Maybe it's time to create an advanced mode in the ui.
On Wed, Jul 9, 2014 at 12:23 PM, Kay Ousterhout <k...@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 > ) >
