Scala Programming Introduction
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The document outlines an introduction to Scala programming, focusing on the differences between functional and imperative programming, the fundamentals of Scala, and its integration with Apache Spark. It emphasizes the advantages of functional programming, such as reduced side effects, more concise code, and lazy evaluation. Additionally, it highlights Scala's unique features like type inference, case classes, and its collections framework compared to Java.
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- 1. Scala Programming Introduction March 10, 2016
- 2. Agenda Functional Programming Vs Imperative Programming Why Functional Programming? Scala Programming Fundamentals REPL Scala Runnable Program Scala classes and objects Tuples Scala Collections Vs Java Collections Apache Spark Scala API Intro
- 3. Imperative Versus Functional Programming In imperative approach, a developer writes code that describes in exacting detail the steps that the computer must take to accomplish the goal. Functional approach involves composing the problem as a set of functions to be executed. “Pure Functions” makes the order of execution irrelevant - since no side- effect can change the value of an expression, it can be evaluated at any time. Characteristic Imperative approach Functional approach Programmer focus How to perform tasks (algorithms) and how to track changes in state. What information is desired and what transformations are required. State changes Important. Non-existent. Order of execution Important. Low importance. Primary flow control Loops, conditionals, and function (method) calls. Function calls, including recursion. Primary manipulation unit Instances of structures or classes. Functions as first-class objects and data collections.
- 4. Why Functional Programming? Describe what you want, rather than how to get it. Instead of creating a for-loop with an iterator variable and marching through an collection doing something to each cell, pass a function and it will be executed for all the elements in the collection which can be optimized More concise and expressive code Functional programming moves more basic programming ideas into the compiler. Syntactic Sugar – case classes, pattern matching Type Inference List comprehension conversion to primitives, tail recursion Implicit conversions Concurrency No Shared mutable state – so no locking required Pure functional languages support lazy evaluation. Can create infinitely large collections Value will be calculated only when required and function call be substituted in place of functional value (Referential integrity)
- 5. Scala Programming Fundamentals Scala brings together concepts from both Functional Programming and Objected Oriented Programming. Provides a more comprehensive API, a superior compiler but stills runs on the JVM. Demos: REPL Runnable Program in Scala Scala classes and Objects Tuples
- 10. Why Spark Uses Scala?
- 11. Apache Spark Execution Model Transformations + lazy evaluation = Optimization