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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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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

Streaming

Hive can also leverage the streaming feature in Hadoop to transform data in an alternative way. The streaming API opens an I/O pipe to an external process, such as a script. Then, the process reads data from the standard input and writes the results out through the standard output. In HQL, we can use TRANSFORM clauses directly to embed the mapper and the reducer scripts written in commands, shell scripts, Java, or other programming languages. Although streaming brings overhead by using serialization/deserialization between processes, it provides a simple coding mode for non-Java developers. The syntax of the TRANSFORM clause is as follows:

FROM (
    FROM src
    SELECT TRANSFORM '(' expression (',' expression)* ')'
    (inRowFormat)?
    USING 'map_user_script'
    (AS colName (',' colName)*)?
    (outRowFormat)? (outRecordReader...
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