AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company runs an Amazon Redshift RA3 cluster. Every day the data engineering team loads click-stream files from Amazon S3. Each file is a JSON array whose event attributes change frequently as the web application evolves. The team must ensure that newly added attributes are immediately queryable in Redshift with minimal ongoing maintenance while still delivering good analytic performance. Which solution meets these requirements?

  • Stream the files into an Amazon RDS PostgreSQL database with AWS DMS and query the data from Redshift using federated queries.

  • Create a Redshift table that contains a single SUPER column, run COPY with FORMAT JSON 'noshred', and use PartiQL to query new attributes.

  • Maintain a JSONPaths file listing all attributes, use COPY with the JSONPaths option, and ALTER TABLE ADD COLUMN for every new attribute.

  • Run an AWS Glue crawler before each load to update a Glue Data Catalog table on S3 and query it from Redshift Spectrum.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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