How to introduce delay time between retry attempts for spark streaming job

[#1]

We are running a spark streaming job which reads data from kafka and writes to RDBMS. We dont want this job to fail easily due to minor fluctuations in cluster health/issue. Write now spark job has configuration to retry 5 attempts before the whole job fails. But all these retries are happening in quick succession , one after another. Is there a way we can put some delay/sleep time between retry attempts for this job?

[#2]

Hi @sat_046 

I don't think we have a specific configuration parameter to handle the task retry attempts with some delay. But we have a parameters to blacklist the node if the task is failed with some no of attempts in the node.

References:

1. https://community.cloudera.com/t5/Community-Articles/Configuring-spark-task-maxFailures-amp-spark-bl...

2.  https://www.waitingforcode.com/apache-spark/failed-tasks-resubmit/read

[#3]

@sat_046 Has the reply helped resolve your issue? If so, please mark the appropriate reply as the solution, as it will make it easier for others to find the answer in the future. 

[#4]

Hi @sat_046 

As i mentioned earlier comment, unfortunately it is not possible to delay the tasks. You can find the Spark code when tasks failed.

https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/TaskSetMa...

Please accept the solution if you liked my answer.