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Answer: Optimize the data ingestion rate and ensure it matches the processing capacity of the cluster.
A high number of late batches indicates that the data ingestion rate might be exceeding the processing capacity of the cluster. Optimizing the ingestion rate to match the cluster's processing capacity can help ensure timely processing of batches and meet the latency SLA.
Author: LeetQuiz Editorial Team
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Consider a scenario where a Spark streaming job is failing to meet its latency SLA. Upon inspection, you find that the Spark UI shows a high number of late batches. What steps would you take to address this issue?
A
Increase the batch interval to reduce the processing load.
B
Optimize the data ingestion rate and ensure it matches the processing capacity of the cluster.
C
Reduce the number of executors to focus on processing efficiency.
D
Increase the memory allocation for the streaming job.
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