Data Algorithms: Recipes for Scaling Up with Hadoop and Spark (Paperback)

Mahmoud Parsian





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