如何将scala矢量转换为火花ML矢量?

时间:2017-02-24 05:17:30

标签: scala apache-spark scala-collections apache-spark-ml

我有一个scala.collection.immutable.Vector类型的向量,并希望将其转换为org.apache.spark.ml.linalg.Vector类型的向量。

例如,我想要以下内容;

import org.apache.spark.ml.linalg.Vectors
val scalaVec = Vector(1,2,3)
val sparkVec = Vectors.dense(scalaVec)

请注意,我只需键入val sparkVec = Vectors.dense(1,2,3),但我想转换现有的scala集合向量。我想这样做是为了将这些DenseVectors嵌入到DataFrame中以提供给spark.ml管道。

1 个答案:

答案 0 :(得分:3)

Vectors.dense可以采用一系列双精度数。可能导致您麻烦的是Vectors.dense在您的示例中不会接受您在scalaVec中使用的Ints。所以以下失败:

val test = Seq(1,2,3,4,5).to[scala.Vector].toArray
Vectors.dense(test)

import org.apache.spark.ml.linalg.Vectors
test: Array[Int] = Array(1, 2, 3, 4, 5)
<console>:67: error: overloaded method value dense with alternatives:
  (values: Array[Double])org.apache.spark.ml.linalg.Vector <and>
  (firstValue: Double,otherValues: Double*)org.apache.spark.ml.linalg.Vector cannot be applied to (Array[Int])
   Vectors.dense(test)

虽然这有效:

val testDouble = Seq(1,2,3,4,5).map(x=>x.toDouble).to[scala.Vector].toArray
Vectors.dense(testDouble)

testDouble: Array[Double] = Array(1.0, 2.0, 3.0, 4.0, 5.0)
res11: org.apache.spark.ml.linalg.Vector = [1.0,2.0,3.0,4.0,5.0]