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From Peter Marron <Peter.Mar...@trilliumsoftware.com>
Subject RE: Partition performance
Date Tue, 02 Jul 2013 09:34:39 GMT
Hi Owen,

I’m curious about this advice about partitioning. Is there some fundamental reason why Hive
is slow when the number of partitions is 10,000 rather than 1,000? And the improvements
that you mention are they going to be in version 12? Is there a JIRA raised so that I can
track them?
(It’s not currently a problem for me but I can see that I am going to need to be able to
explain the situation.)

Warm regards,

Z

From: Owen O'Malley [mailto:omalley@apache.org]
Sent: 05 April 2013 00:26
To: user@hive.apache.org
Subject: Re: Partition performance

See slide #9 from my Optimizing Hive Queries talk http://www.slideshare.net/oom65/optimize-hivequeriespptx
. Certainly, we will improve it, but for now you are much better off with 1,000 partitions
than 10,000.

-- Owen

On Thu, Apr 4, 2013 at 4:21 PM, Ramki Palle <ramki.palle@gmail.com<mailto:ramki.palle@gmail.com>>
wrote:
Is it possible for you to send the explain plan of these two queries?
Regards,
Ramki.

On Thu, Apr 4, 2013 at 4:06 PM, Sanjay Subramanian <Sanjay.Subramanian@wizecommerce.com<mailto:Sanjay.Subramanian@wizecommerce.com>>
wrote:
The slow down is most possibly due to large number of partitions.
I believe the Hive book authors tell us to be cautious with large number of partitions :-)
 and I abide by that.

Users
Please add your points of view and experiences

Thanks
sanjay

From: Ian <liuhy0@yahoo.com<mailto:liuhy0@yahoo.com>>
Reply-To: "user@hive.apache.org<mailto:user@hive.apache.org>" <user@hive.apache.org<mailto:user@hive.apache.org>>,
Ian <liuhy0@yahoo.com<mailto:liuhy0@yahoo.com>>
Date: Thursday, April 4, 2013 4:01 PM
To: "user@hive.apache.org<mailto:user@hive.apache.org>" <user@hive.apache.org<mailto:user@hive.apache.org>>
Subject: Partition performance

Hi,

I created 3 years of hourly log files (totally 26280 files), and use External Table with partition
to query. I tried two partition methods.

1). Log files are stored as /test1/2013/04/02/16/000000_0 (A directory per hour). Use date
and hour as partition keys. Add 3 years of directories to the table partitions. So there are
26280 partitions.
        CREATE EXTERNAL TABLE test1 (logline string) PARTITIONED BY (dt string, hr int);
        ALTER TABLE test1 ADD PARTITION (dt='2013-04-02', hr=16) LOCATION '/test1/2013/04/02/16';

2). Log files are stored as /test2/2013/04/02/16_000000_0 (A directory per day, 24 files in
each directory). Use date as partition key. Add 3 years of directories to the table partitions.
So there are 1095 partitions.
        CREATE EXTERNAL TABLE test2 (logline string) PARTITIONED BY (dt string);
        ALTER TABLE test2 ADD PARTITION (dt='2013-04-02') LOCATION '/test2/2013/04/02';

When doing a simple query like
    SELECT * FROM  test1/test2  WHERE  dt >= '2013-02-01' and dt <= '2013-02-14'
Using approach #1 takes 320 seconds, but #2 only takes 70 seconds.

I'm wondering why there is a big performance difference between these two? These two approaches
have the same number of files, only the directory structure is different. So Hive is going
to load the same amount of files. Why does the number of partitions have such big impact?
Does that mean #2 is a better partition strategy?

Thanks.



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