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Apache Hive Essentials
Apache Hive Essentials

Apache Hive Essentials: Immerse yourself on a fantastic journey to discover the attributes of big data by using Hive

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Apache Hive Essentials

Chapter 2. 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 vendor packages
  • Starting Hive in the cloud
  • Using the Hive command line and Beeline
  • The Hive-integrated development environment

Installing Hive from Apache

To introduce the Hive installation, we use Hive version 1.0.0 as an example. The pre-installation requirements for this installation are as follows:

The following steps describe how to install Hive from Apache through the Linux command line:

  1. Download Hive from Apache Hive and unpack it:
    bash-4.1$ wget http://apache.mirror.rafal.ca/hive/hive-1.0.0/apache-hive-1.0.0-bin.tar.gz
    bash-4.1$ tar -zxvf apache-hive-1.0.0-bin.tar.gz
    
  2. Add Hive to the system path by opening /etc/profile or ~/.bashrc and add the following two rows:
    export HIVE_HOME=/home/hivebooks/apache-hive-1.0.0-bin
    export PATH=$PATH...

Installing Hive from vendor packages

Right now, many companies, such as Cloudera, MapR, IBM, and Hortonworks, have packaged Hadoop into more easily manageable distributions. Each company takes a slightly different strategy, but the consensus for all of these packages is to make Hadoop easier to use for enterprise. For example, we can easily install Hive from Cloudera Distributed Hadoop (CDH), which can be downloaded from http://www.cloudera.com/content/cloudera/en/downloads/cdh.html.

Once CDH is installed to have the Hadoop environment ready, we can add Hive to the Hadoop cluster by following a few steps:

  1. Log in to the Cloudera manager and click on the dropdown button after the cluster name to choose Add a Service.
    Installing Hive from vendor packages

    Cloudera manager main page

  2. In the first Add Service Wizard page, choose Hive to install.
    Installing Hive from vendor packages
  3. In the second Add Service Wizard page, set the dependencies for the service. Sentry is the authorization policy service for Hive.
    Installing Hive from vendor packages
  4. In the third Add Service Wizard page, choose the proper hosts...

Starting Hive in the cloud

Right now, Amazon EMR, Cloudera Director, and Microsoft Azure HDInsight Service are some of the major vendors offering matured Hadoop and Hive services in the cloud. Using the cloud version of Hive is very convenient. It almost requests 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 sourced version of Hadoop, but is customized to run only on AWS cloud. Cloudera is one of the first few players that offered open source Hadoop solutions to the enterprise. Since the middle of October 2014, Cloudera has delivered Cloudera Director (http://www.cloudera.com/content/cloudera/en/products-and-services/director.html), which opens up Hadoop deployments in the cloud through a simple, self-service interface, and is fully supported on Amazon Web Services. Windows Azure HDInsight Service (http://azure.microsoft.com/en-us/documentation/services/hdinsight/) is a service that...

Using the Hive command line and Beeline

Hive first started with HiveServer1. However, this version of the Hive server was not very stable. It sometimes suspended or blocked clients' connection quietly. Since version 11, Hive includes a new Hive server called HiveSever2 as an addition to HiveServer1. HiveServer2 is an enhanced Hive server designed for multiclient concurrency and improved authentication. HiveServer2 also supports Beeline as the alternative command-line interface. HiveServer1 is deprecated and removed from Hive since version 1.0.0.

The primary difference between the two Hive servers is how the clients connect to Hive. Hive CLI is an Apache Thrift-based client, and Beeline is a JDBC client based on SQLLine (http://sqlline.sourceforge.net/) CLI. The Hive CLI directly connects to the Hive drivers and requires installing Hive on the same machine as the client. However, Beeline connects to HiveServer2 through JDBC connections and does not require the installation of Hive libraries...

The Hive-integrated development environment

Besides the command-line interface, there are a few integrated development environment (IDE) tools available for Hive development. One of the best is Oracle SQL Developer, which leverages the powerful functionalities of Oracle IDE and is totally free to use. If we have to use Oracle along with Hive in a project, it is quite convenient to switch between them only from the same IDE.

Oracle SQL developer has supported Hive since version 4.0.3. Configuring it to work with Hive is quite straightforward. The following are a few steps to configure the IDE to connect to Hive:

  1. Download Hive JDBC drivers from the vendor website, such as Cloudera.
  2. Unzip the JDBC version 4 driver to a local directory.
  3. Start Oracle SQL Developer and navigate to Preferences | Database | Third Party JDBC Drivers.
  4. Add all of the JAR files contained in the unzipped directory to the Third-party JDBC Driver Path setting as follows:
    The Hive-integrated development environment

    SQL developer configuration

  5. Click on the OK button and...

Installing Hive from Apache


To introduce the Hive installation, we use Hive version 1.0.0 as an example. The pre-installation requirements for this installation are as follows:

The following steps describe how to install Hive from Apache through the Linux command line:

  1. Download Hive from Apache Hive and unpack it:

    bash-4.1$ wget http://apache.mirror.rafal.ca/hive/hive-1.0.0/apache-hive-1.0.0-bin.tar.gz
    bash-4.1$ tar -zxvf apache-hive-1.0.0-bin.tar.gz
    
