AWS Certified Data Analytics – Specialty — Question 149

A technology company has an application with millions of active users every day. The company queries daily usage data with Amazon Athena to understand how users interact with the application. The data includes the date and time, the location ID, and the services used. The company wants to use Athena to run queries to analyze the data with the lowest latency possible.
Which solution meets these requirements?

Answer options

• A. Store the data in Apache Avro format with the date and time as the partition, with the data sorted by the location ID.
• B. Store the data in Apache Parquet format with the date and time as the partition, with the data sorted by the location ID.
• C. Store the data in Apache ORC format with the location ID as the partition, with the data sorted by the date and time.
• D. Store the data in .csv format with the location ID as the partition, with the data sorted by the date and time.

Correct answer: B

Explanation

Option B is the correct choice because Apache Parquet is a columnar storage format that provides efficient data compression and encoding schemes, which helps to reduce query latency. Other options, such as Avro, ORC, and CSV, do not offer the same level of performance for analytical queries in Athena, particularly when it comes to large datasets and low latency requirements.