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Explain the key differences between Spark DataFrames and Pandas on Spark DataFrames. Discuss how these differences impact performance and scalability when handling large datasets.
A
Spark DataFrames are optimized for distributed computing, while Pandas on Spark DataFrames are optimized for single-node performance.
B
Pandas on Spark DataFrames are designed to be used in conjunction with PySpark, while Spark DataFrames are standalone.
C
Spark DataFrames use lazy evaluation, whereas Pandas on Spark DataFrames use eager evaluation.
D
Spark DataFrames are immutable, while Pandas on Spark DataFrames are mutable.
