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Stream Data Management [ADBS 30] by Chaudhry, Shaw & Abdelguerfi--L
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所在地：Belmont, California, 美國
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- ISBN
- 9780387243931
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Product Identifiers
Publisher
Springer
ISBN-10
0387243933
ISBN-13
9780387243931
eBay Product ID (ePID)
45386684
Product Key Features
Number of Pages
Xiv, 170 Pages
Publication Name
Stream Data Management
Language
English
Subject
Telecommunications, System Administration / Storage & Retrieval, Interactive & Multimedia, Databases / General
Publication Year
2005
Type
Textbook
Subject Area
Computers, Technology & Engineering
Series
Advances in Database Systems Ser.
Format
Hardcover
Dimensions
Item Weight
34.6 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2005-040440
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), 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)
Dewey Edition
22
Series Volume Number
30
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
005.74
Table Of Content
to Stream Data Management.- Query Execution and Optimization.- Filtering, Punctuation, Windows and Synopses.- XML & Data Streams.- CAPE: A Constraint-Aware Adaptive Stream Processing Engine.- Efficient Support for Time Series Queries in Data Stream Management Systems.- Managing Distributed Geographical Data Streams with the GIDB Portal System.- Streaming Data Dissemination Using Peer-Peer Systems.
Synopsis
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., Streaming applications pose new and interesting challenges for data management systems, requiring a major rethink of almost all aspects of traditional database management systems to support streaming applications. This book introduces a coherent body of work spanning various aspects of streaming data. Eight invited chapters by distinguished researchers active in stream data management provide exposition of algorithms and languages, as well as systems proposed and implemented from managing streaming data.
LC Classification Number
QA76.9.D3
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