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Exam Certified Associate Developer for Apache Spark topic 1 question 41 discussion

Actual exam question from Databricks's Certified Associate Developer for Apache Spark

Question #: 41
Topic #: 1

[All Certified Associate Developer for Apache Spark Questions]

The code block shown below should create and register a SQL UDF named "ASSESS_PERFORMANCE" using the Python function assessPerformance() and apply it to column customerSatisfaction in table stores. Choose the response that correctly fills in the numbered blanks within the code block to complete this task.
Code block:
spark._1_._2_(_3_, _4_)
spark.sql("SELECT customerSatisfaction, _5_(customerSatisfaction) AS result FROM stores")

A. 1. udf
2. register
3. "ASSESS_PERFORMANCE"
4. assessPerformance
5. ASSESS_PERFORMANCE
B. 1. udf
2. register
3. assessPerformance
4. "ASSESS_PERFORMANCE"
5. "ASSESS_PERFORMANCE"
C. 1. udf
2. register
3."ASSESS_PERFORMANCE"
4. assessPerformance
5. "ASSESS_PERFORMANCE"
D. 1. register
2. udf
3. "ASSESS_PERFORMANCE"
4. assessPerformance
5. "ASSESS_PERFORMANCE"
E. 1. udf
2. register
3. ASSESS_PERFORMANCE
4. assessPerformance
5. ASSESS_PERFORMANCE

Show Suggested Answer

Suggested Answer: A 🗳️

by 4be8126 at May 1, 2023, 3:01 p.m.

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jds0

1 month, 2 weeks ago

Selected Answer: A

Answer: A See code example below with Spark 3.5.1: from pyspark.sql import SparkSession spark = SparkSession.builder.appName("MyApp").getOrCreate() data = [ (0, 43161, "A"), (1, 51200, "A"), (3, 78367, "B"), ] storesDF = spark.createDataFrame(data, ["storeID", "sqft", "division"]) def assess_performance(x): return "Large" if x > 50000 else "Small" spark.udf.register("ASSESS_PERFORMANCE", assess_performance, "STRING") storesDF.createOrReplaceTempView("stores") df = spark.sql("SELECT StoreID, ASSESS_PERFORMANCE(sqft) AS performance FROM stores") df.show()

upvoted 1 times

...

azurearch

6 months ago

def assessperformance(): return 'Good' spark.udf.register("assessperformance",assessperformance) df = spark.sql("SELECT assessperformance()") df.show() A

upvoted 2 times

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4be8126

1 year, 4 months ago

Selected Answer: A

Answer: A Explanation: udf: create a user-defined function (UDF) in PySpark register: register the UDF with Spark so it can be used in SQL queries "ASSESS_PERFORMANCE": name the UDF "ASSESS_PERFORMANCE" assessPerformance: specify the Python function to use for the UDF ASSESS_PERFORMANCE: use the registered UDF in the SQL query to apply the assessPerformance() function to the customerSatisfaction column.