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DATABRICKS-CERTIFIED-ASSOCIATE-DEVELOPER-FOR-APACHE-SPARK · Question #159
DATABRICKS-CERTIFIED-ASSOCIATE-DEVELOPER-FOR-APACHE-SPARK Question #159: Real Exam Question with Answer & Explanation
The correct answer is B: assessPerformanceUDF = udf(assessPerformance, IntegerType()) storesDF.withColumn("result",. See the full explanation below for the reasoning.
Implementing User-Defined Functions (UDFs) in PySpark
Question
Which of the following code blocks creates a Python UDF assessPerformanceUDF() using the integer-returning Python function assessPerformance() and applies it to Column customerSatisfaction in DataFrame storesDF?
Options
- AassessPerformanceUDF = udf(assessPerformance, IntegerType) storesDF.withColumn("result",
- BassessPerformanceUDF = udf(assessPerformance, IntegerType()) storesDF.withColumn("result",
- CassessPerformanceUDF - udf(assessPerformance) storesDF.withColumn("result",
- DassessPerformanceUDF = udf(assessPerformance) storesDF.withColumn("result",
- EassessPerformanceUDF = udf(assessPerformance, IntegerType()) storesDF.withColumn("result",
Topics
#PySpark UDFs#DataFrame Transformations#Spark SQL Data Types#Python for Spark
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