PySpark SQL Recipes - With HiveQL, Dataframe and Graphframes (Paperback, 1st ed.)

Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code. PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graphframes. On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases. What You Will Learn Understand PySpark SQL and its advanced features Use SQL and HiveQL with PySpark SQL Work with structured streaming Optimize PySpark SQL Master graphframes and graph processing Who This Book Is ForData scientists, Python programmers, and SQL programmers.

General

Imprint:	Apress
Country of origin:	United States
Release date:	March 2019
First published:	2019
Authors:	Raju Kumar Mishra • Sundar Rajan Raman
Dimensions:	235 x 155 x 23mm (L x W x T)
Format:	Paperback
Pages:	323
Edition:	1st ed.
ISBN-13:	978-1-4842-4334-3
Categories:	Books > Computing & IT > Computer programming > Programming languages > General Books > Computing & IT > Computer software packages > Database software > General Promotions
LSN:	1-4842-4334-X
Barcode:	9781484243343

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