Hadoop the Definitive Guide PDF Download
Struggling to work with Hadoop? Finding it super difficult to analyze vast datasets? Want to become a pro in building and maintaining the most reliable Apache Hadoop’s distributed systems? If so, then this Hadoop’s definitive guide is no less than a Bible for you. You can download Hadoop the definitive guide pdf from here.
| Book title | Hadoop the definitive guide pdf |
| Author | Tom White |
| No. Of pages | 628 Pages |
| PDF Size | 10 MB |
| Language | English |
| Category | Programming, Computers |
Book Summary
This book mainly focuses on educating programmers and fresh Hadoop developers on the art of setting up Hadoop systems and running them professionally. It doesn’t matter how vast or minor the dataset you are up to evaluating, this guide will help you throughout in a straightforward, stepwise method. Not only Hadoop databases but can also learn the proper method of running complicated Hadoop clusters.
Several chapters of this comprehensive guide cover multiple advanced and basic projects of Hadoop, including YARN, Crunch, Flume, Spark, Parquet, and many others. It means it’s a one-stop guide with which you can rise to newer and higher levels of Hadoop development and processing.
Many newbies get confused while learning Hadoop due to the absence of a proper sequence of concepts. Although this problem can be solved by hiring a professional or tutor, self-teaching is not possible unless you have some prior knowledge of fundamentals. And that’s the best part of this book; all the concepts and topics are covered thoroughly in a proper sequence so you won’t find a gap or find yourself stuck in a blind alleyway.
First chapter overview
The very first chapters of this guide describe the basic concepts and components like YARN, HDFS, and MapReduce. Once you’ll learn the basics, the author moves towards the detailed concept of MapReduce, stating the stepwise method for developing web applications. After this, the reader is taught the procedure of setting up and maintaining the Hadoop cluster and MapReduce on HDFS and YARN, respectively.
Speaking of data analysis, two different data formats are described in detail here; Avro and Parquet which can be used easily for data serialization and nested data. Furthermore, the data ingestion tools and features are also there like Swoop and Flume using with which, you can learn the right way of streaming data smoothly and transfer data in the form of bulk.
Speaking of data analysis
There’s no need to worry if you are accustomed to using high-end data processing tools such as Spark, Church, and Pig since all these tools are completely compatible with Hadoop – no need to learn something new other than what you want to learn! In the last few chapters, the author mentioned some case studies for practicing and exercising what you’ve learned.
For example, the very first case study discusses how to handle composable data at a data center. The second case study discusses how you can save lives with the help of software using the advanced tactics of biological data science (Zookeeping distribution). And the third and last case study explains cascading. To expand your point of view, recent updates and changes in Hadoop are also discussed so you can keep your skill upgraded.