Running JAR in Hadoop on Google Cloud using Yarn-client - hadoop

Question

i want to run a JAR in Hadoop on Google Cloud using Yarn-client.
i use this command in the master node of hadoop
spark-submit --class find --master yarn-client find.jar
but it return this error
15/06/17 10:11:06 INFO client.RMProxy: Connecting to ResourceManager at hadoop-m-on8g/10.240.180.15:8032
15/06/17 10:11:07 INFO ipc.Client: Retrying connect to server: hadoop-m-on8g/10.240.180.15:8032. Already tried 0
time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
What is the problem? In case it is useful this is my yarn-site.xml
<?xml version="1.0" ?>
<!--
<configuration>
<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/yarn-logs/</value>
<description>
The remote path, on the default FS, to store logs.
</description>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>hadoop-m-on8g</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>5999</value>
<description>

Answer 1

In your case, it looks like the YARN ResourceManager may be unhealthy for unknown reasons; you can try to fix yarn with the following:
sudo sudo -u hadoop /home/hadoop/hadoop-install/sbin/stop-yarn.sh
sudo sudo -u hadoop /home/hadoop/hadoop-install/sbin/start-yarn.sh
However, it looks like you're using the Click-to-Deploy solution; Click-to-Deploy's Spark + Hadoop 2 deployment actually doesn't support Spark on YARN at the moment, due to some bugs and lack of memory configs. You'd normally run into something like this if you just try to run it with --master yarn-client out-of-the-box:
15/06/17 17:21:08 INFO cluster.YarnClientSchedulerBackend: Application report from ASM:
appMasterRpcPort: -1
appStartTime: 1434561664937
yarnAppState: ACCEPTED
15/06/17 17:21:09 INFO cluster.YarnClientSchedulerBackend: Application report from ASM:
appMasterRpcPort: -1
appStartTime: 1434561664937
yarnAppState: ACCEPTED
15/06/17 17:21:10 INFO cluster.YarnClientSchedulerBackend: Application report from ASM:
appMasterRpcPort: 0
appStartTime: 1434561664937
yarnAppState: RUNNING
15/06/17 17:21:15 ERROR cluster.YarnClientSchedulerBackend: Yarn application already ended: FAILED
15/06/17 17:21:15 INFO handler.ContextHandler: stopped o.e.j.s.ServletContextHandler{/metrics/json,null}
15/06/17 17:21:15 INFO handler.ContextHandler: stopped o.e.j.s.ServletContextHandler{/stages/stage/kill,null}
The well-supported way to deploy is a cluster on Google Compute Engine with Hadoop 2 and Spark configured to be able to run on YARN is to use bdutil. You'd run something like:
./bdutil -P <instance prefix> -p <project id> -b <bucket> -z <zone> -d \
-e extensions/spark/spark_on_yarn_env.sh generate_config my_custom_env.sh
./bdutil -e my_custom_env.sh deploy
# Shorthand for logging in to the master
./bdutil -e my_custom_env.sh shell
# Handy way to run a socks proxy to make it easy to access the web UIs
./bdutil -e my_custom_env.sh socksproxy
# When done, delete your cluster
./bdutil -e my_custom_env.sh delete
With spark_on_yarn_env.sh Spark should default to yarn-client, though you can always re-specify --master yarn-client if you want. You can see a more detailed explanation of the flags available in bdutil with ./bdutil --help. Here are the help entries just for the flags I included above:
-b, --bucket
Google Cloud Storage bucket used in deployment and by the cluster.
-d, --use_attached_pds
If true, uses additional non-boot volumes, optionally creating them on
deploy if they don't exist already and deleting them on cluster delete.
-e, --env_var_files
Comma-separated list of bash files that are sourced to configure the cluster
and installed software. Files are sourced in order with later files being
sourced last. bdutil_env.sh is always sourced first. Flag arguments are
set after all sourced files, but before the evaluate_late_variable_bindings
method of bdutil_env.sh. see bdutil_env.sh for more information.
-P, --prefix
Common prefix for cluster nodes.
-p, --project
The Google Cloud Platform project to use to create the cluster.
-z, --zone
Specify the Google Compute Engine zone to use.