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Apache Hive Essentials. - Second Edition

You're reading from  Apache Hive Essentials. - Second Edition

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788995092
Pages 210 pages
Edition 2nd Edition
Languages
Author (1):
Dayong Du Dayong Du
Profile icon Dayong Du

Table of Contents (12) Chapters

Preface 1. Overview of Big Data and Hive 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

Basic aggregation

Data aggregation is the process of gathering and expressing data in a summary to get more information about particular groups based on specific conditions. HQL offers several built-in aggregate functions, such as max(...), min(...), and avg(...). It also supports advanced aggregation using keywords such as GROUPING SETS, ROLLUP, and CUBE, and different types of window function.

The basic built-in aggregate functions are usually used with the GROUP BY clause. If there is no GROUP BY clause specified, it aggregates over the whole row (all columns) by default. Besides aggregate functions, all columns selected must also be included in the GROUP BY clause. The following are a few examples involving the built-in aggregate functions:

  1. Aggregation without GROUP BY columns:
      > SELECT 
> count(*) as rowcnt1,
> count(1) as rowcnt2 -- same to...
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