'How to get date from different year, month and day columns in spark (scala)
I have a DataFrame including data like:
+----+-----+---+-----+
|Year|Month|Day|... |
+----+-----+---+-----+
|2012| 2| 20| |
|2011| 7| 6| |
|2015| 3| 15| |
and I would like to add a column with date
Solution 1:[1]
Not so complex as Shaido, just
df.withColumn("date", F.to_date(F.concat_ws("-", "Year", "Month", "Day")) ).show()
Work on spark 2.4 .
Solution 2:[2]
For Spark 3+, you can use make_date function:
df.withColumn("date", expr("make_date(Year, Month, Day)"))
Solution 3:[3]
You can just use the concat_ws function to create a date in string data type and just cast that to date.
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._
//Source Data
val df = Seq((2012,2,20),(2011,7,6),(2015,3,15)).toDF("Year","Month","Day")
//using concat_ws function to create Date column and cast that column data type to date
val df1 = df.withColumn("Date",concat_ws("-",$"Year",$"Month",$"Day"))
.withColumn("Date",$"Date".cast("Date"))
display(df1)
You can see the output as below :
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Mithril |
| Solution 2 | blackbishop |
| Solution 3 | Nikunj Kakadiya |

