AWS Certified Data Engineer Associate DEA-C01 Practice Question
An ecommerce company stores 10 TB of click-stream data in an Amazon Redshift RA3 cluster. New records are appended hourly. Most queries filter on a recent date range and occasionally on user_id, then join to small dimension tables. The team wants the fastest scans with the least maintenance effort. Which table design best meets these requirements?
Define no sort key, enable automatic table optimization, and set DISTSTYLE ALL for the fact table.
Specify an interleaved sort key on event_date and user_id and schedule weekly deep VACUUM REINDEX operations.
Create the table with a compound sort key headed by event_date, keep DISTSTYLE AUTO, and run ANALYZE COMPRESSION to assign column encodings.
Use an interleaved sort key on user_id and event_date, and set DISTSTYLE KEY on user_id.
A compound sort key whose leading column is the event date keeps newly appended rows in the latest data blocks, allowing Redshift to skip older blocks when queries specify a date filter. Because inserts follow the sort order, little or no VACUUM is required. Leaving the table in DISTSTYLE AUTO lets the service pick an even distribution, which is appropriate for a large fact table that joins to smaller dimensions. Running ANALYZE COMPRESSION applies optimal encodings such as AZ64 or ZSTD, reducing storage and I/O without manual tuning. Interleaved sort keys are not recommended for monotonically increasing inserts and require frequent deep VACUUM. Choosing no sort key forces full scans, and DISTSTYLE ALL copies the large table to every node, increasing cost and load time.
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AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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