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Apache Hive Essentials

You're reading from   Apache Hive Essentials Immerse yourself on a fantastic journey to discover the attributes of big data by using Hive

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783558575
Length 208 pages
Edition 1st Edition
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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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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 Selection and Scope 5. Data Manipulation 6. Data Aggregation and Sampling 7. Performance Considerations 8. Extensibility Considerations 9. Security Considerations 10. Working with Other Tools Index

Analytic functions


Analytic functions, available since Hive 0.11.0, are a special group of functions that scan the multiple input rows to compute each output value. Analytic functions are usually used with OVER, PARTITION BY, ORDER BY, and the windowing specification. Different from the regular aggregate functions used with the GROUP BY clause that is limited to one result value per group, analytic functions operate on windows where the input rows are ordered and grouped using flexible conditions expressed through an OVER PARTITION clause. Though analytic functions give aggregate results, they do not group the result set. They return the group value multiple times with each record. The analytic functions offer great flexibility and functionalities than the regular GROUP BY clause and make special aggregations in Hive easier and powerful. The syntax for the analyze function is as follows:

Function (arg1,..., argn) OVER ([PARTITION BY <...>] [ORDER BY <....>] [<window_clause...
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