Spark ML库

我正在测试我在MLlib:Main指南中找到的Scala代码 Machine Learning Library (MLlib) Guide

import org.apache.spark.ml.linalg.{Matrix, Vectors, Vector}
import org.apache.spark.ml.stat.Correlation
import org.apache.spark.sql.Row
import scala.collection.Seq

object BasicStatistics {
  def main(args: Array[String]): Unit = {

    val data: Seq[Vector] = Seq(
      Vectors.sparse(4, Seq((0, 1.0), (3, -2.0))),
      Vectors.dense(4.0, 5.0, 0.0, 3.0),
      Vectors.dense(6.0, 7.0, 0.0, 8.0),
      Vectors.sparse(4, Seq((0, 9.0), (3, 1.0))))

    val df = data.map(Tuple1.apply).toDF("features")
    val Row(coeff1: Matrix) = Correlation.corr(df, "features").head
    println(s"Pearson correlation matrix:\n $coeff1")

    val Row(coeff2: Matrix) = Correlation.corr(df, "features", "spearman").head
    println(s"Spearman correlation matrix:\n $coeff2")

  }
}

但此行报告了一个错误。

val df = data.map(Tuple1.apply).toDF("features")

上面说, “value toDF不是Seq[(org.apache.spark.ml.linalg.Vector,)]的成员”

值数据(Seq[向量])似乎没有映射方法?

关于如何进行有什么想法吗?

下面是我的pom。xml

<dependencies>
    <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-mllib -->
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-mllib_2.11</artifactId>
        <version>2.3.0</version>
    </dependency>
    <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.11</artifactId>
        <version>2.3.0</version>
    </dependency>

</dependencies>