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180228s2016 caua ob 000 0 eng d |
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|a 1491970774
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|a 9781491970775
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|z 9781491970775
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|a (OCoLC)1026400600
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|a 004.654
|2 23
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|a UAMI
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|a Wampler, Dean,
|e author.
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|a Fast data architectures for streaming applications :
|b getting answers now from data sets that never end /
|c Dean Wampler.
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|a First edition.
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264 |
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|a Sebastopol, CA :
|b O'Reilly Media,
|c 2016.
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300 |
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|a 1 online resource (1 volume) :
|b illustrations
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a data file
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|a Online resource; title from title page (Safari, viewed February 27, 2018).
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|a Includes bibliographical references.
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|a Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? In this report, author Dean Wampler examines the rise of streaming systems for handling time-sensitive problems--such as detecting fraudulent financial activity as it happens. You'll explore the characteristics of fast data architectures, along with several open source tools for implementing them. Batch-mode processing isn't going away, but exclusive use of these systems is now a competitive disadvantage. You'll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention. Learn step-by-step how a basic fast data architecture works Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool Use methods for analyzing infinite data sets, where you don't have all the data and never will Take a tour of open source streaming engines, and discover which ones work best for different use cases Get recommendations for making real-world streaming systems responsive, resilient, elastic, and message driven Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems.
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590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
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|a Service-oriented architecture (Computer science)
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|a Application software
|x Development.
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|a Data mining.
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|a Big data.
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650 |
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|a Data Mining
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650 |
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|a Architecture orientée service (Informatique)
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650 |
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|a Logiciels d'application
|x Développement.
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650 |
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6 |
|a Exploration de données (Informatique)
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650 |
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|a Données volumineuses.
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650 |
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|a Application software
|x Development
|2 fast
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|a Big data
|2 fast
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|a Data mining
|2 fast
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|a Service-oriented architecture (Computer science)
|2 fast
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4 |
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|u https://learning.oreilly.com/library/view/~/9781492038771/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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994 |
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|a 92
|b IZTAP
|