Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-04-14 Thread Nezih Yigitbasi
Thanks Imran. I will give it a shot when I have some time. Nezih On Thu, Apr 14, 2016 at 9:25 AM Imran Rashid wrote: > Hi Nezih, > > I just reported a somewhat similar issue, and I have a potential fix -- > SPARK-14560, looks like you are already watching it :). You can try out > that patch, y

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-04-14 Thread Imran Rashid
Hi Nezih, I just reported a somewhat similar issue, and I have a potential fix -- SPARK-14560, looks like you are already watching it :). You can try out that patch, you have to explicitly enable the change in behavior with "spark.shuffle.spillAfterRead=true". Honestly, I don't think these issue

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-04-04 Thread Nezih Yigitbasi
Nope, I didn't have a chance to track the root cause, and IIRC we didn't observe it when dyn. alloc. is off. On Mon, Apr 4, 2016 at 6:16 PM Reynold Xin wrote: > BTW do you still see this when dynamic allocation is off? > > On Mon, Apr 4, 2016 at 6:16 PM, Reynold Xin wrote: > >> Nezih, >> >> Hav

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-04-04 Thread Reynold Xin
Nezih, Have you had a chance to figure out why this is happening? On Tue, Mar 22, 2016 at 1:32 AM, james wrote: > I guess different workload cause diff result ? > > > > -- > View this message in context: > http://apache-spark-developers-list.1001551.n3.nabble.com/java-lang-OutOfMemoryError-Una

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-04-04 Thread Reynold Xin
BTW do you still see this when dynamic allocation is off? On Mon, Apr 4, 2016 at 6:16 PM, Reynold Xin wrote: > Nezih, > > Have you had a chance to figure out why this is happening? > > > On Tue, Mar 22, 2016 at 1:32 AM, james wrote: > >> I guess different workload cause diff result ? >> >> >> >

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-22 Thread james
I guess different workload cause diff result ? -- View this message in context: http://apache-spark-developers-list.1001551.n3.nabble.com/java-lang-OutOfMemoryError-Unable-to-acquire-bytes-of-memory-tp16773p16789.html Sent from the Apache Spark Developers List mailing list archive at Nabble.com

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-22 Thread Nezih Yigitbasi
Interesting. After experimenting with various parameters increasing spark.sql.shuffle.partitions and decreasing spark.buffer.pageSize helped my job go through. BTW I will be happy to help getting this issue fixed. Nezih On Tue, Mar 22, 2016 at 1:07 AM james wrote: Hi, > I also found 'Unable to

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-22 Thread james
Hi, I also found 'Unable to acquire memory' issue using Spark 1.6.1 with Dynamic allocation on YARN. My case happened with setting spark.sql.shuffle.partitions larger than 200. From error stack, it has a diff with issue reported by Nezih and not sure if these has same root cause. Thanks James 16

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-21 Thread Nezih Yigitbasi
Andrew, thanks for the suggestion, but unfortunately it didn't work -- still getting the same exception. On Mon, Mar 21, 2016 at 10:32 AM Andrew Or wrote: > @Nezih, can you try again after setting `spark.memory.useLegacyMode` to > true? Can you still reproduce the OOM that way? > > 2016-03-21 10:

Re: java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-21 Thread Andrew Or
@Nezih, can you try again after setting `spark.memory.useLegacyMode` to true? Can you still reproduce the OOM that way? 2016-03-21 10:29 GMT-07:00 Nezih Yigitbasi : > Hi Spark devs, > I am using 1.6.0 with dynamic allocation on yarn. I am trying to run a > relatively big application with 10s of j

java.lang.OutOfMemoryError: Unable to acquire bytes of memory

2016-03-21 Thread Nezih Yigitbasi
Hi Spark devs, I am using 1.6.0 with dynamic allocation on yarn. I am trying to run a relatively big application with 10s of jobs and 100K+ tasks and my app fails with the exception below. The closest jira issue I could find is SPARK-11293 , which