Elasticsearch 6.5.0 brings support for JDK 11 and several new features

Elasticsearch 6.5.0 is here and it brings some big updates and changes.

Let’s have a closer look at the highlights of this release.

Cross-cluster replication – 6.5 marks the first beta version of cross-cluster replication. Cross-cluster replication is a Platinum-level feature for Elasticsearch in which in your local cluster you can create an index to follow an index in a remote cluster or automatically-follow indices in a remote cluster that match a pattern. Check out the cross-cluster getting started documentation, for information on how to set up cross-cluster replication.

Minimal snapshots – Introducing a new source-only repository which you can use to make that trade-off. The idea of these source-only snapshots is that you store a minimal amount of information (namely, the _source and index metadata) so that the indices can be rebuilt through a reindex operation if necessary. The advantage can be significant: up to a 50% reduction in disk space of the snapshots. They will take longer to restore (in full) though, as you’ll need to do a reindex to make them searchable, so they aren’t for everyone. But if you have longer recovery windows and are space constrained, you may want to consider making use of this new feature.

SQL / ODBC – Releasing an initial (alpha status) ODBC driver for Elasticsearch, which you can find here. This complements the existing JDBC driver, useful for java-y goodness. As ODBC is supported by many BI tools, you can now connect Elasticsearch to a lot of your favorite 3rd party tools (notably, many of your favorite BI tools), which gives you the speed, flexibility, and power of full-text search and relevance. Furthermore, a few more functions and SQL capabilities were added with this release. Check them out here.

Search use cases – The latest Elasticsearch release features several new features specific to the search use case including token filtering and a new text type, called annotated_text. Check them all out here.

JDK 11 & G1GC – Elasticsearch now supports JDK 11. What’s more, Elasticsearch is now committed to supporting the G1 garbage collector on JDK 10+.

SEE ALSO: Meet dejavu, the Elasticsearch web UI that supports importing data via JSON and CSV files

Security and audit logging – Introducing several new security features, including authorization realms that allow an authenticating realm to delegate the task of pulling the user information (with the user name, the user’s roles, etc) to one or more other realms. Another security-related feature is structured security audit logging where all attributes are named. Specifically, each log entry is a one-line JSON document and each one is printed on a separate line.

Machine learning – Anomaly scoring for multi-metric jobs has been updated so that the scores for each time-series are now less affected by the behavior of other time series in the job. This brings a significant change to the individual results for each partitioned time series, making them similar to having been run as a single metric machine learning job, while the overall anomaly score remains a top level and rate limited view of the job as a whole. Furthermore, 6.5 introduces multi-bucket analysis for machine learning jobs, where features from multiple contiguous buckets are used for anomaly detection. The final anomaly score is a combination of values from both the “standard” single-bucket analysis and the new multi-bucket analysis.

Getting started

Elasticsearch can be run on your own hardware or using the hosted Elasticsearch Service on Elastic Cloud, which is available on AWS and GCP. You can also download and install Elasticsearch yourself and it’s provided in several package formats.

Check out the installation guide here and the getting started guide here.

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