Algorithms and Data Structures for Massive Datasets, Video Edition

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets.
In Algorithms and Data Structures for Massive Datasets you will learn
Probabilistic sketching data structures for practical problems
Choosing the right database engine for your application
Evaluating and designing efficient on-disk data structures and algorithms
Understanding the algorithmic trade-offs involved in massive-scale systems
Deriving basic statistics from streaming data
Correctly sampling streaming data
Computing percentiles with limited space resources
Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Hands-on industry examples make complex ideas practical to implement in your projects-and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy.
About the Technology
Standard algorithms and data structures may become slow-or fail altogether-when applied to large distributed datasets. Choosing...

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