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From Hemant Bhanawat <hemant9...@gmail.com>
Subject Re: how about a custom coalesce() policy?
Date Sun, 03 Apr 2016 05:39:00 GMT
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 <
nyigitbasi@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 <rxin@databricks.com> wrote:
>
>> Using the right email for Nezih
>>
>>
>> On Fri, Feb 26, 2016 at 12:01 AM, Reynold Xin <rxin@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 <
>>> nyigitbasi@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
>>>> ​
>>>>
>>>
>>>
>>

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