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Scala Data Analysis Cookbook

You're reading from  Scala Data Analysis Cookbook

Product type Book
Published in Oct 2015
Publisher
ISBN-13 9781784396749
Pages 254 pages
Edition 1st Edition
Languages
Author (1):
Arun Manivannan Arun Manivannan
Profile icon Arun Manivannan

Table of Contents (14) Chapters

Scala Data Analysis Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with Breeze 2. Getting Started with Apache Spark DataFrames 3. Loading and Preparing Data – DataFrame 4. Data Visualization 5. Learning from Data 6. Scaling Up 7. Going Further Index

Creating a DataFrame from Scala case classes


In this recipe, we'll see how to create a new DataFrame from Scala case classes.

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/DataFrameFromCaseClasses.scala.

How to do it...

  1. We create a new entity called Employee with the id and name fields, like this:

    case class Employee(id:Int, name:String)
    

    Similar to the previous recipe, we create SparkContext and SQLContext.

    val conf = new SparkConf().setAppName("colRowDataFrame").setMaster("local[2]")
    
    //Initialize Spark context with Spark configuration.  This is the core entry point to do anything with Spark
    val sc = new SparkContext(conf)
    
    //The easiest way to query data in Spark is to use SQL queries.
    val sqlContext=new SQLContext(sc)
    
  2. We can source these employee objects from a variety of sources, such as an RDBMS data source, but for the sake of this example, we construct a list...

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