Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

An Amazon Athena query joins a large, 1 TB Parquet table named sales with a small, 50 MB CSV table named regions. The sales table is partitioned by order_date. The query must return last year's sales for the 'APAC' region but currently scans the entire sales table. Which SQL rewrite will most effectively reduce the amount of data scanned while returning the same result?

  • WITH filtered_sales AS ( SELECT * FROM sales WHERE order_date BETWEEN DATE '2023-01-01' AND DATE '2023-12-31' ) SELECT s.*, r.region_name FROM filtered_sales s JOIN regions r ON s.region_id = r.id WHERE r.region_name = 'APAC';

  • SELECT s.*, r.region_name FROM sales s JOIN regions r ON s.region_id = r.id WHERE r.region_name = 'APAC' AND s.order_date BETWEEN DATE '2023-01-01' AND DATE '2023-12-31';

  • SELECT r.region_name, s.* FROM regions r JOIN sales s ON s.region_id = r.id WHERE r.region_name = 'APAC' AND s.order_date BETWEEN DATE '2023-01-01' AND DATE '2023-12-31';

  • SELECT * FROM sales s WHERE order_date BETWEEN DATE '2023-01-01' AND DATE '2023-12-31' AND EXISTS (SELECT 1 FROM regions r WHERE r.id = s.region_id AND r.region_name = 'APAC');

AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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