Window functions, available since Hive v0.11.0, are a special group of functions that scan multiple input rows to compute each output value. Window 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, and limited to one result value per group, window functions operate on windows where the input rows are ordered and grouped using flexible conditions expressed through an OVER and PARTITION clause. Window functions give aggregate results, but they do not group the result set. They return the group value multiple times with each record. Window functions offer great flexibility and functionalities compared term the regular GROUP BY clause and make special aggregations by HQL easier and more powerful. The syntax for a window function is as follows...
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Table Of Contents
Apache Hive Essentials - Second Edition
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Apache Hive Essentials
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Overview of this book
In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment.
Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey.
By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
Table of Contents (12 chapters)
Preface
Free Chapter
Overview of Big Data and Hive
Setting Up the Hive Environment
Data Definition and Description
Data Correlation and Scope
Data Manipulation
Data Aggregation and Sampling
Performance Considerations
Extensibility Considerations
Security Considerations
Working with Other Tools
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