Programming Spark transformations and actions

In this section, we will leverage the various functions exposed by RDD APIs and analyze our Chicago crime dataset. We will start with simple operations and move on to the complex transformations. First, let's create/define some base classes and then we will develop our transformation logic.

Perform the following steps to write the basic building blocks:

1. We will extend our Spark-Examples projects and create a new Scala class by the name of chapter.seven.ScalaCrimeUtil.scala. This class will contain some utility functions that will be utilized by our main transformation job.

2. Open and edit ScalaCrimeUtil.scala and add the following piece of code:

   package chapter.seven
   
   class ScalaCrimeUtil extends Serializable{
     
      /**
      * Create a Map of the data which is extracted by applying Regular expression.
      */
     def createDataMap(data:String): Map[String, String] = {
       
       //Replacing Empty columns with the blank Spaces, 
       //so that split function...