Chapter 1, Overview of Big Data and Hive, begins with the evolution of big data, Hadoop ecosystem, and Hive. You will also learn the Hive architecture and advantages of using Hive in big data analysis.

Chapter 2, Setting Up the Hive Environment, presents the Hive environment setup and configuration. It also covers using Hive through the command line and development tools.

Chapter 3, Data Definition and Description, outlines the basic data types and data definition language for tables, partitions, buckets, and views in Hive.

Chapter 4, Data Correlation and Scope, shows you ways to discover the data by querying, linking, and scoping the data in Hive.

Chapter 5, Data Manipulation, focuses on the process of exchanging, moving, sorting, and transforming the data in Hive.

Chapter 6, Data Aggregation and Sampling, explains the way of doing aggregation and sample using aggregation functions, analytic functions, windowing, and sample clauses.

Chapter 7, Performance Considerations, introduces the best practices of performance considerations in the aspect of design, file format, compression, storage, query, and job.

Chapter 8, Extensibility Considerations, describes the way of extending Hive by creating user-defined functions, streaming, serializers, and deserializers.

Chapter 9, Security Considerations, introduces the area of Hive security in terms of authentication, authorization, and encryption.

Chapter 10, Working with Other Tools, discusses how Hive works with other big data tools.