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商品描述
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.
商品描述(中文翻譯)
隨著數據生成的速度越來越快,處理大量數據對數據分析軟體來說正變得越來越具挑戰性。針對性能問題,雲端運算:數據密集型計算與排程 探討了經典技術的演變,並描述了全新的方法和創新算法。本書詳細闡述了雲端運算中使用的許多概念、模型、方法、算法和軟體。
在對該領域進行一般介紹後,文本涵蓋了資源管理,包括實時任務的排程算法以及用戶競標和拍賣定價的實用算法。接下來解釋了數據分析查詢處理的方法,包括預計算、數據索引和數據分區。然後介紹了 MapReduce 的應用,這是一種新的並行編程模型。作者還討論了如何優化多重 group-by 查詢處理,並介紹了一種 MapReduce 實時排程算法。
本書是學習和使用 MapReduce 及雲端運算平台的有用參考,展示了雲端運算如何滿足商業需求並作為多維數據分析應用的基礎設施。