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Solve a coding question related to window functions using SQL and PySpark.

SQLmedium0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Cognizant
Key Concepts Tested
partitionsparksqlwindow
Expert AnswerPremium
68 wordsInterview-ready
Window in SQL: SELECT id, SUM(amount) OVER (PARTITION BY customer ORDER BY date) running_sum FROM sales. PySpark: from pyspark.sql.window import Window; w = Window.partitionBy('customer').orderBy('date'); df.withColumn('running_sum', sum('amount').over(w)). Same logic: partition, order, aggregate/rank. Use for: running totals, rank, lead/lag. **Why it matters**: Design choices compound at scale—wrong approach can cause 100× overhead....
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