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In a Spark streaming application that processes events from Azure Event Hubs, which method is best for ensuring stateful computation across batches for windowed aggregations?
A
Employing watermarking to manage late-arriving data
B
Using updateStateByKey function
C
Applying reduceByKeyAndWindow with a sliding window function
D
Implementing mapWithState for efficient state updates
