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Practical concurrent Haskell = with big data applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Practical concurrent Haskell/ by Stefania Loredana Nita, Marius Mihailescu.
其他題名:	with big data applications /
作者:	Nita, Stefania Loredana.
其他作者:	Mihailescu, Marius.
出版者:	Berkeley, CA :Apress : : 2017.,
面頁冊數:	xv, 266 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Haskell (Computer program language) -
電子資源:	http://dx.doi.org/10.1007/978-1-4842-2781-7
ISBN:	9781484227817

Practical concurrent Haskell = with big data applications /
Nita, Stefania Loredana.

Practical concurrent Haskellwith big data applications /[electronic resource] :by Stefania Loredana Nita, Marius Mihailescu. - Berkeley, CA :Apress :2017. - xv, 266 p. :ill., digital ;24 cm.

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++.

ISBN: 9781484227817

Standard No.: 10.1007/978-1-4842-2781-7doiSubjects--Topical Terms:

567055
Haskell (Computer program language)

LC Class. No.: QA76.73.H37 / N583 2017

Dewey Class. No.: 005.133

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