Hi Matei - I read your post with great interest. Could you possibly comment in more depth on some of the issues you guys saw when scaling up spark and how you resolved them? I am interested specifically in spark-related problems. I'm working on scaling up spark to very large datasets and have been running into a variety of issues. Thanks in advance! On Oct 10, 2014 10:54 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 > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >