Identify Trends in Job Performance Using the Lakeflow Jobs Run History View to Compare Current Execution Times Against Historical Baselines. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 5)

Questions 21–23

1. 21foundation · easy

   In the run history view, what is the purpose of comparing the current execution time to historical baselines?

   • ATo calculate the cost of the current run
   • BTo check the cluster configuration used
   • CTo identify if the current run is performing as expected
   • DTo determine the exact cause of a failure
   Reveal Solution Discussion Select an answer first
2. 22expert · hard

   A company runs a critical ETL job every hour. The run history view shows that for the past two weeks, the job's duration has been steadily increasing from 10 minutes to 25 minutes. The data volume is constant. The team suspects a memory leak in the Spark application. They need to confirm the trend and identify the root cause. Which combination of actions is most appropriate?

   • AUse the run history view to confirm the increasing trend, then examine the Spark UI metrics (e.g., garbage collection, memory usage) from the latest run.
   • BCheck the job's schedule to see if the trigger time has changed.
   • CImmediately increase the cluster size to reduce execution time, then monitor the next few runs.
   • DReview the job's run history to see if the status is 'Succeeded' or 'Failed' for each run.
   Reveal Solution Discussion Select an answer first
3. 23foundation · easy

   A data engineer is looking at the run history view for a job. Which of the following is NOT a typical metric shown for each run?

   • AStatus
   • BStart time
   • CEnd time
   • DCluster ID
   Reveal Solution Discussion Select an answer first