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Answer: df.withColumn('year', year('transaction_date'))
The correct answer is A because it correctly uses the `year` function to extract the year from the `transaction_date` column and adds it as a new column 'year'.
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You have a DataFrame df with a column transaction_date in timestamp format. How would you extract the year from this timestamp using Spark? Provide the code snippet.
A
df.withColumn('year', year('transaction_date'))
B
df.select(year('transaction_date'))
C
df.withColumn('year', extract('year', 'transaction_date'))
D
df.select(extract('year', 'transaction_date'))