Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r98011972
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -263,17 +288,21 @@ class GeneralizedLinearRegression @Since("2.0.0")
(@Since("2.0.0") override val
}
val w = if (!isDefined(weightCol) || $(weightCol).isEmpty) lit(1.0)
else col($(weightCol))
- val instances: RDD[Instance] =
- dataset.select(col($(labelCol)), w, col($(featuresCol))).rdd.map {
- case Row(label: Double, weight: Double, features: Vector) =>
- Instance(label, weight, features)
+ val off = if (!isDefined(offsetCol) || $(offsetCol).isEmpty) lit(0.0)
else col($(offsetCol))
+ val instances: RDD[OffsetInstance] =
+ dataset.select(col($(labelCol)), w, off,
col($(featuresCol))).rdd.map {
+ case Row(label: Double, weight: Double, offset: Double, features:
Vector) =>
+ OffsetInstance(label, weight, offset, features)
}
val model = if (familyObj == Gaussian && linkObj == Identity) {
// TODO: Make standardizeFeatures and standardizeLabel configurable.
+ val wlsInstances: RDD[Instance] = instances.map { instance =>
+ Instance(instance.label - instance.offset, instance.weight,
instance.features)
--- End diff --
going over all OffsetInstance and converting again to Instance seems like
it would be expensive and it would increase memory usage. What do you think
about the alternative of making OffsetInstance inherit from Instance - but then
you would have to change Instance from a case class - and then just passing
Instance to the fit below? Is there anything else we could do here?
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