Re: Task manger isn’t initiating with defined values in Flink 1.11 version as part of EMR 6.1.0

2021-01-11 Thread Till Rohrmann
Hi Deep, Could you take a look at the logs of the TM which was lost? They might help us to debug the root cause. My guess would be that we are exceeding some memory threshold and that the kernel kills the process. Cheers, Till On Mon, Jan 11, 2021 at 1:46 PM DEEP NARAYAN Singh wrote: > Hi

Re: Task manger isn’t initiating with defined values in Flink 1.11 version as part of EMR 6.1.0

2021-01-11 Thread DEEP NARAYAN Singh
Hi Till, Thanks for your support on task manager, in continuation to above email when we increased the TM and JM memory to run the job with increased parallelism but the job is getting failed in *one day* with below exception. Logs : *org.apache.flink.client.program.ProgramInvocationException:

Re: Task manger isn’t initiating with defined values in Flink 1.11 version as part of EMR 6.1.0

2021-01-04 Thread DEEP NARAYAN Singh
Thanks Till, for the detailed explanation.I tried and it is working fine. Once again thanks for your quick response. Regards, -Deep On Mon, 4 Jan, 2021, 2:20 PM Till Rohrmann, wrote: > Hi Deep, > > Flink has dropped support for specifying the number of TMs via -n since the > introduction of

Re: Task manger isn’t initiating with defined values in Flink 1.11 version as part of EMR 6.1.0

2021-01-04 Thread Till Rohrmann
Hi Deep, Flink has dropped support for specifying the number of TMs via -n since the introduction of Flip-6. Since then, Flink will automatically start TMs depending on the required resources. Hence, there is no need to specify the -n parameter anymore. Instead, you should specify the parallelism

Task manger isn’t initiating with defined values in Flink 1.11 version as part of EMR 6.1.0

2021-01-03 Thread DEEP NARAYAN Singh
Hi Guys, I’m struggling while initiating the task manager with flink 1.11.0 in AWS EMR but with older versions it is not. Let me put the full context here. *When using Flink 1.9.1 and EMR 5.29.0* To create a long running session, we used the below command. *sudo flink-yarn-session -n -s -jm