scala - 带点 Spark 的列名

Question

我正在尝试从 DataFrame 中获取列并将其转换为 RDD[Vector] .

问题是我有名称中带有“点”的列作为以下数据集:

"col0.1","col1.2","col2.3","col3.4"
1,2,3,4
10,12,15,3
1,12,10,5

这就是我正在做的:

val df = spark.read.format("csv").options(Map("header" -> "true", "inferSchema" -> "true")).load("C:/Users/mhattabi/Desktop/donnee/test.txt")
val column=df.columns.map(c=>s"`${c}`")
val rows = new VectorAssembler().setInputCols(column).setOutputCol("vs")
  .transform(df)
  .select("vs")
  .rdd
val data =rows.map(_.getAs[org.apache.spark.ml.linalg.Vector](0))
  .map(org.apache.spark.mllib.linalg.Vectors.fromML)

val mat: RowMatrix = new RowMatrix(data)
//// Compute the top 5 singular values and corresponding singular vectors.
val svd: SingularValueDecomposition[RowMatrix, Matrix] = mat.computeSVD(mat.numCols().toInt, computeU = true)
val U: RowMatrix = svd.U  // The U factor is a RowMatrix.
val s: Vector = svd.s  // The singular values are stored in a local dense vector.
val V: Matrix = svd.V  // The V factor is a local dense matrix.

println(V)

请帮助我考虑名称中带有点的列。谢谢

Answer 1

如果您的问题是 .(dot)在列名中，您可以使用 `(backticks)将列名括起来。
df.select("`col0.1`")