Exam Certified Associate Developer for Apache Spark topic 1 question 143 discussion

pyspark.sql.functions.from_unixtime(timestamp: ColumnOrName, format: str = 'yyyy-MM-dd HH:mm:ss') → pyspark.sql.column.Column[source] Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the given format.

The correct code block that returns a DataFrame containing a column openDateString, which is a string representation of Java's SimpleDateFormat, is: A. storesDF.withColumn("openDatestring", from_unixtime(col("openDate"), "EEEE, MMM d, yyyy h:mm a")) This option correctly converts the openDate column from UNIX epoch format to a human-readable string format using the from_unixtime function in PySpark, which is equivalent to Java's SimpleDateFormat. The format "EEEE, MMM d, yyyy h:mm a" aligns with the example provided: "Sunday, Dec 4, 2008 1:05 pm".

new column should be a String, existing column is Int

A. storesDF.withColumn("openDatestring", from unixtime(col("openDate“), “EEEE, MMM d, yyyy h:mm a"))

A is the right answer # Assuming you have a SparkSession created (replace with your setup if needed) from pyspark.sql import SparkSession from pyspark.sql.functions import from_unixtime # Sample data (replace with your actual DataFrame) data = [("store1", 1668518400), ("store2", 1668432000)] # Sample UNIX epoch timestamps df = spark.createDataFrame(data, ["storeName", "openDate"]) # Convert openDate to formatted string formatted_df = df.withColumn( "openDateString", from_unixtime(col("openDate"), "EEEE, MMM d, yyyy h:mm a") ) # Print the resulting DataFrame formatted_df.show(truncate=False) # Stop the SparkSession (optional) #spark.stop()

B is likely tru, because A option has some typo issue and the underscore in from keyword is missing before unixtime, and the return type is not specified.