Practical session, introduction to Spark

Apache Spark

Purpose

• Getting up and running with
• Getting experience with non-trivial installation
• Using IntelliJ IDEA.
• Writing and running your own first Spark program

For a general introduction, see the slides to Session 2 on Apache Spark. Here is a useful tutorial: https://www.tutorialspoint.com/spark_sql/spark_introduction.htm . Configuring Spark dependency in InjelliJ IDEA http://spark.apache.org/docs/latest/rdd-programming-guide.html

Preparations

As for Hadoop, you will run Spark standalone on your computers (and independently of your previous Hadoop installation to keep things simple). Running Spark on a cluster of many computers is harder to set up (and you will need a cluster of computers), but after that, the coding and running of code is the same. Installing Spark Standalone to a Cluster http://spark.apache.org/docs/latest/spark-standalone.html

Follow these preparations to install Spark on your Linux or Windows-machine. If you are on MacOS, it runs BSD Unix under the hood, so most Linux-commands should work in a Terminal window on your Mac too.

Tasks

• Getting started with Apache Spark

Steps

1 - Install Spark:

https://wiki.uib.no/info310/index.php/Spark_preparations

Linux: [1]

2 – Install IntelliJ IDE

               https://www.jetbrains.com/idea/

3 – Install Scala plugin in IntelliJ

https://docs.scala-lang.org/getting-started-intellij-track/getting-started-with-scala-in-intellij.html

4 - Linking spark with intellij

Scala: [2] Python: [3]

http://spark.apache.org/docs/latest/rdd-programming-guide.html

5 – Do some exercise tasks

Extra links:

Apache Spark with Python:

• Install and Setup Apache Spark 2.2.0 Python in Windows - PySpark: [4]
• Setup Jupyter Notebook for Apache Spark: [5]