Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic (Englis

Description: Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic, Emin Tahirovic, Ines Dedovic Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. Youll 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 theres no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and youll find the sweet spot of saving space without sacrificing your datas accuracy. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. 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. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. Youll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. Whats inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting Author Biography Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab of the computer science department at Stony Brook University, NY in 2014. She has worked on a number of projects in algorithms for massive data, taught algorithms at various levels and also spent some time at Microsoft. Emin Tahirovic earned his doctorate in biostatistics from UPenn in 2016, and his masters degree in theoretical computer science from Goethe University in Frankfurt in 2008. He has worked for DBahn AG as an IT consultant and he regularly consults on projects for pharma and tech companies. Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision of the Department of Electrical Engineering at RWTH Aachen University, Germany. She has worked as a researcher at the Research Center JÜlich and is currently employed as a software developer for camera systems at Jonas & Redmann, an automation company. Details ISBN 1617298034 ISBN-13 9781617298035 Title Algorithms and Data Structures for Massive Datasets Author Dzejla Medjedovic, Emin Tahirovic, Ines Dedovic Format Paperback Year 2022 Pages 304 Publisher Manning Publications GE_Item_ID:137716720; About Us Grand Eagle Retail is the ideal place for all your shopping needs! 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Price: 72.35 USD

Location: Fairfield, Ohio

End Time: 2024-12-01T04:22:47.000Z

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