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Practical Concurrent Haskell

With Big Data Applications

  • Stefania Loredana Nita
  • Marius Mihailescu

Table of contents

  1. Front Matter
    Pages i-xv
  2. Haskell Foundations. General Introductory Notions

    1. Front Matter
      Pages 1-1
    2. Stefania Loredana Nita, Marius Mihailescu
      Pages 3-11
    3. Stefania Loredana Nita, Marius Mihailescu
      Pages 13-46
    4. Stefania Loredana Nita, Marius Mihailescu
      Pages 47-65
    5. Stefania Loredana Nita, Marius Mihailescu
      Pages 67-76
    6. Stefania Loredana Nita, Marius Mihailescu
      Pages 77-86
    7. Stefania Loredana Nita, Marius Mihailescu
      Pages 87-100
    8. Stefania Loredana Nita, Marius Mihailescu
      Pages 101-112
    9. Stefania Loredana Nita, Marius Mihailescu
      Pages 113-131
  3. Haskell for Big Data and Cloud Computing

    1. Front Matter
      Pages 133-133
    2. Stefania Loredana Nita, Marius Mihailescu
      Pages 135-164
    3. Stefania Loredana Nita, Marius Mihailescu
      Pages 165-175
    4. Stefania Loredana Nita, Marius Mihailescu
      Pages 177-194
    5. Stefania Loredana Nita, Marius Mihailescu
      Pages 195-203
    6. Stefania Loredana Nita, Marius Mihailescu
      Pages 205-220
    7. Stefania Loredana Nita, Marius Mihailescu
      Pages 221-230
    8. Stefania Loredana Nita, Marius Mihailescu
      Pages 231-235
    9. Stefania Loredana Nita, Marius Mihailescu
      Pages 237-245
    10. Stefania Loredana Nita, Marius Mihailescu
      Pages 247-252
  4. Back Matter
    Pages 253-266

About this book

Introduction

Learn to use the APIs and frameworks for parallel and concurrent applications in Haskell. This book will show you how to exploit multicore processors with the help of parallelism in order to increase the performance of your applications. 

Practical Concurrent Haskell teaches you how concurrency enables you to write programs using threads for multiple interactions. After accomplishing this, you will be ready to make your move into application development and portability with applications in cloud computing and big data.  You'll use MapReduce and other, similar big data tools as part of your Haskell big data applications development.  

What You'll Learn
  • Program with Haskell
  • Harness concurrency to Haskell
  • Apply Haskell to big data and cloud computing applications
  • Use Haskell concurrency design patterns in big data
  • Accomplish iterative data processing on big data using Haskell
  • Use MapReduce and work with Haskell on large clusters

Who This Book Is For

Those with at least some prior experience with Haskell and some prior experience with big data in another programming language such as Java, C#, Python, or C++.

Keywords

Haskell programming big data language concurrent threads parallel concurrency cloud applications practical

Authors and affiliations

  • Stefania Loredana Nita
    • 1
  • Marius Mihailescu
    • 2
  1. 1.BucharestRomania
  2. 2.BucharestRomania

Bibliographic information