Spark UDF not working with null values in Double field

I'm trying to write a spark UDF that replaces the null values of a Double field with 0.0. I'm using the Dataset API. Here's the UDF:

val coalesceToZero=udf((rate: Double) =>  if(Option(rate).isDefined) rate else 0.0)

This is based on the following function that I tested to be working fine:

def cz(value: Double): Double = if(Option(value).isDefined) value else 0.0

cz(null.asInstanceOf[Double])
cz: (value: Double)Double
res15: Double = 0.0

But when I use it in Spark in the following manner the UDF doesn't work.

myDS.filter($"rate".isNull)
    .select($"rate", coalesceToZero($"rate")).show

+----+---------+
|rate|UDF(rate)|
+----+---------+
|null|     null|
|null|     null|
|null|     null|
|null|     null|
|null|     null|
|null|     null|
+----+---------+

However the following works:

val coalesceToZero=udf((rate: Any) =>  if(rate == null) 0.0 else rate.asInstanceOf[Double])

So I was wondering if Spark has some special way of handling null Double values.