The source system exports two timestamps as STRING columns: ordered_at and shipped_at, both formatted like '2026-07-02 14:45:00'. In the silver transformation, the team must add fulfillment_days with the number of calendar days between the order date and the ship date, written in Spark SQL. Which approach should they use?
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Correct answer: Parse both columns with to_timestamp(col, 'yyyy-MM-dd HH:mm:ss'), then compute datediff(shipped_at, ordered_at)
Reference: https://docs.databricks.com/aws/en/sql/language-manual/sql-ref-functions
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02 — The Myelin Layer · Canonical Discussion
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Official Answer (A): Parse both columns with to_timestamp(col, 'yyyy-MM-dd HH:mm:ss'), then compute datediff(shipped_at, ordered_at)
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