If you use DStream.saveAsHadoopFiles (or equivalent RDD ops) with the
appropriate output format (for Avro) then each partition of the RDDs will
be written to a different file. However there is probably going to be a
large number of small files and you may have to run a separate compaction
phase to coalesce them into larger files.
On Mar 12, 2015 9:47 AM, "Maiti, Samya" <samya.ma...@philips.com> wrote:

>  Hi TD,
>
>  I want to append my record to a AVRO file which will be later used for
> querying.
>
>  Having a single file is not mandatory for us but then how can we make
> the executors append the AVRO data to multiple files.
>
>  Thanks,
> Sam
>  On Mar 12, 2015, at 4:09 AM, Tathagata Das <t...@databricks.com> wrote:
>
>  Why do you have to write a single file?
>
>
>
> On Wed, Mar 11, 2015 at 1:00 PM, SamyaMaiti <samya.maiti2...@gmail.com>
> wrote:
>
>> Hi Experts,
>>
>> I have a scenario, where in I want to write to a avro file from a
>> streaming
>> job that reads data from kafka.
>>
>> But the issue is, as there are multiple executors and when all try to
>> write
>> to a given file I get a concurrent exception.
>>
>> I way to mitigate the issue is to repartition & have a single writer task,
>> but as my data is huge that is not a feasible option.
>>
>> Any suggestions welcomed.
>>
>> Regards,
>> Sam
>>
>>
>>
>> --
>> View this message in context:
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>>
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>
>
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