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Discuss the limitations of Pandas API on Spark when compared to native Spark DataFrames. Provide specific examples and explain how these limitations can impact data processing tasks.
A
Pandas API on Spark lacks support for distributed processing, leading to slower performance for large datasets.
B
Pandas API on Spark has limited support for advanced data manipulation functions, impacting complex data processing tasks.
C
Pandas API on Spark does not support lazy evaluation, which can lead to inefficient query execution for large datasets.
D
Pandas API on Spark has a higher memory footprint due to the InternalFrame structure, potentially causing memory issues for large datasets.
