Question 1

Which of the following code blocks immediately removes the previously cached DataFrame transactionsDf from memory and disk?

Options :

A : array_remove(transactionsDf, "*")

B : transactionsDf.unpersist()

C : del transactionsDf

D : transactionsDf.clearCache()

E : transactionsDf.persist()

Answer: B

Question 2

Which of the following code blocks reads all CSV files in directory filePath into a single DataFrame, with

column names defined in the CSV file headers?

Content of directory filePath:

1._SUCCESS

2._committed_2754546451699747124

3._started_2754546451699747124

4.part-00000-tid-2754546451699747124-10eb85bf-8d91-4dd0-b60b-2f3c02eeecaa-298-1-c000.csv.gz

5.part-00001-tid-2754546451699747124-10eb85bf-8d91-4dd0-b60b-2f3c02eeecaa-299-1-c000.csv.gz

6.part-00002-tid-2754546451699747124-10eb85bf-8d91-4dd0-b60b-2f3c02eeecaa-300-1-c000.csv.gz

7.part-00003-tid-2754546451699747124-10eb85bf-8d91-4dd0-b60b-2f3c02eeecaa-301-1-c000.csv.gz

spark.option("header",True).csv(filePath)

Options :

A : spark.read.format("csv").option("header",True).option("compression","zip").load(filePath)

B : spark.read().option("header",True).load(filePath)

C : spark.read.format("csv").option("header",True).load(filePath)

D : spark.read.load(filePath)

Answer: C

Question 3

Given the code block down below, a database test containing nulls, identify the error

1. def my_udf(s):

2. If s is not null:

3. return len(s)

4.

5. spark.udf.register("strlen", my_udf)

6. spark.sql("select s from test where s is not null and strlen(s) > 1")

Options :

A : There are no problems in this query.

B : We need to use function ‘query’ instead of ‘sql’ to query table test.

C : We need to create the function first and then pass it to udf.register

D : This WHERE clause does not guarantee the strlen UDF to be invoked after filtering out nulls. So we will have null pointer

Answer: A

Question 4

Which of the following code blocks reads from a csv file where values are separated with ‘;’ ?

Options :

A : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “true”).toDf(file)

B : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).load(file)

C : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)

D : spark.load.format("csv").option("header", "true").option(“inferSchema”, “true”).read(file)

Answer: C

Question 5

Which of the following code blocks silently writes DataFrame itemsDf in avro format to location fileLocation if a file does not yet exist at that location?

Options :

A : itemsDf.write.avro(fileLocation)

B : itemsDf.write.format("avro").mode("ignore").save(fileLocation)

C : itemsDf.write.format("avro").mode("errorifexists").save(fileLocation)

D : itemsDf.save.format("avro").mode("ignore").write(fileLocation)

E : spark.DataFrameWriter(itemsDf).format("avro").write(fileLocation)

Answer: A

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