PySpark SQL Recipes

With HiveQL, Dataframe and Graphframes

Autor: Raju Kumar Mishra, Sundar Rajan Raman

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Legare: Carte broșată

Editura: APress

Disponibilitate: În depozitul extern

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204.67 lei

Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-sol...

Informații despre carte

Autor

Raju Kumar Mishra, Sundar Rajan Raman

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2019

Pagini

323

EAN

9781484243343

Enbook ID

20634971

Editura

APress

Greutate

518

Dimensiuni

155 x 235 x 23

Descriere completă

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 For Data scientists, Python programmers, and SQL programmers.

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PySpark SQL Recipes

With HiveQL, Dataframe and Graphframes

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