Split 1 row into multiple rows by range on 2 column values in scala

If you're on Spark 2.4+, use sequence with the IP integer range as arguments to generate an ArrayType column, followed by explode-ing it:

val df = Seq((100, 105, "USA", "Boston")).
  toDF("start_ip_int", "end_ip_int", "country", "city")

df.withColumn("ip", explode(sequence($"start_ip_int", $"end_ip_int"))).show
// +------------+----------+-------+------+---+                                    
// |start_ip_int|end_ip_int|country|  city| ip|
// +------------+----------+-------+------+---+
// |         100|       105|    USA|Boston|100|
// |         100|       105|    USA|Boston|101|
// |         100|       105|    USA|Boston|102|
// |         100|       105|    USA|Boston|103|
// |         100|       105|    USA|Boston|104|
// |         100|       105|    USA|Boston|105|
// +------------+----------+-------+------+---+

For older Spark version, consider creating a simple UDF to mimic the sequence function:

val rangeSequence = udf{ (lower: Int, upper: Int) =>
  Seq.iterate(lower, upper - lower + 1)(_ + 1)
}

// Applying the UDF, followed by `explode`
df.withColumn("ip", explode(rangeSequence($"start_ip_int", $"end_ip_int")))