Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/17090#discussion_r103397271
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -285,6 +288,57 @@ class ALSModel private[ml] (
@Since("1.6.0")
override def write: MLWriter = new ALSModel.ALSModelWriter(this)
+
+ /**
+ * Returns top `numItems` items recommended for each user, for all users.
+ * @param numItems max number of recommendations for each user
+ * @return a DataFrame of (userCol: Int, recommendations), where
recommendations are
+ * stored as an array of (itemId: Int, rating: Double) tuples.
+ */
+ @Since("2.2.0")
+ def recommendForAllUsers(numItems: Int): DataFrame = {
+ recommendForAll(userFactors, itemFactors, $(userCol), $(itemCol),
numItems)
+ }
+
+ /**
+ * Returns top `numUsers` users recommended for each item, for all items.
+ * @param numUsers max number of recommendations for each item
+ * @return a DataFrame of (itemCol: Int, recommendations), where
recommendations are
+ * stored as an array of (userId: Int, rating: Double) tuples.
+ */
+ @Since("2.2.0")
+ def recommendForAllItems(numUsers: Int): DataFrame = {
+ recommendForAll(itemFactors, userFactors, $(itemCol), $(userCol),
numUsers)
+ }
+
+ /**
+ * Makes recommendations for all users (or items).
+ * @param srcFactors src factors for which to generate recommendations
+ * @param dstFactors dst factors used to make recommendations
+ * @param srcOutputColumn name of the column for the source in the
output DataFrame
+ * @param dstOutputColumn name of the column for the destination in the
output DataFrame
+ * @param num max number of recommendations for each record
+ * @return a DataFrame of (srcOutputColumn: Int, recommendations), where
recommendations are
+ * stored as an array of (dstId: Int, rating: Double) tuples.
+ */
+ private def recommendForAll(
+ srcFactors: DataFrame,
+ dstFactors: DataFrame,
+ srcOutputColumn: String,
+ dstOutputColumn: String,
--- End diff --
Is dstOutputColumn from WIP specifying the schema? I'll get back soon
about ways to specify the schema
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