The code block shown below contains an error. The code block intended to create a single- column DataFrame from Scala List years which is made up of integers. Identify the error. Code block…

Question

Options

• AThe years list should be wrapped in another list like List(years) to make clear that it is a column
• BThe data type is not specified - the second argument to createDataset should be IntegerType.
• CThere is no operation createDataset - the createDataFrame operation should be used instead.
• DThe result of the above is a Dataset rather than a DataFrame - the toDF operation must be called
• EThe column name must be specified as the second argument to createDataset.

• A
  15% (8)
• B
  73% (38)
• C
  2% (1)
• D
  4% (2)
• E
  6% (3)

Explanation

Option B is correct because createDataset requires an explicit Encoder (type specification) as a second argument - without it, Spark cannot determine how to serialize the data. The correct call would be spark.createDataset(years, Encoders.INT()), supplying the IntegerType-equivalent encoder.

Why the distractors are wrong:

• A - Wrapping in List(years) would produce a Dataset of Lists, not a flat single-column structure.
• C - createDataset is a valid Spark API method; no substitution is needed.
• D - While createDataset does return a Dataset[T] (not a DataFrame), this is a type-conversion consideration, not the root error in the call itself.
• E - createDataset has no column-name parameter; single-column Datasets default to a column named "value".

Memory tip: Think "Dataset needs Data-type" - whenever you call createDataset, you must supply the encoder that tells Spark how to handle the type, otherwise the call is incomplete.

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