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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