| Περίληψη: | Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you'll set up the Scala environment ready for examining your first Scala programs. You'll start with code blocks that allow you to group and execute related statements together as a block and see the implications for Scala's type system. The author discusses functions at length and highlights a number of associated concepts such as zero-parity functions, single-line functions, and anonymous functions. Along the way you'll see the development life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You'll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics. You will: See the fundamentals of Scala as a general-purpose programming language Understand functional programming and object-oriented programming constructs in Scala Comprehend the use and various features of Scala REPL (shell) Use Scala collections and functions Employ functional programming constructs.
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