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PySpark Recipes: A Problem-Solution Approach with PySpark2
book

PySpark Recipes: A Problem-Solution Approach with PySpark2

by Raju Kumar Mishra
December 2017
Intermediate to advanced
280 pages
5h 56m
English
Apress
Content preview from PySpark Recipes: A Problem-Solution Approach with PySpark2
©  Raju Kumar Mishra 2018
Raju Kumar MishraPySpark Recipeshttps://doi.org/10.1007/978-1-4842-3141-8_8

8. PySparkSQL

Raju Kumar Mishra1 
(1)
Bangalore, Karnataka, India
 

Most data that a data scientist deals with is either structured or semistructured. Nowadays, the amount of unstructured data is increasing rapidly. The PySparkSQL module is a higher-level abstraction over PySpark Core for processing structured and semistructured datasets. By using PySparkSQL, we can use SQL and HiveQL code too, which makes this module popular among database programmers and Apache Hive users. The APIs provided by PySparkSQL are optimized. PySparkSQL can read data from many file types such as CSV files, JSON files, and files from other databases.

The DataFrame abstraction ...

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Publisher Resources

ISBN: 9781484231418