Leverage your knowledge of SQL to easily write distributed data processing applications on Hadoop using Apache Hive
Hadoop provides a robust framework for building distributed applications, but working directly with Hadoop requires writing a lot of code. Adding structure to data and using a higher-level language such as SQL makes working with Hadoop both easier and faster.
"Instant Apache Hive Essentials How-to" contains a series of practical recipes that introduce the power and flexibility of Hive. Starting with your first query, this book will provide step-by-step instructions and behind-the-scenes explanations for how to effectively write MapReduce jobs with SQL.
This book looks at how Hive transforms SQL statements into MapReduce jobs and demonstrates how you can extend Hive to support your own use cases. Its recipes will teach you how to leverage the scale of Hadoop while retaining the benefits of using a structured query language.You will learn how Hive translates a query into MapReduce jobs and explore how to structure your queries for better performance. You will extend Hive to understand your own file formats, simplifying the loading of data into the warehouse. You will finally add your own custom functions to Hive to support whatever use cases you may have.
"Instant Apache Hive Essentials How-to" is a quick introduction for adding Hive to your data toolkit. It is packed with high-level instructions for making Hive work as well as drawing connections to the underlying Hadoop framework to explain how things happen.