Attempting to run h2o on a HDP 3.1 cluster and running into error that appears to be about YARN resource capacity...
[ml1user@HW04 h2o-3.26.0.1-hdp3.1]$ hadoop jar h2odriver.jar -nodes 3 -mapperXmx 10g
Determining driver host interface for mapper->driver callback...
[Possible callback IP address: 192.168.122.1]
[Possible callback IP address: 172.18.4.49]
[Possible callback IP address: 127.0.0.1]
Using mapper->driver callback IP address and port: 172.18.4.49:46015
(You can override these with -driverif and -driverport/-driverportrange and/or specify external IP using -extdriverif.)
Memory Settings:
mapreduce.map.java.opts: -Xms10g -Xmx10g -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -Dlog4j.defaultInitOverride=true
Extra memory percent: 10
mapreduce.map.memory.mb: 11264
Hive driver not present, not generating token.
19/07/25 14:48:05 INFO client.RMProxy: Connecting to ResourceManager at hw01.ucera.local/172.18.4.46:8050
19/07/25 14:48:06 INFO client.AHSProxy: Connecting to Application History server at hw02.ucera.local/172.18.4.47:10200
19/07/25 14:48:07 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /user/ml1user/.staging/job_1564020515809_0006
19/07/25 14:48:08 INFO mapreduce.JobSubmitter: number of splits:3
19/07/25 14:48:08 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1564020515809_0006
19/07/25 14:48:08 INFO mapreduce.JobSubmitter: Executing with tokens: []
19/07/25 14:48:08 INFO conf.Configuration: found resource resource-types.xml at file:/etc/hadoop/3.1.0.0-78/0/resource-types.xml
19/07/25 14:48:08 INFO impl.YarnClientImpl: Submitted application application_1564020515809_0006
19/07/25 14:48:08 INFO mapreduce.Job: The url to track the job: http://HW01.ucera.local:8088/proxy/application_1564020515809_0006/
Job name 'H2O_47159' submitted
JobTracker job ID is 'job_1564020515809_0006'
For YARN users, logs command is 'yarn logs -applicationId application_1564020515809_0006'
Waiting for H2O cluster to come up...
ERROR: Timed out waiting for H2O cluster to come up (120 seconds)
ERROR: (Try specifying the -timeout option to increase the waiting time limit)
Attempting to clean up hadoop job...
19/07/25 14:50:19 INFO impl.YarnClientImpl: Killed application application_1564020515809_0006
Killed.
19/07/25 14:50:23 INFO client.RMProxy: Connecting to ResourceManager at hw01.ucera.local/172.18.4.46:8050
19/07/25 14:50:23 INFO client.AHSProxy: Connecting to Application History server at hw02.ucera.local/172.18.4.47:10200
----- YARN cluster metrics -----
Number of YARN worker nodes: 3
----- Nodes -----
Node: http://HW03.ucera.local:8042 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 15.0 GB used, 0 / 3 vcores used
Node: http://HW04.ucera.local:8042 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 15.0 GB used, 0 / 3 vcores used
Node: http://HW02.ucera.local:8042 Rack: /default-rack, RUNNING, 0 containers used, 0.0 / 15.0 GB used, 0 / 3 vcores used
----- Queues -----
Queue name: default
Queue state: RUNNING
Current capacity: 0.00
Capacity: 1.00
Maximum capacity: 1.00
Application count: 0
Queue 'default' approximate utilization: 0.0 / 45.0 GB used, 0 / 9 vcores used
----------------------------------------------------------------------
ERROR: Unable to start any H2O nodes; please contact your YARN administrator.
A common cause for this is the requested container size (11.0 GB)
exceeds the following YARN settings:
yarn.nodemanager.resource.memory-mb
yarn.scheduler.maximum-allocation-mb
----------------------------------------------------------------------
For YARN users, logs command is 'yarn logs -applicationId application_1564020515809_0006'
Looking in the YARN configs in Ambari UI, these properties are nowhere to be found. But checking the YARN logs in the YARN resource manager UI and checking some of the logs for the killed application, I see what appears to be unreachable-host errors...
Container: container_e05_1564020515809_0006_02_000002 on HW03.ucera.local_45454_1564102219781
LogAggregationType: AGGREGATED
=============================================================================================
LogType:stderr
LogLastModifiedTime:Thu Jul 25 14:50:19 -1000 2019
LogLength:2203
LogContents:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/hadoop/yarn/local/filecache/11/mapreduce.tar.gz/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/hadoop/yarn/local/usercache/ml1user/appcache/application_1564020515809_0006/filecache/10/job.jar/job.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
log4j:WARN No appenders could be found for logger (org.apache.hadoop.mapred.YarnChild).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
java.net.NoRouteToHostException: No route to host (Host unreachable)
at java.net.PlainSocketImpl.socketConnect(Native Method)
....
at java.net.Socket.<init>(Socket.java:211)
at water.hadoop.EmbeddedH2OConfig$BackgroundWriterThread.run(EmbeddedH2OConfig.java:38)
End of LogType:stderr
***********************************************************************
Taking note of "java.net.NoRouteToHostException: No route to host (Host unreachable)". However, I can access all the other nodes from each other and they can all ping each other, so not sure what is going on here. Any suggestions for debugging or fixing?
Think I found the problem, TLDR: firewalld (nodes running on centos7) was still running, when should be disabled on HDP clusters.
From another community post:
For Ambari to communicate during setup with the hosts it deploys to and manages, certain ports must be open and available. The easiest way to do this is to temporarily disable iptables, as follows:
systemctl disable firewalld
service firewalld stop
So apparently iptables and firewalld need to be disabled across the cluster (supporting docs can be found here, I only disabled them on the Ambari installation node). After stopping these services across the cluster (I recommend using clush), was able to run the yarn job without incident.