any views on the problem
From: saurabhmishra.i...@outlook.com
To: user@hive.apache.org; navis....@nexr.com
Subject: RE: Hive Query Unable to distribute load evenly in reducers
Date: Tue, 16 Oct 2012 11:23:29 +0530
by using mapjoin if you are implying setting
set hive.auto.convert.join=true;
then this configuration i am already using, but to no avail...:(
Date: Tue, 16 Oct 2012 14:17:47 +0900
Subject: Re: Hive Query Unable to distribute load evenly in reducers
From: navis....@nexr.com
To: user@hive.apache.org
How about using MapJoin?
2012/10/16 Saurabh Mishra <saurabhmishra.i...@outlook.com>
no there is apparently no heavy skewing. also another stats i wanted to point
was, following is approximate table contents in this 4 table join query :
tableA : 170 million (actual number, + i am also exploding these records, so
the number could be much much higher)
tableB:15
tableC:45
tableD:45
tableE : 45
tableF : 14000
Also i cannot put any filter condition on tableA ,situation does not permit so.
:(
Kindly suggest, some alternative solution or some hive configuration to better
load distribute in the reducers
> Date: Mon, 15 Oct 2012 16:29:56 +0100
> Subject: Re: Hive Query Unable to distribute load evenly in reducers
> From: philip.j.trom...@gmail.com
> To: user@hive.apache.org
>
> Is your data heavily skewed towards certain values of a.x etc?
>
> On 15 October 2012 15:23, Saurabh Mishra <saurabhmishra.i...@outlook.com>
> wrote:
> > The queries are simple joins, something on the lines of
> > select a, b, c, count(D) from tableA join tableB on a.x=b.y join.... group
> > by a, b,c;
> >
> >
> >> From: liy...@gmail.com
> >> Date: Mon, 15 Oct 2012 21:10:39 +0800
> >> Subject: Re: Hive Query Unable to distribute load evenly in reducers
> >> To: user@hive.apache.org
> >
> >>
> >> And your queries were?
> >>
> >> On Mon, Oct 15, 2012 at 8:09 PM, Saurabh Mishra
> >> <saurabhmishra.i...@outlook.com> wrote:
> >> > Hi,
> >> > I am firing some hive queries joining tables containing upto 30millions
> >> > records each. Since the load on the reducers is very significant in
> >> > these
> >> > cases, i specifically set the following parameters before executing the
> >> > queries :
> >> >
> >> > set mapred.reduce.tasks=100;
> >> > set hive.exec.reducers.bytes.per.reducer=500000000;
> >> > set hive.optimize.cp=true;
> >> >
> >> > The number of reducer the job spouts in now 160, but despite the high
> >> > number
> >> > most of the load remains upon 1 or 2 reducers. Hence in the final
> >> > statistics, 158 reducers go completed with 2-3 minutes of start and 2
> >> > reducers took 2 hrs to run.
> >> > Is there any way to overcome this load distribution disparity.
> >> > Any help in this regards will be highly appreciated.
> >> >
> >> > Sincerely
> >> > Saurabh Mishra
