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Apache Hive Essentials

You're reading from   Apache Hive Essentials Essential techniques to help you process, and get unique insights from, big data

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788995092
Length 210 pages
Edition 2nd Edition
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Concepts
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Author (1):
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Dayong Du Dayong Du
Author Profile Icon Dayong Du
Dayong Du
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Toc

Table of Contents (12) Chapters Close

Preface 1. Overview of Big Data and Hive 2. Setting Up the Hive Environment FREE CHAPTER 3. Data Definition and Description 4. Data Correlation and Scope 5. Data Manipulation 6. Data Aggregation and Sampling 7. Performance Considerations 8. Extensibility Considerations 9. Security Considerations 10. Working with Other Tools 11. Other Books You May Enjoy

Summary

After going through this chapter, we are now able to understand when and why to use big data instead of a traditional relational database. We also learned about the difference between batch processing, real-time processing, and stream processing. We are now familiar with the Hadoop ecosystem, especially Hive. We have traveled back in time and brushed through the history of databases, data warehouse, and big data. We also explored some big data terms, the Hadoop ecosystem, the Hive architecture, and the advantage of using Hive.

In the next chapter, we will practice installing Hive and review all the tools needed to start using Hive in the command-line environment.

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