Programming in scala a comprehensive step-by-step guide pdf

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Get started with a FREE account. Apache Spark is amazing when everything clicks. Develop applications for the big data landscape with Spark and Hadoop. An error occurred, please try again later. Programming inScala Second EditionUpdated for Scala 2. This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below! Programming in Scala Second Edition Martin Odersky is the creator of the Scala language and a professor at EPFL in Lausanne, Switzerland. Book 2010 Second edition published 2010 Build date of this impression December 13, 2010 Produced in the United States of America No part of this publication may be reproduced, modified, distributed, stored in a retrieval system, republished, displayed, or performed, for commercial or noncommercial purposes or for compensation of any kind without prior written permission from Artima, Inc. Overview Contents List of Figures List of Tables List of Listings Foreword Foreword to the First Edition Acknowledgments Introduction 1. Concise access to related code Imports . The sequence traits Seq, IndexedSeq, and LinearSeq Sets . Conversions between Java and Scala collections . Treating native threads as actors . Better performance through thread reuse . Parallel discrete event simulation Conclusion . Writing a test method with Suite. Writing a test function with FunSuite. Writing a JUnit test with JUnit3Suite. Writing a TestNG test with TestNGSuite. Specifying and testing behavior with the specs framework. Mixing in the SynchronizedMap trait. An actor that uses a helper actor to avoid blocking itself. An actor that uses case classes for messages. I first came across the Scala language. David Pollak, creator of the Lift web framework, and Steve Jenson, a former colleague at Twitter and generally brilliant programmer. The mailing lists were full of spirited debates, announcements of exciting libraries, and a general camaraderie and shared joy for seeing what this powerful new tool could do. What Scala lacked, at that point, was a collection of success stories around major production deployments. The decision to use Scala at Twitter, where I then worked, was not an easy one to make. Our infrastructure was buckling under the weight of extreme growth. To understand Scala, though, is to understand its goal of being a scalable language. Scala there to wield to your advantage. Each feature of the language is another light bulb waiting to switch on over your head. It can be done, and it can be fun. While Scala has been a perfectly productive language to work with for some time, as of 2. In my experience, Scala was ready for production deployments two years ago. For me, Scala has gone from being a risky gamble to a trusted tool in two short years. I look forward to taking advantage of the latest features in Scala 2. Foreword to the First Edition Martin Odersky made a huge impact on the Java world with his design of the Pizza language. Meanwhile, Martin continued his work on more powerful orthogonal language primitives that allow programmers to provide solutions in libraries. Lately, there has been a backlash against statically typed languages. Experience with Java has shown that programming in a static language results in an abundance of boilerplate. The common wisdom is that one must abandon static typing to eliminate the boilerplate, and there is a rising interest in dynamic languages such as Python, Ruby, and Groovy. The syntax is so lightweight, and its primitives so expressive, that APIs can be used with virtually no syntactic overhead at all. Examples can be found in standard libraries such as parser combinators and actors. Will Scala be the next great language? Scala sets a new standard against which future languages will be measured. Acknowledgments Francisco Reverbel, Jim Balter, and Freek de Bruijn. Lastly, Bill would also like to thank Gary Cornell, Greg Doench, Andy Hunt, Mike Leonard, Tyler Ortman, Bill Pollock, Dave Thomas, and Adam Wright for providing insight and advice on book publishing. Although the same pages appear in the eBook as the printed book, blank pages are removed and the remaining pages renumbered. The chapter concludes with a case study on discrete event simulation, which shows some stateful objects in action. Not only methods, but also fields and types can be declared abstract. If you find an error, please report it at the above URL, so that we can be sure to fix it in a future printing or edition of this book. Associative maps are very useful because they help keep programs legible and concise. As multicore processors proliferate in the coming years, achieving acceptable performance may increasingly require that you exploit more parallelism in your applications. If the mailbox does not contain any messages that match one of the filexlib.
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