Explain Window Functions in Spark.

Updated May 5, 2026

Short answer

Window functions perform calculations across a group of rows related to the current row.

Deep explanation

They involve a WindowSpec which defines partitioning, ordering, and frame boundaries (e.g., row_number, rank, moving average).

Real-world example

Calculating a running total of sales for each store daily.

Common mistakes

  • Not defining an 'orderBy' in a window spec that requires it (like rank), leading to non-deterministic results.

Follow-up questions

  • Does Windowing cause a shuffle?

More Apache Spark interview questions

View all →