PySpark and AWS: Master Big Data with PySpark and AWS - Spark DF with Column Renamed and Alias

This video tutorial covers various techniques for manipulating columns in a DataFrame using Spark. It emphasizes the proper way to rename columns with the 'withColumnRenamed' method and highlights the importance of reassigning transformed DataFrames to retain changes. Additionally, it explains how to use aliases for temporary column renaming, similar to SQL, without altering the original DataFrame.

What is the proper way to rename a column in a DataFrame according to the video?

Explain why the DataFrame does not show the updated column after renaming it without assigning it back.

Describe the process of updating a column name in a DataFrame and the importance of assigning it back.

What is the significance of using 'DF.show()' after renaming a column?

What happens if you try to rename a column that does not exist in the DataFrame?

How can you rename a column while reading data from a DataFrame without altering the original DataFrame?

What is the difference between using 'withColumnRenamed' and using an alias when selecting a column?