You're reading from Essential PySpark for Scalable Data Analytics

Product typeBook

Published inOct 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781800568877

Edition1st Edition

Languages

Python

Tools

PySpark

Concepts

Big Data

Author (1)

Sreeram Nudurupati

Technical requirements

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

Sign-up instructions can be found at https://databricks.com/try-databricks.

The code used in this chapter can be downloaded from https://github.com/PacktPublishing/Essential-PySpark-for-Data-Analytics/tree/main/Chapter01.

The datasets used in this chapter can be found at https://github.com/PacktPublishing/Essential-PySpark-for-Data-Analytics/tree/main/data.

The original datasets can be taken from their sources, as follows:

Online Retail: https://archive.ics.uci.edu/ml/datasets/Online+Retail+II
Image Data: https://archive.ics.uci.edu/ml/datasets/Rice+Leaf+Diseases
Census Data: https://archive.ics.uci.edu/ml/datasets/Census+Income
Country Data: https://public.opendatasoft.com/explore/dataset/countries-codes/information/

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Essential PySpark for Scalable Data Analytics

Published in: Oct 2021Publisher: PacktISBN-13: 9781800568877

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Author (1)

Sreeram 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.
Read more about Sreeram Nudurupati

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