Steps

• Install SBT: brew install sbt
• Copy this directory
• Remove the .git setup: rm -rf .git
• Change the project name and version in build.sbt
• Change the project name in src/main/scala/myproject/Main.scala
• Run an sbt console just to check if everything's ok: sbt console. It could take a few minutes the first time. It will will create the directories project/target and target (which are .gitignored). The result is a scala 2.10.4 console, with all the project dependencies loaded.
• Optionnaly intitialize a new git project: git init

Import the project in IntelliJ IDEA

• Start IntelliJ IDEA. In the Welcome window, click on "Import Project"
• Enter the project path
• Choose the external model SBT
• Check
  • Use auto-import
  • Download sources and docs
• Choose a Project SDK with a version >= 1.7.
• Move the Main and Schema classes to your package name
• Right-click on the Main class and click Run Main

Build and run your Spark job on a Spark cluster

We use sbt-assembly to bundle the application in a fat JAR, ready to be submitted to a Spark cluster. The JAR must not include the Spark components (spark-core, spark-sql, hadoop-client, etc) and their dependencies.

To build the JAR:

• first exit Intellij IDEA if it's configured to track the changes to build.sbt
• edit build.sbt, to switch the spark-* and hadoop-* dependencies (see the comments inside build.sbt)
• run sbt assembly. The generated is in target/scala-2.10/{projectname}-assembly-{version}.jar

TODO: try to remove the manual part of editing build.sbt.

To submit the JAR:

• scp the JAR on the spark master
• ssh on the spark master
• to prevent the job from stopping if you disconnect from the server, run: screen
• submit the JAR with the command: ~/spark/bin/spark-submit --master spark://ec2-w-x-y-z.eu-west-1.compute.amazonaws.com:7077 --class io.basilic.MySparkJob ~/MyProject-assembly-1.0.jar > /mnt/job.out &> /mnt/job.err
• tail logs with: tail -f /mnt/job.{out,err}

Treats

• Visualize the graph of dependencies with the command sbt dependency-graph.

Starting a Spark Cluster on EC2

TODO: write this paragraph

TODO: By default, spark-ec2 runs with hadoop-client on 1.0.4.
  One can also run the cluster on 2.0.x with `--hadoop-major-version=2`,
  which is an alpha version. @see http://mvnrepository.com/artifact/org.apache.hadoop/hadoop-client
  spark-ec2 does not provide a way to use the stable 2.4
  It would be nice to find a way to run spark-ec2 with the hadoop-client 2.4.x.
  @see https://groups.google.com/d/msg/spark-users/pHaF01sPwBo/faHr-fEAFbYJ