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)

Job optimization

Job optimization covers experience and skills to improve performance in the areas of job-running mode, JVM reuse, job parallel running, and query join optimizations.

Local mode

Hadoop can run in standalone, pseudo-distributed, and fully distributed mode. Most of the time, we need to configure it to run in fully distributed mode. When the data to process is small, it is an overhead to start distributed data processing since the launch time of the fully distributed mode takes more time than the job processing time. Since v0.7.0, Hive has supported automatic conversion of a job to run in local mode with the following settings:

> SET; -- default false
> SET hive.exec.mode.local...