Related question - is execution of different stages optimized? I.e. map followed by a filter will require 2 loops or they will be combined into single one?
On Tue, Jan 20, 2015 at 4:33 AM, Bob Tiernay <btier...@hotmail.com> wrote: > I found the following to be a good discussion of the same topic: > > http://apache-spark-user-list.1001560.n3.nabble.com/The-concurrent-model-of-spark-job-stage-task-td13083.html > > >> From: so...@cloudera.com >> Date: Tue, 20 Jan 2015 10:02:20 +0000 >> Subject: Re: Does Spark automatically run different stages concurrently >> when possible? >> To: paliwalash...@gmail.com >> CC: davidkl...@hotmail.com; user@spark.apache.org > >> >> You can persist the RDD in (2) right after it is created. It will not >> cause it to be persisted immediately, but rather the first time it is >> materialized. If you persist after (3) is calculated, then it will be >> re-calculated (and persisted) after (4) is calculated. >> >> On Tue, Jan 20, 2015 at 3:38 AM, Ashish <paliwalash...@gmail.com> wrote: >> > Sean, >> > >> > A related question. When to persist the RDD after step 2 or after Step >> > 3 (nothing would happen before step 3 I assume)? >> > >> > On Mon, Jan 19, 2015 at 5:17 PM, Sean Owen <so...@cloudera.com> wrote: >> >> From the OP: >> >> >> >> (1) val lines = Import full dataset using sc.textFile >> >> (2) val ABonly = Filter out all rows from "lines" that are not of type >> >> A or B >> >> (3) val processA = Process only the A rows from ABonly >> >> (4) val processB = Process only the B rows from ABonly >> >> >> >> I assume that 3 and 4 are actions, or else nothing happens here at all. >> >> >> >> When 3 is invoked, it will compute 1, then 2, then 3. 4 will happen >> >> after 3, and may even cause 1 and 2 to happen again if nothing is >> >> persisted. >> >> >> >> You can invoke 3 and 4 in parallel on the driver if you like. That's >> >> fine. But actions are blocking in the driver. >> >> >> >> >> >> >> >> On Mon, Jan 19, 2015 at 8:21 AM, davidkl <davidkl...@hotmail.com> >> >> wrote: >> >>> Hi Jon, I am looking for an answer for a similar question in the doc >> >>> now, so >> >>> far no clue. >> >>> >> >>> I would need to know what is spark behaviour in a situation like the >> >>> example >> >>> you provided, but taking into account also that there are multiple >> >>> partitions/workers. >> >>> >> >>> I could imagine it's possible that different spark workers are not >> >>> synchronized in terms of waiting for each other to progress to the >> >>> next >> >>> step/stage for the partitions of data they get assigned, while I >> >>> believe in >> >>> streaming they would wait for the current batch to complete before >> >>> they >> >>> start working on a new one. >> >>> >> >>> In the code I am working on, I need to make sure a particular step is >> >>> completed (in all workers, for all partitions) before next >> >>> transformation is >> >>> applied. >> >>> >> >>> Would be great if someone could clarify or point to these issues in >> >>> the doc! >> >>> :-) >> >>> >> >>> >> >>> >> >>> >> >>> -- >> >>> View this message in context: >> >>> http://apache-spark-user-list.1001560.n3.nabble.com/Does-Spark-automatically-run-different-stages-concurrently-when-possible-tp21075p21227.html >> >>> Sent from the Apache Spark User List mailing list archive at >> >>> Nabble.com. >> >>> >> >>> --------------------------------------------------------------------- >> >>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> >>> For additional commands, e-mail: user-h...@spark.apache.org >> >>> >> >> >> >> --------------------------------------------------------------------- >> >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> >> For additional commands, e-mail: user-h...@spark.apache.org >> >> >> > >> > >> > >> > -- >> > thanks >> > ashish >> > >> > Blog: http://www.ashishpaliwal.com/blog >> > My Photo Galleries: http://www.pbase.com/ashishpaliwal >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
