Kafka 2.3 and Kafka Connect Improvements

Robin Moffatt goes over improvements in Kafka Connect with the release of Apache Kafka 2.3:

A Kafka Connect cluster is made up of one or more worker processes, and the cluster distributes the work of connectors as tasks. When a connector or worker is added or removed, Kafka Connect will attempt to rebalance these tasks. Before version 2.3 of Kafka, the cluster stopped all tasks, recomputed where to run all tasks, and then started everything again. Each rebalance halted all ingest and egress work for usually short periods of time, but also sometimes for a not insignificant duration of time.

Now with KIP-415, Apache Kafka 2.3 instead uses incremental cooperative rebalancing, which rebalances only those tasks that need to be started, stopped, or moved. For more details, there are available resources that you can readlisten, and watch, or you can hear the lead engineer on the work, Konstantine Karantasis, talk about it in person at the upcoming Kafka Summit.

Looks like some nice improvements here.

Related Posts

Calculating YARN Utilization Metrics

Dmitry Tolpeko shows how you can calculate per-second cluster utilization measures from YARN’s resource manager logs: But even if you query YARN REST API every second it still can only provide a snapshot of the used YARN resources. It does not show which application allocates or releases containers, their memory and CPU capacity, in which […]

Read More

Spark Streaming DStreams

Manish Mishra explains the fundamental abstraction of Spark Streaming: Before going into details of the operations available on the DStream API, let us look at the input sources from which we can start a Stream. There are multiple ways in which we can get the inputs from e.g. Kafka, Flume, etc. Or simple Idle files. […]

Read More

Categories

August 2019
MTWTFSS
« Jul Sep »
 1234
567891011
12131415161718
19202122232425
262728293031