DP-203 · Question #114
Drag and Drop Question You have an Apache Spark DataFrame named temperatures. A sample of the data is shown in the following table. You need to produce the following table by using a Spark SQL…
The correct answer is COLLATE; PIVOT; CAST. The correct sequence uses COLLATE to handle string comparison/ordering, PIVOT to transform row-based temperature data into a columnar format (rotating distinct values from a column into multiple columns), and CAST to convert data types (such as converting numeric temperature…
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Correct arrangement
- COLLATE
- PIVOT
- CAST
Explanation
The correct sequence uses COLLATE to handle string comparison/ordering, PIVOT to transform row-based temperature data into a columnar format (rotating distinct values from a column into multiple columns), and CAST to convert data types (such as converting numeric temperature values to the appropriate type for display). PIVOT is the core operation here - it reshapes the DataFrame by turning row values (e.g., city or month names) into column headers, which is exactly what produces the target table structure from the source data.
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