AWS Certified Data Engineer Associate DEA-C01 Practice Question

An ecommerce company keeps 3 years of web-server logs as uncompressed .txt files in the s3://company-data/logs/ prefix. Data analysts must run interactive ad-hoc SQL queries against only the most recent 90 days of logs. The solution must minimize query cost, leave the raw files unchanged, and avoid managing long-running infrastructure. Which approach best meets these requirements?

  • Copy the most recent 90 days of logs into an Amazon Redshift cluster and pause the cluster when queries are finished.

  • Create external tables in Amazon Athena that reference the existing .txt files and add day-based partitions for the last 90 days.

  • Import all .txt logs into an Amazon RDS for PostgreSQL instance with auto-scaling storage and index the timestamp column.

  • Use an AWS Glue ETL job to convert the latest 90 days of .txt logs to compressed Parquet files in a separate S3 prefix and query that prefix with Amazon Athena.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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