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020 _a9780387252292
_9978-0-387-25229-2
024 7 _a10.1007/b106968
_2doi
035 _avtls000330128
039 9 _a201509030445
_bVLOAD
_c201405070459
_dVLOAD
_c201401311330
_dstaff
_c201401311154
_dstaff
_y201401291448
_zstaff
_wmsplit0.mrc
_x548
050 4 _aQA76.9.D3
100 1 _aChaudhry, Nauman A.
_eeditor.
_9302920
245 1 0 _aStream Data Management /
_cedited by Nauman A. Chaudhry, Kevin Shaw, Mahdi Abdelguerfi.
264 1 _aBoston, MA :
_bSpringer US,
_c2005.
300 _aXIV, 170 páginas,
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aAdvances in Database Systems,
_x1386-2944 ;
_v30
500 _aSpringer eBooks
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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aShaw, Kevin.
_eeditor.
_9302921
700 1 _aAbdelguerfi, Mahdi.
_eeditor.
_9302922
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387243931
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b106968
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c278936
_d278936