Algorithms and Data Structures for Massive Datasets
暫譯: 大規模數據集的演算法與資料結構

Medjedovic, Dzejla, Tahirovic, Emin, Dedovic, Ines

Algorithms and Data Structures for Massive Datasets

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商品描述

In Algorithms and Data Structures for Massive Datasets, you'll discover methods for reducing and sketching data so it fits in small memory without losing accuracy, and unlock the algorithms and data structures that form the backbone of a big data system.

Data structures and algorithms that are great for traditional software may quickly slow or fail altogether when applied to huge datasets. Algorithms and Data Structures for Massive Datasets introduces a toolbox of new techniques that are perfect for handling modern big data applications.

In Algorithms and Data Structures for Massive Datasets, you'll discover methods for reducing and sketching data so it fits in small memory without losing accuracy, and unlock the algorithms and data structures that form the backbone of a big data system. Filled with fun illustrations and examples from real-world businesses, you'll learn how each of these complex techniques can be practically applied to maximize the accuracy and throughput of big data processing and analytics.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

商品描述(中文翻譯)

在《大數據的演算法與資料結構》中，您將發現減少和草圖化數據的方法，使其能夠適應小型記憶體而不損失準確性，並解鎖構成大數據系統基礎的演算法和資料結構。

對於傳統軟體而言，優秀的資料結構和演算法在應用於龐大的數據集時，可能會迅速變慢或完全失效。《大數據的演算法與資料結構》介紹了一套新的技術工具，這些技術非常適合處理現代大數據應用。

在《大數據的演算法與資料結構》中，您將發現減少和草圖化數據的方法，使其能夠適應小型記憶體而不損失準確性，並解鎖構成大數據系統基礎的演算法和資料結構。本書充滿有趣的插圖和來自真實商業的範例，您將學習如何將這些複雜技術實際應用，以最大化大數據處理和分析的準確性與吞吐量。

購買印刷版書籍可獲得Manning Publications提供的免費電子書，格式包括PDF、Kindle和ePub。

作者簡介

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 master's 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.

作者簡介(中文翻譯)

**Dzejla Medjedovic** 於2014年在紐約州的史東布魯克大學計算機科學系的應用演算法實驗室獲得博士學位。她參與了多個大數據演算法的項目，並在不同層級教授演算法，還曾在微軟工作過一段時間。

**Emin Tahirovic** 於2016年在賓夕法尼亞大學獲得生物統計學博士學位，並於2008年在法蘭克福的歌德大學獲得理論計算機科學碩士學位。他曾在DBahn AG擔任IT顧問，並定期為製藥和科技公司提供項目諮詢。

**Ines Dedovic** 在德國亞琛工業大學電機工程系的成像與計算機視覺研究所獲得博士學位。她曾在尤利希研究中心擔任研究員，目前在自動化公司Jonas & Redmann擔任攝影系統的軟體開發人員。

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