PySpark SQL Recipes With HiveQL, Dataframe and Graphframes /

• Main Authors: Mishra, Raju Kumar (Author, http://id.loc.gov/vocabulary/relators/aut), Raman, Sundar Rajan (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
• Edition: 1st ed. 2019.
• Subjects: Big data.; Open source software.; Computer programming.; Python (Computer program language).; Programming languages (Electronic computers).; Big Data.; Open Source.; Python.; Programming Languages, Compilers, Interpreters.

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 gra...

Table of Contents:

• Chapter 1: Introduction to PySparkSQL
• Chapter 2: Some time with Installation
• Chapter 3: IO in PySparkSQL
• Chapter 4 : Operations on PySparkSQL DataFrames
• Chapter 5 : Data Merging and Data Aggregation using PySparkSQL
• Chapter 6: SQL, NoSQL and PySparkSQL
• Chapter 7: Structured Streaming
• Chapter 8 : Optimizing PySparkSQL
• Chapter 9 : GraphFrames.