I need to filter a dataframe with the below criteria.
I have 2 columns 4Wheel(Subaru, Toyota, GM, null/empty) and 2Wheel(Yamaha, Harley, Indian, null/empty).
I have to filter on 4Wheel with values (Subaru, Toyota), if 4Wheel contain empty/null then filter on 2Wheel with values (Yamaha, Harley)
I couldn't find this type of filtering in different examples. I am new to spark/scala, so could not get enough idea to implement this.
Thanks, Barun.
You can use spark SQL built-in function when to check if a column is null or empty, and filter accordingly:
import org.apache.spark.sql.functions.{col, when}
dataframe.filter(when(col("4Wheel").isNull || col("4Wheel").equalTo(""),
col("2Wheel").isin("Yamaha", "Harley")
).otherwise(
col("4Wheel").isin("Subaru", "Toyota")
))
So if you have the following input:
+---+------+------+
|id |4Wheel|2Wheel|
+---+------+------+
|1 |Toyota|null |
|2 |Subaru|null |
|3 |GM |null |
|4 |null |Yamaha|
|5 | |Yamaha|
|6 |null |Harley|
|7 | |Harley|
|8 |null |Indian|
|9 | |Indian|
|10 |null |null |
+---+------+------+
You get the following filtered ouput:
+---+------+------+
|id |4Wheel|2Wheel|
+---+------+------+
|1 |Toyota|null |
|2 |Subaru|null |
|4 |null |Yamaha|
|5 | |Yamaha|
|6 |null |Harley|
|7 | |Harley|
+---+------+------+
