Free Big Data: Principles And Best Practices Of Scalable Realtime Data Systems Ebooks Online
SummaryBig Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the BookWeb-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive.Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful.What's InsideIntroduction to big data systemsReal-time processing of web-scale dataTools like Hadoop, Cassandra, and StormExtensions to traditional database skillsAbout the AuthorsNathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing.Table of ContentsA new paradigm for Big DataPART 1 BATCH LAYERData model for Big DataData model for Big Data: IllustrationData storage on the batch layerData storage on the batch layer: IllustrationBatch layerBatch layer: IllustrationAn example batch layer: Architecture and algorithmsAn example batch layer: ImplementationPART 2 SERVING LAYERServing layerServing layer: IllustrationPART 3 SPEED LAYERRealtime viewsRealtime views: IllustrationQueuing and stream processingQueuing and stream processing: IllustrationMicro-batch stream processingMicro-batch stream processing: IllustrationLambda Architecture in depth
Paperback: 328 pages
Publisher: Manning Publications; 1 edition (May 10, 2015)
Language: English
ISBN-10: 1617290343
ISBN-13: 978-1617290343
Product Dimensions: 7.3 x 0.6 x 9.1 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review: 4.4 out of 5 stars See all reviews (32 customer reviews)
Best Sellers Rank: #32,670 in Books (See Top 100 in Books) #3 in Books > Computers & Technology > Web Development & Design > User Generated Content #9 in Books > Computers & Technology > Business Technology > Management Information Systems #19 in Books > Computers & Technology > Databases & Big Data > Data Mining
Here's my bottom line: Get this book, whether you are new to working with Big Data or now an old hand at dealing with Big Data’s seemingly never-ending (and steadily expanding) complexities.You may not agree with all that the authors offer or contend in this well-written "theory" text. But Nathan Marz’s Lambda Architecture is well worth serious consideration, especially if you are now trying to come up with more reliable and more efficient approaches to processing and mining Big Data. The writers' explanations of some of the power, problems, and possibilities of Big Data systems are among the clearest and best I have read."More than 30,000 gigabytes of data are generated every second, and the rate of data creation is only accelerating," Marz and Warren point out.Thus, previous "solutions" for working with Big Data are now getting overwhelmed, not only by the sheer volume of information pouring in but by greater system complexities and failures of overworked hardware that now plague many outmoded systems.The authors have structured their book to show "how to approach building a solution to any Big Data problem. The principles you’ll learn hold true regardless of the tooling in the current landscape, and you can use these principles to rigorously choose what tools are appropriate for your application.” In other words, they write, you will “learn how to fish, not just how to use a particular fishing rod.”However, a particular Big Data architecture IS featured, as well: Marz's Lambda Architecture. It is, the two authors explain, "an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data.
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