If you are writing to S3, also make sure that you are using the direct output committer. I don't have streaming jobs but it helps in my machine learning jobs. Also, though more partitions help in processing faster, they do slow down writes to S3. So you might want to coalesce before writing to S3.
Regards Sab On 29-Oct-2015 6:21 pm, "Afshartous, Nick" <nafshart...@turbine.com> wrote: > < Does it work as expected with smaller batch or smaller load? Could it be > that it's accumulating too many events over 3 minutes? > > Thanks for you input. The 3 minute window was chosen because we write the > output of each batch into S3. And with smaller batch time intervals there > were many small files being written to S3, something to avoid. That was > the explanation of the developer who made this decision (who's no longer on > the team). We're in the process of re-evaluating. > -- > Nick > > -----Original Message----- > From: Adrian Tanase [mailto:atan...@adobe.com] > Sent: Wednesday, October 28, 2015 4:53 PM > To: Afshartous, Nick <nafshart...@turbine.com> > Cc: user@spark.apache.org > Subject: Re: Spark/Kafka Streaming Job Gets Stuck > > Does it work as expected with smaller batch or smaller load? Could it be > that it's accumulating too many events over 3 minutes? > > You could also try increasing the parallelism via repartition to ensure > smaller tasks that can safely fit in working memory. > > Sent from my iPhone > > > On 28 Oct 2015, at 17:45, Afshartous, Nick <nafshart...@turbine.com> > wrote: > > > > > > Hi, we are load testing our Spark 1.3 streaming (reading from Kafka) > job and seeing a problem. This is running in AWS/Yarn and the streaming > batch interval is set to 3 minutes and this is a ten node cluster. > > > > Testing at 30,000 events per second we are seeing the streaming job get > stuck (stack trace below) for over an hour. > > > > Thanks on any insights or suggestions. > > -- > > Nick > > > > org.apache.spark.streaming.api.java.AbstractJavaDStreamLike.mapPartiti > > onsToPair(JavaDStreamLike.scala:43) > > com.wb.analytics.spark.services.streaming.drivers.StreamingKafkaConsum > > erDriver.runStream(StreamingKafkaConsumerDriver.java:125) > > com.wb.analytics.spark.services.streaming.drivers.StreamingKafkaConsum > > erDriver.main(StreamingKafkaConsumerDriver.java:71) > > sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.j > > ava:57) > > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccess > > orImpl.java:43) > > java.lang.reflect.Method.invoke(Method.java:606) > > org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(Application > > Master.scala:480) > > > > Notice: This communication is for the intended recipient(s) only and may > contain confidential, proprietary, legally protected or privileged > information of Turbine, Inc. If you are not the intended recipient(s), > please notify the sender at once and delete this communication. > Unauthorized use of the information in this communication is strictly > prohibited and may be unlawful. For those recipients under contract with > Turbine, Inc., the information in this communication is subject to the > terms and conditions of any applicable contracts or agreements. > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For > > additional commands, e-mail: user-h...@spark.apache.org > > > > Notice: This communication is for the intended recipient(s) only and may > contain confidential, proprietary, legally protected or privileged > information of Turbine, Inc. If you are not the intended recipient(s), > please notify the sender at once and delete this communication. > Unauthorized use of the information in this communication is strictly > prohibited and may be unlawful. For those recipients under contract with > Turbine, Inc., the information in this communication is subject to the > terms and conditions of any applicable contracts or agreements. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
