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AWS Certified Data Engineer Associate DEA-C01 Practice Question

An analytics team runs ad-hoc queries from an Amazon Redshift cluster against 15 TB of application logs in Amazon S3 by using Redshift Spectrum. The logs are gzip-compressed CSV files stored under a single prefix. Queries are slow and incur high data-scanned charges. The team cannot load the data into Redshift but can transform the S3 data once. Which change will most effectively improve performance and reduce Spectrum cost?

  • Enable Amazon Redshift Concurrency Scaling and increase the number of query slots in the WLM configuration.

  • Re-compress the CSV files with bzip2 to achieve a higher compression ratio before running Spectrum queries.

  • Create an Amazon Redshift materialized view that references the existing CSV files through a Spectrum manifest file.

  • Convert the log files to Parquet and partition the dataset (for example by date), then recreate the external table to reference the new location.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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