Check if the number of points to sample for top-level tree is less than the number of records in training dataset

[jaceklaskowski]

Just faced the issue and the reason was that the number of points (defaults to 1000) was higher than the number of records in the training dataset. Perhaps obvious for ML practitioners, but I spent few minutes debugging to nail it down.

It'd be nice to know it before fitting a model or get a more user-friendly error message.

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Sampling fraction (333.3333333333333) must be on interval [0, 1]
	at scala.Predef$.require(Predef.scala:224)
	at org.apache.spark.util.random.BernoulliSampler.<init>(RandomSampler.scala:148)
	at org.apache.spark.rdd.RDD$$anonfun$sample$2.apply(RDD.scala:495)
	at org.apache.spark.rdd.RDD$$anonfun$sample$2.apply(RDD.scala:490)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
	at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
	at org.apache.spark.rdd.RDD.sample(RDD.scala:490)
	at org.apache.spark.ml.knn.KNN.fit(KNN.scala:387)

[kaushikacharya]

In org.apache.spark.rdd.RDD.scala sample function,
there's a check for fraction >= 0

require(fraction >= 0,
      s"Fraction must be nonnegative, but got ${fraction}")

But corresponding check for fraction <= 1 isn't present.
I am just wondering shouldn't this check should also be there.

EDIT: It does throw an error like this:

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Sampling fraction (1.7921146953405018) must be on interval [0, 1]