1.Spark
(1) Spark fast big data analysis
Introduction: Written by spark developers, without too many implementation details, focusing on basic concepts, suitable for Xiaobai version, data scientists and engineers can get started immediately. You can learn how to implement complex parallel jobs with short code, and learn about applications ranging from simple batch jobs to stream processing and machine learning.
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(2) Trilogy of Spark Big Data Commercial Practice: Kernel Decryption | Business Case | Performance Tuning
Introduction: Domestic author, more than 1000 pages, covering source code, practice and tuning, currently reading, the first edition in March 2018, although there are many text errors, but the content is pretty good, if you have been into spark for a while Now, you can read this book, read the source code part , do the practical part, and finally read the tuning part, there should be a great improvement.
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2.Hadoop
Awaiting to be added. . . .
3. Learning Websites
(1) http://www.chinahadoop.cn/bigdata/all/list Little Elephant Academy
Introduction: There are a lot of good free courses, some of them are paid, and it feels okay. Examples of courses: "Design and Implementation of Real-time Big Data Processing Platform", "Cache Application in Advertising System"
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(2) Geek Academy
Introduction: The fees are very reasonable. Other websites often offer hundreds of thousands of courses, which is simply a money grab. According to the membership model, the monthly membership is only tens of dollars. You can watch all the videos. It pays more attention to the basics and covers a wide range of content.
! ! ! The point is, he has a very good website with summary information on the technical routes of different occupations, career planning and knowledge systems.
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