Stream Data Management

  • Nauman A. Chaudhry
  • Kevin Shaw
  • Mahdi Abdelguerfi

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

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Nauman A. Chaudhry
    Pages 1-13
  3. Stratis D. Viglas
    Pages 15-33
  4. David Maier, Peter A. Tucker, Minos Garofalakis
    Pages 35-58
  5. Nicolas Bruno, Luis Gravano, Nick Koudas, Divesh Srivastava
    Pages 59-81
  6. Elke A. Rundensteiner, Luping Ding, Yali Zhu, Timothy Sutherland, Braeford Pielech
    Pages 83-111
  7. Yijian Bai, Chang R. Luo, Hetal Thakkar, Carlo Zaniolo
    Pages 113-132
  8. John T. Sample, Frank P. McCreedy, Michael Thomas
    Pages 133-151
  9. Shetal Shah, Krithi Ramamritham
    Pages 153-168
  10. Back Matter
    Pages 169-170

About this book

Introduction

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.

 

Keywords

Extensible Markup Language (XML) Windows algorithms computer science database optimization

Editors and affiliations

  • Nauman A. Chaudhry
    • 1
  • Kevin Shaw
    • 2
  • Mahdi Abdelguerfi
    • 1
  1. 1.University of New OrleansUSA
  2. 2.Naval Research LabUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b106968
  • Copyright Information Springer Science+Business Media, Inc. 2005
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-0-387-24393-1
  • Online ISBN 978-0-387-25229-2
  • Series Print ISSN 1386-2944
  • About this book