srowen commented on a change in pull request #25789: [SPARK-28927][ML] Show
warning when input data to ALS is indeterminate
URL: https://github.com/apache/spark/pull/25789#discussion_r324475932
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File path: R/pkg/R/mllib_recommendation.R
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@@ -82,6 +82,10 @@ setClass("ALSModel", representation(jobj = "jobj"))
#' statsS <- summary(modelS)
#' }
#' @note spark.als since 2.1.0
+#' @note the input rating dataframe to the ALS implementation should not be
indeterminate.
Review comment:
Is there any way to make, say, the result of randomSplit deterministic after
it has been computed? I understand the usual answer of caching isn't 100%
foolproof. But if there is no way to do it, hm, is it worth warning? because
this is just generally true of lots of things in Spark
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