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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):

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

In this chapter, we will be using the Databricks Community Edition to run our code: https://community.cloud.databricks.com.

Sign-up instructions can be found at https://databricks.com/try-databricks.
The code and data used in this chapter can be downloaded from https://github.com/PacktPublishing/Essential-PySpark-for-Scalable-Data-Analytics/tree/main/Chapter05.

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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