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From Sandy Ryza <sandy.r...@cloudera.com>
Subject Re: SPARK-streaming app running 10x slower on YARN vs STANDALONE cluster
Date Mon, 29 Dec 2014 18:15:46 GMT
*oops, I mean are you setting --executor-cores to 8

On Mon, Dec 29, 2014 at 10:15 AM, Sandy Ryza <sandy.ryza@cloudera.com>
wrote:

> Are you setting --num-executors to 8?
>
> On Mon, Dec 29, 2014 at 10:13 AM, Mukesh Jha <me.mukesh.jha@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.ryza@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.jha@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.jha@gmail.com>*
>>
>
>

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