Data stream management
By: Lukasz Golab, M. Tamer Özsu
Contributors: Özsu, M. Tamer, 1951-
Series: Synthesis lectures on data management -- # 5
Publisher: Morgan & Claypool; Morgan & Claypool Publishers
Published: 2010
Place of publication: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Language: eng
Format: [electronic resource] /
Number of pages: 65
ISBN-13: 9781608452736; 9781608452729
Subjects: Streaming technology (Telecommunications); Data transmission systems
Other titles: Synthesis digital library of engineering and computer science.
Description: In this lecture many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs).A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization.The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage.
Notes: Part of: Synthesis digital library of engineering and computer science.

Title from PDF t.p. (viewed on June 4, 2010).

Series from website.

Includes bibliographical references (p. 49-64).

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Table of contents: title: 1. Introduction; title: Overview of data stream management; title: Organization; title: 2. Data stream management systems; title: Preliminaries; title: Stream models; title: Stream windows; title: Continuous query semantics and operators; title: Semantics and algebras; title: Operators; title: Continuous queries as views; title: Semantics of relations in continuous queries; title: Continuous query languages; title: Streams, relations and windows; title: User-defined functions; title: Sampling; title: Summary; title: Stream query processing; title: Scheduling; title: Heartbeats and punctuations; title: Processing queries-as-views and negative tuples; title: Stream query optimization; title: Static analysis and query rewriting; title: Operator optimization, join; title: Operator optimization, aggregation; title: Multi-query optimization; title: Load shedding and approximation; title: Load balancing; title: Adaptive query optimization; title: Distributed query optimization; title: 3. Streaming data warehouses; title: Data extraction, transformation and loading; title: Update propagation; title: Data expiration; title: Update scheduling; title: Querying a streaming data warehouse; title: 4. Conclusions; title: Bibliography; title: Authors' biographies.