000 04567nam a22005775i 4500
001 978-3-540-28608-0
003 DE-He213
005 20200421111842.0
007 cr nn 008mamaa
008 160711s2016 gw | s |||| 0|eng d
020 _a9783540286080
_9978-3-540-28608-0
024 7 _a10.1007/978-3-540-28608-0
_2doi
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aUMT
_2bicssc
072 7 _aCOM021000
_2bisacsh
082 0 4 _a005.74
_223
245 1 0 _aData Stream Management
_h[electronic resource] :
_bProcessing High-Speed Data Streams /
_cedited by Minos Garofalakis, Johannes Gehrke, Rajeev Rastogi.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2016.
300 _aVII, 537 p. 103 illus., 16 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aData-Centric Systems and Applications,
_x2197-9723
505 0 _aPart I: Introduction -- Part II: Computation of Basic Stream Synopses -- Part III: Mining Data Streams -- Part IV: Advanced Topics -- Part V: Systems and Architectures -- Part VI: Applications. .
520 _aWe 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 streaming systems 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 products and 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. .
650 0 _aComputer science.
650 0 _aBig data.
650 0 _aData structures (Computer science).
650 0 _aDatabase management.
650 0 _aData mining.
650 0 _aInformation storage and retrieval.
650 1 4 _aComputer Science.
650 2 4 _aDatabase Management.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aBig Data/Analytics.
650 2 4 _aData Structures.
650 2 4 _aInformation Storage and Retrieval.
700 1 _aGarofalakis, Minos.
_eeditor.
700 1 _aGehrke, Johannes.
_eeditor.
700 1 _aRastogi, Rajeev.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540286073
830 0 _aData-Centric Systems and Applications,
_x2197-9723
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-28608-0
912 _aZDB-2-SCS
942 _cEBK
999 _c55607
_d55607