000			03560nam a22005415i 4500
001			978-0-387-25229-2
003			DE-He213
005			20250710083933.0
007			cr nn 008mamaa
008			100301s2005 xxu| s |||| 0|eng d
020			_a9780387252292 _a99780387252292
024	7		_a10.1007/b106968 _2doi
082	0	4	_a005.74 _223
100	1		_aChaudhry, Nauman A. _eeditor.
245	1	0	_aStream Data Management _h[recurso electrónico] / _cedited by Nauman A. Chaudhry, Kevin Shaw, Mahdi Abdelguerfi.
264		1	_aBoston, MA : _bSpringer US, _c2005.
300			_aXIV, 170 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvances in Database Systems, _x1386-2944 ; _v30
505	0		_ato 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.
520			_aResearchers 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.
650		0	_aCOMPUTER SCIENCE.
650		0	_aCOMPUTER COMMUNICATION NETWORKS.
650		0	_aDATABASE MANAGEMENT.
650		0	_aINFORMATION STORAGE AND RETRIEVAL SYSTEMS.
650		0	_aINFORMATION SYSTEMS.
650		0	_aMULTIMEDIA SYSTEMS.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aDATABASE MANAGEMENT.
650	2	4	_aINFORMATION STORAGE AND RETRIEVAL.
650	2	4	_aMULTIMEDIA INFORMATION SYSTEMS.
650	2	4	_aCOMPUTER COMMUNICATION NETWORKS.
650	2	4	_aMODELS AND PRINCIPLES.
650	2	4	_aINFORMATION SYSTEMS APPLICATIONS (INCL.INTERNET).
700	1		_aShaw, Kevin. _eeditor.
700	1		_aAbdelguerfi, Mahdi. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387243931
830		0	_aAdvances in Database Systems, _x1386-2944 ; _v30
856	4	0	_uhttp://dx.doi.org/10.1007/b106968 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c56411 _d56411