Stream Data Management (Advances in Database Systems Book 30)

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.

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.

"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."--Résumé de l'éditeur Introduction to Stream Data Management....Pages 1-13 Query Execution and Optimization....Pages 15-33 Filtering, Punctuation, Windows and Synopses....Pages 35-58 XML & Data Streams....Pages 59-81 CAPE: A Constraint-Aware Adaptive Stream Processing Engine....Pages 83-111 Efficient Support for Time Series Queries in Data Stream Management Systems....Pages 113-132 Managing Distributed Geographical Data Streams with the GIDB Portal System....Pages 133-151 Streaming Data Dissemination Using Peer-Peer Systems....Pages 153-168 Streaming applications pose interesting challenges for data management systems. Such application domains require queries to be evaluated continuously. This book comprises eight chapters providing exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data