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)

Hivemall

Apache Hivemall (https://hivemall.incubator.apache.org/) is a collection of Hive UDFs for machine learning. It contains a number of ML algorithm implementations across classification, regression, recommendations, loss functions, and feature engineering, all as UDFs. This allows end users to use SQL and only SQL to apply machine learning algorithms to a large volume of training data. Perform the following steps to set it up:

  1. Download Hivemall from https://hivemall.incubator.apache.org/download.html and put it into HDFS:
      $ hdfs fs -mkdir -p /apps/hivemall
$ hdfs fs -put hivemall-all-xxx.jar /apps/hivemall
  1. Create permanent functions using script here (https://github.com/apache/incubator-hivemall/blob/master/resources/ddl/define-all-as-permanent.hive):
      > CREATE DATABASE IF NOT EXISTS hivemall; -- create a db for the 
udfs
> USE hivemall...