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From Soumya Simanta <soumya.sima...@gmail.com>
Subject Re: Flink 1.0 Critical memory issue/leak with a high throughput stream
Date Fri, 10 Jun 2016 00:31:31 GMT
Till, Fabian and Stephan - thanks for responding and providing a great

In the short term we cannot get away with Redis because we are keeping some
global state there. We do lookups on this global state as the stream is
processed, so we cannot treat it just as a sink (as suggested by Stephan).

Some more points/observations about our implementation:
1. Currently we are creating a new ActorSystem to run Rediscala
2. Since Rediscala is a non-blocking async library the results of all
operations are wrapped inside a Future. So we end up a lot of these
3. Currently all futures are being executed inside the global execution

We upgraded Rediscala to Akka 2.3.15 without any impact. Next we are trying
to upgrade Flink to Akka 2.3.15.

Just curious if there is a way to keep global state in a fault-tolerant
fashion in Flink? If yes, then we can get away from Redis in the near

Thanks again!


On Fri, Jun 10, 2016 at 12:23 AM, Stephan Ewen <sewen@apache.org> wrote:

> Hi!
> Is it possible for you to run an experiment with a job that does not use
> any Redis communication?
> If Flink is only writing to Redis, one way to test this would be to use a
> "dummy sink" operation that does not instantiate Rediscala.
> That would help to see whether the issue in in Flink's use of Akka, or in
> Rediscala's use of Akka...
> Greetings,
> Stephan
> On Thu, Jun 9, 2016 at 5:42 PM, Fabian Hueske <fhueske@gmail.com> wrote:
>> Hi Soumya,
>> this looks like an issue with Rediscala or Akka (or the way Rediscala
>> uses Akka) to me.
>> I am not aware of any other Flink user having a similar issue with too
>> many AbstractNodeQueue$Nodes.
>> Trying to upgrade to Akka 2.3.15 sounds like a good idea to me.
>> It would be great if you could report whether this fixes the problems or
>> not.
>> Thanks, Fabian
>> 2016-06-09 10:29 GMT+02:00 Soumya Simanta <soumya.simanta@gmail.com>:
>>> We are using Flink in production and running into some high CPU and
>>> memory issues. Our initial analysis points to high memory utilization that
>>> exponentially increases the CPU required for GC and ultimately takes down
>>> the task managers.
>>> We are running Flink 1.0 on YARN (on Amazon EMR).
>>> [image: Inline image 1]
>>> We consuming a real-time stream from Kafka and creating some windows and
>>> making some calls to Redis (using Rediscala - a non-blocking Redis client
>>> lib based on Akka).
>>> We took some heap dumps and looks like we have a large number of
>>> instances of
>>> akka.dispatch.AbstractQueueNode.
>>> [image: Inline image 2]
>>> And most of these are *unreachable*.
>>> [image: Inline image 3]
>>> It is not clear if this is
>>> 1) an Akka issue [1,2]
>>> 2) a Flink issue
>>> 3) a Rediscala client library issue
>>> 4) an issue with the way we are using Scala Futures inside Flink code.
>>> 5) Flink running on YARN issue
>>> Has anyone else seen a similar issue in Flink? We are planning to test
>>> this again with a custom build with a newer version of Akka (see [1])
>>> [1]https://github.com/akka/akka/issues/19216
>>> [2]https://groups.google.com/forum/#!topic/akka-user/D_qYP47Mc8Y
>>> -Soumya

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