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#! [euphoria-flink] Avoid extra shuffle when windowing on streaming #52

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Mar 21, 2017
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#! [euphoria-flink] Avoid extra shuffle when windowing on streaming #52

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4 changes: 3 additions & 1 deletion ...ia-flink/src/main/java/cz/seznam/euphoria/flink/streaming/ReduceStateByKeyTranslator.java
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,9 @@ public DataStream<?> translate(FlinkOperator<ReduceStateByKey> operator,
// assign windows
DataStream<KeyedMultiWindowedElement> windowed = input.map(new WindowAssigner(
windowing, keyExtractor, valueExtractor, eventTimeAssigner))
.setParallelism(operator.getParallelism());
// ~ execute in the same chain of the input's processing
// so far, thereby, avoiding an unnecessary shuffle
.setParallelism(input.getParallelism());
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What is the difference of input.getParallelism() and operator.getParallelism()? Shouldn't this be the same provided that to operator didn't define its own parallelism?

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  • input.getParallelism() returns the parallelism the corresponding flink's dataset
  • operator.getParallism() returns the target parallelism intended for the operator (in this case, rsbk)

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Yes, okay, but if the user code does not define specific parallelism (for RSBK), shouldn't this be the same?

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ah, yes. that's correct! in that case input.parallelism will equal operator.parallelism, that's right.

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Okay, I didn't look into details of this PR, but will the RSBK respect the user-supplied parallelism (if any) after this change?

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yes, it will. the attached execution plan shows a program where the RSBK is instructed for a 120 partitions output.

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Yes, user-supplied parallelism is correctly applied to the operation after shuffle. It's basically map -> keyBy -> setParallelism -> reduceByKey.


DataStream<WindowedElement<?, Pair>> reduced = (DataStream) windowed.keyBy(new KeyExtractor())
.transform(operator.getName(), TypeInformation.of(WindowedElement.class), new WindowOperator<>(
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