I have set up a hadoop cluster with 3 machines one master and 2 slave In the master i have installed spark
SPARK_HADOOP_VERSION=2.4.0 SPARK_YARN=true sbt/sbt clean assembly
Added HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop spark-env.sh
Then i ran SPARK_JAR=./assembly/target/scala-2.10/spark-assembly-1.0.0-SNAPSHOT-hadoop2.4.0.jar HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop ./bin/spark-submit --master yarn --deploy-mode cluster --class org.apache.spark.examples.SparkPi --num-executors 3 --driver-memory 4g --executor-memory 2g --executor-cores 1 examples/target/scala-2.10/spark-examples-1.0.0-SNAPSHOT-hadoop2.4.0.jar
I checked localhost:8088 and i saw application SparkPi running..
Is it just this or i should install spark in the 2 slave machines.. How can i get all the machine started?
Is there any help doc out there.. I feel like i am missing something..
In spark standalone more we start the master and worker ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT
i also wanted to know how to get more than one worked running in this case as well
and i know we can can configure slaves in conf/slave but can anyone share an example
Please help i am stuck
Assuming you're using Spark 1.1.0, as it says in the documentation (http://spark.apache.org/docs/1.1.0/submitting-applications.html#master-urls), for the master parameter you can use values yarn-cluster or yarn-client. You do not need to use deploy-mode parameter in that case.
You do not have to install Spark on all the YARN nodes. That is what YARN is for: to distribute your application (in this case Spark) over a Hadoop cluster.