DEA-C01 · Question #302
An ecommerce company collects daily customer transaction logs in CSV format and stores the logs in Amazon S3. The company uses Amazon Athena to scan a subset of attributes from the logs on the same da
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Question
An ecommerce company collects daily customer transaction logs in CSV format and stores the logs in Amazon S3. The company uses Amazon Athena to scan a subset of attributes from the logs on the same day the company receives each log. Query times are increasing because of increasing transaction volume. The company wants to improve query performance. Which solution will meet these requirements with the SHORTEST query times?
Options
- AConvert the CSV logs into multiple ORC files for better parallelism in Athena. Partition by date in
- BConvert the CSV logs to JSON. Partition by date in Amazon S3. Use Athena with dynamic
- CConvert the CSV logs to Avro. Partition by date in Amazon S3. Use Athena with projection-based
- DConvert the CSV logs to a single Apache Parquet file for each day Partition the data by date in
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