Cloudera CDP Data Engineer - Certification - CDP-3002무료 덤프문제 풀어보기

A. Delete old snapshots

B. Rebuild the Iceberg metadata table

C. Compact data files

D. Rewrite manifest files

A. No additional security measures are needed, as Spark handles data security

B. Rely on Spark's lineage tracking to prevent unauthorized access

C. Implement custom access control mechanisms within your application

D. Encrypt the data before persisting it and decrypt it when needed

A. They allow for faster query processing by scanning only relevant partitions.

B. They ensure that all data is stored in a single file, simplifying access.

C. They decrease the security of the data.

D. They automatically encrypt data based on the partition key.

A. Use Spark's Lineage Viewer to visualize data flow and identify potential errors

B. Implement unit tests for individual Spark operations within your application

C. Print debug statements throughout the code to inspect intermediate data

D. Leverage Spark's web UI and Hive logs for general error messages

A. OFF HEAP

B. MEMORY AND DISK

C. MEMORY ONLY

D. DISK ONLY

A. Schema versioning via external services

B. Strong data typing

C. Manual schema declaration

D. Embedded schema within data files

A. You need to manually inspect the code for potential issues.

B. The DAG run details page displays the task logs, providing insights into the specific error encountered.

C. The Airflow web server logs might contain relevant information about the error.

D. All of the above

A. 'spark.dynamicAllocation.minExecutors', 'spark.dynamicAllocation.maxExecutors'

B. 'spark.kubernetes.container.image', 'spark.kubernetes.executor.limit.cores'

C. 'spark.executor.instances', 'spark.executor.cores'

D. 'spark.executor.memory', 'spark.executor.memoryoverhead'

A. Use the cron expression "@hourly".

B. Define a custom Python function to schedule the DAG at the desired time.

C. Utilize Airflow triggers to initiate the DAG execution at midnight.

D. Set the schedule_interval parameter to "0 0 ".

A. Rely on the error message displayed on the Airflow UI, even if it's generic.

B. Inspect the code of failed tasks directly within the Airflow web Ul for potential issues.

C. Utilize Airflow logs (scheduler, worker) to analyze detailed error messages and stack traces.

D. All of the above

A. Utilize Airflow XCom to share information about failed tasks with downstream tasks for alternative processing.

B. Implement custom logic within each task to handle potential errors and retry failed tasks manually.

C. Configure the DAG to automatically retry failed tasks a specific number of times.

D. All of the above

A. Implement the Retry operator to automatically retry failed tasks.

B. Increase the priority_weight of memory-intensive tasks to ensure they run first.

C. Use the Pool feature to limit the number of concurrent memory-intensive tasks.

D. Split the DAG into multiple smaller DAGs to reduce the load on workers.

A.

B.

C.

D.