DAS-C01 · Question #97
A marketing company is storing its campaign response data in Amazon S3. A consistent set of sources has generated the data for each campaign. The data is saved into Amazon S3 as .csv files. A…
The correct answer is A. Convert the .csv files to Apache Parquet. C. Partition the data by campaign. Athena bills per terabyte of data scanned. Two techniques directly reduce the amount of data scanned per query: (A) Converting CSV to Apache Parquet stores data in a columnar, compressed format. Athena reads only the columns referenced in a query rather than entire rows, often…
Question
A marketing company is storing its campaign response data in Amazon S3. A consistent set of sources has generated the data for each campaign. The data is saved into Amazon S3 as .csv files. A business analyst will use Amazon Athena to analyze each campaign's data. The company needs the cost of ongoing data analysis with Athena to be minimized. Which combination of actions should a data analytics specialist take to meet these requirements? (Choose two.)
Options
- AConvert the .csv files to Apache Parquet.
- BConvert the .csv files to Apache Avro.
- CPartition the data by campaign.
- DPartition the data by source.
- ECompress the .csv files.
How the community answered
(19 responses)- A84% (16)
- B11% (2)
- D5% (1)
Explanation
Athena bills per terabyte of data scanned. Two techniques directly reduce the amount of data scanned per query: (A) Converting CSV to Apache Parquet stores data in a columnar, compressed format. Athena reads only the columns referenced in a query rather than entire rows, often reducing scanned data by 60–90%. (C) Partitioning by campaign means Athena applies partition pruning - a query for a single campaign scans only that campaign's S3 prefix instead of the entire dataset. Together, columnar format plus partitioning yield the greatest cost reduction. Apache Avro (option B) is row-oriented and provides no columnar scan benefit. Partitioning by source (option D) does not align with the per-campaign query pattern. Compressing CSV (option E) reduces storage cost but Athena still scans entire rows, so savings are much smaller than with Parquet.
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