Introducing Imply 2021.01 LTS – our first Long Term Support release

Earlier this year, we explained how we’re moving to monthly releases that fall into two different categories: Short Term Support releases and Long Term Support releases. Each of the two categories is geared towards the needs of a specific set of Imply users.

Short Term Support (STS) releases  bring you new features every month. You can try things out and give us feedback to influence Imply’s roadmap or to use that new function you need without having to wait a quarter or more for it. Critical security fixes are included too.

Long Term Support (LTS) releases are stable versions of our products that include bug fixes for a year and security fixes for two years. LTS releases are for customers who prioritize operational stability over new features.

You can check the support end dates for our different versions here.

2021.01 LTS is our first Long Term Support (LTS) release. It mainly includes bug fixes and security updates, but there are some Druid changes too. Below is a quick summary of the release notes:

Limit percentage of segments considered for segment balancing: You can now set the percentOfSegmentsToConsiderPerMove on coordinator dynamic configuration to limit the number of segments considered when picking a candidate segment to move. This new configuration speeds up the segment balancing by preventing Druid from iterating through all available segments. It’s especially useful for larger clusters with lots of segments.

status and selfDiscovered endpoints for Indexers: New endpoints that provide status information and indicate whether the node has joined the cluster allow you to better monitor the health of indexers. Note: Indexer is still considered an alpha feature and should not be used for production.

Improved handling for missing arguments: Expression processing can now be vectorized when columns are missing from part of the data.

Zero period for TIMESTAMPADD: The TIMESTAMPADD function now allows zero period. This functionality is required for some BI tools, such as Tableau.

Native re-ingestion is less memory intensive: Parallel tasks now sort segments by ID before assigning them to subtasks. This sorting minimizes the number of time chunks for each subtask to handle and thus minimizes their memory consumption.

Partitioning information in the web console: The web console now shows datasource partitioning information on the new Segment granularity and Partitioning columns.

Query timeout metric: A new metric provides the number of timed out queries. Previously, timed out queries were treated as interrupted and included in the query/interrupted/count.

Support for legacy Kafka versions: Druid now supports Apache Kafka versions older than 0.11. We recommend using newer versions of Kafka when possible.

Finally, over the past couple of months we’ve also made a few updates and additions to our lineup of tutorials:

• Data ingestion
• Kafka ingestion
• Connecting to Amazon Kinesis
• Querying data