本书将向您展示如何利用Python的强大功能并将其用于Spark生态系统中。您将首先了解Spark 2.0的架构以及如何为Spark设置Python环境。通过本书，你将会使用Python操作RDD、DataFrames、MLlib以及GraphFrames等；在本书结束时，您将对Spark Python API有了全局的了解，并且学习到如何使用它来构建数据密集型应用程序。通过本书你将学习到以下的知识：

• Learn about Apache Spark and the Spark 2.0 architecture
• Build and interact with Spark DataFrames using Spark SQL
• Learn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectively
• Read, transform, and understand data and use it to train machine learning models
• Build machine learning models with MLlib and ML
• Learn how to submit your applications programmatically using spark-submit
• Deploy locally built applications to a cluster

本书由Tomasz Drabas所著，全书共273页；Packt Publishing出版社于2017年02月出版。

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本书的章节

1 UNDERSTANDING SPARK
2 RESILIENT DISTRIBUTED DATASETS
3 DATAFRAMES
4 PREPARE DATA FOR MODELING
5 INTRODUCING MLLIB
6 INTRODUCING THE ML PACKAGE
7 GRAPHFRAMES
8 TENSORFRAMES
9 POLYGLOT PERSISTENCE WITH BLAZE
10 STRUCTURED STREAMING
11 PACKAGING SPARK APPLICATIONS

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