Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12762#discussion_r61489680
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -53,24 +53,43 @@ import org.apache.spark.util.random.XORShiftRandom
*/
private[recommendation] trait ALSModelParams extends Params with
HasPredictionCol {
/**
- * Param for the column name for user ids.
+ * Param for the column name for user ids. Ids must be integers. Other
+ * numeric types are supported for this column, but will be cast to
integers as long as they
+ * fall within the integer value range.
* Default: "user"
* @group param
*/
- val userCol = new Param[String](this, "userCol", "column name for user
ids")
+ val userCol = new Param[String](this, "userCol", "column name for user
ids. Must be within " +
+ "the integer value range.")
/** @group getParam */
def getUserCol: String = $(userCol)
/**
- * Param for the column name for item ids.
+ * Param for the column name for item ids. Ids must be integers. Other
+ * numeric types are supported for this column, but will be cast to
integers as long as they
--- End diff --
Ah ok. Could cast to double or float here... I was just concerned about any
storage / performance impact, but if everything is pipelines through the
cast -> udf then no problem
On Thu, 28 Apr 2016 at 21:27, Holden Karau <notificati...@github.com> wrote:
> In mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
> <https://github.com/apache/spark/pull/12762#discussion_r61487974>:
>
> >
> > /** @group getParam */
> > def getUserCol: String = $(userCol)
> >
> > /**
> > - * Param for the column name for item ids.
> > + * Param for the column name for item ids. Ids must be integers.
Other
> > + * numeric types are supported for this column, but will be cast to
integers as long as they
>
> Ah yes, I didn't notice the first cast from input type to Long - it seems
> like that would be OK[ish] most of the time (except with floats/doubles),
> but also with certain BigDecimal you could end up throwing away the high
> bits when going to a Long and a very out of range value would pass the
> range check.
>
> â
> You are receiving this because you authored the thread.
> Reply to this email directly or view it on GitHub
>
<https://github.com/apache/spark/pull/12762/files/73ea0b62f1c0ae6a9897ec83f5c8dfedea86f3f9#r61487974>
>
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