AWS Certified Data Engineer Associate DEA-C01 Practice Question
An Amazon Redshift fact table ingests 5 million clickstream rows per hour. The table uses EVEN distribution and a compound sort key on event_time. Most analytics dashboards retrieve individual user sessions by filtering on session_id equality. Occasional monthly reports aggregate data by event_time range. Data engineers notice that session queries now require full table scans. Which schema change will most improve session query performance with minimal impact on load time?
Change the distribution style to KEY on session_id and retain the existing event_time sort key.
Keep EVEN distribution but switch the sort key to session_id only.
Replace the compound sort key with an interleaved sort key on session_id and event_time.
Convert the table to ALL distribution and set session_id as the sort key.
Filtering by session_id causes Redshift to broadcast the predicate to every slice because the table is evenly distributed. Changing the distribution style to KEY on session_id colocates all rows for a given session on the same slice, so the query reads only a small portion of each node's disk. Keeping the existing event_time sort key still supports range-based aggregate reports. Switching only the sort key, using ALL distribution, or choosing an interleaved key does not minimize cross-node data access for equality predicates and may increase storage or maintenance overhead.
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Why does changing the distribution style to KEY on session_id improve query performance?
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What is the difference between a compound sort key and an interleaved sort key in Redshift?
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What are the trade-offs of using ALL distribution in Amazon Redshift?
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What is Amazon Redshift distribution style?
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What is a compound sort key, and how is it used in Amazon Redshift?
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How does changing the distribution style to KEY improve query performance?
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AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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