Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17090#discussion_r104006071
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala ---
@@ -594,6 +595,95 @@ class ALSSuite
model.setColdStartStrategy(s).transform(data)
}
}
+
+ private def getALSModel = {
+ val spark = this.spark
+ import spark.implicits._
+
+ val userFactors = Seq(
+ (0, Array(6.0f, 4.0f)),
+ (1, Array(3.0f, 4.0f)),
+ (2, Array(3.0f, 6.0f))
+ ).toDF("id", "features")
+ val itemFactors = Seq(
+ (3, Array(5.0f, 6.0f)),
+ (4, Array(6.0f, 2.0f)),
+ (5, Array(3.0f, 6.0f)),
+ (6, Array(4.0f, 1.0f))
+ ).toDF("id", "features")
+ val als = new ALS().setRank(2)
+ new ALSModel(als.uid, als.getRank, userFactors, itemFactors)
+ .setUserCol("user")
+ .setItemCol("item")
+ }
+
+ test("recommendForAllUsers with k < num_items") {
+ val topItems = getALSModel.recommendForAllUsers(2)
+ assert(topItems.count() == 3)
+ assert(topItems.columns.contains("user"))
+
+ val expected = Map(
+ 0 -> Array(Row(3, 54f), Row(4, 44f)),
+ 1 -> Array(Row(3, 39f), Row(5, 33f)),
+ 2 -> Array(Row(3, 51f), Row(5, 45f))
+ )
+ checkRecommendations(topItems, expected, "item")
+ }
+
+ test("recommendForAllUsers with k = num_items") {
+ val topItems = getALSModel.recommendForAllUsers(4)
+ assert(topItems.count() == 3)
+ assert(topItems.columns.contains("user"))
+
+ val expected = Map(
+ 0 -> Array(Row(3, 54f), Row(4, 44f), Row(5, 42f), Row(6, 28f)),
+ 1 -> Array(Row(3, 39f), Row(5, 33f), Row(4, 26f), Row(6, 16f)),
+ 2 -> Array(Row(3, 51f), Row(5, 45f), Row(4, 30f), Row(6, 18f))
+ )
+ checkRecommendations(topItems, expected, "item")
+ }
+
+ test("recommendForAllItems with k < num_users") {
+ val topUsers = getALSModel.recommendForAllItems(2)
+ assert(topUsers.count() == 4)
+ assert(topUsers.columns.contains("item"))
+
+ val expected = Map(
+ 3 -> Array(Row(0, 54f), Row(2, 51f)),
+ 4 -> Array(Row(0, 44f), Row(2, 30f)),
+ 5 -> Array(Row(2, 45f), Row(0, 42f)),
+ 6 -> Array(Row(0, 28f), Row(2, 18f))
+ )
+ checkRecommendations(topUsers, expected, "user")
+ }
+
+ test("recommendForAllItems with k = num_users") {
+ val topUsers = getALSModel.recommendForAllItems(3)
+ assert(topUsers.count() == 4)
+ assert(topUsers.columns.contains("item"))
+
+ val expected = Map(
+ 3 -> Array(Row(0, 54f), Row(2, 51f), Row(1, 39f)),
+ 4 -> Array(Row(0, 44f), Row(2, 30f), Row(1, 26f)),
+ 5 -> Array(Row(2, 45f), Row(0, 42f), Row(1, 33f)),
+ 6 -> Array(Row(0, 28f), Row(2, 18f), Row(1, 16f))
+ )
+ checkRecommendations(topUsers, expected, "user")
+ }
+
+ private def checkRecommendations(
+ topK: DataFrame,
+ expected: Map[Int, Array[Row]],
+ dstColName: String): Unit = {
+ assert(topK.columns.contains("recommendations"))
+ topK.collect().foreach { row =>
--- End diff --
It's a little strange to have all the `Row` stuff in these tests.
You can do `topK.as[(Int, Seq[(Int, Float)])].collect.foreach { case (id,
recs) => ...`
Then adjust `expected` accordingly
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