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During the deployment of a Spark batch job, you need to ensure that the job can handle large datasets efficiently while adhering to cost constraints. What strategies would you employ to achieve this?
A
Use a high number of small, inexpensive clusters to distribute the load and reduce costs.
B
Implement dynamic resource allocation and autoscaling based on real-time metrics to optimize both cost and performance.
C
Run the batch job on a single, large cluster to minimize latency.
D
Increase the batch interval to reduce processing costs.
