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From sueann <...@git.apache.org>
Subject [GitHub] spark pull request #17090: [Spark-19535][ML] RecommendForAllUsers RecommendF...
Date Thu, 02 Mar 2017 21:40:10 GMT
Github user sueann commented on a diff in the pull request:

    https://github.com/apache/spark/pull/17090#discussion_r104036563
  
    --- 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 =>
    +      val id = row.getInt(0)
    +      val recs = row.getAs[WrappedArray[Row]]("recommendations")
    +      assert(recs === expected(id))
    +      assert(recs(0).fieldIndex(dstColName) == 0)
    +      assert(recs(0).fieldIndex("rating") == 1)
    --- End diff --
    
    Actually nevermind. Either way is committing to an incompatible API so the name one seems
preferable. 


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