DEA-C01 Question 150
Select 2Your company is building a data lake on Amazon S3 to store and analyze terabytes of semi-structured data. You need to optimize the data for query performance and cost efficiency using Amazon Athena. What are the best practices you should follow when storing and managing the data in Amazon S3?
- A
Partition the data based on frequently queried attributes, such as date or region.
- B
Store data in its original format without applying compression to avoid overhead during queries.
- C
Convert data into a columnar format like Apache Parquet or ORC before storing it in S3.
- D
Use a flat namespace in S3 without organizing data into folders or prefixes.
- E
Enable S3 Transfer Acceleration for faster query processing in Athena.
Show answer and explanation
Correct answers: A, C
Explanation
To optimize a data lake on Amazon S3 for Amazon Athena, it is essential to partition the data by frequently queried attributes and convert the data into columnar formats like Parquet or ORC. These practices reduce the amount of data scanned during queries, improving performance and reducing query costs. Avoid storing uncompressed data and ensure proper organization of the S3 bucket to maintain efficiency.
- A. Correct.
Partitioning data by frequently queried attributes like date or region reduces the amount of data scanned during a query, improving query performance and reducing costs. This is a best practice for Athena.
- B. Incorrect.
Storing data without compression leads to higher storage costs and slower query performance. Compression formats like GZIP or Snappy are recommended for efficiency.
- C. Correct.
Converting data into columnar formats like Parquet or ORC optimizes for analytics workloads by reducing the amount of data read during queries, improving performance and cost efficiency.
- D. Incorrect.
Using a flat namespace without organizing data into folders or prefixes makes it harder to manage and query data efficiently. Data organization is critical for performance.
- E. Incorrect.
S3 Transfer Acceleration is designed for speeding up uploads and downloads to S3 from remote locations, not for query performance in Athena.