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Download Databricks Certified Associate Developer for Apache Spark 3.0 Exam Exam Dumps

NEW QUESTION 25
Which of the following code blocks uses a schema fileSchema to read a parquet file at location filePath into a DataFrame?

• A. spark.read.schema("fileSchema").format("parquet").load(filePath)
• B. spark.read.schema(fileSchema).format("parquet").load(filePath)
• C. spark.read().schema(fileSchema).format(parquet).load(filePath)
• D. spark.read.schema(fileSchema).open(filePath)
• E. spark.read().schema(fileSchema).parquet(filePath)

Answer: B

Explanation:
Explanation
Pay attention here to which variables are quoted. fileSchema is a variable and thus should not be in quotes.
parquet is not a variable and therefore should be in quotes.
SparkSession.read (here referenced as spark.read) returns a DataFrameReader which all subsequent calls reference - the DataFrameReader is not callable, so you should not use parentheses here.
Finally, there is no open method in PySpark. The method name is load.
Static notebook | Dynamic notebook: See test 1

NEW QUESTION 26
Which of the following code blocks applies the boolean-returning Python function evaluateTestSuccess to column storeId of DataFrame transactionsDf as a user-defined function?

• A. 1.evaluateTestSuccessUDF = udf(evaluateTestSuccess)
  2.transactionsDf.withColumn("result", evaluateTestSuccessUDF(storeId))
• B. 1.from pyspark.sql import types as T
  2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.BooleanType())
  3.transactionsDf.withColumn("result", evaluateTestSuccess(col("storeId")))
• C. 1.from pyspark.sql import types as T
  2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.BooleanType())
  3.transactionsDf.withColumn("result", evaluateTestSuccessUDF(col("storeId")))
• D. 1.evaluateTestSuccessUDF = udf(evaluateTestSuccess)
  2.transactionsDf.withColumn("result", evaluateTestSuccessUDF(col("storeId")))
• E. 1.from pyspark.sql import types as T
  2.evaluateTestSuccessUDF = udf(evaluateTestSuccess, T.IntegerType())
  3.transactionsDf.withColumn("result", evaluateTestSuccess(col("storeId")))

Answer: C

Explanation:
Explanation
Recognizing that the UDF specification requires a return type (unless it is a string, which is the default) is important for solving this question. In addition, you should make sure that the generated UDF (evaluateTestSuccessUDF) and not the Python function (evaluateTestSuccess) is applied to column storeId.
More info: pyspark.sql.functions.udf - PySpark 3.1.2 documentation
Static notebook | Dynamic notebook: See test 2

NEW QUESTION 27
Which is the highest level in Spark's execution hierarchy?

• A. Task
• B. Stage
• C. Slot
• D. Executor
• E. Job

Answer: E

NEW QUESTION 28
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