Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/12560#discussion_r60531928
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -395,13 +395,21 @@ class ALS(@Since("1.4.0") override val uid: String)
extends Estimator[ALSModel]
.map { row =>
Rating(row.getInt(0), row.getInt(1), row.getFloat(2))
}
+ val instr = Instrumentation.create(this, ratings)
+ instr.logParams(rank, numUserBlocks, numItemBlocks, implicitPrefs,
alpha,
+ userCol, itemCol, ratingCol, predictionCol, maxIter,
+ regParam, nonnegative, checkpointInterval, seed)
val (userFactors, itemFactors) = ALS.train(ratings, rank = $(rank),
numUserBlocks = $(numUserBlocks), numItemBlocks = $(numItemBlocks),
maxIter = $(maxIter), regParam = $(regParam), implicitPrefs =
$(implicitPrefs),
alpha = $(alpha), nonnegative = $(nonnegative),
checkpointInterval = $(checkpointInterval), seed = $(seed))
val userDF = userFactors.toDF("id", "features")
val itemDF = itemFactors.toDF("id", "features")
+ val numUserFeatures = userDF.collect.size
--- End diff --
I don't think we need to collect the dataframes locally here to get the
counts (maybe just use `count`) or maybe we could put this logging somewhere
that already have the counts?
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