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From Sanjay Subramanian <>
Subject Re: single output file per partition?
Date Wed, 21 Aug 2013 19:15:58 GMT

I tried file crusher with LZO but it does not work….I have LZO correctly configured in production
and my jobs are running daily using LZO compression.

I like Crusher so I will see why its not working…Thanks to Edward the code is there to tweak
:-)  and test locally


From: Stephen Sprague <<>>
Reply-To: "<>" <<>>
Date: Wednesday, August 21, 2013 12:07 PM
To: "<>" <<>>
Subject: Re: single output file per partition?

I see.  I'll have to punt then.  However, there is an after the fact file crusher Ed Capriolo
wrote a while back here: YMMV

On Wed, Aug 21, 2013 at 11:12 AM, Igor Tatarinov <<>>
Using a single bucket per partition seems to create a single reducer which is too slow.
I've tried enforcing small files merge but that didn't work. I still got multiple output files.

Creating a temp table and then "combining" the multiple files into one using a simple select
* is the only option that seems to work. It's odd that I have to create the temp table but
I don't see a workaround.

On Wed, Aug 21, 2013 at 8:51 AM, Stephen Sprague <<>>
hi igor,
lots of ideas there!  I can't speak for them all but let me confirm first that "cluster by
X into 1 bucket" didn't work?  I would have thought that would have done it.

On Tue, Aug 20, 2013 at 2:29 PM, Igor Tatarinov <<>>
What's the best way to enforce a single output file per partition?

FROM ...

It tried adding CLUSTER BY x,y,z at the end thinking that sorting will force a single reducer
per partition but that didn't work. I still got multiple files per partition.

Do I have to use a single reduce task? With a few TB of data that's probably not a good idea.

My current idea is to create a temp table with the same partitioning structure. Insert into
that table first and then select * from that table into the output table. With combineinputformat=true
that should work right?

Or should I make Hive merge output files instead? (using hive.merge.mapfiles) Will that work
with a partitioned table?


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