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PySpark SQL Recipes

- With HiveQL, Dataframe and Graphframes

About PySpark SQL Recipes

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.

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  • Language:
  • English
  • ISBN:
  • 9781484243343
  • Binding:
  • Paperback
  • Pages:
  • 323
  • Published:
  • March 18, 2019
  • Edition:
  • 1
  • Dimensions:
  • 232x156x23 mm.
  • Weight:
  • 518 g.
Delivery: 2-4 weeks
Expected delivery: August 10, 2025

Description of PySpark SQL Recipes

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.

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