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Titlebook: Stream Data Management; Nauman A. Chaudhry,Kevin Shaw,Mahdi Abdelguerfi Book 2005 Springer-Verlag US 2005 Extensible Markup Language (XML)

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發(fā)表于 2025-3-21 17:25:14 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Stream Data Management
編輯Nauman A. Chaudhry,Kevin Shaw,Mahdi Abdelguerfi
視頻videohttp://file.papertrans.cn/880/879479/879479.mp4
概述Introduces a coherent body of work spanning various aspects of streaming data.Comprises eight invited chapters by well-distinguished researchers active in stream data management.The collected chapters
叢書名稱Advances in Database Systems
圖書封面Titlebook: Stream Data Management;  Nauman A. Chaudhry,Kevin Shaw,Mahdi Abdelguerfi Book 2005 Springer-Verlag US 2005 Extensible Markup Language (XML)
描述.Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. ..Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. ..Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science
出版日期Book 2005
關(guān)鍵詞Extensible Markup Language (XML); Windows; algorithms; computer science; database; optimization
版次1
doihttps://doi.org/10.1007/b106968
isbn_softcover978-1-4419-3738-4
isbn_ebook978-0-387-25229-2Series ISSN 1386-2944
issn_series 1386-2944
copyrightSpringer-Verlag US 2005
The information of publication is updating

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發(fā)表于 2025-3-21 22:50:28 | 只看該作者
Query Execution and Optimization,assume the environment is completely dynamic and highly unpredictable. In this chapter we explore both approaches and present novel query optimization and evaluation techniques for queries over streaming sources.
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Introduction to Stream Data Management,ibed and the challenges for data management systems in supporting these requirements are identified. This is followed by a description of solutions aimed at providing the required functionality. The chapter concludes with a tour of the rest of the chapters in the book.
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Filtering, Punctuation, Windows and Synopses,r query processing over such streams, such as outstripping CPU or memory resources, operators that wait for the end of input and unbounded query state. We then consider various techniques for meeting those challenges. . attempts to reduce stream volume in order to save on system resources. . incorpo
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發(fā)表于 2025-3-23 06:55:07 | 只看該作者
XML & Data Streams,groups. . algorithms compute results by analyzing an input stream of documents one tag at a time. In contrast, . algorithms take advantage of (precomputed or computed-on-demand) numbering schemes over each input XML document in the stream. In this chapter, we present an index-based technique, ., to
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