AWS Certified Data Analytics – Specialty — Question 70

A company has collected more than 100 TB of log files in the last 24 months. The files are stored as raw text in a dedicated Amazon S3 bucket. Each object has a key of the form year-month-day_log_HHmmss.txt where HHmmss represents the time the log file was initially created. A table was created in Amazon Athena that points to the S3 bucket. One-time queries are run against a subset of columns in the table several times an hour.
A data analyst must make changes to reduce the cost of running these queries. Management wants a solution with minimal maintenance overhead.
Which combination of steps should the data analyst take to meet these requirements? (Choose three.)

Answer options

• A. Convert the log files to Apace Avro format.
• B. Add a key prefix of the form date=year-month-day/ to the S3 objects to partition the data.
• C. Convert the log files to Apache Parquet format.
• D. Add a key prefix of the form year-month-day/ to the S3 objects to partition the data.
• E. Drop and recreate the table with the PARTITIONED BY clause. Run the ALTER TABLE ADD PARTITION statement.
• F. Drop and recreate the table with the PARTITIONED BY clause. Run the MSCK REPAIR TABLE statement.

Correct answer: B, C, F

Explanation

Choosing options B, C, and F is correct as they collectively optimize the data for query performance and cost efficiency. Option B partitions the data effectively, while option C converts the logs into a more efficient columnar format, reducing the amount of data scanned by queries. Option F allows the table to recognize the new partitions, ensuring optimal query performance, while the other options do not effectively address the requirements.