Where does the output go when submitting a Python file to Spark using spark-submit
I am trying to execute a spark-submit command to submit my Python application to a cluster (3 machine clusters on AWS-EMR).
Surprisingly, I do not see any intended exit from the problem. Then I simplified my application to only print some fixed lines, but still I didn't see any of these printed messages. I am attaching the app and command below. Hope someone can help me find the reason. Many thanks!
submit-test.py:
import sys
from pyspark import SparkContext
if __name__ == "__main__":
sc = SparkContext(appName="sparkSubmitTest")
for item in range(50):
print "I love this game!"
sc.stop()
The command I am using is:
./spark/bin/spark-submit --master yarn-cluster ./submit-test.py
The result I got is below:
[hadoop@ip-172-31-34-124 ~]$ ./spark/bin/spark-submit --master yarn-cluster ./submit-test.py
15/08/04 23:50:25 INFO client.RMProxy: Connecting to ResourceManager at /172.31.34.124:9022
15/08/04 23:50:25 INFO yarn.Client: Requesting a new application from cluster with 2 NodeManagers
15/08/04 23:50:25 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (11520 MB per container)
15/08/04 23:50:25 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
15/08/04 23:50:25 INFO yarn.Client: Setting up container launch context for our AM
15/08/04 23:50:25 INFO yarn.Client: Preparing resources for our AM container
15/08/04 23:50:25 INFO yarn.Client: Uploading resource file:/home/hadoop/.versions/spark-1.3.1.e/lib/spark-assembly-1.3.1-hadoop2.4.0.jar -> hdfs://172.31.34.124:9000/user/hadoop/.sparkStaging/application_1438724051797_0007/spark-assembly-1.3.1-hadoop2.4.0.jar
15/08/04 23:50:26 INFO metrics.MetricsSaver: MetricsConfigRecord disabledInCluster: false instanceEngineCycleSec: 60 clusterEngineCycleSec: 60 disableClusterEngine: false maxMemoryMb: 3072 maxInstanceCount: 500
15/08/04 23:50:26 INFO metrics.MetricsSaver: Created MetricsSaver j-2LU0EQ3JH58CK:i-048c1ded:SparkSubmit:24928 period:60 /mnt/var/em/raw/i-048c1ded_20150804_SparkSubmit_24928_raw.bin
15/08/04 23:50:27 INFO metrics.MetricsSaver: 1 aggregated HDFSWriteDelay 1053 raw values into 1 aggregated values, total 1
15/08/04 23:50:27 INFO yarn.Client: Uploading resource file:/home/hadoop/submit-test.py -> hdfs://172.31.34.124:9000/user/hadoop/.sparkStaging/application_1438724051797_0007/submit-test.py
15/08/04 23:50:27 INFO yarn.Client: Setting up the launch environment for our AM container
15/08/04 23:50:27 INFO spark.SecurityManager: Changing view acls to: hadoop
15/08/04 23:50:27 INFO spark.SecurityManager: Changing modify acls to: hadoop
15/08/04 23:50:27 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoop); users with modify permissions: Set(hadoop)
15/08/04 23:50:27 INFO yarn.Client: Submitting application 7 to ResourceManager
15/08/04 23:50:27 INFO impl.YarnClientImpl: Submitted application application_1438724051797_0007
15/08/04 23:50:28 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:28 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time: 1438732227551
final status: UNDEFINED
tracking URL: http://172.31.34.124:9046/proxy/application_1438724051797_0007/
user: hadoop
15/08/04 23:50:29 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:30 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:31 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:32 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:33 INFO yarn.Client: Application report for application_1438724051797_0007 (state: ACCEPTED)
15/08/04 23:50:34 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:34 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: ip-172-31-39-205.ec2.internal
ApplicationMaster RPC port: 0
queue: default
start time: 1438732227551
final status: UNDEFINED
tracking URL: http://172.31.34.124:9046/proxy/application_1438724051797_0007/
user: hadoop
15/08/04 23:50:35 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:36 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:37 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:38 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:39 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:40 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:41 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:42 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:43 INFO yarn.Client: Application report for application_1438724051797_0007 (state: RUNNING)
15/08/04 23:50:44 INFO yarn.Client: Application report for application_1438724051797_0007 (state: FINISHED)
15/08/04 23:50:44 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: ip-172-31-39-205.ec2.internal
ApplicationMaster RPC port: 0
queue: default
start time: 1438732227551
final status: SUCCEEDED
tracking URL: http://172.31.34.124:9046/proxy/application_1438724051797_0007/A
user: hadoop
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2 answers
Posting my answer here, since I haven't found them elsewhere.
I tried it first: the log threads -applicationId applicationid_xxxx was told "Log aggregation not completed or not enabled".
Below are the steps to dig up a print message:
1. Follow the link at the end of the execution, http://172.31.34.124:9046/proxy/application_1438724051797_0007/A (here reverse ssh and proxy needs to be setup).
2. at the application overview page, find out the AppMaster Node id: ip-172-31-41-6.ec2.internal:9035
3. go back to AWS EMR cluster list, find out the public dns for this id.
4. ssh from the driver node into this AppMaster Node. same key_pair.
5. cd /var/log/hadoop/userlogs/application_1438796304215_0005/container_1438796304215_0005_01_000001 (always choose the first container).
6. cat stdout
As you can see, this is very confusing. It will probably be better to write the output to a file hosted on S3.
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