Hi Mukesh, Based on your spark-submit command, it looks like you're only running with 2 executors on YARN. Also, how many cores does each machine have?
-Sandy On Mon, Dec 29, 2014 at 4:36 AM, Mukesh Jha <me.mukesh....@gmail.com> wrote: > Hello Experts, > I'm bench-marking Spark on YARN ( > https://spark.apache.org/docs/latest/running-on-yarn.html) vs a > standalone spark cluster ( > https://spark.apache.org/docs/latest/spark-standalone.html). > I have a standalone cluster with 3 executors, and a spark app running on > yarn with 4 executors as shown below. > > The spark job running inside yarn is 10x slower than the one running on > the standalone cluster (even though the yarn has more number of workers), > also in both the case all the executors are in the same datacenter so there > shouldn't be any latency. On YARN each 5sec batch is reading data from > kafka and processing it in 5sec & on the standalone cluster each 5sec batch > is getting processed in 0.4sec. > Also, In YARN mode all the executors are not getting used up evenly as > vm-13 & vm-14 are running most of the tasks whereas in the standalone mode > all the executors are running the tasks. > > Do I need to set up some configuration to evenly distribute the tasks? > Also do you have any pointers on the reasons the yarn job is 10x slower > than the standalone job? > Any suggestion is greatly appreciated, Thanks in advance. > > YARN(5 workers + driver) > ======================== > Executor ID Address RDD Blocks Memory Used DU AT FT CT TT TT Input > ShuffleRead > ShuffleWrite Thread Dump > 1 vm-18.cloud.com:51796 0 0.0B/530.3MB 0.0 B 1 0 16 17 634 ms 0.0 B 2047.0 > B 1710.0 B Thread Dump > 2 vm-13.cloud.com:57264 0 0.0B/530.3MB 0.0 B 0 0 1427 1427 5.5 m 0.0 B 0.0 > B 0.0 B Thread Dump > 3 vm-14.cloud.com:54570 0 0.0B/530.3MB 0.0 B 0 0 1379 1379 5.2 m 0.0 B 1368.0 > B 2.8 KB Thread Dump > 4 vm-11.cloud.com:56201 0 0.0B/530.3MB 0.0 B 0 0 10 10 625 ms 0.0 B 1368.0 > B 1026.0 B Thread Dump > 5 vm-5.cloud.com:42958 0 0.0B/530.3MB 0.0 B 0 0 22 22 632 ms 0.0 B 1881.0 > B 2.8 KB Thread Dump > <driver> vm.cloud.com:51847 0 0.0B/530.0MB 0.0 B 0 0 0 0 0 ms 0.0 B 0.0 B 0.0 > B Thread Dump > > /homext/spark/bin/spark-submit > --master yarn-cluster --num-executors 2 --driver-memory 512m > --executor-memory 512m --executor-cores 2 > --class com.oracle.ci.CmsgK2H /homext/lib/MJ-ci-k2h.jar > vm.cloud.com:2181/kafka spark-yarn avro 1 5000 > > STANDALONE(3 workers + driver) > ============================== > Executor ID Address RDD Blocks Memory Used DU AT FT CT TT TT Input ShuffleRead > ShuffleWrite Thread Dump > 0 vm-71.cloud.com:55912 0 0.0B/265.0MB 0.0 B 0 0 1069 1069 6.0 m 0.0 B 1534.0 > B 3.0 KB Thread Dump > 1 vm-72.cloud.com:40897 0 0.0B/265.0MB 0.0 B 0 0 1057 1057 5.9 m 0.0 B 1368.0 > B 4.0 KB Thread Dump > 2 vm-73.cloud.com:37621 0 0.0B/265.0MB 0.0 B 1 0 1059 1060 5.9 m 0.0 B 2.0 > KB 1368.0 B Thread Dump > <driver> vm.cloud.com:58299 0 0.0B/265.0MB 0.0 B 0 0 0 0 0 ms 0.0 B 0.0 B 0.0 > B Thread Dump > > /homext/spark/bin/spark-submit > --master spark://chsnmvproc71vm3.usdc2.oraclecloud.com:7077 > --class com.oracle.ci.CmsgK2H /homext/lib/MJ-ci-k2h.jar > vm.cloud.com:2181/kafka spark-standalone avro 1 5000 > > PS: I did go through the spark website and > http://www.virdata.com/tuning-spark/, but was out of any luck. > > -- > Cheers, > Mukesh Jha >
