Databricks Certified Data Engineer - Professional
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Consider a scenario where a Spark application is experiencing high latency during the execution of a batch job. Using the Spark UI, you notice that the event timeline shows a significant number of long-running tasks in a specific stage. What steps would you take to diagnose and potentially resolve this performance issue?
Consider a scenario where a Spark application is experiencing high latency during the execution of a batch job. Using the Spark UI, you notice that the event timeline shows a significant number of long-running tasks in a specific stage. What steps would you take to diagnose and potentially resolve this performance issue?
Simulated
Explanation:
The presence of long-running tasks in a specific stage indicates a possible data skew issue. Analyzing task metrics can help identify if certain tasks are processing disproportionately larger amounts of data. Repartitioning the data can help distribute the load more evenly across tasks, thereby improving performance.