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Exam AWS Certified Database - Specialty topic 1 question 344 discussion

Exam question from Amazon's AWS Certified Database - Specialty
Question #: 344
Topic #: 1
[All AWS Certified Database - Specialty Questions]

A coffee machine manufacturer is equipping all of its coffee machines with IoT sensors. The IoT core application is writing measurements for each record to Amazon Timestream. The records have multiple dimensions and measures. The measures include multiple measure names and values.

An analysis application is running queries against the Timestream database and is focusing on data from the current week. A database specialist needs to optimize the query costs of the analysis application.

Which solution will meet these requirements?

  • A. Ensure that queries contain whole records over the relevant time range.
  • B. Use time range, measure name, and dimensions in the WHERE clause of the query.
  • C. Avoid canceling any query after the query starts running.
  • D. Implement exponential backoff in the application.
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

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Chosen Answer:
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MultiAZ
1 year, 6 months ago
Selected Answer: B
B is mandatory for efficiency
upvoted 3 times
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YOAber
1 year, 6 months ago
Selected Answer: B
https://docs.aws.amazon.com/timestream/latest/developerguide/queries-bp.html Where possible, use the equality operator when comparing dimensions and measures in the WHERE clause of a query. An equality predicate on dimensions and measure names allows for improved query performance and reduced query costs.
upvoted 4 times
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aws_s2
1 year, 6 months ago
Selected Answer: A
Either A or B. B is the best option if selecting a subset of the measures. Since in A it gets the complete record, I think it may be faster. But did not see any documentation supporting that.
upvoted 1 times
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dbkorn
1 year, 7 months ago
B: It' s work. use SELECT clause and WHERE clause as applicable to improve query performance and reduce cost. https://docs.aws.amazon.com/timestream/latest/developerguide/queries-bp.html
upvoted 2 times
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A (35%)
C (25%)
B (20%)
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