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)

Mahmoud Parsian

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

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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)

學習您需要的算法和工具，以便使用 Hadoop 和 Spark 建立 MapReduce 應用程式，處理在一般硬體集群上大小為千兆字節、太字節或拍字節的數據集。這本實用的書籍由 Illumina 大數據團隊負責人 Mahmoud Parsian 撰寫，將逐步引導您設計機器學習算法，例如 Naive Bayes 和馬可夫鏈，並展示如何將它們應用於臨床和生物數據集，使用 MapReduce 設計模式。

- 將 MapReduce 算法應用於臨床和生物數據，例如 DNA-Seq 和 RNA-Seq
- 使用最相關的回歸/分析算法，針對不同的生物數據類型
- 使用 MapReduce/Hadoop 和 Spark 應用 t 檢驗、聯接、前十名和相關算法

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