Data Algorithms: Recipes for Scaling Up with Hadoop and Spark (Paperback)
Mahmoud Parsian
- 出版商: O'Reilly|英文2書85折
- 出版日期: 2015-08-11
- 定價: $2,300
- 售價: 9.5 折 $2,185
- 貴賓價: 9.0 折 $2,070
- 語言: 英文
- 頁數: 778
- 裝訂: Paperback
- ISBN: 1491906189
- ISBN-13: 9781491906187
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相關分類:
Hadoop、Spark、Algorithms-data-structures
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相關翻譯:
數據算法:Hadoop/Spark大數據處理技巧 (簡中版)
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商品描述
Learn the algorithms and tools you need to build MapReduce applications with Hadoop and Spark for processing gigabyte, terabyte, or petabyte-sized datasets on clusters of commodity hardware. With this practical book, author Mahmoud Parsian, head of the big data team at Illumina, takes you step-by-stepthrough the design of machine-learning algorithms, such as Naive Bayes and Markov Chain, and shows you how apply them to clinical and biological datasets, using MapReduce design patterns.
- Apply MapReduce algorithms to clinical and biological data, such as DNA-Seq and RNA-Seq
- Use the most relevant regression/analytical algorithms used for different biological data types
- Apply t-test, joins, top-10, and correlation algorithms using MapReduce/Hadoop and Spark
商品描述(中文翻譯)
學習使用Hadoop和Spark建立MapReduce應用程式所需的演算法和工具,以處理吉比、太比或拍比級別的資料集,並在廉價硬體集群上進行處理。在這本實用書中,作者Mahmoud Parsian(Illumina的大數據團隊負責人)逐步介紹機器學習演算法的設計,例如Naive Bayes和Markov Chain,並展示如何應用這些演算法於臨床和生物資料集,使用MapReduce設計模式。
本書內容包括:
- 將MapReduce演算法應用於臨床和生物資料,例如DNA-Seq和RNA-Seq
- 使用最相關的迴歸/分析演算法處理不同類型的生物資料
- 使用MapReduce/Hadoop和Spark應用t-test、連接、前10名和相關性演算法