Creating a DataFrame from CSV

In this recipe, we'll look at how to create a new DataFrame from a delimiter-separated values file.

Note

The code for this recipe can be found at https://github.com/arunma/ScalaDataAnalysisCookbook/blob/master/chapter1-spark-csv/src/main/scala/com/packt/scaladata/spark/csv/DataFrameCSV.scala.

How to do it...

This recipe involves four steps:

1. Add the spark-csv support to our project.

2. Create a Spark Config object that gives information on the environment that we are running Spark in.

3. Create a Spark context that serves as an entry point into Spark. Then, we proceed to create an SQLContext from the Spark context.

4. Load the CSV using the SQLContext.

5. CSV support isn't first-class in Spark, but it is available through an external library from Databricks. So, let's go ahead and add that to our build.sbt.

   After adding the spark-csv dependency, our complete build.sbt looks like this:

   organization := "com.packt"
   
   name := "chapter1-spark-csv"
   
   scalaVersion := "2.10.4"
   
   val sparkVersion...