Question
A data engineer needs Amazon Athena queries to finish faster. The data engineer notices that all the files the Athena queries use are currently stored in uncompressed .csv format. The data engineer also notices that users perform most queries by selecting a specific column.
Which solution will MOST speed up the Athena query performance?
- A. Change the data format from .csv to JSON format. Apply Snappy compression.
- B. Compress the .csv files by using Snappy compression.
- C. Change the data format from .csv to Apache Parquet. Apply Snappy compression. Correct
- D. Compress the .csv files by using gzip compression.
Explanation
Changing the data format from .csv to Apache Parquet and applying Snappy compression (Option C) will most speed up Athena query performance because Apache Parquet is a columnar storage file format that significantly improves read performance, especially for queries selecting specific columns. Additionally, using Snappy compression reduces I/O costs while maintaining fast decompression speeds during query execution.
