Data Algorithms: Recipes for Scaling Up with Hadoop and Spark (Paperback)
暫譯: 數據演算法：使用 Hadoop 和 Spark 擴展的配方 (平裝本)

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