View source for Install HDFS and YARN on the cluster

== Install Java ==
You need Java on each instance. We will use an older, stable version in case some of the tools are not upgraded to more recent versions:
 sudo apt update  # ('sudo apt upgrade' is also a good idea on a new instance)
 sudo apt install -y openjdk-8-jdk-headless
 export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64
 cp ~/.bashrc ~/.bashrc-bkp-$(date --iso-8601=minutes --utc)
 echo "export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64" >> ~/.bashrc

Explanation:
* ''export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64:'' sets an environment variable ''temporarily''
* ''cp ~/.bashrc ~/.bashrc-bkp-$(date --iso-8601=minutes --utc):'' creates a time-stamped backup of the initialisation file ''~/.bashrc''
* ''echo "export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64" >> ~/.bashrc:'' adds the ''export'' command to the initialisation so the environment variable becomes permanent

== Install Hadoop ==
On each instance, go to http://hadoop.apache.org and download a recent binary distribution to ''~/volume''. For example:
 cd ~/volume
 wget https://dlcdn.apache.org/hadoop/common/hadoop-3.3.4/hadoop-3.3.4.tar.gz
 tar xzvf hadoop-3.3.4.tar.gz
 rm hadoop-3.3.4.tar.gz
 ln -fns hadoop-3.3.4 hadoop

On each instance, set the environment variable HADOOP_HOME and add Hadoop's bin folder to your PATH:
 export HADOOP_HOME=/home/ubuntu/volume/hadoop
 export PATH=${PATH}:${HADOOP_HOME}/bin:${HADOOP_HOME}/sbin
 cp ~/.bashrc ~/.bashrc-bkp-$(date --iso-8601=minutes --utc)
 echo "export HADOOP_HOME=/home/ubuntu/volume/hadoop" >> ~/.bashrc
 echo "export PATH=\${PATH}:\${HADOOP_HOME}/bin:\${HADOOP_HOME}/sbin" >> ~/.bashrc

If something goes wrong with a file update, install a text editor to fix it, such as '''sudo apt emacs''' or '''sudo apt nano'''.

On each instance, set additional environment variables for Hadoop:
 export HADOOP_MAPRED_HOME=${HADOOP_HOME}
 export HADOOP_COMMON_HOME=${HADOOP_HOME}
 export HADOOP_HDFS_HOME=${HADOOP_HOME}
 export YARN_HOME=${HADOOP_HOME}
 export HADOOP_CONF=${HADOOP_HOME}/etc/hadoop
 export HADOOP_CONF_DIR=${HADOOP_CONF}
 export LD_LIBRARY_PATH=${HADOOP_HOME}/lib/native:${LD_LIBRARY_PATH}
 export HDFS_DATA=${HADOOP_HOME}/hdfs/data
 cp ~/.bashrc ~/.bashrc-bkp-$(date --iso-8601=minutes --utc)
 echo "export HADOOP_MAPRED_HOME=\${HADOOP_HOME}" >> ~/.bashrc
 echo "export HADOOP_COMMON_HOME=\${HADOOP_HOME}" >> ~/.bashrc
 echo "export HADOOP_HDFS_HOME=\${HADOOP_HOME}" >> ~/.bashrc
 echo "export YARN_HOME=\${HADOOP_HOME}" >> ~/.bashrc
 echo "export HADOOP_CONF=\${HADOOP_HOME}/etc/hadoop" >>  ~/.bashrc
 echo "export HADOOP_CONF_DIR=\${HADOOP_CONF}" >>  ~/.bashrc
 echo "export LD_LIBRARY_PATH=\${HADOOP_HOME}/lib/native:\${LD_LIBRARY_PATH}" >>  ~/.bashrc
 echo "export HDFS_DATA=\${HADOOP_HOME}/hdfs/data" >>  ~/.bashrc
 
 mkdir -p ${HDFS_DATA}  # this is where HDFS will store its data

On each instance, extract further environment variables from ''/etc/hosts'':
 export MASTER_NODE=$(grep spark-driver /etc/hosts | cut -d" " -f1)
 export HADOOP_NAMENODE=${MASTER_NODE}
 export NUM_WORKERS=$(grep spark- /etc/hosts | wc -l | cut -d" " -f1)
 cp ~/.bashrc ~/.bashrc-bkp-$(date --iso-8601=minutes --utc)
 echo "export MASTER_NODE=\$(grep spark-driver /etc/hosts | cut -d\" \" -f1)" >>  ~/.bashrc
 echo "export HADOOP_NAMENODE=\${MASTER_NODE}" >>  ~/.bashrc
 echo "export NUM_WORKERS=\$(grep spark- /etc/hosts | wc -l | cut -d\" \" -f1)" >>  ~/.bashrc

