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Define what a User-Defined Function (UDF) is and how to register it 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
Capgemini
Key Concepts Tested
optimizationpythonsparksql
Expert AnswerPremium
76 wordsInterview-ready
**Why UDFs matter**: Custom logic when built-ins don't suffice; but UDFs break Catalyst optimization. **UDF**: Custom function; runs row-by-row in Python (slow) or as Pandas UDF (vectorized, faster). **Registration**: `@udf(ReturnType)` or `spark.udf.register("name", func)` for SQL. **Scalability trade-offs**: Python UDF = serialization overhead, no predicate pushdown; Pandas UDF = vectorized, better. **Cost implications**: UDFs often 10–50x slower than built-in; avoid when possible....
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