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Nine algorithms that changed the future : The ingenious ideas that drive today’s computers
Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world’s biggest haystack. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers, and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease?
Facebook API Developers Guide
The Facebook API allows web developers to create Facebook applications and access Facebook data from other applications. Facebook API Developers Guide covers the use and implementation of the Facebook API—what the key features are and how you can access them. You will learn, through practical examples, the main features of the Facebook API including an introduction to the API–specific languages FQL and FBML. These examples are further supported by the introduction of other technologies like language libraries, relational database management systems, and XML. Covers all key features of the Facebook API Explains the API languages FQL and FBML Teaches by example, with useful code and tips you can use in your own applications
Algorithms and data structures for massive datasets
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. Graphics, illustrations, and 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 algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
