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Concurrent Patterns and Best Practices

Concurrent Patterns and Best Practices

By : S. Khot
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Concurrent Patterns and Best Practices

Concurrent Patterns and Best Practices

5 (1)
By: S. Khot

Overview of this book

Selecting the correct concurrency architecture has a significant impact on the design and performance of your applications. Concurrent design patterns help you understand the different characteristics of parallel architecture to make your code faster and more efficient. This book will help Java developers take a hands-on approach to building scalable and distributed apps by following step-by-step explanations of essential concepts and practical examples. You’ll begin with basic concurrency concepts and delve into the patterns used for explicit locking, lock-free programming, futures, and actors. You’ll explore coding with multithreading design patterns, including master, slave, leader, follower, and map-reduce, and then move on to solve problems using synchronizer patterns. You'll even discover the rationale for these patterns in distributed and parallel applications, and understand how future composition, immutability, and the monadic flow help you create more robust code. By the end of the book, you’ll be able to use concurrent design patterns to build high performance applications confidently.
Table of Contents (9 chapters)
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Concurrency – An Introduction

–What are concurrency and parallelism? Why should we study them? In this chapter, we will look at the many aspects of the concurrent programming world. The chapter starts with a brief overview of parallel programming and why we need it.  We cover ground pretty fast here, touching upon the basic concepts. 

As two major forces, huge data size and fault tolerance drive concurrent programming. As we go through this chapter, some of our examples will touch upon some clustered computing patterns, such as MapReduceApplication scaling is an extremely important concept for today's developer. We will look at how concurrency helps applications scale. Horizontal scaling (https://stackoverflow.com/questions/11707879/difference-between-scaling-horizontally-and-vertically-for-databases) is the magic behind today's massively parallel software systems. 

Concurrency entails communication between the concurrent entities. We will look at two primary concurrency models: message passing and shared memory. We will describe the message passing model using a UNIX shell pipeline. We will then describe the shared memory model and show how explicit synchronization creates so many problems.   

A design pattern is a solution to a design problem in context. Knowledge of the catalog of patterns helps us to come up with a good design for specific problems. This book explains the common concurrency design pattern.   

We will wrap up the chapter by looking at some alternative ways of achieving concurrency, namely the actor paradigm and software transactional memory.  

In this chapter, we will cover the following topics:

  • Concurrency
  • Message passing model  
  • Shared memory and shared state model
  • Of patterns and paradigms
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