Hi Nezih, Can you share JIRA and PR numbers?
This partial de-coupling of data partitioning strategy and spark parallelism would be a useful feature for any data store. Hemant Hemant Bhanawat <https://www.linkedin.com/in/hemant-bhanawat-92a3811> www.snappydata.io On Fri, Apr 1, 2016 at 10:33 PM, Nezih Yigitbasi < nyigitb...@netflix.com.invalid> wrote: > Hey Reynold, > Created an issue (and a PR) for this change to get discussions started. > > Thanks, > Nezih > > On Fri, Feb 26, 2016 at 12:03 AM Reynold Xin <r...@databricks.com> wrote: > >> Using the right email for Nezih >> >> >> On Fri, Feb 26, 2016 at 12:01 AM, Reynold Xin <r...@databricks.com> >> wrote: >> >>> I think this can be useful. >>> >>> The only thing is that we are slowly migrating to the Dataset/DataFrame >>> API, and leave RDD mostly as is as a lower level API. Maybe we should do >>> both? In either case it would be great to discuss the API on a pull >>> request. Cheers. >>> >>> On Wed, Feb 24, 2016 at 2:08 PM, Nezih Yigitbasi < >>> nyigitb...@netflix.com.invalid> wrote: >>> >>>> Hi Spark devs, >>>> >>>> I have sent an email about my problem some time ago where I want to >>>> merge a large number of small files with Spark. Currently I am using Hive >>>> with the CombineHiveInputFormat and I can control the size of the >>>> output files with the max split size parameter (which is used for >>>> coalescing the input splits by the CombineHiveInputFormat). My first >>>> attempt was to use coalesce(), but since coalesce only considers the >>>> target number of partitions the output file sizes were varying wildly. >>>> >>>> What I think can be useful is to have an optional PartitionCoalescer >>>> parameter (a new interface) in the coalesce() method (or maybe we can >>>> add a new method ?) that the callers can implement for custom coalescing >>>> strategies — for my use case I have already implemented a >>>> SizeBasedPartitionCoalescer that coalesces partitions by looking at >>>> their sizes and by using a max split size parameter, similar to the >>>> CombineHiveInputFormat (I also had to expose HadoopRDD to get access >>>> to the individual split sizes etc.). >>>> >>>> What do you guys think about such a change, can it be useful to other >>>> users as well? Or do you think that there is an easier way to accomplish >>>> the same merge logic? If you think it may be useful, I already have an >>>> implementation and I will be happy to work with the community to contribute >>>> it. >>>> >>>> Thanks, >>>> Nezih >>>> >>>> >>> >>> >>
