DEA-C01 · Question #270
A company has a data processing pipeline that runs multiple SQL queries in sequence against an Amazon Redshift cluster. The company merges with a second company. The original company modifies a…
The correct answer is B. Use the KEY distribution style for both sales tables. Select a high cardinality column to use for the E. Use Amazon Redshift Advisor to review and select optimizations to implement. Choosing KEY distribution on both tables with a high-cardinality join column colocates matching rows across nodes and avoids data skew, improving join performance. Redshift Advisor provides automated, actionable recommendations (e.g., distribution and sort keys, stats) to…
Question
A company has a data processing pipeline that runs multiple SQL queries in sequence against an Amazon Redshift cluster. The company merges with a second company. The original company modifies a query that aggregates sales revenue data to join sales tables from both companies. The sales table for the first company is named Table S1. The sales table for the second company is named Table S2. Table S1 contains 10 billion records. Table S2 contains 900 million records. The query becomes slow after the modification. A data engineer must improve the query performance. Which solutions will meet these requirements? (Choose two.)
Options
- AUse the KEY distribution style for both sales tables. Select a low cardinality column to use for the
- BUse the KEY distribution style for both sales tables. Select a high cardinality column to use for the
- CUse the EVEN distribution style for Table S1. Use the ALL distribution style for Table S2.
- DUse the Amazon Redshift query optimizer to review and select optimizations to implement.
- EUse Amazon Redshift Advisor to review and select optimizations to implement.
How the community answered
(14 responses)- A14% (2)
- B71% (10)
- C7% (1)
- D7% (1)
Explanation
Choosing KEY distribution on both tables with a high-cardinality join column colocates matching rows across nodes and avoids data skew, improving join performance. Redshift Advisor provides automated, actionable recommendations (e.g., distribution and sort keys, stats) to further optimize the slow query with minimal effort.
Topics
Community Discussion
No community discussion yet for this question.