Data Manipulation with Spark DataFrames
Data manipulation is a prerequisite for any data analysis. To draw meaningful insights from the data, we first need to understand, process, and massage the data. But this step becomes particularly hard with the increase in the size of data. Due to the scale of data, even simple operations such as filtering and sorting become complex coding problems. Spark DataFrames make data manipulation on big data a piece of cake.
Manipulating the data in Spark DataFrames is quite like working on regular pandas DataFrames. Most of the data manipulation operations on Spark DataFrames can be done using simple and intuitive one-liners. We will use the Spark DataFrame containing the Iris dataset that we created in previous exercises for these data manipulation exercises.
Exercise 29: Selecting and Renaming Columns from the DataFrame
In this exercise, we will first rename the column using the withColumnRenamed method and then select and print the schema using the select...
