LEADER 00000cam a22005777i 4500 003 OCoLC 005 20240129213017.0 006 m o d 007 cr cnu|||unuuu 008 230920s2011 caua ob 001 0 eng d 035 (OCoLC)1398334883 037 0738436151|bO'Reilly Media 040 ORMDA|beng|erda|epn|cORMDA|dOCLCO|dOCLCF|dINARC 049 INap 082 04 004/.33 082 04 004/.33|223/eng/20230920 099 eBook O'Reilly for Public Libraries 100 1 Ballard, Chuck,|eauthor. 245 10 IBM InfoSphere Streams :|bassembling continuous insight in the information revolution /|cChuck Ballard, Kevin Foster, Andy Frenkiel, Bugra Gedik, Michael P. Koranda, Senthil Nathan, Deepak Rajan, Roger Rea, Mike Spicer, Brian Williams, Vitali N. Zoubov.|h[O'Reilly electronic resource] 264 1 [San Jose, California] :|bIBM Corporation,|c[2011] 300 1 online resource (456 pages) :|billustrations 336 text|btxt|2rdacontent 337 computer|bc|2rdamedia 338 online resource|bcr|2rdacarrier 490 1 Redbooks 504 Includes bibliographical references and index. 520 In this IBM® Redbooks® publication, we discuss and describe the positioning, functions, capabilities, and advanced programming techniques for IBM InfoSphere™ Streams (V2), a new paradigm and key component of IBM Big Data platform. Data has traditionally been stored in files or databases, and then analyzed by queries and applications. With stream computing, analysis is performed moment by moment as the data is in motion. In fact, the data might never be stored (perhaps only the analytic results). The ability to analyze data in motion is called real-time analytic processing (RTAP). IBM InfoSphere Streams takes a fundamentally different approach to Big Data analytics and differentiates itself with its distributed runtime platform, programming model, and tools for developing and debugging analytic applications that have a high volume and variety of data types. Using in- memory techniques and analyzing record by record enables high velocity. Volume, variety and velocity are the key attributes of Big Data. The data streams that are consumable by IBM InfoSphere Streams can originate from sensors, cameras, news feeds, stock tickers, and a variety of other sources, including traditional databases. It provides an execution platform and services for applications that ingest, filter, analyze, and correlate potentially massive volumes of continuous data streams. This book is intended for professionals that require an understanding of how to process high volumes of streaming data or need information about how to implement systems to satisfy those requirements. See: http:// www.redbooks.ibm.com/abstracts/sg247865.html for the IBM InfoSphere Streams (V1) release. 590 O'Reilly|bO'Reilly Online Learning: Academic/Public Library Edition 650 0 Streaming technology (Telecommunications) 650 0 Real-time data processing. 650 0 Parallel processing (Electronic computers) 650 6 En continu (Télécommunications) 650 6 Temps réel (Informatique) 650 6 Parallélisme (Informatique) 650 7 Parallel processing (Electronic computers)|2fast |0(OCoLC)fst01052928 650 7 Real-time data processing.|2fast|0(OCoLC)fst01091219 650 7 Streaming technology (Telecommunications)|2fast |0(OCoLC)fst01134637 700 1 Foster, Kevin,|eauthor. 700 1 Frenkiel, Andy,|eauthor. 700 1 Gedik, Buğra,|eauthor. 700 1 Koranda, Michael P.,|eauthor. 700 1 Nathan, Senthil,|eauthor. 700 1 Rajan, Deepak,|eauthor. 700 1 Rea, Roger,|eauthor. 700 1 Spicer, Mike,|eauthor. 700 1 Williams, Brian,|eauthor. 700 1 Zoubov, Vitali N.,|eauthor. 830 0 IBM redbooks. 856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https:// learning.oreilly.com/library/view/~/0738436151/?ar |zAvailable on O'Reilly for Public Libraries 938 Internet Archive|bINAR|nisbn_9780738436159 994 92|bJFN