spark ml 归一化操作完整版

话不多说，上代码

  val docTopicData = sc.textFile("src\\main\\resources\\model\\111.txt", 1)
      .map(s => Vectors.dense(s.split(' ').map(_.toDouble)))

  import spark.implicits._
  val docTopicDF = docTopicData.zipWithIndex.map(_.swap).toDF("id","features")

  val normalizer = new Normalizer()
      .setInputCol("features")
      .setOutputCol("normalfeatures")
      .setP(1.0)
  val row_normalized_dt: DataFrame = normalizer.transform(docTopicDF)
  row_normalized_dt.show()

自动导入，运行出错，提示：

org.apache.spark.mllib.linalg.DenseVector cannot be cast to org.apache.spark.ml.linalg.Vector

结果是包导错了

导入正确包：

import org.apache.spark.ml.feature.Normalizer
import org.apache.spark.ml.linalg.Vectors