Q12Data Operations and Support
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?
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C 14
Selected Answer: C
If the exam had only questions like these, everyone would be blessed
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C. Change the data format from .csv to Apache Parquet. Apply Snappy compression.
Explanation:
Apache Parquet is a columnar storage format built for analytical queries. It is very efficient for query performance, especially when queries involve selecting specific columns, because it enables column pruning and predicate pushdown optimizations.
C 2
Selected Answer: C
https://aws.amazon.com/jp/blogs/news/top-10-performance-tuning-tips-for-amazon-athena/
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C is easy
C 1
Selected Answer: C
Parquet is columnar storage and the question says that users performs most queries by selecting a specific column.
C 1
Selected Answer: C
switching to Apache Parquet format with Snappy compression provides the most significant improvement in Athena query performance, especially for queries that select specific columns
C 1
Selected Answer: C
C is correct
C 1
Selected Answer: C
C is the way to do It based on best practices recommended by AWS (https://aws.amazon.com/pt/blogs/big-data/top-10-performance-tuning-tips-for-amazon-athena/)
C 1
Selected Answer: C
C is correct
C 1
Selected Answer: C
C is correct
C 1
Selected Answer: C
C is correct
C 1
Selected Answer: C
Parquet is a columnar format, so Athena scans only the needed columns. With Snappy compression, this gives the highest performance improvement.