Synopsis
Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive― rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers.
Big Data shows how to build these 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 use them in practice, and how to deploy and operate them once they're built.
AUDIENCE
This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful.
ABOUT THE TECHNOLOGY
To tackle the challenges of Big Data, a new breed of technologies has emerged. Many of which have been grouped under the term "NoSQL." In some ways these new technologies can be more complex than traditional databases and in other ways, simpler. Using them effectively requires a fundamentally new set of techniques
"synopsis" may belong to another edition of this title.
About the Author
Nathan Marz is an engineer at Twitter. He was previously Lead Engineer at BackType, a marketing intelligence company that was acquired by Twitter in July of 2011. He is the author of two major open source projects: Storm, a distributed realtime computation system, and Cascalog, a tool for processing data on Hadoop. He is a frequent speaker and writes a blog at nathanmarz.com. James Warren is an analytics architect at Storm8 with a background in big data processing, machine learning and scientific computing.
"About this title" may belong to another edition of this title.
Search results for Big Data:Principles and best practices of scalable...
Stock Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Seller Inventory # 00090148986
Seller Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: Zoom Books East, Glendale Heights, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: very_good. Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service. Seller Inventory # ZEV.1617290343.VG
Stock Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Good condition ex-library book with usual library markings and stickers. Seller Inventory # 00103547041
Seller Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: Greenworld Books, Arlington, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: very_good. Fast Free Shipping â" Very Good condition book with a firm cover and clean pages. Shows normal use and some light wear or limited notes markings. A solid, nice copy to enjoy. Seller Inventory # GWV.1617290343.VG
Stock Image
Big Data: Principles and best practices of scalable realtime data systems
Published by
Manning (edition First Edition), 2015
ISBN 10: 1617290343
ISBN 13: 9781617290343
Used
Paperback
First Edition
Seller: BooksRun, Philadelphia, PA, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. First Edition. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Seller Inventory # 1617290343-11-18
Stock Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: Evergreen Goodwill, Seattle, WA, U.S.A.
Seller rating 5 out of 5 stars
paperback. Condition: Acceptable. Seller Inventory # mon0000636469
Seller Image
Big Data: Principles and best practices of scalable realtime data systems
Seller: Off The Shelf, Antonia, MO, U.S.A.
Seller rating 5 out of 5 stars
Condition: good. The item shows wear from consistent use, but it remains in good condition and works perfectly. All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May NOT include discs, access code or other supplemental materials. Seller Inventory # 4WILKM00M4BQ
Stock Image
Big Data: Principles and Best Practices of Scalable Realtime Data Systems
Seller: ThriftBooks-Reno, Reno, NV, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617290343I4N10
Stock Image
Big Data: Principles and Best Practices of Scalable Realtime Data Systems
Seller: ThriftBooks-Reno, Reno, NV, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617290343I3N00
Stock Image
Big Data: Principles and Best Practices of Scalable Realtime Data Systems
Seller: ThriftBooks-Phoenix, Phoenix, AZ, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617290343I4N00