structure of the range field. Lucene-level benchmarks show a 10-15% increase in indexing speed for these field types. Elasticsearch indexes and dataflows that are primarily composed of these fields may see significant improvements in indexing speed.
You can now upload PyTorch models trained outside of Elasticsearch and use them for inference. Third-party model support brings modern natural language processing (NLP) and search use cases to the Elastic Stack.
Aggregations

:

  • Delete adjacency matrix setting #46327 (issues: #46257, #46324)

  • remove MovingAverage pipeline aggregate #39328

  • Remove deprecated

  • _time and _term sort #39450 Remove deprecated

  • date history interval #75000

Allocation:
  • delete include_ relocations setting #47717 (issues: #46079, #47443)

Analysis:

    > Versioning deprecation in cleanup analysis #41560 (issue: #41164)

  • removes preconfigured delimited_payload_ filter #43686 (issues: #41560, #43684)

Authentication:
  • Always add files and native Realm #69096 (issue: #50892)

  • does not format NameID in Policy by default #44090 (issue: #40353)

  • Enforce order for Realm configuration #51195 (issue: #37614 )

Cluster Coordination:
    Delete

  • connection timeout #60873  (issue: #60872)

  • Removed support for delayed state resume suspend master #53845 (issue: #51806).

Distributed

:

    Delete

  • sync refresh #50882 (issues: #50776.). , #50835)

  • Remove cluster.remote.connect setting #54175 (issue: #53924).

Engine:
  • Force merge should reject only_expunge_deletes sum set max_num_segments request #44761 (issue: #43102)

  • to delete per-type index statistics #47203 (issue: #41059)

  • Remove translog retention setting #51697 (issue: #50775).

Features/CAT APIs:
  • _cat/indices Remove the deprecated local parameter #64868 (issue: #62198.)

  • ) to remove the deprecated local parameter #64867 (issue: #62197) for _cat/shards

Features/ILM+SLM:

    >default cluster.routing.allocation.enforce_default_ tier_preference true #79275 (issues: #76147, #79210)

Features/Indices APIs
  • set the default value of the prefer_v2_templates parameter to true  #55489 (issues: #53101, #55411)

  • Remove the deprecated _upgrade API #64732 (issue: #21337)

  • to remove the parameter include_type_name from the REST layer

  • Delete the template

  • field #49460 (issue: #21009)

Infra/Core

in the index template

  • remove the nodes/0 folder prefix

  • from the data path bootstrap.system_call_filter setting #72848

  • to remove node.max_local_storage_nodes #42428 (issue.) : #42426)

  • Remove

  • Joda dependency #79007

  • Remove hump case for named date/time format #60044

Packaging
    Remove

  • SysV initialization support #51716

  • Removed support for JAVA_HOME #69149

  • Java 17 is required to run Elasticsearch #79873

……
For more details, please see: https://www.elastic.co/cn/blog/whats-new-elastic-8-0-0

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