Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/1192
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dc.contributor.authorNita, Stefania Loredana. ;en_US
dc.contributor.authorMihailescu, Marius. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:26:23Z-
dc.date.available2020-05-17T08:26:23Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484227817 ;en_US
dc.identifier.isbn9781484227800 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/1192-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484227800. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn 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.e 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. eYou'll use MapReduce and other, similar big data tools as part of your Haskell big data applications development. e 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++. ;en_US
dc.description.statementofresponsibilityby Stefania Loredana Nita, Marius Mihailescu.en_US
dc.format.extentXV, 266 p. 26 illus., 19 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484227817.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectComputer Scienceen_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.subjectProgramming Techniquesen_US
dc.titlePractical Concurrent Haskellen_US
dc.title.alternativeWith Big Data Applications /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.76.C65 ;en_US
dc.classification.dc005.13 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorNita, Stefania Loredana. ;en_US
dc.contributor.authorMihailescu, Marius. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:26:23Z-
dc.date.available2020-05-17T08:26:23Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484227817 ;en_US
dc.identifier.isbn9781484227800 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/1192-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484227800. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn 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.e 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. eYou'll use MapReduce and other, similar big data tools as part of your Haskell big data applications development. e 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++. ;en_US
dc.description.statementofresponsibilityby Stefania Loredana Nita, Marius Mihailescu.en_US
dc.format.extentXV, 266 p. 26 illus., 19 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484227817.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectComputer Scienceen_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.subjectProgramming Techniquesen_US
dc.titlePractical Concurrent Haskellen_US
dc.title.alternativeWith Big Data Applications /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.76.C65 ;en_US
dc.classification.dc005.13 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484227817.pdf3.78 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNita, Stefania Loredana. ;en_US
dc.contributor.authorMihailescu, Marius. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:26:23Z-
dc.date.available2020-05-17T08:26:23Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484227817 ;en_US
dc.identifier.isbn9781484227800 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/1192-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484227800. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn 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.e 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. eYou'll use MapReduce and other, similar big data tools as part of your Haskell big data applications development. e 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++. ;en_US
dc.description.statementofresponsibilityby Stefania Loredana Nita, Marius Mihailescu.en_US
dc.format.extentXV, 266 p. 26 illus., 19 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484227817.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectComputer Scienceen_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.subjectProgramming Techniquesen_US
dc.titlePractical Concurrent Haskellen_US
dc.title.alternativeWith Big Data Applications /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.76.C65 ;en_US
dc.classification.dc005.13 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484227817.pdf3.78 MBAdobe PDFThumbnail
Preview File