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From Shivaram Venkataraman <shiva...@eecs.berkeley.edu>
Subject Re: CPU/Disk/network performance instrumentation
Date Wed, 09 Jul 2014 21:17:51 GMT
I think it would be very useful to have this. We could put the ui display
either behind a flag or a url parameter

Shivaram


On Wed, Jul 9, 2014 at 12:25 PM, Reynold Xin <rxin@databricks.com> wrote:

> Maybe it's time to create an advanced mode in the ui.
>
>
> On Wed, Jul 9, 2014 at 12:23 PM, Kay Ousterhout <keo@eecs.berkeley.edu>
> wrote:
>
> > Hi all,
> >
> > I've been doing a bunch of performance measurement of Spark and, as part
> of
> > doing this, added metrics that record the average CPU utilization, disk
> > throughput and utilization for each block device, and network throughput
> > while each task is running.  These metrics are collected by reading the
> > /proc filesystem so work only on Linux.  I'm happy to submit a pull
> request
> > with the appropriate changes but first wanted to see if sufficiently many
> > people think this would be useful.  I know the metrics reported by Spark
> > (and in the UI) are already overwhelming to some folks so don't want to
> add
> > more instrumentation if it's not widely useful.
> >
> > These metrics are slightly more difficult to interpret for Spark than
> > similar metrics reported by Hadoop because, with Spark, multiple tasks
> run
> > in the same JVM and therefore as part of the same process.  This means
> > that, for example, the CPU utilization metrics reflect the CPU use across
> > all tasks in the JVM, rather than only the CPU time used by the
> particular
> > task.  This is a pro and a con -- it makes it harder to determine why
> > utilization is high (it may be from a different task) but it also makes
> the
> > metrics useful for diagnosing straggler problems.  Just wanted to clarify
> > this before asking folks to weigh in on whether the added metrics would
> be
> > useful.
> >
> > -Kay
> >
> > (if you're curious, the instrumentation code is on a very messy branch
> > here:
> >
> >
> https://github.com/kayousterhout/spark-1/tree/proc_logging_perf_minimal_temp/core/src/main/scala/org/apache/spark/performance_logging
> > )
> >
>

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