If you press on the +details you could see the code that takes time. Did you already check it?
On Tue, Jul 14, 2015 at 9:56 AM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> wrote: > Job view. Others are fast, but the first one (repartition) is taking 95% > of job run time. > > On Mon, Jul 13, 2015 at 9:23 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> > wrote: > >> It completed in 32 minutes. Attached is screenshots. How do i speed it up >> ? >> >> >> On Mon, Jul 13, 2015 at 9:19 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >> wrote: >> >>> Its been 30 minutes and still the partitioner has not completed yet, its >>> ever. >>> >>> Without repartition, i see this error >>> https://issues.apache.org/jira/browse/SPARK-5928 >>> >>> >>> FetchFailed(BlockManagerId(1, imran-2.ent.cloudera.com, 55028), >>> shuffleId=1, mapId=0, reduceId=0, message= >>> org.apache.spark.shuffle.FetchFailedException: Adjusted frame length >>> exceeds 2147483647: 3021252889 - discarded >>> at >>> org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$.org$apache$spark$shuffle$hash$BlockStoreShuffleFetcher$$unpackBlock$1(BlockStoreShuffleFetcher.scala:67) >>> at >>> org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83) >>> at >>> org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83) >>> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) >>> at >>> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32) >>> >>> >>> >>> >>> On Mon, Jul 13, 2015 at 8:34 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> >>> wrote: >>> >>>> I have 100 MB of Avro data. and i do repartition(307) is taking forever. >>>> >>>> 2. val x = input.repartition(7907).map( {k1,k2,k3,k4}, {inputRecord} ) >>>> 3. val quantiles = x.map( {k1,k2,k3,k4}, TDigest(inputRecord).asBytes >>>> ).reduceByKey() [ This was groupBy earlier ] >>>> 4. x.join(quantiles).coalesce(100).writeInAvro >>>> >>>> >>>> Attached is full Scala code. >>>> >>>> I have 340 Yarn node cluster with 14G Ram on each node and have input >>>> data of just just 100 MB. (Hadoop takes 2.5 hours on 1 TB dataset) >>>> >>>> >>>> ./bin/spark-submit -v --master yarn-cluster --jars >>>> /apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/hdfs/hadoop-hdfs-2.4.1-EBAY-2.jar,/home/dvasthimal/spark1.4/lib/spark_reporting_dep_only-1.0-SNAPSHOT.jar >>>> --num-executors 330 --driver-memory 14g --driver-java-options >>>> "-XX:MaxPermSize=512M -Xmx4096M -Xms4096M -verbose:gc -XX:+PrintGCDetails >>>> -XX:+PrintGCTimeStamps" --executor-memory 14g --executor-cores 1 --queue >>>> hdmi-others --class com.ebay.ep.poc.spark.reporting.SparkApp >>>> /home/dvasthimal/spark1.4/lib/spark_reporting-1.0-SNAPSHOT.jar >>>> startDate=2015-06-20 endDate=2015-06-21 >>>> input=/apps/hdmi-prod/b_um/epdatasets/exptsession subcommand=ppwmasterprime >>>> output=/user/dvasthimal/epdatasets/ppwmasterprime buffersize=128 >>>> maxbuffersize=1068 maxResultSize=200G >>>> >>>> >>>> I see this in stdout of the task on that executor >>>> >>>> 15/07/13 19:58:48 WARN hdfs.BlockReaderLocal: The short-circuit local >>>> reads feature cannot be used because libhadoop cannot be loaded. >>>> 15/07/13 20:00:08 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (1 time so far) >>>> 15/07/13 20:01:31 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (2 times so far) >>>> 15/07/13 20:03:07 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (3 times so far) >>>> 15/07/13 20:04:32 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (4 times so far) >>>> 15/07/13 20:06:21 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (5 times so far) >>>> 15/07/13 20:08:09 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (6 times so far) >>>> 15/07/13 20:09:51 INFO collection.ExternalSorter: Thread 47 spilling >>>> in-memory map of 2.2 GB to disk (7 times so far) >>>> >>>> >>>> >>>> Also attached is the thread dump >>>> >>>> >>>> -- >>>> Deepak >>>> >>>> >>> >>> >>> -- >>> Deepak >>> >>> >> >> >> -- >> Deepak >> >> > > > -- > Deepak > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > -- Thanks & regards, Nirmal Associate Technical Lead - Data Technologies Team, WSO2 Inc. Mobile: +94715779733 Blog: http://nirmalfdo.blogspot.com/
