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From JOAQUIN GUANTER GONZALBEZ <joaquin.guantergonzal...@telefonica.com>
Subject RE: Partitions at DataSource API V2
Date Wed, 13 Mar 2019 08:32:57 GMT
I'd like to bump this. I agree with Carlos that there is very little information at the DataSoruceWrite/DataSourceReader
level. To me, ideally, the DataSourceWriter/Reader should have as much information as possible.
Not only the number of partitions, but also ideally the whole execution plan.

This would not only enable things like automatic creation of kafka topics with the correct
number of partitions (like Carlos mentioned), but it would also allow advanced DataSources
that, for example, analyze the execution plan to choose the correct parameters to implement
differential privacy.

CC'ing in Ryan, since he is leading the DataSourceV2 workgroup (sorry I can't joint the sync
meetings, but I'm in CET time and the time logictics of that meeting don't work for Europe).

Ryan, do you think it would be a good idea to provide extra information at the DataSourceWriter/Reader
level to enable more advanced datasources? Would a PR contribution with these changed be a
welcome addition?

Thanks,
Ximo

-----Mensaje original-----
De: CARLOS DEL PRADO MOTA <carlos.delpradomota@telefonica.com>
Enviado el: jueves, 7 de marzo de 2019 10:19
Para: dev@spark.apache.org
Asunto: Partitions at DataSource API V2

Hello, I’m Carlos del Prado, developer at Telefonica.

We are working with Spark's DataSource API V2 building a custom Kafka connector that creates
the topic upon write. In order to do that, we need to know the number of partitions before
writing data in each partition, at the DataSourceWriter level.

Is there any way for us do that?

King regards,
Carlos.

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