DBS-C01 · Question #353
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…
The correct answer is B. Use time range, measure name, and dimensions in the WHERE clause of the query. 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…
Question
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?
Options
- AEnsure that queries contain whole records over the relevant time range.
- BUse time range, measure name, and dimensions in the WHERE clause of the query.
- CAvoid canceling any query after the query starts running.
- DImplement exponential backoff in the application.
How the community answered
(24 responses)- A4% (1)
- B83% (20)
- C13% (3)
Explanation
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.
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