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Posted to user@spark.apache.org by Debabrata Ghosh <ma...@gmail.com> on 2018/05/08 11:35:48 UTC
Help Required - Unable to run spark-submit on YARN client mode
Hi Everyone,
I have been trying to run spark-shell in YARN client mode, but am getting
lot of ClosedChannelException errors, however the program works fine on
local mode. I am using spark 2.2.0 build for Hadoop 2.7.3. If you are
familiar with this error, please can you help with the possible resolution.
Any help would be greatly appreciated!
Here is the error message:
18/05/08 00:01:18 ERROR TransportClient: Failed to send RPC
7905321254854295784 to /9.30.94.43:60220:
java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
at
io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)
18/05/08 00:01:18 ERROR YarnSchedulerBackend$YarnSchedulerEndpoint: Sending
RequestExecutors(5,0,Map(),Set()) to AM was unsuccessful
java.io.IOException: Failed to send RPC 7905321254854295784 to /
9.30.94.43:60220: java.nio.channels.ClosedChannelException
at
org.apache.spark.network.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)
at
io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
at
io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)
at
io.netty.util.concurrent.DefaultPromise.access$000(DefaultPromise.java:34)
at
io.netty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:431)
at
io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)
at
io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at
io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
Cheers,
Debu
Re: Help Required - Unable to run spark-submit on YARN client mode
Posted by Deepak Sharma <de...@gmail.com>.
Can you try increasing the partition for the base RDD/dataframe that you
are working on?
On Tue, May 8, 2018 at 5:05 PM, Debabrata Ghosh <ma...@gmail.com>
wrote:
> Hi Everyone,
> I have been trying to run spark-shell in YARN client mode, but am getting
> lot of ClosedChannelException errors, however the program works fine on
> local mode. I am using spark 2.2.0 build for Hadoop 2.7.3. If you are
> familiar with this error, please can you help with the possible resolution.
>
> Any help would be greatly appreciated!
>
> Here is the error message:
>
> 18/05/08 00:01:18 ERROR TransportClient: Failed to send RPC
> 7905321254854295784 to /9.30.94.43:60220: java.nio.channels.
> ClosedChannelException
> java.nio.channels.ClosedChannelException
> at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown
> Source)
> 18/05/08 00:01:18 ERROR YarnSchedulerBackend$YarnSchedulerEndpoint:
> Sending RequestExecutors(5,0,Map(),Set()) to AM was unsuccessful
> java.io.IOException: Failed to send RPC 7905321254854295784 to /
> 9.30.94.43:60220: java.nio.channels.ClosedChannelException
> at org.apache.spark.network.client.TransportClient.lambda$
> sendRpc$2(TransportClient.java:237)
> at io.netty.util.concurrent.DefaultPromise.notifyListener0(
> DefaultPromise.java:507)
> at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(
> DefaultPromise.java:481)
> at io.netty.util.concurrent.DefaultPromise.access$000(
> DefaultPromise.java:34)
> at io.netty.util.concurrent.DefaultPromise$1.run(
> DefaultPromise.java:431)
> at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(
> SingleThreadEventExecutor.java:399)
> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)
> at io.netty.util.concurrent.SingleThreadEventExecutor$2.
> run(SingleThreadEventExecutor.java:131)
> at io.netty.util.concurrent.DefaultThreadFactory$
> DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: java.nio.channels.ClosedChannelException
>
> Cheers,
>
> Debu
>
--
Thanks
Deepak
www.bigdatabig.com
www.keosha.net