HiveThriftserver2 itself has no such functionality.
Have you tried adaptive execution in spark?
I have not used this yet though, it seems this experimental feature is to tune
#tasks depending on partition size.

// maropu

On Thu, Aug 4, 2016 at 1:13 AM, Chanh Le <giaosudau@gmail.com> wrote:
I believe there is no way to reduce tasks by Hive using coalesce because when It come to Hive just read the files and depend on number of files you put into. So The way to did was coalesce at the ELT layer put a small number of files as possible reduce IO time for reading file.

> On Aug 3, 2016, at 7:03 PM, Yana Kadiyska <yana.kadiyska@gmail.com> wrote:
> Hi folks, I have an ETL pipeline that drops a file every 1/2 hour. When spark reads these files, I end up with 315K tasks for a dataframe reading a few days worth of data.
> I now with a regular Spark job, I can use coalesce to come to a lower number of tasks. Is there a way to tell HiveThriftserver2 to coalsce? I have a line in hive-conf that says to use CombinedInputFormat but I'm not sure it's working.
> (Obviously haivng fewer large files is better but I don't control the file generation side of this)
> Tips much appreciated

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Takeshi Yamamuro