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Exam AWS Certified Data Analytics - Specialty All Questions

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Exam AWS Certified Data Analytics - Specialty topic 1 question 106 discussion

A company uses Amazon Redshift for its data warehousing needs. ETL jobs run every night to load data, apply business rules, and create aggregate tables for reporting. The company's data analysis, data science, and business intelligence teams use the data warehouse during regular business hours. The workload management is set to auto, and separate queues exist for each team with the priority set to NORMAL.
Recently, a sudden spike of read queries from the data analysis team has occurred at least twice daily, and queries wait in line for cluster resources. The company needs a solution that enables the data analysis team to avoid query queuing without impacting latency and the query times of other teams.
Which solution meets these requirements?

  • A. Increase the query priority to HIGHEST for the data analysis queue.
  • B. Configure the data analysis queue to enable concurrency scaling.
  • C. Create a query monitoring rule to add more cluster capacity for the data analysis queue when queries are waiting for resources.
  • D. Use workload management query queue hopping to route the query to the next matching queue.
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Suggested Answer: D 🗳️

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SamChan
Highly Voted 3 years, 7 months ago
Answer is B https://docs.aws.amazon.com/redshift/latest/dg/concurrency-scaling.html You manage which queries are sent to the concurrency-scaling cluster by configuring WLM queues. When you turn on concurrency scaling, eligible queries are sent to the concurrency-scaling cluster instead of waiting in a queue.
upvoted 11 times
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imgeek
Highly Voted 3 years, 6 months ago
correct answer is B. (https://docs.aws.amazon.com/redshift/latest/dg/concurrency-scaling.html) D is wrong because it works only for manual WLM config. (https://docs.aws.amazon.com/redshift/latest/dg/wlm-queue-hopping.html)
upvoted 9 times
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pk349
Most Recent 2 years ago
B: I passed the test
upvoted 1 times
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cloudlearnerhere
2 years, 6 months ago
Correct answer is B as concurrency scaling can help scale the avoiding query queuing without impacting latency and the query times of other teams. With the Concurrency Scaling feature, you can support virtually unlimited concurrent users and concurrent queries, with consistently fast query performance.When you turn on concurrency scaling, Amazon Redshift automatically adds additional cluster capacity to process an increase in both read and write queries. Users see the most current data, whether the queries run on the main cluster or a concurrency-scaling cluster. You're charged for concurrency-scaling clusters only for the time they're actively running queries. Option D is wrong as workload management query queue hopping works only with manual WLM config. Option A is wrong as it does not help avoid query queuing. Option C is wrong as concurrency scaling does the same automatically.
upvoted 3 times
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rocky48
2 years, 9 months ago
Selected Answer: B
Answer is B
upvoted 1 times
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moon2351
3 years, 1 month ago
Selected Answer: B
Answer is B
upvoted 1 times
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taizo777
3 years, 7 months ago
I think B is right answer
upvoted 1 times
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