You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@spark.apache.org by lu...@sina.com on 2015/07/03 05:35:02 UTC
回复：All master are unreponsive issue
Hi there， i check the source code and found that in org.apache.spark.deploy.client.AppClient, there is a parameter tells(line 52): val REGISTRATION_TIMEOUT = 20.seconds
val REGISTRATION_RETRIES = 3As I know If I wanna increase the retry times, must I modify this value,rebuild the entire Spark project and then redeply spark cluster with my modified version?Or is there a better way to solve this issue?Thanks.
--------------------------------
Thanks&Best regards!
San.Luo
----- 原始邮件 -----
发件人：<lu...@sina.com>
收件人："user" <us...@spark.apache.org>
主题：All master are unreponsive issue
日期：2015年07月02日 17点31分
Hi there: I got an problem that "Application has been killed.Reason:All masters are unresponsive!Giving up." I check the network I/O and found sometimes it is really high when running my app. Pls refer to the attached pic for more info.I also checked http://databricks.gitbooks.io/databricks-spark-knowledge-base/content/troubleshooting/connectivity_issues.html, and set SPARK_LOCAL_IP in every node's spark-env.sh of my spark cluster. However it does not benifit in solving this problem.I am not sure if this parameter is correctly set,my setting is like this:On node1:export SPARK_LOCAL_IP={node1's IP}On node2:export SPARK_LOCAL_IP={node2's IP}......
BTW,I guess that the akka will retry 3 times when communicate between master and slave, it is possible to increase the akka retries?
And except expand the network bandwidth, is there another way to solve this problem?
thanks for any coming ideas.
--------------------------------
Thanks&Best regards!
San.Luo
Re: All master are unreponsive issue
Posted by Aaron Davidson <il...@gmail.com>.
Are you seeing this after the app has already been running for some time,
or just at the beginning? Generally, registration should only occur once
initially, and a timeout would be due to the master not being accessible.
Try telneting to the master IP/port from the machine on which the driver
will run.
Re: All master are unreponsive issue
Posted by Ted Yu <yu...@gmail.com>.
Currently the number of retries is hardcoded.
You may want to open a JIRA which makes the retry count configurable.
Cheers
On Thu, Jul 2, 2015 at 8:35 PM, <lu...@sina.com> wrote:
> Hi there，
>
> i check the source code and found that in
> org.apache.spark.deploy.client.AppClient, there is a parameter tells(line
> 52):
>
> val REGISTRATION_TIMEOUT = 20.seconds
>
> val REGISTRATION_RETRIES = 3
>
> As I know If I wanna increase the retry times, must I modify this
> value,rebuild the entire Spark project and then redeply spark cluster with
> my modified version?
>
> Or is there a better way to solve this issue?
>
> Thanks.
>
>
>
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>
> ----- 原始邮件 -----
> 发件人：<lu...@sina.com>
> 收件人："user" <us...@spark.apache.org>
> 主题：All master are unreponsive issue
> 日期：2015年07月02日 17点31分
>
> Hi there:
>
> I got an problem that "Application has been killed.Reason:All
> masters are unresponsive!Giving up." I check the network I/O and found
> sometimes it is really high when running my app. Pls refer to the attached
> pic for more info.
>
> I also checked
> http://databricks.gitbooks.io/databricks-spark-knowledge-base/content/troubleshooting/connectivity_issues.html,
> and set SPARK_LOCAL_IP in every node's spark-env.sh of my spark cluster.
> However it does not benifit in solving this problem.
>
> I am not sure if this parameter is correctly set,my setting is like this:
>
> On node1:
>
> export SPARK_LOCAL_IP={node1's IP}
>
> On node2:
>
> export SPARK_LOCAL_IP={node2's IP}
>
> ......
>
>
>
> BTW,I guess that the akka will retry 3 times when communicate between
> master and slave, it is possible to increase the akka retries?
>
>
> And except expand the network bandwidth, is there another way to solve
> this problem?
>
>
> thanks for any coming ideas.
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>