Data Parallel Computing with Spark

Estimated time 60 minutes

Overview

Questions

• How does Linux come to be?

Objectives

• Explain the historical development of Linux

Data parallel computing with Spark

Hands-on: Data analytics in Spark

• Download Move Dataset
• Unzip the movie data file.
• Open a terminal.
• Activate the pyspark conda environment, then launch Jupyter notebook

$ conda activate pyspark
$ jupyter notebook

• Create a new notebook using the pyspark kernel, then change the notebook’s name to spark-2.
• Copy the code from spark-1 to setup and launch a Spark application.

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