I see. Hopefully someone with more familiarity with Spark runner will chime
in.

On Fri, Sep 7, 2018 at 1:41 PM Vishwas Bm <[email protected]> wrote:

> Hi,
>
> In our use case the watermark is the processing time.
>
> As per beam capability matrix (
> https://beam.apache.org/documentation/runners/capability-matrix/)
> lateness is not supported by spark runner.  But as per the output in our
> use case we are able to see late data getting emitted.
>
> So we wanted to know whether spark runner supports allowed lateness or
> not.
>
>
> Regards,
> Vishwas
>
>
> On Fri, Sep 7, 2018, 10:09 PM Raghu Angadi <[email protected]> wrote:
>
>> Lateness depends on watermark. How did you configure your KafkaIO reader?
>> Did you set custom timestamp function? By default watermark in KafkaIO is
>> set to same as processing time, in which case, your watermark could be
>> close to 13-38-37 (processing time).  Note that this is in general true
>> across all the runners, though I am not aware of any subtle differences in
>> Spark runner.
>>
>> On Fri, Sep 7, 2018 at 7:03 AM rahul patwari <[email protected]>
>> wrote:
>>
>>> Hi,
>>>
>>> We are running a Beam program on Spark. We are using 2.5.0 Beam and
>>> SparkRunner versions. We are seeing Late data in the output emitted by
>>> Spark. As per the capability Matrix, Lateness is not supported in Spark. Is
>>> it supported now? or Are we missing something?
>>>
>>> Steps:
>>>  Read from Kafka, Apply a Fixed Window of 1 Min with Lateness as 2 Min
>>> with Late firings when an element is found with Accumulating Fired Panes,
>>> GroupByKey, ParDo to display the result.
>>>
>>> Below is the output of the ParDo in which we are printing the GroupByKey
>>> result:
>>> Pane Timing                : LATE
>>> Processing Time         : 2018-09-07----13-38-37-7290----+0000
>>> Element Time              : 2018-09-07----13-36-59-9990----+0000
>>> Window Start Time      : 2018-09-07----13-36-00-0000----+0000
>>> Window End Time       : 2018-09-07----13-37-00-0000----+0000
>>> Pane Index                  : 1
>>> Pane NonSpeculativeIndex : 1
>>>
>>> Regards,
>>> Rahul
>>>
>>

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