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Essential PySpark for Scalable Data Analytics

You're reading from Essential PySpark for Scalable Data Analytics A beginner's guide to harnessing the power and ease of PySpark 3

Product type Paperback

Published in Oct 2021

Publisher Packt

ISBN-13 9781800568877

Length 322 pages

Edition 1st Edition

Languages

Python

Tools

PySpark

Concepts

Big Data

Author (1):

Sreeram Nudurupati

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Data Engineering

2. Chapter 1: Distributed Computing Primer FREE CHAPTER

3. Chapter 2: Data Ingestion

4. Chapter 3: Data Cleansing and Integration

5. Chapter 4: Real-Time Data Analytics

6. Section 2: Data Science

7. Chapter 5: Scalable Machine Learning with PySpark

8. Chapter 6: Feature Engineering – Extraction, Transformation, and Selection

9. Chapter 7: Supervised Machine Learning

10. Chapter 8: Unsupervised Machine Learning

11. Chapter 9: Machine Learning Life Cycle Management

12. Chapter 10: Scaling Out Single-Node Machine Learning Using PySpark

13. Section 3: Data Analysis

14. Chapter 11: Data Visualization with PySpark

15. Chapter 12: Spark SQL Primer

16. Chapter 13: Integrating External Tools with Spark SQL

17. Chapter 14: The Data Lakehouse

18. Other Books You May Enjoy

Technical requirements

Here is what you'll need for this chapter:

In this chapter, we will be using Databricks Community Edition to run our code (https://community.cloud.databricks.com). Sign-up instructions can be found at https://databricks.com/try-databricks.
We will be using a free and open source SQL editor tool called SQL Workbench/J, which can be downloaded from https://www.sql-workbench.eu/downloads.html.
You will need to download a JDBC driver for SQL Workbench/J to be able to connect with Databricks Community Edition. This can be downloaded from https://databricks.com/spark/jdbc-drivers-download.
We will also be using Tableau Online to demonstrate BI tool integration. You can request a free 14-day Tableau Online trial at https://www.tableau.com/products/online/request-trial.

The rest of the chapter is locked

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Authors (1)

Nudurupati

Nudurupati

Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.

See other products by Nudurupati

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