[ https://issues.apache.org/jira/browse/FLINK-8712 ]
Weihua Hu deleted comment on FLINK-8712:
----------------------------------
was (Author: huwh):
[~xtsong],
IMO, there are two options for batch job:
1. Calculate the accurate min required slot number according to whether the
ResultPartitionType is PIPELINED or BLOCKING. This is a little complicated.
2. We can just sum up these max-parallelism for different groups. Then both
streaming and batch job can run successfully. For batch job, user can adjust
the slot number in configuration.
I would like use the option 2, and the name of getMaximumParallelism will
change to getSumOfSharingGroupMaximumParallelism
> Cannot execute job with multiple slot sharing groups on LocalExecutor
> ---------------------------------------------------------------------
>
> Key: FLINK-8712
> URL: https://issues.apache.org/jira/browse/FLINK-8712
> Project: Flink
> Issue Type: Bug
> Components: Runtime / Task
> Affects Versions: 1.5.0
> Reporter: Till Rohrmann
> Priority: Not a Priority
> Labels: auto-deprioritized-critical, auto-deprioritized-major,
> auto-deprioritized-minor
>
> Currently, it is not possible to run a job with multiple slot sharing groups
> on the LocalExecutor. The problem is that we determine the number of required
> slots simply by looking for the max parallelism of the job but do not
> consider slot sharing groups.
>
> {code:java}
> // set up the streaming execution environment
> final StreamExecutionEnvironment env =
> StreamExecutionEnvironment.getExecutionEnvironment();
> env.setParallelism(1);
> final DataStreamSource<Integer> input = env.addSource(new InfinitySource());
> final SingleOutputStreamOperator<Integer> different = input.map(new
> MapFunction<Integer, Integer>() {
> @Override
> public Integer map(Integer integer) throws Exception {
> return integer;
> }
> }).slotSharingGroup("Different");
> different.print();
> // execute program
> env.execute("Flink Streaming Java API Skeleton");{code}
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
