Reputation: 463
I have a dataframe with following columns:
groupid,unit,height
----------------------
1,in,55
2,in,54
I want to create another dataframe with additional rows where unit=cm and height=height*2.54.
Resulting dataframe:
groupid,unit,height
----------------------
1,in,55
2,in,54
1,cm,139.7
2,cm,137.16
Not sure how I can use spark udf and explode here. Any help is appreciated. Thanks in advance.
Upvotes: 6
Views: 12231
Reputation: 41987
you can create another dataframe
with changes you require using withColumn
and then union
both dataframes
as
import sqlContext.implicits._
import org.apache.spark.sql.functions._
val df = Seq(
(1, "in", 55),
(2, "in", 54)
).toDF("groupid", "unit", "height")
val df2 = df.withColumn("unit", lit("cm")).withColumn("height", col("height")*2.54)
df.union(df2).show(false)
you should have
+-------+----+------+
|groupid|unit|height|
+-------+----+------+
|1 |in |55.0 |
|2 |in |54.0 |
|1 |cm |139.7 |
|2 |cm |137.16|
+-------+----+------+
Upvotes: 11