What this book covers
Chapter 1, Overview of Big Data and Hive, introduces the evolution of big data, the Hadoop ecosystem, and Hive. You will also learn the Hive architecture and the advantages of using Hive in big data analysis.
Chapter 2, Setting Up the Hive Environment, describes the Hive environment setup and configuration. It also covers using Hive through the command line and development tools.
Chapter 3, Data Definition and Description, introduces the basic data types and data definition language for tables, partitions, buckets, and views in Hive.
Chapter 4, Data Selection and Scope, shows you ways to discover the data by querying, linking, and scoping the data in Hive.
Chapter 5, Data Manipulation, describes the process of exchanging, moving, sorting, and transforming the data in Hive.
Chapter 6, Data Aggregation and Sampling, explains how to do 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 aspects of design, file format, compression, storage, query, and job.
Chapter 8, Extensibility Considerations, describes how to extend 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. It also reviews the key milestones of Hive releases.
