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From Shannon Quinn <>
Subject Re: Spark standalone network configuration problems
Date Fri, 27 Jun 2014 00:17:49 GMT
In the interest of completeness, this is how I invoke spark:

[on master]

> sbin/
> spark-submit --py-files


> On Jun 26, 2014, at 17:29, Shannon Quinn <> wrote:
> My *best guess* (please correct me if I'm wrong) is that the master (machine1) is sending
the command to the worker (machine2) with the localhost argument as-is; that is, machine2
isn't doing any weird address conversion on its end.
> Consequently, I've been focusing on the settings of the master/machine1. But I haven't
found anything to indicate where the localhost argument could be coming from. /etc/hosts lists
only as localhost; spark-defaults.conf list spark.master as the full IP address
(not; on the master also lists the full IP under SPARK_MASTER_IP.
The *only* place on the master where it's associated with localhost is SPARK_LOCAL_IP.
> In looking at the logs of the worker spawned on master, it's also receiving a "spark://localhost:5060"
argument, but since it resides on the master that works fine. Is it possible that the master
is, for some reason, passing "spark://{SPARK_LOCAL_IP}:5060" to the workers?
> That was my motivation behind commenting out SPARK_LOCAL_IP;     however, that's when
the master crashes immediately due to the address already being in use.
> Any ideas? Thanks!
> Shannon
>> On 6/26/14, 10:14 AM, Akhil Das wrote:
>> Can you paste your file?
>> Thanks
>> Best Regards
>>> On Thu, Jun 26, 2014 at 7:01 PM, Shannon Quinn <> wrote:
>>> Both /etc/hosts have each other's IP addresses in them. Telneting from machine2
to machine1 on port 5060 works just fine.
>>> Here's the output of lsof:
>>> user@machine1:~/spark/spark-1.0.0-bin-hadoop2$ lsof -i:5060
>>> java    23985 user   30u  IPv6 11092354      0t0  TCP machine1:sip (LISTEN)
>>> java    23985 user   40u  IPv6 11099560      0t0  TCP machine1:sip->machine1:48315
>>> java    23985 user   52u  IPv6 11100405      0t0  TCP machine1:sip->machine2:54476
>>> java    24157 user   40u  IPv6 11092413      0t0  TCP machine1:48315->machine1:sip
>>> Ubuntu seems to recognize 5060 as the standard port for "sip"; it's not actually
running anything there besides Spark, it just does a s/5060/sip/g.
>>> Is there something to the fact that every time I comment out SPARK_LOCAL_IP in
spark-env, it crashes immediately upon spark-submit due to the "address already being in use"?
Or am I barking up the wrong tree on that one?
>>> Thanks again for all your help; I hope we can knock this one out.
>>> Shannon
>>>> On 6/26/14, 9:13 AM, Akhil Das wrote:
>>>> Do you have <ip>            machine1 in your workers /etc/hosts also?
If so try telneting from your machine2 to machine1 on port 5060. Also make sure nothing else
is running on port 5060 other                           than Spark (lsof -i:5060)
>>>> Thanks
>>>> Best Regards
>>>>> On Thu, Jun 26, 2014 at 6:35 PM, Shannon Quinn <>
>>>>> Still running into the same problem. /etc/hosts on the master says
>>>>>    localhost
>>>>> <ip>            machine1
>>>>> <ip> is the same address set in for SPARK_MASTER_IP.
Any other ideas?
>>>>>> On 6/26/14, 3:11 AM, Akhil Das wrote:
>>>>>> Hi Shannon,
>>>>>> It should be a configuration issue, check in your /etc/hosts and
make sure localhost is not associated with the SPARK_MASTER_IP you provided.
>>>>>> Thanks
>>>>>> Best Regards
>>>>>> On Thu, Jun 26, 2014 at 6:37 AM, Shannon Quinn <>
>>>>>>> Hi all,
>>>>>>> I have a 2-machine Spark network I've set up: a master and worker
on machine1, and worker on machine2. When I run 'sbin/', everything starts up
as it should. I see both workers                                           listed on the UI
page. The logs of both workers indicate successful registration with the Spark master.
>>>>>>> The problems begin when I attempt to submit a job: I get an "address
already in use" exception that crashes the program. It says "Failed to bind to " and lists
the exact port and address of the master.
>>>>>>> At this point, the only items I have set in my are
SPARK_MASTER_IP and SPARK_MASTER_PORT (non-standard, set to 5060).
>>>>>>> The next step I took, then, was to explicitly set SPARK_LOCAL_IP
on the master to This allows the master to successfully send out the jobs; however,
it ends up canceling the stage after running this command several times:
>>>>>>> 14/06/25 21:00:47 INFO AppClient$ClientActor: Executor added:
app-20140625210032-0000/8 on worker-20140625205623-machine2-53597 (machine2:53597) with 8
>>>>>>> 14/06/25 21:00:47 INFO SparkDeploySchedulerBackend: Granted executor
ID app-20140625210032-0000/8 on hostPort machine2:53597 with 8 cores, 8.0 GB RAM
>>>>>>> 14/06/25 21:00:47 INFO AppClient$ClientActor: Executor updated:
app-20140625210032-0000/8 is now RUNNING
>>>>>>> 14/06/25 21:00:49 INFO AppClient$ClientActor: Executor updated:
app-20140625210032-0000/8 is now FAILED (Command exited with code 1)
>>>>>>> The "/8" started at "/1", eventually becomes "/9", and then "/10",
at which point the program crashes. The worker on machine2 shows similar messages in its logs.
Here are the last bunch:
>>>>>>> 14/06/25 21:00:31 INFO Worker: Executor app-20140625210032-0000/9
finished with state FAILED message Command exited with code 1 exitStatus 1
>>>>>>> 14/06/25 21:00:31 INFO Worker: Asked to launch executor app-20140625210032-0000/10
for app_name
>>>>>>> Spark assembly has been built with Hive, including Datanucleus
jars on classpath
>>>>>>> 14/06/25 21:00:32 INFO ExecutorRunner: Launch command: "java"
"-cp" "::/home/spark/spark-1.0.0-bin-hadoop2/conf:/home/spark/spark-1.0.0-bin-hadoop2/lib/spark-assembly-1.0.0-hadoop2.2.0.jar:/home/spark/spark-1.0.0-bin-hadoop2/lib/datanucleus-rdbms-3.2.1.jar:/home/spark/spark-1.0.0-bin-hadoop2/lib/datanucleus-core-3.2.2.jar:/home/spark/spark-1.0.0-bin-hadoop2/lib/datanucleus-api-jdo-3.2.1.jar"
"-XX:MaxPermSize=128m" "-Xms8192M" "-Xmx8192M" "org.apache.spark.executor.CoarseGrainedExecutorBackend"
"akka.tcp://spark@localhost:5060/user/CoarseGrainedScheduler" "10" "machine2" "8" "akka.tcp://sparkWorker@machine2:53597/user/Worker"
>>>>>>> 14/06/25 21:00:33 INFO Worker: Executor app-20140625210032-0000/10
                                          finished with state FAILED message Command exited
with code 1 exitStatus 1
>>>>>>> I highlighted the part that seemed strange to me; that's the
master port number (I set it to 5060), and yet it's referencing localhost? Is this the reason
why machine2 apparently can't seem to give a confirmation to the master once the job is submitted?
(The logs from the worker on the master node indicate that it's running just fine)
>>>>>>> I appreciate any assistance you can offer!
>>>>>>> Regards,
>>>>>>> Shannon Quinn

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