Practical Concurrent Haskell
- نوع فایل : کتاب
- زبان : انگلیسی
- نویسندگان : Marius Mihailescu, Stefania Loredana Nita
- چاپ و سال / کشور: 2017
- تعداد صفحه : 266
- شابک / ISBN : 1484227808
Description
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++.
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++.
