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https://issues.apache.org/jira/browse/BEAM-7589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16887847#comment-16887847
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Brachi Packter commented on BEAM-7589:
--------------------------------------
[~aromanenko] Still happens, can't run Data Flow with the latest snapshot.
getting abstract method error: (Can it be related to this PR
[https://github.com/apache/beam/pull/8311]?)
Adding again the stack trace:
{code:java}
java.lang.AbstractMethodError:
org.apache.beam.runners.dataflow.worker.repackaged.org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.schemaElement(I)Ljava/lang/Object;
org.apache.beam.sdk.schemas.transforms.Convert$ConvertTransform$1$DoFnInvoker.invokeProcessElement(Unknown
Source)
org.apache.beam.runners.dataflow.worker.repackaged.org.apache.beam.runners.core.SimpleDoFnRunner.invokeProcessElement(SimpleDoFnRunner.java:213)
org.apache.beam.runners.dataflow.worker.repackaged.org.apache.beam.runners.core.SimpleDoFnRunner.processElement(SimpleDoFnRunner.java:178)
org.apache.beam.runners.dataflow.worker.SimpleParDoFn.processElement(SimpleParDoFn.java:330)
org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:44)
org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:49)
org.apache.beam.runners.dataflow.worker.SimpleParDoFn$1.output(SimpleParDoFn.java:276){code}
> Kinesis IO.write throws LimitExceededException
> ----------------------------------------------
>
> Key: BEAM-7589
> URL: https://issues.apache.org/jira/browse/BEAM-7589
> Project: Beam
> Issue Type: Bug
> Components: io-java-kinesis
> Affects Versions: 2.11.0
> Reporter: Anton Kedin
> Assignee: Alexey Romanenko
> Priority: Major
> Fix For: 2.15.0
>
> Time Spent: 5h 20m
> Remaining Estimate: 0h
>
> Follow up from https://issues.apache.org/jira/browse/BEAM-7357:
>
> ----
> Brachi Packter added a comment - 13/Jun/19 09:05
> [~aromanenko] I think I find what makes the shard map update now.
> You create a producer per bundle (in SetUp function) and if I multiply it by
> the number of workers, this gives huge amount of producers, I belive this
> make the "update shard map" call.
> If I copy your code and create *one* producer ** for every wroker, then this
> error disappear.
> Can you just remove the producer creation from setUp method, and move it to
> some static field in the class, that created once the class is initiated.
> See similar issue that was with JDBCIO, connection pool was created per setup
> method, and we moved it to be a static member, and then we will have one pool
> for JVM. ask [~iemejia] for more detail.
> ----
> Alexey Romanenko added a comment -14/Jun/19 14:31- edited
>
> [~brachi_packter] What kind of error do you have in this case? Could you
> post an error stacktrace / exception message?
> Also, it would be helpful (if it's possible) if you could provide more
> details about your environment and pipeline, like what is your pipeline
> topology, which runner do you use, number of workers in your cluster, etc.
> For now, I can't reproduce it on my side, so all additional info will be
> helpful.
> ----
> Brachi Packter added a comment - 16/Jun/19 06:44
> I get same Same error:
> {code:java}
> [0x00001728][0x00007f13ed4c4700] [error] [shard_map.cc:150] Shard map update
> for stream "**" failed. Code: LimitExceededException Message: Rate exceeded
> for stream poc-test under account **.; retrying in 5062 ms
> {code}
> I'm not seeing full stack trace, but can see in log also this:
> {code:java}
> [2019-06-13 08:29:09.427018] [0x000007e1][0x00007f8d508d3700] [warning] [AWS
> Log: WARN](AWSErrorMarshaller)Encountered AWSError Throttling Rate exceeded
> {code}
> More details:
> I'm using DataFlow runner, java SDK 2.11.
> 60 workers initally, (with auto scalling and also with flag
> "enableStreamingEngine")
> Normally, I'm producing 4-5k per second, but when I have latency, this can be
> even multiply by 3-4 times.
> When I'm starting the DataFlow job I have latency, so I produce more data,
> and I fail immediately.
> Also, I have consumers, 3rd party tool, I know that they call describe stream
> each 30 seconds.
> My job pipeline, running on GCP, reading data from PubSub, it read around
> 20,000 record per second (in regular time, and in latency time even 100,000
> records per second) , it does many aggregation and counting base on some
> diamnesions (Using Beam sql) , This is done for 1 minutes window slide, and
> wrting the result of aggregations to Kinesis stream.
> My stream has 10 shards, and my partition key logic is generating UUid per
> each record:
> UUID.randomUUID().toString()
> Hope this gave you some more context on my problem.
> Another suggestion I have, can you try fix the issue as I suggest and provide
> me some specific version for testing? without merging it to master? (I would
> di it myself, but I had truobles building locally the hue repository of
> apache beam..)
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