Internet today has entered the era of big data, big data technology has been widely used in finance, health care, education, telecommunications, government and so on. Businesses are generating large amounts of data every day, units of measurement data from B, KB, MB, GB, TB developed to PB, EB, ZB, YB even BB, NB, DB. The next few years, global data will show explosive growth. Google, Alibaba, Baidu, Jingdong and other Internet companies are in urgent need of technical talent to master big data, and large data relevant personnel have seen a shortage situation.
Hadoop big data as the core framework for eco-system, designed for off-line and large-scale data processing and design. The core composition Hadoop HDFS provides distributed storage of massive data; massive data was provided the MapReduce distributed computing. Many Internet companies are using Hadoop to achieve the company's core business, such as Huawei's cloud computing platform, Taobao's recommendation system, as long as the vast amounts of data and related areas have Hadoop figure.
The book as a primer and around the Hadoop framework, knowledge and broad, covering the current mainstream of the entire ecosystem Hadoop big data technology development. Comprehensive, code readability strong, practical operation to the main theory, supplemented by hands-on, step by step commonly used off-line computing and real-time computing systems such as in-depth explanation.
The book 16 chapters, Chapter 1 explained installed in VMware CentOS 7 operating system; Chapter 2 explains the configuration of the operating system cluster environment before the big data development; 3 to chapter 16 explain each frame HDFS Hadoop ecosystem, MapReduce, YARN, ZooKeeper, HBase, Hive, Sqoop and real-time data processing system Flume, Kafka, Storm, Spark and distributed search system Elasticsearch and other basics, architecture principle, to build a clustered environment, including both common Shell command, API operation , source code analysis, and to deepen the understanding and application of each frame through actual cases.
So how does this book?
This book is recommended reading mode in accordance with the order of the chapters read from start to finish, because many of the later chapters are based on the previous chapters, and this step by step, progressive approach to the way will make you more smoothly master big data development skills.
When studying this book, the first to build a good development environment in accordance with Chapters 1 and 2, followed by learning ~ Chapter 316, to learn when each chapter to understand the basics of architecture principles and framework of the chapter, and then to build a clustered environment , Shell command operations and other practical operation, this study would be better. When the theoretical knowledge and practical operation of the book in all of them, you can learn by analogy, to develop their own large data a program, or to apply the knowledge to their own programming projects can also go to various online forums and other big data enthusiasts discussions, help each other.
Reference book can get started as a novice guide books or Hadoop Big Data Developers of books, it asks the reader to have some basic Java language and the Linux system infrastructure, even without any large data base of readers, the book can also control steps to build success their own big data cluster, is a real ability to improve the reader to the practical operation of the main entry books. By studying this book, readers can quickly understand and master data relevant for large frame, can skillfully use Hadoop big data integration environment for development projects.
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