Hi Till,
Thank you very much for looking into it! According to our investigation,
this is indeed a Kinesis issue. Flink (FlinkKinesisProducer) uses
KPL(Kinesis Producer Library), but hasn't tune it up yet. I have identified
a bunch of issues, opened the following Flink tickets, and are working on
them.
- [FLINK-7367][kinesis connector] Parameterize more configs for
FlinkKinesisProducer (RecordMaxBufferedTime, MaxConnections,
RequestTimeout, etc)
- [FLINK-7366][kinesis connector] Upgrade kinesis producer library in
flink-connector-kinesis
- [FLINK-7508] switch FlinkKinesisProducer to use KPL's ThreadingMode to
ThreadedPool mode rather than Per_Request mode
I do have a question for Flink performance. We are using a 1-day sized
sliding window with 1-hour slide to count some features of items based on
event time. We have about 20million items. We observed that Flink only emit
results on a fixed time in an hour (e.g. 1am, 2am, 3am, or 1:15am, 2:15am,
3:15am with a 15min offset). That's means 20million windows/records are
generated at the same time every hour, which burns down
FlinkKinesisProducer and the underlying KPL, but nothing is generated in
the rest of that hour. The pattern is like this:
load
|
| /\ /\
| / \ / \
|_/_ \_______/__\_
time
Is there any way to even out the number of generated windows/records in an
hour? Can we have evenly distributed generated load like this?
load
|
|
| ------------------------
|_______________
time
Thanks,
Bowen
On Tue, Aug 22, 2017 at 2:56 AM, Till Rohrmann <trohrm...@apache.org> wrote:
> Hi Bowen,
>
> sorry for my late answer. I dug through some of the logs and it seems that
> you have the following problem:
>
> 1.
>
> Once in a while the Kinesis producer fails with a
> UserRecordFailedException saying “Expired while waiting in HttpClient queue
> Record has reached expiration”. This seems to be a problem on the Kinesis
> side. This will trigger the task failure and the cancellation of all other
> tasks as well.
> 2.
>
> Somehow Flink does not manage to cancel all tasks within a period of
> 180 seconds. This value is configurable via task.cancellation.timeout
> (unit ms) via the Flink configuration. It looks a bit like you have a lot
> of logging going on, because the the code is waiting for example on
> Category.java:204 and other log4j methods. This could, however also cover
> the true issue. What you could do is to try out a different logging backend
> such as logback [1], for example.
> 3.
>
> The failing cancellation is a fatal error which leads to the
> termination of the TaskManager. This will be notified by the
> YarnResourceManager and it will restart the container. This goes on until
> it reaches the number of maximum failed containers. This value can be
> configured via yarn.maximum-failed-containers. Per default it is the
> number of initial containers you requested. If you set this value to -1,
> then it will never fail and always restart failed containers. Once the
> maximum is reached, Flink terminates the Yarn application.
>
> [1] https://ci.apache.org/projects/flink/flink-docs-release-1.3/dev/best_
> practices.html#using-logback-instead-of-log4j
>
> In order to further debug the problem, which version of Flink are you
> using and maybe you could provide us with the debug log level logs of the
> TaskManagers.
>
> Cheers,
> Till
>
>
> On Fri, Aug 11, 2017 at 5:37 AM, Bowen Li <bowen...@offerupnow.com> wrote:
>
>> Hi Till,
>> Any idea why it happened? I've tried different configurations for
>> configuring our Flink cluster, but the cluster always fails after 4 or 5
>> hours.
>>
>> According to the log, looks like the total number of slots becomes 0
>> at the end, and YarnClusterClient shuts down application master as a
>> result. Why the slots are not released? Or are they actually crushed and
>> thus no longer available?
>>
>> I'm trying to deploy the first Flink cluster within out company. And this
>> issue is slowing us down from proving that Flink actually works for us.
>> We'd appreciate your help on it!
>>
>> Thanks,
>> Bowen
>>
>> On Wed, Aug 9, 2017 at 1:33 PM, Bowen Li <bowen...@offerupnow.com> wrote:
>>
>>> Hi Till,
>>> Thanks for taking this issue.
>>>
>>> We are not comfortable sending logs to a email list which is this
>>> open. I'll send logs to you.
>>>
>>> Thanks,
>>> Bowen
>>>
>>>
>>> On Wed, Aug 9, 2017 at 2:46 AM, Till Rohrmann <trohrm...@apache.org>
>>> wrote:
>>>
>>>> Hi Bowen,
>>>>
>>>> if I'm not mistaken, then Flink's current Yarn implementation does not
>>>> actively releases containers. The `YarnFlinkResourceManager` is started
>>>> with a fixed number of containers it always tries to acquire. If a
>>>> container should die, then it will request a new one.
>>>>
>>>> In case of a failure all slots should be freed and then they should be
>>>> subject to rescheduling the new tasks. Thus, it is not necessarily the case
>>>> that 12 new slots will be used unless the old slots are no longer available
>>>> (failure of a TM). Therefore, it sounds like a bug what you are describing.
>>>> Could you share the logs with us?
>>>>
>>>> Cheers,
>>>> Till
>>>>
>>>> On Wed, Aug 9, 2017 at 9:32 AM, Bowen Li <bowen...@offerupnow.com>
>>>> wrote:
>>>>
>>>>> Hi guys,
>>>>> I was running a Flink job (12 parallelism) on an EMR cluster with
>>>>> 48 YARN slots. When the job starts, I can see from Flink UI that the job
>>>>> took 12 slots, and 36 slots were left available.
>>>>>
>>>>> I would expect that when the job fails, it would restart from
>>>>> checkpointing by taking another 12 slots and freeing the original 12
>>>>> slots. *Well,
>>>>> I observed that the job took new slots but never free original slots. The
>>>>> Flink job ended up killed by YARN because there's no available slots
>>>>> anymore.*
>>>>>
>>>>> Here's the command I ran Flink job:
>>>>>
>>>>> ```
>>>>> flink run -m yarn-cluster -yn 6 -ys 8 -ytm 40000 xxx.jar
>>>>> ```
>>>>>
>>>>> Does anyone know what's going wrong?
>>>>>
>>>>> Thanks,
>>>>> Bowen
>>>>>
>>>>
>>>>
>>>
>>
>
