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From Andrew Melo <>
Subject Re: Feature request: split dataset based on condition
Date Mon, 04 Feb 2019 17:16:26 GMT
Hello Ryan,

On Mon, Feb 4, 2019 at 10:52 AM Ryan Blue <> wrote:
> Andrew, can you give us more information about why partitioning the output data doesn't
work for your use case?
> It sounds like all you need to do is to create a table partitioned by A and B, then you
would automatically get the divisions you want. If what you're looking for is a way to scale
the number of combinations then you can use formats that support more partitions, or you could
sort by the fields and rely on Parquet row group pruning to filter out data you don't want.

TBH, I don't understand what that would look like in pyspark and what
the consequences would be. Looking at the docs, it doesn't appear to
be the syntax for partitioning on a condition (most of our conditions
are of the form 'X > 30'). The use of Spark is still somewhat new in
our field, so it's possible we're not using it correctly.


> rb
> On Mon, Feb 4, 2019 at 8:33 AM Andrew Melo <> wrote:
>> Hello
>> On Sat, Feb 2, 2019 at 12:19 AM Moein Hosseini <> wrote:
>> >
>> > I've seen many application need to split dataset to multiple datasets based
on some conditions. As there is no method to do it in one place, developers use filter method
multiple times. I think it can be useful to have method to split dataset based on condition
in one iteration, something like partition method of scala (of-course scala partition just
split list into two list, but something more general can be more useful).
>> > If you think it can be helpful, I can create Jira issue and work on it to send
>> This would be a really useful feature for our use case (processing
>> collision data from the LHC). We typically want to take some sort of
>> input and split into multiple disjoint outputs based on some
>> conditions. E.g. if we have two conditions A and B, we'll end up with
>> 4 outputs (AB, !AB, A!B, !A!B). As we add more conditions, the
>> combinatorics explode like n^2, when we could produce them all up
>> front with this "multi filter" (or however it would be called).
>> Cheers
>> Andrew
>> >
>> > Best Regards
>> > Moein
>> >
>> > --
>> >
>> > Moein Hosseini
>> > Data Engineer
>> > mobile: +98 912 468 1859
>> > site:
>> > email:
>> >
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> --
> Ryan Blue
> Software Engineer
> Netflix

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