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
<mailto: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
<mailto: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
