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Fast Data Processing Systems with SMACK Stack

You're reading from  Fast Data Processing Systems with SMACK Stack

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781786467201
Pages 376 pages
Edition 1st Edition
Languages
Author (1):
Raúl Estrada Raúl Estrada
Profile icon Raúl Estrada

Table of Contents (15) Chapters

Fast Data Processing Systems with SMACK Stack
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
An Introduction to SMACK The Model - Scala and Akka The Engine - Apache Spark The Storage - Apache Cassandra The Broker - Apache Kafka The Manager - Apache Mesos Study Case 1 - Spark and Cassandra Study Case 2 - Connectors Study Case 3 - Mesos and Docker

The language - Scala


The objective of this section is to think in a functional programming way.

As good data architects, here we will understand collections. We will not cover other issues of the language other than collection management.

We need to be clear regarding the following two statements:

  • Scala collections are different from Java collections
  • Scala collections are different from Spark collections

So, a list in Java is different from a list in Scala. Lists are a fundamental part of functional languages. The first functional programming language, LISP, is an acronym for List Processing.

We have to master three key concepts of functional programming to understand Scala collections:

  • Predicates
  • Literal functions (anonymous functions)
  • Implicit loops

A predicate is just a function that receives several parameters and returns a Boolean value.

For example:

def isOdd (i: Int) = if (i % 2 != 0) true else false 

A literal function is an alternate syntax for defining a function. It's useful when we want...

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