Exam AWS Certified Data Analytics - Specialty topic 1 question 5 discussion

Answer: B B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter. Similar question is there in Jon Bonso's practice exam.

Correct answer is B as job metrics can be used to estimate the number of DPUs needed. Options A & D are wrong as Job bookmarks help AWS Glue maintain state information and prevent the reprocessing of old data. Options A & D are wrong as Job bookmarks help AWS Glue maintain state information and prevent the reprocessing of old data.

B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter.

It's a B

B: I passed the test

B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter. The data analyst should enable job metrics in AWS Glue to estimate the number of data processing units (DPUs) and profile the job to understand its resource requirements. Based on the profiled metrics, the data analyst should increase the value of the maximum capacity job parameter. This parameter controls the maximum number of DPUs that the job can use. By increasing the maximum capacity, the job can use more resources and complete faster without overprovisioning. Enabling job bookmarks can help with incremental processing but will not directly improve job execution time. Increasing the value of the executor-cores job parameter or the spark.yarn.executor.memoryOverhead job parameter may improve performance, but these parameters depend on the specific job requirements and are not directly related to the job's resource utilization. Similarly, increasing the num-executors job parameter will not directly improve job execution time.

Answer: B

정답:B 북마크는 상태를 표시하는것이기때문에 A,D는 제외. 메트릭을 통해서 dpu적정 개수를 추정하고, 최대용량을 늘리면 됩니다. 오버헤드 파라미터는 에러가 발생했을때 수정해야하지만, 문제는 3시간동안 러닝상태이기때문에 에러가 난것은 아니므로 C 제외 https://docs.aws.amazon.com/ko_kr/glue/latest/dg/monitor-debug-capacity.html#monitor-debug-capacity-fix

I suggest taking Jon Bonso's practice exams too.

This question is quite confused because for Glue version 2.0 jobs, you cannot instead specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers. However since A, D (no such parameters) and C (memoryOverhead not help in this case) are wrong, the best choice is B

Ans B A and D = wrong, the name “bookmark” suggests persistency of a in-progress state, and so it is, used to track processed data, not for scaling. C = wrong, although you can set this parameter, the job metrics won’t help you, and this parameter won’t help long job running times because that was due to lack of computational power not memory.

B is correct.

B. A, D. Bookmark is not used for monitoring ETL job status.

B is the right answer

B. B and C can make sense but C will be right only if the job returned the error spark.yarn.executor.memoryOverhead. If no error, then the job is just taking too long so increase the max capacity For AWS Glue version 2.0 jobs, you cannot instead specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers. https://docs.aws.amazon.com/glue/latest/dg/add-job.html

b is correct!

Option B for sure. We can eliminate the two options with Bookmarks and spark.yarn.executor.memoryOverhead has nothing to do with Glue.