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From Vinod Kumar Vavilapalli <vino...@hortonworks.com>
Subject Re: hadoop1.2.1 speedup model
Date Sat, 07 Sep 2013 07:38:05 GMT

Clearly your input size isn't changing. And depending on how they are distributed on the nodes,
there could be Datanode/disks contention.

The better way to model this is by scaling the input data also linearly. More nodes should
process more data in the same amount of time.

Thanks,
+Vinod

On Sep 6, 2013, at 8:27 AM, 牛兆捷 wrote:

> Hi all:
> 
> I vary the computational nodes of cluster and get the speedup result in attachment.
> 
> In my mind, there are three type of speedup model: linear, sub-linear and super-linear.
However the curve of my result seems a little strange. I have attached it.
> <speedup.png>
> 
> This is sort in example.jar, actually it is done only using the default map-reduce mechanism
of Hadoop.
> 
> I use hadoop-1.2.1, set 8 map slots and 8 reduce slots per node(12 cpu, 20g men)
>  io.sort.mb = 512, block size = 512mb, heap size = 1024mb,  reduce.slowstart = 0.05,
the others are default.
> 
> Input data: 20g, I divide it to 64 files
> 
> Sort example: 64 map tasks, 64 reduce tasks
> 
> Computational nodes: varying from 2 to 9
> 
> Why the speedup mechanism is like this? How can I model it properly?
> 
> Thanks~
> 
> -- 
> Sincerely,
> Zhaojie
> 


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