Spark Programming in Python for Beginners with Apache Spark 3 - Spark DataFrameReader API

This video tutorial introduces the basics of using Spark Data Frame Reader API to read data from various sources. It covers the supported formats, options, and read modes, including permissive, drop malformed, and fail fast. The tutorial also explains schema inference and the importance of following standard practices over shortcuts for better code maintainability.

What is the primary purpose of the Spark Data Frame Reader API?

List the four main things you can specify when using the Data Frame Reader.

What are the three read modes available in Spark when encountering a malformed record?

Explain the permissive read mode in Spark Data Frame Reader.

Why might you not need to specify a schema when using the Data Frame Reader?

What is the significance of the load method in the Data Frame Reader API?

Discuss the importance of following standard practices when using the Data Frame Reader API.