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From Chen Qin <qinnc...@gmail.com>
Subject fan out parallel-able operator sub-task beyond total slots number
Date Sun, 17 Apr 2016 16:54:10 GMT
Hi there,


I try run large number of subtasks within a task slot using slot sharing
group. The usage scenario tried to adress operator that makes a network
call with high latency yet less memory or cpu footprint. (sample code below)

>From doc provided, slotsharinggroup seems the place to look at. Yet it
seems it were not designed to address the scenario above.
https://ci.apache.org/projects/flink/flink-docs-master/concepts/concepts.html#workers-slots-resources

My question is, which is best way to fan out large number of sub tasking
parallel within a task?

public void testFanOut() throws Exception{
    env = StreamExecutionEnvironment.getExecutionEnvironment();
...
    env.addSource(...).setParallelism(1).disableChaining().shuffle().flatMap(new
FlatMapFunction<DummyFlinkRecord, Long>() {
        @Override
        public void flatMap(DummyFlinkRecord dummyFlinkRecord,
Collector<Long> collector) throws Exception {
            Thread.sleep(1000); //latency is high, needs to fan out
            collector.collect(1l);
        }
    }).slotSharingGroup("flatmap").setParallelism(100).rebalance().filter(new
FilterFunction<Long>() {
        @Override
        public boolean filter(Long aLong) throws Exception {
            return true;
        }
    }).setParallelism(10).addSink(new SinkFunction<Long>() {
        @Override
        public void invoke(Long aLong) throws Exception {
            System.out.println(aLong);
        }
    });
    env.execute("fan out 100 subtasks for 1s delay mapper");
}

Thanks,
Chen Qin

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