Book Image

Scala and Spark for Big Data Analytics

By : Md. Rezaul Karim, Sridhar Alla
Book Image

Scala and Spark for Big Data Analytics

By: Md. Rezaul Karim, Sridhar Alla

Overview of this book

Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big.
Table of Contents (19 chapters)

Implicit in Scala

Implicit is another exciting and powerful feature introduced by Scala, and it can refer to two different things:

  • A value that can be automatically passed
  • Automatic conversion from one type to another
  • They can be used for extending the capabilities of a class

Actual automatic conversion can be accomplished with implicit def, as seen in the following example (supposing you are using the Scala REPL):

scala> implicit def stringToInt(s: String) = s.toInt
stringToInt: (s: String)Int

Now, having the preceding code in my scope, it's possible for me to do something like this:

scala> def add(x:Int, y:Int) = x + y
add: (x: Int, y: Int)Int

scala> add(1, "2")
res5: Int = 3
scala>

Even if one of the parameters passed to add() is a String (and add() would require you to provide two integers), having the implicit conversion in scope allows the compiler...