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From: Bruno Aranda <brunoaranda@gmail.com>
Date: Fri, 17 Feb 2017 09:56:50 +0000
Message-ID: <CAEv5b0xtq6fEwqYMw_yh+HUGPeHteVJGbxsACttkPPYNZc3eJQ@mail.gmail.com>
Subject: Re: One Kafka consumer operator subtask sending many more bytes than
 the others
To: user@flink.apache.org
Content-Type: multipart/related; boundary=001a11451b2c6737240548b6efb9
archived-at: Fri, 17 Feb 2017 09:57:16 -0000

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Cool, thanks for your feedback Till. I will investigate the logs and our
Kafka installation. So far we use Flink 1.2 with Kafka 0.10.0.0 on AWS.
Flink client is 0.10 (with underlying java client 0.10.0.0). Will have a
look at the logs and try different things with Kafka today (ie upgrade it,
configure the availability zones, etc), to see if I can pinpoint the issue.

Thanks!

Bruno

On Fri, 17 Feb 2017 at 09:44 Till Rohrmann <trohrmann@apache.org> wrote:

> Hi Bruno,
>
> do you resume from the savepoints with a changed parallelism? Which
> version of Flink are you running? Which Kafka version are you using (+
> which Kafka consumer version).
>
> The partitions should be distributed among all 6 parallel subtasks which
> means that every subtask should read from 100 partitions. You can check in
> the logs how many partitions each consumer has been assigned by searching
> for "Got x partitions from these topics" or "Consumer is going to read the
> following topics". If you don't see 100 partitions assigned to each
> consumer, then something is clearly going wrong.
>
> Cheers,
> Till
>
> On Thu, Feb 16, 2017 at 1:42 PM, Bruno Aranda <baranda@apache.org> wrote:
>
> Hi,
>
> I am trying to understand this issue in one of my Flink jobs with a Kafka
> source. At the moment I am using parallelism 6. The operator subtask just
> read the Kafka records (from a topic with 600 partitions), applies a keyBy
> and sends them to the next operator after the hashing.
>
> What I can see is that one of the subtasks is sending much more data than
> the others. The kafka partitions are well-balanced, as in they roughly
> contain the same number of records.
>
> I attach a screenshot. One subtask has sent 429 MB and the others around
> 4.88 KB.
>
> Could this be related that I originally created this stream with just
> parallelism one and I increased it later at some point. This is from a
> performance test suite where I am increasing parallelism between runs to
> check the performance, in a highly available cluster setup with zookeeper
> and checkpoints in S3.
>
> I am not cancelling the job with savepoints.
>
> Any ideas or things I can look for?
>
> Thanks!
>
> Bruno
>
> [image: Screen Shot 2017-02-16 at 12.36.29.png]
>
>
>
>

--001a11451b2c6737220548b6efb8
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">Cool, thanks for your feedback Till. I will investigate th=
e logs and our Kafka installation. So far we use Flink 1.2 with Kafka 0.10.=
0.0 on AWS. Flink client is 0.10 (with underlying java client 0.10.0.0). Wi=
ll have a look at the logs and try different things with Kafka today (ie up=
grade it, configure the availability zones, etc), to see if I can pinpoint =
the issue.=C2=A0<div><br></div><div>Thanks!<div><br></div><div>Bruno</div><=
/div></div><br><div class=3D"gmail_quote"><div dir=3D"ltr">On Fri, 17 Feb 2=
017 at 09:44 Till Rohrmann &lt;<a href=3D"mailto:trohrmann@apache.org">troh=
rmann@apache.org</a>&gt; wrote:<br></div><blockquote class=3D"gmail_quote" =
style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><di=
v dir=3D"ltr" class=3D"gmail_msg">Hi Bruno,<div class=3D"gmail_msg"><br cla=
ss=3D"gmail_msg"></div><div class=3D"gmail_msg">do you resume from the save=
points with a changed parallelism? Which version of Flink are you running? =
Which Kafka version are you using (+ which Kafka consumer version).</div><d=
iv class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_ms=
g">The partitions should be distributed among all 6 parallel subtasks which=
 means that every subtask should read from 100 partitions. You can check in=
 the logs how many partitions each consumer has been assigned by searching =
for &quot;Got x partitions from these topics&quot; or &quot;Consumer is goi=
ng to read the following topics&quot;. If you don&#39;t see 100 partitions =
assigned to each consumer, then something is clearly going wrong.</div><div=
 class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_msg"=
>Cheers,</div><div class=3D"gmail_msg">Till</div></div><div class=3D"gmail_=
extra gmail_msg"><br class=3D"gmail_msg"><div class=3D"gmail_quote gmail_ms=
g">On Thu, Feb 16, 2017 at 1:42 PM, Bruno Aranda <span dir=3D"ltr" class=3D=
"gmail_msg">&lt;<a href=3D"mailto:baranda@apache.org" class=3D"gmail_msg" t=
arget=3D"_blank">baranda@apache.org</a>&gt;</span> wrote:<br class=3D"gmail=
_msg"><blockquote class=3D"gmail_quote gmail_msg" style=3D"margin:0 0 0 .8e=
x;border-left:1px #ccc solid;padding-left:1ex"><div dir=3D"ltr" class=3D"gm=
ail_msg">Hi,<div class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div cla=
ss=3D"gmail_msg">I am trying to understand this issue in one of my Flink jo=
bs with a Kafka source. At the moment I am using parallelism 6. The operato=
r subtask just read the Kafka records (from a topic with 600 partitions), a=
pplies a keyBy and sends them to the next operator after the hashing.</div>=
<div class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_=
msg">What I can see is that one of the subtasks is sending much more data t=
han the others. The kafka partitions are well-balanced, as in they roughly =
contain the same number of records.</div><div class=3D"gmail_msg"><br class=
=3D"gmail_msg"></div><div class=3D"gmail_msg">I attach a screenshot. One su=
btask has sent 429 MB and the others around 4.88 KB.</div><div class=3D"gma=
il_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_msg">Could this b=
e related that I originally created this stream with just parallelism one a=
nd I increased it later at some point. This is from a performance test suit=
e where I am increasing parallelism between runs to check the performance, =
in a highly available cluster setup with zookeeper and checkpoints in S3.</=
div><div class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div class=3D"gm=
ail_msg">I am not cancelling the job with savepoints.</div><div class=3D"gm=
ail_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_msg">Any ideas o=
r things I can look for?</div><div class=3D"gmail_msg"><br class=3D"gmail_m=
sg"></div><div class=3D"gmail_msg">Thanks!</div><div class=3D"gmail_msg"><b=
r class=3D"gmail_msg"></div><div class=3D"gmail_msg">Bruno</div><div class=
=3D"gmail_msg"><br class=3D"gmail_msg"></div><div class=3D"gmail_msg"><img =
src=3D"cid:15a46ee3c9b79d801e61" alt=3D"Screen Shot 2017-02-16 at 12.36.29.=
png" style=3D"max-width:100%;opacity:1" class=3D"gmail_msg"><br class=3D"gm=
ail_msg"></div><div class=3D"gmail_msg"><br class=3D"gmail_msg"></div><div =
class=3D"gmail_msg"><br class=3D"gmail_msg"></div></div>
</blockquote></div><br class=3D"gmail_msg"></div>
</blockquote></div>

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--001a11451b2c6737240548b6efb9--