Databricks Data Engineer Associate Question 449
Select 3You are debugging a failed task in a Databricks job. Upon examining the task's logs, you notice an error indicating 'OutOfMemoryError'. Which of the following steps should you take to resolve this issue effectively?
- A
Increase the executor memory configuration for the cluster running the job.
- B
Inspect the dataset's size and optimize the data processing logic to reduce memory usage.
- C
Reduce the number of shuffle partitions to minimize memory overhead.
- D
Enable adaptive query execution (AQE) to optimize the execution plan dynamically.
- E
Add more nodes to the cluster to distribute the workload.
Show answer and explanation
Correct answers: A, B, D
Explanation
An 'OutOfMemoryError' occurs when the job's memory demand exceeds the available memory. To resolve this, you can increase executor memory, optimize the data processing logic, and enable features like AQE to dynamically adjust the execution plan. Simply adding more nodes or reducing shuffle partitions may not address the core issue and might lead to inefficiencies.
- A. Correct.
Increasing the executor memory configuration can help address the 'OutOfMemoryError' by providing more memory to handle the workload.
- B. Correct.
Inspecting the dataset size and optimizing the logic (e.g., using efficient transformations) can reduce memory utilization, addressing the root cause of the issue.
- C. Incorrect.
Reducing the number of shuffle partitions may increase memory usage per partition, potentially worsening the 'OutOfMemoryError' issue.
- D. Correct.
Enabling adaptive query execution (AQE) dynamically adjusts the query execution plan, which can optimize resource usage and reduce memory pressure.
- E. Incorrect.
Adding more nodes to the cluster may not resolve the issue if the root cause is inefficient memory utilization or configuration. It is better to optimize the job first.