Hi all,
I'm trying to use ReplicateFn mentioned in this
<https://s.apache.org/splittable-do-fn> doc in my pipeline to speed up a
nested for loop. The use case is exactly the same as "*Counting friends in
common (cross join by key)*" section. However, I have trouble to make it
work with beam 2.4.0 SDK.
I'm implementing @SplitRestriction as follows:
@SplitRestriction
public void splitRestriction(A element, OffsetRange range,
OutputReceiver<OffsetRange> out) {
for (final OffsetRange p : range.split(1000, 10)) {
out.output(p);
}
}
Dataflow runner throws exception like this:
java.util.NoSuchElementException
com.google.cloud.dataflow.worker.repackaged.com.google.common.collect.MultitransformedIterator.next(MultitransformedIterator.java:63)
com.google.cloud.dataflow.worker.repackaged.com.google.common.collect.TransformedIterator.next(TransformedIterator.java:47)
com.google.cloud.dataflow.worker.repackaged.com.google.common.collect.Iterators.getOnlyElement(Iterators.java:308)
com.google.cloud.dataflow.worker.repackaged.com.google.common.collect.Iterables.getOnlyElement(Iterables.java:294)
com.google.cloud.dataflow.worker.DataflowProcessFnRunner.getUnderlyingWindow(DataflowProcessFnRunner.java:97)
com.google.cloud.dataflow.worker.DataflowProcessFnRunner.placeIntoElementWindow(DataflowProcessFnRunner.java:71)
com.google.cloud.dataflow.worker.DataflowProcessFnRunner.processElement(DataflowProcessFnRunner.java:61)
com.google.cloud.dataflow.worker.SimpleParDoFn.processElement(SimpleParDoFn.java:323)
com.google.cloud.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:43)
com.google.cloud.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:48)
com.google.cloud.dataflow.worker.util.common.worker.ReadOperation.runReadLoop(ReadOperation.java:200)
com.google.cloud.dataflow.worker.util.common.worker.ReadOperation.start(ReadOperation.java:158)
com.google.cloud.dataflow.worker.util.common.worker.MapTaskExecutor.execute(MapTaskExecutor.java:75)
com.google.cloud.dataflow.worker.StreamingDataflowWorker.process(StreamingDataflowWorker.java:1211)
com.google.cloud.dataflow.worker.StreamingDataflowWorker.access$1000(StreamingDataflowWorker.java:137)
com.google.cloud.dataflow.worker.StreamingDataflowWorker$6.run(StreamingDataflowWorker.java:959)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
java.lang.Thread.run(Thread.java:745)
I also tried the following as suggested by the javadoc
<https://beam.apache.org/documentation/sdks/javadoc/2.4.0/org/apache/beam/sdk/transforms/DoFn.SplitRestriction.html>
but
it has errors during pipeline construction.
@SplitRestriction
public List<OffsetRange> splitRestriction(A element, OffsetRange range) {
return range.split(1000, 10);
}
Without implementing @SplitRestriction, my pipeline can run without any
errors. However, I think the SDF is not really splitted by default, which
defeats the purpose of improving performance.
Does anyone know if @SplitRestriction is currently supported by Dataflow
runner? How can I write a working version with the latest SDK?
Thanks,
Jiayuan
