Nope, I am setting 5 executors with 2 cores each. Below is the command that I'm using to submit in YARN mode. This starts up 5 executor nodes and a drives as per the spark application master UI.
spark-submit --master yarn-cluster --num-executors 5 --driver-memory 1024m --executor-memory 1024m --executor-cores 2 --class com.oracle.ci.CmsgK2H /homext/lib/MJ-ci-k2h.jar vm.cloud.com:2181/kafka spark-yarn avro 1 5000 On Mon, Dec 29, 2014 at 11:45 PM, Sandy Ryza <sandy.r...@cloudera.com> wrote: > *oops, I mean are you setting --executor-cores to 8 > > On Mon, Dec 29, 2014 at 10:15 AM, Sandy Ryza <sandy.r...@cloudera.com> > wrote: > >> Are you setting --num-executors to 8? >> >> On Mon, Dec 29, 2014 at 10:13 AM, Mukesh Jha <me.mukesh....@gmail.com> >> wrote: >> >>> Sorry Sandy, The command is just for reference but I can confirm that >>> there are 4 executors and a driver as shown in the spark UI page. >>> >>> Each of these machines is a 8 core box with ~15G of ram. >>> >>> On Mon, Dec 29, 2014 at 11:23 PM, Sandy Ryza <sandy.r...@cloudera.com> >>> wrote: >>> >>>> 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 >>>>> >>>> >>>> >>> >>> >>> -- >>> >>> >>> Thanks & Regards, >>> >>> *Mukesh Jha <me.mukesh....@gmail.com>* >>> >> >> > -- Thanks & Regards, *Mukesh Jha <me.mukesh....@gmail.com>*
