本书介绍了用作各种机器学习模型输入的数据集加载和处理的Spark API的基础知识。书中有详细的示例和现实世界的用例，并探索常见的机器学习模型，包括推荐系统，分类，回归，聚类和降维。最后涵盖了一些高级主题，如使用大规模文本数据以及使用Spark Streaming进行在线机器学习和模型评估的方法。

通过本书将学习到以下的知识：
　　（1）、Create your first Spark program in Scala, Java, and Python
　　（2）、Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2
　　（3）、Access public machine learning datasets and use Spark to load, process, clean, and transform data
　　（4）、Use Spark's machine learning library to implement programs utilizing well-known machine learning models including collaborative filtering, classification, regression, clustering, and dimensionality reduction
　　（5）、Write Spark functions to evaluate the performance of your machine learning models
　　（6）、Deal with large-scale text data, including fe