The code block displayed below contains an error. The code block should combine data from DataFrames itemsDf and transactionsDf, showing all rows of DataFrame itemsDf that have a matching value in column itemId with a value in column transactionsId of DataFrame transactionsDf.

Find the error.

Code block:

itemsDf.join(itemsDf.itemId==transactionsDf.transactionId)

A. The join statement is incomplete.

B. The union method should be used instead of join.

C. The join method is inappropriate.

D. The merge method should be used instead of join.

E. The join expression is malformed.

Which of the following code blocks returns a single row from DataFrame transactionsDf?

Full 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.+-------------+---------+-----+-------+---------+----+

A. transactionsDf.where(col("storeId").between(3,25))

B. transactionsDf.filter((col("storeId")!=25) | (col("productId")==2))

C. transactionsDf.filter(col("storeId")==25).select("predError","storeId").distinct()

D. transactionsDf.select("productId", "storeId").where("storeId == 2 OR storeId != 25")

E. transactionsDf.where(col("value").isNull()).select("productId", "storeId").distinct()

Which of the following code blocks returns DataFrame transactionsDf sorted in descending order by column predError, showing missing values last?

A. transactionsDf.sort(asc_nulls_last("predError"))

B. transactionsDf.orderBy("predError").desc_nulls_last()

C. transactionsDf.sort("predError", ascending=False)

D. transactionsDf.desc_nulls_last("predError")

E. transactionsDf.orderBy("predError").asc_nulls_last()

Which of the following code blocks returns a copy of DataFrame transactionsDf in which column productId has been renamed to productNumber?

A. transactionsDf.withColumnRenamed("productId", "productNumber")

B. transactionsDf.withColumn("productId", "productNumber")

C. transactionsDf.withColumnRenamed("productNumber", "productId")

D. transactionsDf.withColumnRenamed(col(productId), col(productNumber))

E. transactionsDf.withColumnRenamed(productId, productNumber)

The code block displayed below contains an error. The code block is intended to perform an outer join of

DataFrames transactionsDf and itemsDf on columns productId and itemId, respectively.

Find the error.

Code block:

transactionsDf.join(itemsDf, [itemsDf.itemId, transactionsDf.productId], "outer")

A. The "outer" argument should be eliminated, since "outer" is the default join type.

B. The join type needs to be appended to the join() operator, like join().outer() instead of listing it as the last argument inside the join() call.

C. The term [itemsDf.itemId, transactionsDf.productId] should be replaced by itemsDf.itemId == transactionsDf.productId.

D. The term [itemsDf.itemId, transactionsDf.productId] should be replaced by itemsDf.col("itemId") == transactionsDf.col("productId").

E. The "outer" argument should be eliminated from the call and join should be replaced by joinOuter.