Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/17059#discussion_r103548602
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -82,12 +82,20 @@ private[recommendation] trait ALSModelParams extends
Params with HasPredictionCo
* Attempts to safely cast a user/item id to an Int. Throws an exception
if the value is
* out of integer range.
*/
- protected val checkedCast = udf { (n: Double) =>
- if (n > Int.MaxValue || n < Int.MinValue) {
- throw new IllegalArgumentException(s"ALS only supports values in
Integer range for columns " +
- s"${$(userCol)} and ${$(itemCol)}. Value $n was out of Integer
range.")
- } else {
- n.toInt
+ protected val checkedCast = udf { (n: Any) =>
+ n match {
+ case v: Int => v // Avoid unnecessary casting
+ case v: Number =>
+ val intV = v.intValue()
+ // Checks if number within Int range and has no fractional part.
+ if (v.doubleValue == intV) {
--- End diff --
Also, if we for some reason do decide to go with the check against the
fractional part, which I would not recommend, we should add a test to verify
the error message is thrown, and possible add this change in accepted input
format to the documentation, since it may break some users (they may have to do
additional conversion to int for their values prior to calling this API if they
run into such floating point precision issues).
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