How do I Generate rows depending upon the column value in spark?

Question

suppose If I have single column with one row

+---+
| id|
+---+
|  4|
+---+

then how do i generate rows depending up on the value of a column

+---+
| id|
+---+
| 1 |
|---|
| 2 |
|---|
| 3 |
|---|
| 4 |
+---+

Answer 1

You can define a udf function for that to generate range and then use explode function to make them to separate rows

import org.apache.spark.sql.functions._
def generateUdf = udf((column: Int)=> (1 to column).toArray)

df.withColumn("id", explode(generateUdf(col("id")))).show(false)

which should give you

+---+
|id |
+---+
|1  |
|2  |
|3  |
|4  |
+---+