Description: As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The book delineates many concepts, models, methods, algorithms, and software used in cloud computing. After a general introduction to the field, the text covers resource management, including scheduling algorithms for real-time tasks and practical algorithms for user bidding and auctioneer pricing. It next explains approaches to data analytical query processing, including pre-computing, data indexing, and data partitioning. Applications of MapReduce, a new parallel programming model, are then presented. The authors also discuss how to optimize multiple group-by query processing and introduce a MapReduce real-time scheduling algorithm. A useful reference for studying and using MapReduce and cloud computing platforms, this book presents various technologies that demonstrate how cloud computing can meet business requirements and serve as the infrastructure of multidimensional data analysis applications.
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EAN: 9780367380847
UPC: 9780367380847
ISBN: 9780367380847
MPN: N/A
Book Title: Cloud Computing: Data-Intensive Computing and Sche
Item Length: 23.1 cm
Number of Pages: 232 Pages
Language: English
Publication Name: Cloud Computing: Data-Intensive Computing and Scheduling
Publisher: Taylor & Francis Ltd
Publication Year: 2019
Subject: Computer Science
Item Height: 229 mm
Item Weight: 340 g
Type: Textbook
Author: Jie Pan, Frederic Magoules, Fei Teng
Item Width: 152 mm
Format: Paperback