In the interest of completeness, this is how I invoke spark:
[on master]
> sbin/start-all.sh
> spark-submit --py-files extra.py main.py
iPhone'd
> On Jun 26, 2014, at 17:29, Shannon Quinn <squ...@gatech.edu> 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 127.0.0.1 as localhost;
> spark-defaults.conf list spark.master as the full IP address (not 127.0.0.1);
> spark-env.sh 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 spark-env.sh file?
>>
>> Thanks
>> Best Regards
>>
>>
>>> On Thu, Jun 26, 2014 at 7:01 PM, Shannon Quinn <squ...@gatech.edu> 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
>>> COMMAND PID USER FD TYPE DEVICE SIZE/OFF NODE NAME
>>> java 23985 user 30u IPv6 11092354 0t0 TCP machine1:sip (LISTEN)
>>> java 23985 user 40u IPv6 11099560 0t0 TCP
>>> machine1:sip->machine1:48315 (ESTABLISHED)
>>> java 23985 user 52u IPv6 11100405 0t0 TCP
>>> machine1:sip->machine2:54476 (ESTABLISHED)
>>> java 24157 user 40u IPv6 11092413 0t0 TCP
>>> machine1:48315->machine1:sip (ESTABLISHED)
>>>
>>> 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 <squ...@gatech.edu> wrote:
>>>>> Still running into the same problem. /etc/hosts on the master says
>>>>>
>>>>> 127.0.0.1 localhost
>>>>> <ip> machine1
>>>>>
>>>>> <ip> is the same address set in spark-env.sh 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 <squ...@gatech.edu> wrote:
>>>>>>> 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/start-all.sh',
>>>>>>> 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 spark-env.sh 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 127.0.0.1. 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$ClientActor: Executor added:
>>>>>>> app-20140625210032-0000/8 on worker-20140625205623-machine2-53597
>>>>>>> (machine2:53597) with 8 cores
>>>>>>> 14/06/25 21:00:47 INFO SparkDeploySchedulerBackend: Granted executor ID
>>>>>>> app-20140625210032-0000/8 on hostPort machine2:53597 with 8 cores, 8.0
>>>>>>> GB RAM
>>>>>>> 14/06/25 21:00:47 INFO AppClient$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"
>>>>>>> "app-20140625210032-0000"
>>>>>>> 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
>
