Shulou(Shulou.com)06/03 Report--

Because the work needs to do some work related to the development of big data, coupled with the scattered knowledge on the Internet, I often go to the library. Read a lot of data-related books, think that the following is basically not, mistakenly recommended to you. Because I have been in contact with big data for less than a year, there must be some misconceptions. If there are any mistakes, please comment in the comments at the bottom of the article.

1. Big data, people's posts and Telecommunications Publishing House, 2013, edited by Ding Shengyong, Fan Yongbing and Min Shiwu.

This book comprehensively explains the relevant terms and concepts about big data. The technical requirements for reading this book are relatively low, so it is very suitable for people who want to learn big data and those who are vague about big data.

2. Hadoop2 for busy people, Electronic Industry Press, 2016 by Douglas Eadline, translated by Lu Tao and Li Ying.

In the technical books "write to busy people" series of books, almost every sentence is practical information, although not suitable for beginners to read, but conducive to have a general understanding of the overall knowledge, so I recommend this book. In the book, hadoop v2 is mainly compared with hadoop1 to explain. Whether developers or operators read this book, I believe it will be of great help to your work. As stated in the book, "Hadoop should no longer be regarded as a separate project as a whole, but as a data processing method that fundamentally does not understand the traditional relational database model" and "a more pragmatic definition of Hadoop is an ecosystem and framework of open (and closed) source tools, libraries, and big data analysis methods", thus it is essential to learn Hadoop well if you want to learn from big data.

3. Hadoop authoritative Guide. Tsinghua University Press, 2015 third Edition. Translated by Tom White, School of data Science and Engineering, East China normal University.

Doug Cutting, the father of Hadoop, makes a preface to this book, and the third edition adds an explanation of the new features of hadoop2, which is of great help to the in-depth study of hadoop2.x, and can be used as a reference book at any time at work. If you have a good command of English, it is recommended to read the fourth edition of this book, Hadoop: The Definitive Guide, 4th Edition.

4. Hive programming Guide, people's posts and Telecommunications Publishing House, 2013 Edward Capriolo, Dean Wampler,Jason Rutherglen, translated by Cao Kun.

There are very few books on Apache Hive alone. I think this writing is more authoritative. I have a comprehensive explanation of Hive. At the same time, the author of this book is also a contributor to the Hadoop/Hive project.

5. Learning HBase Electronic Industry Press, 2015 by Shashwat Shriparv, translated by Zhou Yanwei, Lou Shuai and Pu Cong.

This book gives a comprehensive explanation of HBase and is suitable for the development of tool books that must be read by operation and maintenance. This book has brought great help to my work.

6. Spark Best practices. Turing, people's Post and Telecommunications Publishing House, 2016. By Chen Huan and Lin Shifei.

As the title of the book called "Best practices", from basic explanation to application cases are explained in detail, even for the zero foundation of Spark is also very suitable for reading this book. In addition, the "Scala language reference" in the appendix of this book makes me a great help to the introduction of Scala.

If you find good books at a later stage, you will continue to recommend them. At the same time, you are welcome to recommend what you think are good books in the comments section of this article.

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