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)


Hive can also leverage the streaming feature in Hadoop to transform data in an alternative way. The streaming API opens an I/O pipe to an external process, such as a script. Then, the process reads data from the standard input and writes the results out through the standard output. In HQL, we can use TRANSFORM clauses directly to embed the mapper and the reducer scripts written in commands, shell scripts, Java, or other programming languages. Although streaming brings overhead by using serialization/deserialization between processes, it provides a simple coding mode for non-Java developers. The syntax of the TRANSFORM clause is as follows:

    FROM src
    SELECT TRANSFORM '(' expression (',' expression)* ')'
    USING 'map_user_script'
    (AS colName (',' colName)*)?
    (outRowFormat)? (outRecordReader...