Apache Hive Essentials
- Length: 145 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2015-03-27
- ISBN-10: 1783558571
- ISBN-13: 9781783558575
- Sales Rank: #1309110 (See Top 100 Books)
Immerse yourself on a fantastic journey to discover the attributes of big data by using Hive
About This Book
- Discover how Hive can coexist and work with other tools in the Hadoop ecosystem to create big data solutions
- Grasp the skills needed, learn the best practices, and avoid the pitfalls in writing efficient Hive queries to analyze the big data
- Create an environment to analyze big data using practical, example-oriented scenarios
Who This Book Is For
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.
In Detail
In this book, we prepare you for your journey into big data by firstly introducing you to backgrounds in the big data domain along with 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 skill in using the Hive language in an efficient manner. Towards 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 efficiently to find solutions to big data problems.
Table of Contents
Chapter 1. Overview of Big Data and Hive
Chapter 2. Setting Up the Hive Environment
Chapter 3. Data Definition and Description
Chapter 4. Data Selection and Scope
Chapter 5. Data Manipulation
Chapter 6. Data Aggregation and Sampling
Chapter 7. Performance Considerations
Chapter 8. Extensibility Considerations
Chapter 9. Security Considerations
Chapter 10. Working with Other Tools
