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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 FREE CHAPTER 2. Setting Up the Hive Environment 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

Functions

To further manipulate data, we can also use operators, expressions, and functions in HQL to transform data. The Hive wiki (https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF) offers specifications for all supported expressions and functions, so we do not want to repeat all of them here, except a few important tips in this chapter.

Hive has defined relational operators, arithmetic operators, logical operators, complex type operators, and complex type constructors. For relational, arithmetic, and logical operators, they are similar to standard operators in SQL/Java. For operators on a complex data type, we have already introduced them in the Understanding Hive data types Section in Chapter 3, Data Definition and Description, as well as the example of inserting data into dynamic partitions earlier in this chapter. Functions in HQL are categorized as follows...

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