  2. Add Hive to the system path by opening /etc/profile or ~/.bashrc and add the following two rows:

    export HIVE_HOME=/home/hivebooks/apache-hive-1.0.0-bin
    export PATH=$PATH...
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Description

If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Whether you are new to big data or an expert, with this book, you will be able to master both the basic and the advanced features of Hive. Since Hive is an SQL-like language, some previous experience with the SQL language and databases is useful to have a better understanding of this book.
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 26, 2015
Length: 208 pages
Edition : 1st
Language : English
ISBN-13 : 9781783558575
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Table of Contents

11 Chapters
1. Overview of Big Data and Hive Chevron down icon Chevron up icon
2. Setting Up the Hive Environment Chevron down icon Chevron up icon
3. Data Definition and Description Chevron down icon Chevron up icon
4. Data Selection and Scope Chevron down icon Chevron up icon
5. Data Manipulation Chevron down icon Chevron up icon
6. Data Aggregation and Sampling Chevron down icon Chevron up icon
7. Performance Considerations Chevron down icon Chevron up icon
8. Extensibility Considerations Chevron down icon Chevron up icon
9. Security Considerations Chevron down icon Chevron up icon
10. Working with Other Tools Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(4 Ratings)
5 star 50%
4 star 50%
3 star 0%
2 star 0%
1 star 0%
Ian Stirk May 01, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Hi,I have written a detailed chapter-by-chapter review of this book on www DOT i-programmer DOT info, the first and last parts of this review are given here. For my review of all chapters, search i-programmer DOT info for STIRK together with the book's title.This book aims to introduce you to a popular platform for storing and analyzing big data on Hadoop. How does it fare?Increasing amounts of data are being created, and there’s a need to store and process this data to gain competitive advantage. Hive is a popular platform for storing and analyzing big data on Hadoop. Hive tends to be popular because it uses a SQL-like syntax, familiar to many people. With plenty of built-in functionality, big data analysis can be done in Hive without advanced coded skills.The book is aimed at both the beginner and the more advanced audience (data analysts, developers, and users). Some previous experience of SQL and databases is advantageous.Chapter 1 Overview of Big Data and HiveThe chapter opens with a brief overview of the history of data processing, covering: batch, online, relational databases, and the internet. The latter has led to a massive rise in the amount of data being created, requiring new approaches to processing. This big data can be described in terms of various attributes including: volume, velocity and variety.Big data tends to be processed on relatively cheap commodity hardware, using a distributed processing. Hadoop is a popular platform for big data processing. The chapter discusses the major components of Hadoop:*Hadoop Distributed File System (HDFS) – storage system*MapReduce – computing system (distributes processing and aggregates results)*Associated components (e.g. HBase, Sqoop, Flume, Impala etc)Having described how we arrived at big data and Hadoop, the chapter proceeds with an overview of Hive. Hive allows you to issue queries against petabytes of data, using its Hive Query Language (HQL) which is similar to SQL. Hive gives a table structure to data held in HDFS. Using Hive allows simpler data processing, compared with similar code written in Java.This chapter provides a helpful background on how we arrived at today’s big data and Hadoop platform. An overview of Hadoop and its components is given, together with a very helpful diagram of the Hadoop ecosystem (e.g. HDFS, HBase, Sqoop, Impala, etc). A useful overview of Hive is provided, highlighting its purpose and advantages....ConclusionThis book provides up-to-date detail on Hive, a very popular platform for storing and analyzing big data on Hadoop.Most topics are explained in a very readable manner, a few sections could do with more detail (e.g. transactions). Throughout, there are helpful explanations, screenshots, practical code examples, and inter-chapter references. Some links to websites are provided for further information.This book is especially suitable for developers and data analysts starting out with Hive. Additionally, since it also contains advanced and up-to-date material, it is also suitable for more advanced developers/analysts. If you have a background in SQL the book is even easier to understand.There are very few books dedicated to Hive, and these tend to be out of date now (especially since Hive changes regularly). If you want an up-to-date, practical, wide-ranging review of Hive’s functionality, I highly recommend this book.
Amazon Verified review Amazon
H H C X Apr 10, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is by far the most up to date book about Hive. It's been such a long time I've been waiting for a book to cover most stable and widely used Hive version. It is well written. All topics in each chapter are carefully picked and clearly presented for the all level of readers. You really do not need much programming or big data backgrounds to learn it. By reading the book, I strongly agree to the author that Hive will be the most important and popular tools of big data ecosystem for now and future. And most people can and should start the journey of big data from learning Hive. Of course, this is really a good book to start reading.
Amazon Verified review Amazon
Ryan May 05, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Given the hyped data science and big data framework buzzwords, the topic this book covers is definitely relevant and important to big data practitioners. The author appears to have a long and solid experience in the industry which gave him much practical knowledge on the subject. Having quickly skimmed through the book, my first impression is the book has a broad coverage of Apache Hive, ranging from the basic setup to security, data manipulation and the detailed explanation on the grammar, complemented with relatively straightforward examples.My current feeling is, as a thin book of 200 pages, it did quite a good job.
Amazon Verified review Amazon
Sumit Pal Apr 03, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This is a good starting to intermediate level book for readers getting to learn hie for the 1st time.This book is quite detailed and covers all the basics needed to get you up and running and playing around and working with Hive.The book is well organized and each chapter gets one or few concepts across. I like the chapters on performance optimizations and security.
Amazon Verified review Amazon
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