Hive makes life much easier for developers who work with stored and managed data in Hadoop clusters, such as data warehouses. With this example-driven guide, you'll learn how to use the Hive infrastructure to provide data summarization, query, and analysis - particularly with HiveQL, the query language dialect of SQL. You'll learn how to set up Hive in your environment and optimize its use, and how it interoperates with other tools, such as HBase. You'll also learn how to extend Hive with custom code written in Java or scripting languages. Ideal for developers with prior SQL experience, this book shows you how Hive simplifies many tasks that would be much harder to implement in the lower-level MapReduce API provided by Hadoop.

This is a cookbook and all tasks are approached as recipes. A recipe describes a task and outlines the steps necessary to complete this task. Some recipes in the book are examples of writing code. An example of this is a recipe that stores and accesses the entries of a phone book in Cassandra. The recipe consists of a description of the program, a full code example is given, the example is run, the output is displayed, and finally the how it works section describes the process or code in greater detail. Other recipes in the book describe a task. An example of this is a recipe that takes a snapshot back up of data in Cassandra. This recipe contains a description of the process, it then shows how to run the snapshot command and confirm that it worked, it then explains what the snapshot command does behind the scenes, finally the 'see also' section references other related recipes such as the recipe to restore a snapshot. This book is designed for administrators, developers, and data architects who are interested in Apache Cassandra for redundant, highly performing, and scalable data storage. Typically these users should have experience working with a database technology, multiple node computer clusters, and high availability solutions.