DEA-C01 · Question #90
A financial company wants to use Amazon Athena to run on-demand SQL queries on a petabyte- scale dataset to support a business intelligence (BI) application. An AWS Glue job that runs during…
The correct answer is B. Use the query result reuse feature of Amazon Athena for the SQL queries. https://docs.aws.amazon.com/athena/latest/ug/performance-tuning.html Use the Query Result Reuse Feature of Amazon Athena. This leverages Athena's built-in feature to reduce redundant data scans and thus lowers query costs.
Question
A financial company wants to use Amazon Athena to run on-demand SQL queries on a petabyte- scale dataset to support a business intelligence (BI) application. An AWS Glue job that runs during non-business hours updates the dataset once every day. The BI application has a standard data refresh frequency of 1 hour to comply with company policies. A data engineer wants to cost optimize the company's use of Amazon Athena without adding any additional infrastructure costs. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AConfigure an Amazon S3 Lifecycle policy to move data to the S3 Glacier Deep Archive storage
- BUse the query result reuse feature of Amazon Athena for the SQL queries.
- CAdd an Amazon ElastiCache cluster between the BI application and Athena.
- DChange the format of the files that are in the dataset to Apache Parquet.
How the community answered
(42 responses)- A14% (6)
- B71% (30)
- C5% (2)
- D10% (4)
Explanation
https://docs.aws.amazon.com/athena/latest/ug/performance-tuning.html Use the Query Result Reuse Feature of Amazon Athena. This leverages Athena's built-in feature to reduce redundant data scans and thus lowers query costs.
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