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Support Article

Cassandra partitioning leads to long 'tail' where system is slow

SA-30283

Summary



Due to the way that Cassandra partitioning work, user is finding that at the end of each data flow execution, many of the threads run out of work to do, leaving the remaining threads to complete all of the outstanding work.

This leads to a long period of time where only one or two threads are running and all other threads are idle.

This causes some Cassandra partitions to be very small, and some very large. When large partitions are the last ones to process it may leave a long tail as described in the issue.

This can be up to three hours where the system is hardly doing anything but the next data flow cannot start until the current data flow has finished. This is particularly noticeable in one particular data flow.


Error Messages


Not applicable


Steps to Reproduce



Run a data flow.


Root Cause



The issue is caused by the nature of Cassandra token distribution as described here in New token allocation algorithm in Cassandra 3.0

This causes some Cassandra partitions to be very small, and some very large. When large partitions are the last ones to process it may leave a long tail as described in the issue.

Resolution



Apply HFix-30421.
 
Suggest Edit

Published November 18, 2016 - Updated December 2, 2021

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