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From Vijay Srinivasaraghavan <vijikar...@yahoo.com>
Subject Re: Checkpoint
Date Thu, 10 Mar 2016 18:44:51 GMT
 Thanks Ufuk and Stephan.
I have added Identity mapper and disabled chaining. With that, I am able to see the backpressue
alert on the identify mapper task.
I have noticed one thing that when I introduced delay (sleep) on the subsequent task, sometimes
checkpoint is not working. I could see checkpoint trigger but the files are not moved from
"pending" state. I will try to reproduce to find the pattern but are you aware of any such

    On Thursday, March 10, 2016 2:51 AM, Stephan Ewen <sewen@apache.org> wrote:

 Just to be sure: Is the task whose backpressure you want to monitor the Kafka Source?
There is an open issue that backpressure monitoring does not work for the Kafka Source: https://issues.apache.org/jira/browse/FLINK-3456
To circumvent that, add an "IdentityMapper" after the Kafka source, make sure it is non-chained,
and monitor the backpressure on that MapFunction.

On Thu, Mar 10, 2016 at 11:23 AM, Robert Metzger <rmetzger@apache.org> wrote:

Hi Vijay,

regarding your other questions:

1) On the TaskManagers, the FlinkKafkaConsumers will write the partitions they are going to
read in the log. There is currently no way of seeing the state of a checkpoint in Flink (which
is the offsets).
However, once a checkpoint is completed, the Kafka consumer is committing the offset to the
Kafka broker. (I could not find tool to get the committed offsets from the broker, but its
either stored in ZK or in a special topic by the broker. In Kafka 0.8 that's easily doable
with the kafka.tools.ConsumerOffsetChecker)

2) Do you see duplicate data written by the rolling file sink? Or do you see it somewhere
else?HDP 2.4 is using Hadoop 2.7.1 so the truncate() of invalid data should actually work

On Thu, Mar 10, 2016 at 10:44 AM, Ufuk Celebi <uce@apache.org> wrote:

How many vertices does the web interface show and what parallelism are
you running? If the sleeping operator is chained you will not see

If your goal is to just see some back pressure warning, you can call
env.disableOperatorChaining() and re-run the program. Does this work?

– Ufuk

On Thu, Mar 10, 2016 at 1:35 AM, Vijay Srinivasaraghavan
<vijikarthi@yahoo.com> wrote:
> Hi Ufuk,
> I have increased the sampling size to 1000 and decreased the refresh
> interval by half. In my Kafka topic I have pumped million messages which is
> read by KafkaConsumer pipeline and then pass it to a transofmation step
> where I have introduced sleep (3 sec) for every single message received and
> the final step is HDFS sink using RollingSinc API.
> jobmanager.web.backpressure.num-samples: 1000
> jobmanager.web.backpressure.refresh-interval: 30000
> I was hoping to see the backpressure tab from UI to display some warning but
> I still see "OK" message.
> This makes me wonder if I am testing the backpressure scenario properly or
> not?
> Regards
> Vijay
> On Monday, March 7, 2016 3:19 PM, Ufuk Celebi <uce@apache.org> wrote:
> Hey Vijay!
> On Mon, Mar 7, 2016 at 8:42 PM, Vijay Srinivasaraghavan
> <vijikarthi@yahoo.com> wrote:
>> 3) How can I simulate and verify backpressure? I have introduced some
>> delay
>> (Thread Sleep) in the job before the sink but the "backpressure" tab from
>> UI
>> does not show any indication of whether backpressure is working or not.
> If a task is slow, it is back pressuring upstream tasks, e.g. if your
> transformations have the sleep, the sources should be back pressured.
> It can happen that even with the sleep the tasks still produce their
> data as fast as they can and hence no back pressure is indicated in
> the web interface. You can increase the sleep to check this.
> The mechanism used to determine back pressure is based on sampling the
> stack traces of running tasks. You can increase the number of samples
> and/or decrease the delay between samples via config parameters shown
> in [1]. It can happen that the samples miss the back pressure
> indicators, but usually the defaults work fine.
> [1]
> https://ci.apache.org/projects/flink/flink-docs-master/setup/config.html#jobmanager-web-frontend

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