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Apache Hive Essentials
Apache Hive Essentials

Apache Hive Essentials: Essential techniques to help you process, and get unique insights from, big data , Second Edition

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Apache Hive Essentials

Setting Up the Hive Environment

This chapter will introduce how to install and set up the Hive environment in the cluster and cloud. It also covers the usage of basic Hive commands and the Hive integrated-development environment.

In this chapter, we will cover the following topics:

  • Installing Hive from Apache
  • Installing Hive from vendors
  • Using Hive in the cloud
  • Using the Hive command
  • Using the Hive IDE

Installing Hive from Apache

To introduce the Hive installation, we will use Hive version 2.3.3 as an example. The pre-installation requirements for this installation are as follows:

  • JDK 1.8
  • Hadoop 2.x.y
  • Ubuntu 16.04/CentOS 7
Since we focus on Hive in this book, the installation steps for Java and Hadoop are not provided here. For steps on installing them, please refer to https://www.java.com/en/download/help/download_options.xml and http://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/ClusterSetup.html.

The following steps describe how to install Apache Hive in the command-line environment:

  1. Download Hive from Apache Hive and unpack it:
      $cd /opt
$wget https://archive.apache.org/dist/hive/hive-2.3.3/apache-
hive-2.3.3-bin.tar.gz

$tar -zxvf apache-hive-2.3.3-bin.tar.gz
$ln -sfn /opt/apache-hive-2.3.3 /opt/hive
  1. Add the necessary system...

Installing Hive from vendors

Right now, many companies, such as Cloudera and Hortonworks, have packaged the Hadoop ecosystem and management tools into an easily manageable enterprise distribution. Each company takes a slightly different strategy, but the consensus for all of these packages is to make the Hadoop ecosystem easier and more stable for enterprise usage. For example, we can easily install Hive with the Hadoop management tools, such as Cloudera Manager (https://www.cloudera.com/products/product-components/cloudera-manager.html) or Ambari (https://ambari.apache.org/), which are packed in vendor distributions. Once the management tool is installed and started, we can add the Hive service to the Hadoop cluster with the following steps:

  1. Log in to the Cloudera Manager/Ambari and click the Add a Service option to enter the Add Service Wizard

  2. Choose the service to install...

Using Hive in the cloud

Right now, all major cloud service providers, such as Amazon, Microsoft, and Google, offer matured Hadoop and Hive as services in the cloud. Using the cloud version of Hive is very convenient. It requires almost no installation and setup. Amazon EMR (http://aws.amazon.com/elasticmapreduce/) is the earliest Hadoop service in the cloud. However, it is not a pure open source version since it is customized to run only on Amazon Web Services (AWS). Hadoop enterprise service and distribution providers, such as Cloudera and Hortonworks, also provide tools to easily deploy their own distributions on different public or private clouds. Cloudera Director (http://www.cloudera.com/content/cloudera/en/products-and-services/director.html) and Cloudbreak (https://hortonworks.com/open-source/cloudbreak/), open up Hadoop deployments in the cloud through a simple, self...

Using the Hive command

Hive first started with hiveserver1. However, this version of Hive server was not very stable. It sometimes suspended or blocked the client's connection quietly. Since v0.11.0, Hive has included a new thrift server called hivesever2 to replace hiveserver1. hiveserver2 has an enhanced server designed for multiple client concurrency and improved authentication. It also recommends using beeline as the major Hive command-line interface instead of the hive command. The primary difference between the two versions of servers is how the clients connect to them. hive is an Apache-Thrift-based client, and beeline is a JDBC client. The hive command directly connects to the Hive drivers, so we need to install the Hive library on the client. However, beeline connects to hiveserver2 through JDBC connections without installing Hive libraries on the client. That means...

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Key benefits

  • Grasp the skills needed to write efficient Hive queries to analyze the Big Data
  • Discover how Hive can coexist and work with other tools within the Hadoop ecosystem
  • Uses practical, example-oriented scenarios to cover all the newly released features of Apache Hive 2.3.3

Description

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

Who is this book for?

If you are a data analyst, developer, or simply someone who wants to quickly get started with Hive to explore and analyze Big Data in Hadoop, this is the book for you. Since Hive is an SQL-like language, some previous experience with SQL will be useful to get the most out of this book.

What you will learn

  • Create and set up the Hive environment
  • Discover how to use Hive s definition language to describe data
  • Discover interesting data by joining and filtering datasets in Hive
  • Transform data by using Hive sorting, ordering, and functions
  • Aggregate and sample data in different ways
  • Boost Hive query performance and enhance data security in Hive
  • Customize Hive to your needs by using user-defined functions and integrate it with other tools
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 30, 2018
Length: 210 pages
Edition : 2nd
Language : English
ISBN-13 : 9781788995092
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Apache
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Apache
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Tools :

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Table of Contents

11 Chapters
Overview of Big Data and Hive Chevron down icon Chevron up icon
Setting Up the Hive Environment Chevron down icon Chevron up icon
Data Definition and Description Chevron down icon Chevron up icon
Data Correlation and Scope Chevron down icon Chevron up icon
Data Manipulation Chevron down icon Chevron up icon
Data Aggregation and Sampling Chevron down icon Chevron up icon
Performance Considerations Chevron down icon Chevron up icon
Extensibility Considerations Chevron down icon Chevron up icon
Security Considerations Chevron down icon Chevron up icon
Working with Other Tools Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
(2 Ratings)
5 star 50%
4 star 0%
3 star 50%
2 star 0%
1 star 0%
srinivasa rao cherukumalli Nov 07, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good
Amazon Verified review Amazon
J. Hu Sep 09, 2019
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Since Hadoop is open source software, there is some kind complex for how to install it, and set up both of Windows and Ubuntu operation system. The book didn't mention that.I don't think this is good book for a beginning.
Amazon Verified review Amazon
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