Ultimate access to all questions.
Upgrade Now 🚀
Sign in to unlock AI tutor
In the context of using Pandas API on Spark, explain the key differences between Spark DataFrames and Pandas on Spark DataFrames, and how these differences might impact the performance of a data processing task.
A
Spark DataFrames are optimized for distributed computing, while Pandas on Spark DataFrames are not.
B
Pandas on Spark DataFrames can be used for distributed computing, but they are slower than Spark DataFrames due to the usage of an InternalFrame.
C
Spark DataFrames and Pandas on Spark DataFrames are identical in terms of performance and functionality.
D
Pandas on Spark DataFrames are faster than Spark DataFrames because they utilize the Pandas library for data manipulation.
