It can be far more than that (e.g. https://issues.apache.org/jira/browse/SPARK-11838), and is generally either unrecognized or a greatly under-appreciated and underused feature of Spark.
On Sun, Jan 17, 2016 at 12:20 PM, Koert Kuipers <ko...@tresata.com> wrote: > the re-use of shuffle files is always a nice surprise to me > > On Sun, Jan 17, 2016 at 3:17 PM, Mark Hamstra <m...@clearstorydata.com> > wrote: > >> Same SparkContext means same pool of Workers. It's up to the Scheduler, >> not the SparkContext, whether the exact same Workers or Executors will be >> used to calculate simultaneous actions against the same RDD. It is likely >> that many of the same Workers and Executors will be used as the Scheduler >> tries to preserve data locality, but that is not guaranteed. In fact, what >> is most likely to happen is that the shared Stages and Tasks being >> calculated for the simultaneous actions will not actually be run at exactly >> the same time, which means that shuffle files produced for one action will >> be reused by the other(s), and repeated calculations will be avoided even >> without explicitly caching/persisting the RDD. >> >> On Sun, Jan 17, 2016 at 8:06 AM, Koert Kuipers <ko...@tresata.com> wrote: >> >>> Same rdd means same sparkcontext means same workers >>> >>> Cache/persist the rdd to avoid repeated jobs >>> On Jan 17, 2016 5:21 AM, "Mennour Rostom" <mennou...@gmail.com> wrote: >>> >>>> Hi, >>>> >>>> Thank you all for your answers, >>>> >>>> If I correctly understand, actions (in my case foreach) can be run >>>> concurrently and simultaneously on the SAME rdd, (which is logical because >>>> they are read only object). however, I want to know if the same workers are >>>> used for the concurrent analysis ? >>>> >>>> Thank you >>>> >>>> 2016-01-15 21:11 GMT+01:00 Jakob Odersky <joder...@gmail.com>: >>>> >>>>> I stand corrected. How considerable are the benefits though? Will the >>>>> scheduler be able to dispatch jobs from both actions simultaneously (or on >>>>> a when-workers-become-available basis)? >>>>> >>>>> On 15 January 2016 at 11:44, Koert Kuipers <ko...@tresata.com> wrote: >>>>> >>>>>> we run multiple actions on the same (cached) rdd all the time, i >>>>>> guess in different threads indeed (its in akka) >>>>>> >>>>>> On Fri, Jan 15, 2016 at 2:40 PM, Matei Zaharia < >>>>>> matei.zaha...@gmail.com> wrote: >>>>>> >>>>>>> RDDs actually are thread-safe, and quite a few applications use them >>>>>>> this way, e.g. the JDBC server. >>>>>>> >>>>>>> Matei >>>>>>> >>>>>>> On Jan 15, 2016, at 2:10 PM, Jakob Odersky <joder...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>> I don't think RDDs are threadsafe. >>>>>>> More fundamentally however, why would you want to run RDD actions in >>>>>>> parallel? The idea behind RDDs is to provide you with an abstraction for >>>>>>> computing parallel operations on distributed data. Even if you were to >>>>>>> call >>>>>>> actions from several threads at once, the individual executors of your >>>>>>> spark environment would still have to perform operations sequentially. >>>>>>> >>>>>>> As an alternative, I would suggest to restructure your RDD >>>>>>> transformations to compute the required results in one single operation. >>>>>>> >>>>>>> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Threads >>>>>>>> >>>>>>>> >>>>>>>> El viernes, 15 de enero de 2016, Kira <mennou...@gmail.com> >>>>>>>> escribió: >>>>>>>> >>>>>>>>> Hi, >>>>>>>>> >>>>>>>>> Can we run *simultaneous* actions on the *same RDD* ?; if yes how >>>>>>>>> can this >>>>>>>>> be done ? >>>>>>>>> >>>>>>>>> Thank you, >>>>>>>>> Regards >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> -- >>>>>>>>> View this message in context: >>>>>>>>> http://apache-spark-user-list.1001560.n3.nabble.com/simultaneous-actions-tp25977.html >>>>>>>>> Sent from the Apache Spark User List mailing list archive at >>>>>>>>> Nabble.com <http://nabble.com>. >>>>>>>>> >>>>>>>>> >>>>>>>>> --------------------------------------------------------------------- >>>>>>>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>>>>>>>> For additional commands, e-mail: user-h...@spark.apache.org >>>>>>>>> >>>>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >> >
