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Exam Certified Associate Developer for Apache Spark All Questions

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Exam Certified Associate Developer for Apache Spark topic 1 question 49 discussion

Actual exam question from Databricks's Certified Associate Developer for Apache Spark
Question #: 49
Topic #: 1
[All Certified Associate Developer for Apache Spark Questions]

The code block shown below contains an error. The code block is intended to return a DataFrame containing a column openDateString, a string representation of Java’s SimpleDateFormat. Identify the error.
Note that column openDate is of type integer and represents a date in the UNIX epoch format – the number of seconds since midnight on January 1st, 1970.
An example of Java’s SimpleDateFormat is "Sunday, Dec 4, 2008 1:05 PM".
A sample of storesDF is displayed below:

Code block:
storesDF.withColumn("openDateString", from_unixtime(col("openDate"), "EEE, MMM d, yyyy h:mm a", TimestampType()))

  • A. The from_unixtime() operation only accepts two parameters – the TimestampTime() arguments not necessary.
  • B. The from_unixtime() operation only works if column openDate is of type long rather than integer – column openDate must first be converted.
  • C. The second argument to from_unixtime() is not correct – it should be a variant of TimestampType() rather than a string.
  • D. The from_unixtime() operation automatically places the input column in java’s SimpleDateFormat – there is no need for a second or third argument.
  • E. The column openDate must first be converted to a timestamp, and then the Date() function can be used to reformat to java’s SimpleDateFormat.
Show Suggested Answer Hide Answer
Suggested Answer: A 🗳️
by Jtic at May 28, 2023, 1:56 a.m.

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juliom6
1 year ago
Selected Answer: A
A is correct: from pyspark.sql.functions import from_unixtime, col storesDF = spark.createDataFrame([(0, 1100746394), (1, 1474410343)], ['storeId', 'openDate']) storesDF = storesDF.withColumn("openDateString", from_unixtime(col("openDate"), "EEE, MMM d, yyyy h:mm a")) display(storesDF)
upvoted 2 times
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nicklasbekkevold
1 year, 3 months ago
Selected Answer: A
A is the right answer. Function signature from the docs: pyspark.sql.functions.from_unixtime(timestamp, format='uuuu-MM-dd HH:mm:ss')
upvoted 1 times
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zozoshanky
1 year, 4 months ago
A is also right.
upvoted 2 times
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Jtic
1 year, 6 months ago
Selected Answer: B
B. The from_unixtime() operation only works if column openDate is of type long rather than integer - column openDate must first be converted. This option is correct. The code block has an error because the from_unixtime() function expects the column openDate to be of type long, not integer. The column should be cast to long before applying the function.
upvoted 1 times
ZSun
1 year, 5 months ago
This is completely nonsense about long and integer. long (or bigint): It is a 64-bit signed integer data type anging from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807. integer (or int): It is a 32-bit signed integer data ranging from -2,147,483,648 to 2,147,483,647
upvoted 3 times
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juliom6
1 year ago
That not make sense, the code below works perfectly: from pyspark.sql.functions import from_unixtime, col storesDF = spark.createDataFrame([(0, 1100746394), (1, 1474410343)], ['storeId', 'openDate']) storesDF = storesDF.withColumn('openDate', col('openDate').cast('integer')) storesDF = storesDF.withColumn("openDateString", from_unixtime(col("openDate"), "EEE, MMM d, yyyy h:mm a")) display(storesDF)
upvoted 1 times
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