Regarding # of executors. I get 342 executors in parallel each time and i set executor-cores to 1. Hence i need to set 342 * 2 * x (x = 1,2,3, ..) as number of partitions while running blockJoin. Is this correct.
And is my assumptions on replication levels correct. Did you get a chance to look at my processing. On Sun, Jun 28, 2015 at 3:31 PM, Koert Kuipers <ko...@tresata.com> wrote: > regarding your calculation of executors... RAM in executor is not really > comparable to size on disk. > > if you read from from file and write to file you do not have to set > storage level. > > in the join or blockJoin specify number of partitions as a multiple (say > 2 times) of number of cores available to you across all executors (so not > just number of executors, on yarn you can have many cores per executor). > > On Sun, Jun 28, 2015 at 6:04 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> > wrote: > >> Could you please suggest and help me understand further. >> >> This is the actual sizes >> >> -sh-4.1$ hadoop fs -count dw_lstg_item >> 1 764 2041084436189 >> /sys/edw/dw_lstg_item/snapshot/2015/06/25/00 >> *This is not skewed there is exactly one etntry for each item but its 2TB* >> So should its replication be set to 1 ? >> >> The below two datasets (RDD) are unioned and their total size is 150G. >> These can be skewed and >> hence we use block join with Scoobi + MR. >> *So should its replication be set to 3 ?* >> -sh-4.1$ hadoop fs -count >> /apps/hdmi-prod/b_um/epdatasets/exptsession/2015/06/20 >> 1 101 73796345977 >> /apps/hdmi-prod/b_um/epdatasets/exptsession/2015/06/20 >> -sh-4.1$ hadoop fs -count >> /apps/hdmi-prod/b_um/epdatasets/exptsession/2015/06/21 >> 1 101 85559964549 >> /apps/hdmi-prod/b_um/epdatasets/exptsession/2015/06/21 >> >> Also can you suggest the number of executors to be used in this case , >> each executor is started with max 14G of memory? >> >> Is it equal to 2TB + 150G (Total data) = 20150 GB/14GB = 1500 executors >> ? Is this calculation correct ? >> >> And also please suggest on the >> "(should be memory-and-disk or disk-only), number of partitions (should >> be large, multiple of num executors)," >> >> >> https://spark.apache.org/docs/latest/programming-guide.html#which-storage-level-to-choose >> >> When do i choose this setting ? (Attached is my code for reference) >> >> >> >> On Sun, Jun 28, 2015 at 2:57 PM, Koert Kuipers <ko...@tresata.com> wrote: >> >>> a blockJoin spreads out one side while replicating the other. i would >>> suggest replicating the smaller side. so if lstgItem is smaller try 3,1 >>> or else 1,3. this should spread the "fat" keys out over multiple (3) >>> executors... >>> >>> >>> On Sun, Jun 28, 2015 at 5:35 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >>> wrote: >>> >>>> I am able to use blockjoin API and it does not throw compilation error >>>> >>>> val viEventsWithListings: RDD[(Long, (DetailInputRecord, VISummary, >>>> Long))] = lstgItem.blockJoin(viEvents,1,1).map { >>>> >>>> } >>>> >>>> Here viEvents is highly skewed and both are on HDFS. >>>> >>>> What should be the optimal values of replication, i gave 1,1 >>>> >>>> >>>> >>>> On Sun, Jun 28, 2015 at 1:47 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >>>> wrote: >>>> >>>>> I incremented the version of spark from 1.4.0 to 1.4.0.1 and ran >>>>> >>>>> ./make-distribution.sh --tgz -Phadoop-2.4 -Pyarn -Phive >>>>> -Phive-thriftserver >>>>> >>>>> Build was successful but the script faild. Is there a way to pass the >>>>> incremented version ? >>>>> >>>>> >>>>> [INFO] BUILD SUCCESS >>>>> >>>>> [INFO] >>>>> ------------------------------------------------------------------------ >>>>> >>>>> [INFO] Total time: 09:56 min >>>>> >>>>> [INFO] Finished at: 2015-06-28T13:45:29-07:00 >>>>> >>>>> [INFO] Final Memory: 84M/902M >>>>> >>>>> [INFO] >>>>> ------------------------------------------------------------------------ >>>>> >>>>> + rm -rf /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist >>>>> >>>>> + mkdir -p /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/lib >>>>> >>>>> + echo 'Spark 1.4.0.1 built for Hadoop 2.4.0' >>>>> >>>>> + echo 'Build flags: -Phadoop-2.4' -Pyarn -Phive -Phive-thriftserver >>>>> >>>>> + cp >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/assembly/target/scala-2.10/spark-assembly-1.4.0.1-hadoop2.4.0.jar >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/lib/ >>>>> >>>>> + cp >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/examples/target/scala-2.10/spark-examples-1.4.0.1-hadoop2.4.0.jar >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/lib/ >>>>> >>>>> + cp >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/network/yarn/target/scala-2.10/spark-1.4.0.1-yarn-shuffle.jar >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/lib/ >>>>> >>>>> + mkdir -p >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/examples/src/main >>>>> >>>>> + cp -r >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/examples/src/main >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/examples/src/ >>>>> >>>>> + '[' 1 == 1 ']' >>>>> >>>>> + cp >>>>> '/Users/dvasthimal/ebay/projects/ep/spark-1.4.0/lib_managed/jars/datanucleus*.jar' >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/dist/lib/ >>>>> >>>>> cp: >>>>> /Users/dvasthimal/ebay/projects/ep/spark-1.4.0/lib_managed/jars/datanucleus*.jar: >>>>> No such file or directory >>>>> >>>>> LM-SJL-00877532:spark-1.4.0 dvasthimal$ ./make-distribution.sh --tgz >>>>> -Phadoop-2.4 -Pyarn -Phive -Phive-thriftserver >>>>> >>>>> >>>>> >>>>> On Sun, Jun 28, 2015 at 1:41 PM, Koert Kuipers <ko...@tresata.com> >>>>> wrote: >>>>> >>>>>> you need 1) to publish to inhouse maven, so your application can >>>>>> depend on your version, and 2) use the spark distribution you compiled to >>>>>> launch your job (assuming you run with yarn so you can launch multiple >>>>>> versions of spark on same cluster) >>>>>> >>>>>> On Sun, Jun 28, 2015 at 4:33 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> How can i import this pre-built spark into my application via maven >>>>>>> as i want to use the block join API. >>>>>>> >>>>>>> On Sun, Jun 28, 2015 at 1:31 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> I ran this w/o maven options >>>>>>>> >>>>>>>> ./make-distribution.sh --tgz -Phadoop-2.4 -Pyarn -Phive >>>>>>>> -Phive-thriftserver >>>>>>>> >>>>>>>> I got this spark-1.4.0-bin-2.4.0.tgz in the same working directory. >>>>>>>> >>>>>>>> I hope this is built with 2.4.x hadoop as i did specify -P >>>>>>>> >>>>>>>> On Sun, Jun 28, 2015 at 1:10 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com >>>>>>>> > wrote: >>>>>>>> >>>>>>>>> ./make-distribution.sh --tgz --*mvn* "-Phadoop-2.4 -Pyarn >>>>>>>>> -Dhadoop.version=2.4.0 -Phive -Phive-thriftserver -DskipTests clean >>>>>>>>> package" >>>>>>>>> >>>>>>>>> >>>>>>>>> or >>>>>>>>> >>>>>>>>> >>>>>>>>> ./make-distribution.sh --tgz --*mvn* -Phadoop-2.4 -Pyarn >>>>>>>>> -Dhadoop.version=2.4.0 -Phive -Phive-thriftserver -DskipTests clean >>>>>>>>> package" >>>>>>>>> Both fail with >>>>>>>>> >>>>>>>>> + echo -e 'Specify the Maven command with the --mvn flag' >>>>>>>>> >>>>>>>>> Specify the Maven command with the --mvn flag >>>>>>>>> >>>>>>>>> + exit -1 >>>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> -- >>>>>>>> Deepak >>>>>>>> >>>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Deepak >>>>>>> >>>>>>> >>>>>> >>>>> >>>>> >>>>> -- >>>>> Deepak >>>>> >>>>> >>>> >>>> >>>> -- >>>> Deepak >>>> >>>> >>> >> >> >> -- >> Deepak >> >> > -- Deepak
