[GitHub] [spark] zhengruifeng commented on a diff in pull request #37918: [SPARK-40476][ML][SQL] Reduce the shuffle size of ALS

[GitBox]

zhengruifeng commented on code in PR #37918:
URL: https://github.com/apache/spark/pull/37918#discussion_r974838677


##########
mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala:
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@@ -496,18 +499,23 @@ class ALSModel private[ml] (
               .iterator.map { j => (srcId, dstIds(j), scores(j)) }
           }
         }
-      }
-    // We'll force the IDs to be Int. Unfortunately this converts IDs to Int 
in the output.
-    val topKAggregator = new TopByKeyAggregator[Int, Int, Float](num, 
Ordering.by(_._2))
-    val recs = ratings.as[(Int, Int, 
Float)].groupByKey(_._1).agg(topKAggregator.toColumn)
-      .toDF("id", "recommendations")
+      }.toDF(srcOutputColumn, dstOutputColumn, ratingColumn)
+
+    val aggFunc = CollectOrdered(struct(ratingColumn, dstOutputColumn).expr, 
num, true)
+      .toAggregateExpression(false)

Review Comment:
   sure, I think we don't want to expose it, so mark it `private[spark]`



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