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How to fill null values in PySpark?

Spark/Big Datahard0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Datametica
Key Concepts Tested
optimizationpartitionsparkwindow
Expert AnswerPremium
87 wordsInterview-ready
**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. Fill nulls in PySpark: (1) `fillna(value)` or `fillna(dict)` for specific columns: `df.fillna(0)` or `df.fillna({'col1':0,'col2':'unknown'})`. (2) `na.fill()`. (3) `when/otherwise`: `df.withColumn('col', when(col('col').isNull(), lit(0)).otherwise(col('col')))`. For forward/back fill: Use window functions....
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