Which of the following code blocks reorders the values inside the arrays in column attributes of DataFrame itemsDf from last to first one in the alphabet?
1.+------+-----------------------------+-------------------+
2.|itemId|attributes |supplier |
3.+------+-----------------------------+-------------------+
4.|1 |[blue, winter, cozy] |Sports Company Inc.|
5.|2 |[red, summer, fresh, cooling]|YetiX |
6.|3 |[green, summer, travel] |Sports Company Inc.|
7.+------+-----------------------------+-------------------+

• A. itemsDf.withColumn('attributes', sort_array(col('attributes').desc()))
• B. itemsDf.withColumn("attributes", sort_array("attributes", asc=False))
• C. itemsDf.select(sort_array("attributes"))
• D. itemsDf.withColumn('attributes', sort_array(desc('attributes')))
• E. itemsDf.withColumn('attributes', sort(col('attributes'), asc=False))

Which of the following DataFrame operators is never classified as a wide transformation?

• A. DataFrame.join()
• B. DataFrame.aggregate()
• C. DataFrame.select()
• D. DataFrame.sort()
• E. DataFrame.repartition()

The code block displayed below contains an error. The code block should display the schema of DataFrame transactionsDf. Find the error.
Code block:
transactionsDf.rdd.printSchema

• A. printSchema is only accessible through the spark session, so the code block should be rewritten as spark.printSchema(transactionsDf).
• B. printSchema is a not a method of transactionsDf.rdd. Instead, the schema should be printed via transactionsDf.print_schema().
• C. The code block should be wrapped into a print() operation.
• D. printSchema is a method and should be written as printSchema(). It is also not callable through transactionsDf.rdd, but should be called directly from transactionsDf.
  (Correct)
• E. There is no way to print a schema directly in Spark, since the schema can be printed easily through using print(transactionsDf.columns), so that should be used instead.

In which order should the code blocks shown below be run in order to create a DataFrame that shows the mean of column predError of DataFrame transactionsDf per column storeId and productId, where productId should be either 2 or 3 and the returned DataFrame should be sorted in ascending order by column storeId, leaving out any nulls in that column?
DataFrame transactionsDf:
1.+-------------+---------+-----+-------+---------+----+
2.|transactionId|predError|value|storeId|productId| f|
3.+-------------+---------+-----+-------+---------+----+
4.| 1| 3| 4| 25| 1|null|
5.| 2| 6| 7| 2| 2|null|
6.| 3| 3| null| 25| 3|null|
7.| 4| null| null| 3| 2|null|
8.| 5| null| null| null| 2|null|
9.| 6| 3| 2| 25| 2|null|
10.+-------------+---------+-----+-------+---------+----+
1. .mean("predError")
2. .groupBy("storeId")
3. .orderBy("storeId")
4. transactionsDf.filter(transactionsDf.storeId.isNotNull())
5. .pivot("productId", [2, 3])

• A. 4, 2, 1
• B. 4, 5, 2, 3, 1
• C. 4, 1, 5, 2, 3
• D. 4, 3, 2, 5, 1
• E. 4, 2, 5, 1, 3