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Discuss the role of data partitioning in improving the performance of dataflows and notebooks. Provide specific examples of how partitioning can be used to optimize data processing tasks. Additionally, explain how the choice of partitioning key can impact performance.
A
Use dynamic partitioning to distribute data processing tasks.
B
Increase the number of partitions to improve parallelism.
C
Use a random partitioning key to balance data across partitions.
D
Use a partitioning key based on commonly queried columns.