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)

Java interoperability

As we mentioned earlier, Scala has very rich collection API. The same applies for Java but there are lots of differences between the two collection APIs. For example, both APIs have iterable, iterators, maps, sets, and sequences. But Scala has advantages; it pays more attention to immutable collections and provides more operations for you in order to produce another collection. Sometimes, you want to use or access Java collections or vice versa.

JavaConversions is no longer a sound choice. JavaConverters makes the conversion between Scala and Java collection explicit and you'll be much less likely to experience implicit conversions you didn't intend to use.

As a matter of fact, it's quite trivial to do so because Scala offers in an implicit way to convert between both APIs in the JavaConversion object. So, you might find bidirectional conversions...