The code block shown below contains an error. The code block is intended to create a Python UDF assessPerformanceUDF() using the integer-returning Python function assessPerformance() and apply it to…

Question

Options

• AThe assessPerformance() operation is not properly registered as a UDF.
• BThe withColumn() operation is not appropriate here - UDFs should be applied by iterating over
• CUDFs can only be applied vie SQL and not through the DataFrame API.
• DThe return type of the assessPerformanceUDF() is not specified in the udf() operation.
• EThe assessPerformance() operation should be used on column customerSatisfaction rather than

• A
  3% (1)
• B
  5% (2)
• C
  3% (1)
• D
  87% (34)
• E
  3% (1)

Explanation

When creating a UDF with udf(), PySpark requires an explicit return type so it knows how to serialize the output back into a Spark column. Without specifying the return type (e.g., udf(assessPerformance, IntegerType())), Spark defaults to StringType(), which may cause incorrect results or type mismatches. The line assessPerformanceUDF = udf(assessPerformance) is missing the return type argument, which is the error.

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