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  • © 2005

Stream Data Management

  • 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 provide exposition of algorithms and languages, as well as systems proposed and implemented from managing streaming data

Part of the book series: Advances in Database Systems (ADBS, volume 30)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
  2. Introduction to Stream Data Management

    • Nauman A. Chaudhry
    Pages 1-13
  3. Query Execution and Optimization

    • Stratis D. Viglas
    Pages 15-33
  4. Filtering, Punctuation, Windows and Synopses

    • David Maier, Peter A. Tucker, Minos Garofalakis
    Pages 35-58
  5. XML & Data Streams

    • Nicolas Bruno, Luis Gravano, Nick Koudas, Divesh Srivastava
    Pages 59-81
  6. CAPE: A Constraint-Aware Adaptive Stream Processing Engine

    • Elke A. Rundensteiner, Luping Ding, Yali Zhu, Timothy Sutherland, Braeford Pielech
    Pages 83-111
  7. Efficient Support for Time Series Queries in Data Stream Management Systems

    • Yijian Bai, Chang R. Luo, Hetal Thakkar, Carlo Zaniolo
    Pages 113-132
  8. Managing Distributed Geographical Data Streams with the GIDB Portal System

    • John T. Sample, Frank P. McCreedy, Michael Thomas
    Pages 133-151
  9. Streaming Data Dissemination Using Peer-Peer Systems

    • Shetal Shah, Krithi Ramamritham
    Pages 153-168
  10. Back Matter

    Pages 169-170

About this book

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 interested in learning about stream data management.

Reviews

From the reviews:

"This recent addition to the ‘Advances in Database Systems’ series surveys the latest research in the handling of data streams. … The chapters are written by well-known researchers … . This book is recommended for researchers who want to get up to speed quickly on the latest ideas in data stream management. Application developers who deal with real-time data streams will also benefit by gaining an understanding of the challenges and the research insights that will lead the way to effective system solutions." (A. Hevner, Computing Reviews, January, 2006)

Editors and Affiliations

  • University of New Orleans, USA

    Nauman A. Chaudhry, Mahdi Abdelguerfi

  • Naval Research Lab, USA

    Kevin Shaw

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access