Databricks Certified Data Engineer - Associate
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A data engineer is tasked with transforming quarterly sales data across various geographical regions into a view where each quarter's sales are displayed in separate columns for every year. Given the schema and sample data of the sales table, which SQL command should be used to achieve this?
A
CREATE OR REPLACE VIEW sales_across_quarter AS SELECT year, region, q1, q2, q3, q4 FROM sales TRANSFORM (sum(sales) AS sales FOR quarter IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
B
CREATE OR REPLACE VIEW sales_across_quarter AS SELECT year, region, q1, q2, q3, q4 FROM sales PIVOT (sum(sales) AS sales FOR quarter IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
C
CREATE OR REPLACE VIEW sales_across_quarter AS SELECT year, region, q1, q2, q3, q4 FROM sales REDUCE (sum(sales) AS sales FOR quarter IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
D
CREATE OR REPLACE VIEW sales_across_quarter AS SELECT year, region, q1, q2, q3, q4 FROM sales EXIST(sum(sales) AS sales FOR quarter IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
E
CREATE OR REPLACE VIEW sales_across_quarter AS SELECT year, region, q1, q2, q3, q4 FROM sales ROTATE (sum(sales) AS sales FOR quarter IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));