Create these four files on your local computer:

 File "core-site.xml":
 
 <configuration>
     <property>
         <name>fs.defaultFS</name>
         <value>hdfs://${HADOOP_NAMENODE}:9000</value>
     </property>
 </configuration>
 
 
 File "hdfs-site.xml":
 
 <configuration>
     <property>
         <name>dfs.replication</name>
         <value>${NUM_WORKERS}</value>
     </property>
     <property>
         <name>dfs.namenode.name.dir</name>
         <value>file://${HDFS_DATA}</value>
     </property>
     <property>
         <name>dfs.datanode.data.dir</name>
         <value>file://${HDFS_DATA}</value>
     </property>
 </configuration>
 
 
 File "yarn-site.xml":
 
 <configuration>
     <property>
         <name>yarn.nodemanager.aux-services</name>
         <value>mapreduce_shuffle</value>
     </property>
     <property>
         <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
         <value>org.apache.hadoop.mapred.ShuffleHandler</value>
     </property>
     <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>${HADOOP_NAMENODE}</value>
     </property>
 </configuration>
 
 
 File mapred-site.xml:
 
 <configuration>
     <property>
         <name>mapreduce.jobtracker.address</name>
         <value>${HADOOP_NAMENODE}</value>
     </property>
     <property>
         <name>mapreduce.framework.name</name>
         <value>yarn</value>
     </property>
 </configuration>
 
On your local machine:
 scp {core,hdfs,yarn}-site.xml spark-driver:
 scp {core,hdfs,yarn}-site.xml spark-worker-1:
 ...
 scp mapred-site.xml spark-driver:  # mapred-site.xml is only needed on the driver

On each instance:
 for name in core hdfs yarn mapred; do
     cp ${HADOOP_CONF}/${name}-site.xml ${HADOOP_CONF}/${name}-site.xml.original;
 done
 cd ~
 for name in *-site.xml; do
     envsubst < ${name} > ${HADOOP_CONF}/${name};
 done
 rm ~/*-site.xml

On each instance, define the master and worker IPv4 addresses, and do a few other preparations:
 grep spark-driver /etc/hosts | cut -d" " -f2 > ${HADOOP_CONF}/masters
 grep spark- /etc/hosts | cut -d" " -f2 > ${HADOOP_CONF}/workers
 echo "JAVA_HOME=$JAVA_HOME" >> $HADOOP_CONF/hadoop-env.sh
 mkdir -p -m 0777 $HADOOP_HOME/logs

== Run HDFS on the cluster ==
On ''spark-driver'':
 hdfs namenode -format  # answer 'Y' if you are asked about reformatting
 start-dfs.sh

On any instance, test it with
 hdfs dfs -mkdir -p /user/ubuntu/raw-data
 hdfs dfs -ls /user/ubuntu/  # on any machine in the spark-* cluster

From your local machine (this file is available at mitt.uib.no):
 scp head-100000-latest-all.json spark-ANY-INSTANCE:

On spark-ANY-INSTANCE:
 hdfs dfs -put ~/head-100000-latest-all.json raw-data

From another instance, use ''hdfs dfs -ls ...'' to check that the file is there.

On ''spark-driver'', stop HDFS again:
 stop-dfs.sh

== Run HDFS and YARN on the cluster ==
You are now ready to start YARN and HDFS together. On ''spark-drive'' run:
 start-all.sh

When you want to stop YARN and HDFS, use:
 stop-all.sh

== Web UIs ==
If you have opened the ports on ''spark-driver'', you can now access
* HDFS' web UI at http://158.39.77.125:9870
* YARN's web UI at http://158.39.77.125:8088
(assuming that 158.39.201.197 is the IPv4 address of ''spark-driver'').