Book Image

.NET Design Patterns

By : Praseed Pai, Shine Xavier
Book Image

.NET Design Patterns

By: Praseed Pai, Shine Xavier

Overview of this book

Knowing about design patterns enables developers to improve their code base, promoting code reuse and making their design more robust. This book focuses on the practical aspects of programming in .NET. You will learn about some of the relevant design patterns (and their application) that are most widely used. We start with classic object-oriented programming (OOP) techniques, evaluate parallel programming and concurrency models, enhance implementations by mixing OOP and functional programming, and finally to the reactive programming model where functional programming and OOP are used in synergy to write better code. Throughout this book, we’ll show you how to deal with architecture/design techniques, GoF patterns, relevant patterns from other catalogs, functional programming, and reactive programming techniques. After reading this book, you will be able to convincingly leverage these design patterns (factory pattern, builder pattern, prototype pattern, adapter pattern, facade pattern, decorator pattern, observer pattern and so on) for your programs. You will also be able to write fluid functional code in .NET that would leverage concurrency and parallelism!
Table of Contents (22 chapters)
.NET Design Patterns
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

MapReduce programming idiom


In the FP world, MapReduce is considered as a programming idiom.

Note

The process of mapping can be described as the application of a function or computation on each element of a sequence to produce a new sequence. Reduction gathers computed elements to produce the result of a process, algorithm, or a functional transformation.

In 2003, two Google engineers (Sanjay Ghemawat and Jeff Dean) published a paper about how the company used the MapReduce programming model to simplify their distributed programming tasks. The paper entitled MapReduce: Simplified Data Processing on Large Clusters is available on the public domain. This particular paper was very influential, and the Hadoop distributed programming model was based on the ideas outlined in the paper. You can search the Internet to find the details of the paper and the origin of the Hadoop data operating system.

To reduce the complexity, we are going to implement a MapReduce function to apply the computation on an...