Hi Roman

I am just doing write operations from the flat map. Does it matter If I use
a flap map or sink for this purpose?

Thank you

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On Thu, Apr 29, 2021 at 9:10 PM Roman Khachatryan <ro...@apache.org> wrote:

> Flink uses checkpoint barriers that are sent through along the same
> channels as data. Events are included into the checkpoint if they precede
> the corresponding barrier (or the RPC call for sources). [1] is the
> algorithm description and [2] is about integration with Kafka.
>
> > In my example, I have only 1 Source and 1 Flat Map. Do you mean to say
> that we need to use a sink instead of a flat map?
> I'm not sure I understand the use case. What do you do with the results of
> Flat Map?
>
> [1 https://arxiv.org/pdf/1506.08603.pdf
> [2]
> https://flink.apache.org/features/2018/03/01/end-to-end-exactly-once-apache-flink.html
>
> Regards,
> Roman
>
>
> On Thu, Apr 29, 2021 at 3:16 PM Raghavendar T S <raghav280...@gmail.com>
> wrote:
>
>> Hi Roman
>>
>> In general, how Flink tracks the events from source to downstream
>> operators? We usually emit existing events from an operator or create a new
>> instance of a class and emit it. How does Flink or Flink source know
>> whether the events are which snapshot?
>>
>> > So you don't need to re-process it manually (given that the sink
>> provides exactly once guarantee).
>> In my example, I have only 1 Source and 1 Flat Map. Do you mean to say
>> that we need to use a sink instead of a flat map?
>>
>> Thank you
>>
>>
>>
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>>
>> On Thu, Apr 29, 2021 at 6:13 PM Roman Khachatryan <ro...@apache.org>
>> wrote:
>>
>>> Hi Raghavendar,
>>>
>>> In Flink, checkpoints are global, meaning that a checkpoint is
>>> successful only if all operators acknowledge it. So the offset will be
>>> stored in state and then committed to Kafka [1] only after all the tasks
>>> acknowledge that checkpoint. At that moment, the element must be either
>>> emitted to the external system, stored in the operator state (e.g. window);
>>> or in channel state (with Unaligned checkpoints).
>>>
>>> So you don't need to re-process it manually (given that the sink
>>> provides exactly once guarantee).
>>>
>>> [1]
>>> https://ci.apache.org/projects/flink/flink-docs-stable/dev/connectors/kafka.html#kafka-consumers-offset-committing-behaviour-configuration
>>>
>>> Regards,
>>> Roman
>>>
>>>
>>> On Thu, Apr 29, 2021 at 12:53 PM Raghavendar T S <raghav280...@gmail.com>
>>> wrote:
>>>
>>>> Hi Team
>>>>
>>>> Assume that we have a job (Checkpoint enabled) with Kafka source and a
>>>> stateless operator which consumes events from Kafka source.
>>>> We have a stream of records 1, 2, 3, 4, 5,...Let's say the event 1
>>>> reaches the Flat Map operator and is being processed. Then the Kafka source
>>>> has made a successful checkpoint.
>>>> In this case, does the offset of event 1 will be part of the
>>>> checkpoint? Will Flink track the event from source to all downstream
>>>> operators? If this is a true case and If the processing of the event is
>>>> failed (any third party API/DB failure) in the Flat Map after a successful
>>>> checkpoint, do we need to manually re-process (retry using queue or any
>>>> other business logic) the event?
>>>>
>>>> Job:
>>>> Kafka Source -> Flat Map
>>>>
>>>> Thank you
>>>>
>>>> --
>>>> Raghavendar T S
>>>> www.teknosrc.com
>>>>
>>>>
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>>>>
>>>
>>
>> --
>> Raghavendar T S
>> www.teknosrc.com
>>
>

-- 
Raghavendar T S
www.teknosrc.com

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