Great stuff. Wonderful to see such progress in so short a time.

How about some links to code and instructions so that these benchmarks can
be reproduced?

Regards,
- Steve

From:  Debasish Das <debasish.da...@gmail.com>
Date:  Friday, October 10, 2014 at 8:17
To:  Matei Zaharia <matei.zaha...@gmail.com>
Cc:  user <user@spark.apache.org>, dev <d...@spark.apache.org>
Subject:  Re: Breaking the previous large-scale sort record with Spark

> Awesome news Matei !
> 
> Congratulations to the databricks team and all the community members...
> 
> On Fri, Oct 10, 2014 at 7:54 AM, Matei Zaharia <matei.zaha...@gmail.com>
> wrote:
>> Hi folks,
>> 
>> I interrupt your regularly scheduled user / dev list to bring you some pretty
>> cool news for the project, which is that we've been able to use Spark to
>> break MapReduce's 100 TB and 1 PB sort records, sorting data 3x faster on 10x
>> fewer nodes. There's a detailed writeup at
>> http://databricks.com/blog/2014/10/10/spark-breaks-previous-large-scale-sort-
>> record.html. Summary: while Hadoop MapReduce held last year's 100 TB world
>> record by sorting 100 TB in 72 minutes on 2100 nodes, we sorted it in 23
>> minutes on 206 nodes; and we also scaled up to sort 1 PB in 234 minutes.
>> 
>> I want to thank Reynold Xin for leading this effort over the past few weeks,
>> along with Parviz Deyhim, Xiangrui Meng, Aaron Davidson and Ali Ghodsi. In
>> addition, we'd really like to thank Amazon's EC2 team for providing the
>> machines to make this possible. Finally, this result would of course not be
>> possible without the many many other contributions, testing and feature
>> requests from throughout the community.
>> 
>> For an engine to scale from these multi-hour petabyte batch jobs down to
>> 100-millisecond streaming and interactive queries is quite uncommon, and it's
>> thanks to all of you folks that we are able to make this happen.
>> 
>> Matei
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> 



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