The code block shown below contains an error. The code block intended to return a DataFrame containing a column dayOfYear, an integer representation of the day of the year from column openDate from…

Question

Options

• AThe dayofyear() operation cannot extract the day of year from a column of type integer - column
• BThe dayofyear() operation takes a quoted column name rather than a Column object as its first
• CThe dayofyear() operation cannot extract the day of year from a column of type integer - column
• DThe dayofyear() operation is not applicable in a withColumn() call - the newColumn() operation
• EThere is no dayofyear() operation - the day of year number must be extracted using substring

• A
  78% (21)
• C
  15% (4)
• D
  4% (1)
• E
  4% (1)

Explanation

Option A is correct because dayofyear() in PySpark requires a DateType or TimestampType column - it cannot operate on an IntegerType. Since openDate stores UNIX epoch seconds as an integer, the fix requires first converting it to a timestamp or date using from_unixtime() (and optionally .cast("date")), then applying dayofyear():

storesDF.withColumn("dayOfYear", dayofyear(from_unixtime(col("openDate"))))

Why the distractors are wrong:

• B is incorrect because dayofyear() does accept a Column object (i.e., col("openDate")) - that part of the code is fine.
• C appears similar to A but likely proposes an incorrect or unnecessary fix - the real solution is a type conversion, not something else the distractor suggests.
• D is wrong because dayofyear() works perfectly inside withColumn() - there is no such restriction.
• E is wrong because dayofyear() absolutely exists in pyspark.sql.functions; there's no need to use substring().

Memory tip: Think of Spark date functions as picky about types - they only "speak date/timestamp," never raw integers. Whenever you see UNIX epoch integers paired with a date function, your first instinct should be from_unixtime() as a bridge.

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