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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 FREE CHAPTER 2. Setting Up the Hive Environment 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

Data file optimization


Data file optimization covers the performance improvement on the data files in terms of file format, compression, and storage.

File format

Hive supports TEXTFILE, SEQUENCEFILE, RCFILE, ORC, and PARQUET file formats. The three ways to specify the file format are as follows:

  • CREATE TABLE ... STORE AS <File_Format>

  • ALTER TABLE ... [PARTITION partition_spec] SET FILEFORMAT <File_Format>

  • SET hive.default.fileformat=<File_Format> --default fileformat for table

Here, <File_Type> is TEXTFILE, SEQUENCEFILE, RCFILE, ORC, and PARQUET.

We can load a text file directly to a table with the TEXTFILE format. To load data to the table with other file formats, we need to load the data to a TEXTFILE format table first. Then, use INSERT OVERWRITE TABLE <target_file_format_table> SELECT * FROM <text_format_source_table> to convert and insert the data to the file format as expected.

The file formats supported by Hive and their optimizations are as follows...

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