Book Image

Apache Hive Essentials. - Second Edition

By : Dayong Du
Book Image

Apache Hive Essentials. - Second Edition

By: Dayong Du

Overview of this book

In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
Table of Contents (12 chapters)

Understanding data types

Hive data types are categorized into two types: primitive and complex. String and Int are the most useful primitive types, which are supported by most HQL functions. The details of primitive types are as follows:

ay contain a set of any type of fields. Complex types allow the nesting of types. The details of complex types a

Primitive type Description Example
TINYINT It has 1 byte, from -128 to 127. The postfix is Y. It is used as a small range of numbers. 10Y
SMALLINT It has 2 bytes, from -32,768 to 32,767. The postfix is S. It is used as a regular descriptive number. 10S
INT It has 4 bytes, from -2,147,483,648 to 2,147,483,647. 10
BIGINT It has 8 bytes, from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807. The postfix is L. 100L
FLOAT This is a 4 byte single-precision floating-point number, from 1.40129846432481707e-45 to 3.40282346638528860e...