IMHO you should ask this to dev email for better response and suggestions On Tue, 12 Apr 2022 at 1:47 am, David Diebold <davidjdieb...@gmail.com> wrote:
> Hello, > > I have a few questions related to bucketing and custom partitioning in > dataframe api. > > I am considering bucketing to perform one-side free shuffle join in > incremental jobs, but there is one thing that I'm not happy with. > Data is likely to grow/skew over time. At some point, i would need to > change amount of buckets which would provoke shuffle. > > Instead of this, I would like to use a custom partitioner, that would > replace shuffle by narrow transformation. > That is something that was feasible with RDD developer api. For example, I > could use such partitioning scheme: > partition_id = (nb_partitions-1) * ( hash(column) - Int.minValue) / > (Int.maxValue - Int.minValue) > When I multiply amount of partitions by 2 each new partition depends only > on one partition from parent (=> narrow transformation) > > So, here are my questions : > > 1/ Is it possible to use custom partitioner when saving a dataframe with > bucketing ? > 2/ Still with the API dataframe, is it possible to apply custom > partitioner to a dataframe ? > Is it possible to repartition the dataframe with a narrow > transformation like what could be done with RDD ? > Is there some sort of dataframe developer API ? Do you have any > pointers on this ? > > Thanks ! > > David > -- Best Regards, Ayan Guha
