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Lead and Lag in SQL Using PySpark DataFrame API

SQLmedium0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
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1,863
across 7 categories
Asked at these companies
JIO
Key Concepts Tested
partitionsparksqlwindow
Expert AnswerPremium
87 wordsInterview-ready
Lead/Lag in PySpark: from pyspark.sql.window import Window; from pyspark.sql.functions import lead, lag; w = Window.partitionBy('customer_id').orderBy('order_date'); df.withColumn('next_order', lead('order_id', 1).over(w)).withColumn('prev_order', lag('order_id', 1).over(w)). Lead: next row; Lag: previous row. Default for no row: None. Use lead('col', 1, 0) for default. For SQL: SELECT *, LAG(amount) OVER (PARTITION BY id ORDER BY dt) prev, LEAD(amount) OVER (...) next FROM t....
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