Dive deep into the world of User-Defined Functions (UDFs) in Apache Spark. Learn how to create, register, and apply UDFs to ace your Databricks Certified Associate Developer for Apache Spark certification exam. Understand the nuances through detailed examples and explanations.
Table of Contents
Question
Which of the following code blocks creates and registers a SQL UDF named “ASSESS_PERFORMANCE” using the Scala function assessPerformance() and applies it to column customerSatisfaction in table stores?
A. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
spark.sql(“SELECT customerSatisfaction, ASSESS_PERFORMANCE(customerSatisfaction) AS result FROM stores”)
B. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
C. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
spark.sql(“SELECT customerSatisfaction, assessPerformance(customerSatisfaction) AS result FROM stores”)
D. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
storesDF.withColumn(“result”, assessPerformance(col(“customerSatisfaction”)))
E. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
storesDF.withColumn(“result”, ASSESS_PERFORMANCE(col(“customerSatisfaction”)))
Answer
A. spark.udf.register(“ASSESS_PERFORMANCE”, assessPerformance)
spark.sql(“SELECT customerSatisfaction, ASSESS_PERFORMANCE(customerSatisfaction) AS result FROM stores”)
Explanation
In Apache Spark, User-Defined Functions (UDFs) are a feature that allows you to create your own functions and then use them in SQL statements. The spark.udf.register method is used to register a UDF in Spark. Once a UDF is registered, it can be used in SQL statements.
In Option A, the assessPerformance() function is registered as a UDF with the name “ASSESS_PERFORMANCE”. Then, it is applied to the customerSatisfaction column in the stores table using a SQL statement. The result of the UDF is stored in a new column named result.
The other options are incorrect because they either do not apply the UDF to a column in a table (Option B), use the Scala function name instead of the UDF name in the SQL statement (Option C), or attempt to apply the UDF using DataFrame transformations instead of a SQL statement (Options D and E).
Databricks Certified Associate Developer for Apache Spark certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Databricks Certified Associate Developer for Apache Spark exam and earn Databricks Certified Associate Developer for Apache Spark certification.