APAR status
Closed as Vendor Solution.
Error description
Kafka Connector running in continuous mode, fails with Commit cannot be completed error.
Local fix
Problem summary
Problem conclusion
Temporary fix
Comments
Problem: Kafka Connector running in continuous mode sometimes aborts reporting the following error: Fatal Error: Commit cannot be completed since the group has already rebalanced and assigned the partitions to another member. This means that the time between subsequent calls to poll() was longer than the configured max.poll.interval.ms, which typically implies that the poll loop is spending too much time message processing. You can address this either by increasing the session timeout or by reducing the maximum size of batches returned in poll() with max.poll.records In continuous mode, connector sends an "end of wave" marker to subsequent stages periodically, based on record count or time frame. The flow assumes: - consume a record - write to the link - mark end of wave if needed - commit record consumption to Kafka When 'end of wave' step holds execution of the code for a long time, it may happen that it will exceed the timeout in Kafka to commit consumed records. As a result, the error is reported and job aborts. Resolution: Modify Kafka Connector to use one player process with multiple consumer threads when reading data in continuous mode. The thread count equals the number of available processors by default.
APAR Information
APAR number
JR64492
Reported component name
WIS DATASTAGE
Reported component ID
5724Q36DS
Reported release
B71
Status
CLOSED ISV
PE
NoPE
HIPER
NoHIPER
Special Attention
NoSpecatt / Xsystem
Submitted date
2022-01-11
Closed date
2022-02-25
Last modified date
2022-02-25
APAR is sysrouted FROM one or more of the following:
APAR is sysrouted TO one or more of the following:
Fix information
Applicable component levels
[{"Line of Business":{"code":"LOB10","label":"Data and AI"},"Business Unit":{"code":"BU059","label":"IBM Software w\/o TPS"},"Product":{"code":"SSVSEF","label":"InfoSphere DataStage"},"Platform":[{"code":"PF025","label":"Platform Independent"}],"Version":"11.7"}]
Document Information
Modified date:
26 February 2022