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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

Combining data with UNION

When we want to combine data with the same schema together, we often use set operations. Regular set operations in the relational database are INTERSECT, MINUS, and UNION/UNION ALL. HQL only supports UNION and UNION ALL. The difference between them is that UNION ALL does not remove duplicate rows while UNION does. In addition, all unioned data must have the same name and data type, or else an implicit conversion will be done and may cause a runtime exception. If ORDER BY, SORT BY, CLUSTER BY, DISTRIBUTE BY, or LIMIT are used, they are applied to the whole result set after the union:

> SELECT a.name as nm FROM employee a
> UNION ALL -- Use column alias to make the same name for union
> SELECT b.name as nm FROM employee_hr b;
+-----------+
| nm |
+-----------+
| Michael |
| Will |
| Shelley |
| Lucy |
| Michael |
| Will |
| Steven...
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