Data Stream Management
Processing High-Speed Data Streams
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Beschreibung
We live in the era of “Big Data”: Petabytes of digital information are generated daily, and need to be processed and analyzed for interesting patterns and trends. Besides volume, a defining characteristic of Big Data is its velocity; that is, data is instantiated in the form of continuous, high-speed data streams that arrive at rapid rates, and need to be processed and analyzed on a continuous (24x7) basis. Such data streams pose very difficult challenges for conventional data-management architectures, which are built primarily on the concept of persistent, static data collections. This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streamingsystems and applications built in different domains.
A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming productsand new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field.
The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.
Unlike traditional databases, which are reliable and relatively unchanging, data streams arrive in an uninterrupted flow which must be continuously processed. This timely reference book explores and contrasts the old persistent data set model with today’s seamless data stream environment, and proposes algorithms and systems that work over continuous data streams. This is the first in-depth treatment of this evolving topic, covering basic data stream techniques, data stream synopses, mining data streams, advanced data stream computations, and systems and architectures for data stream management systems.
Comprehensive introduction to the algorithmic and theoretical foundations of data stream processing – from basic mathematical models, algorithms, and analytics, and progressing to more advanced streaming algorithms and techniques Provides a thorough discussion on system and language aspects of data stream processing, through surveys of influential system prototypes and language designs Discusses representative applications of data stream processing techniques in different domains, including network management, financial analytics, publish/subscribe engines, and time-series analysis Includes an overview of current data streaming products and new streaming application domains, such as cloud computing and complex event processing Includes supplementary material: sn.pub/extras
Autor*in
Minos Garofalakis
Themen in »Data Stream Management«
Data streams Data model extensions Database management system engines Data mining Sensor networks XML query languages data structures
Stimmen zu »Data Stream Management«
“This impressive volume … covers both the theory and algorithms related to processing high-speed data streams. … this is a very useful and well-written text that can be recommended for students, practitioners, and researchers alike. The subject matter fills in a range of details, starting from the basics (including related mathematical theorems) and progressing to describe recent developments along with adequate references to the existing literature and suggestions for future research.” (Paparao Kavalipati, Computing Reviews, January, 2017)
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