在 scala spark 中行到向量
row to vector in scala spark
我有一行是通过以下方式获得的:
val row_name = df.collect()(i)
如何将此行转换为类型向量,以便按如下方式将其传递给 fromML()?
val vector_name=org.apache.spark.mllib.linalg.Vectors.fromML(row_name)
提前致谢!
您可以使用 vectorAssembler
:
import org.apache.spark.ml.linalg.Vector
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.ml.feature.VectorAssembler
val df = Seq((1,2),(3,4)).toDF("col1","col2")
val va = new VectorAssembler().setInputCols(Array("col1","col2")).setOutputCol("vector")
val row0 = va.transform(df).select("vector").collect()(0).getAs[Vector](0)
val vector0 = Vectors.fromML(row0)
// vector0: org.apache.spark.mllib.linalg.Vector = [1.0,2.0]
我有一行是通过以下方式获得的:
val row_name = df.collect()(i)
如何将此行转换为类型向量,以便按如下方式将其传递给 fromML()?
val vector_name=org.apache.spark.mllib.linalg.Vectors.fromML(row_name)
提前致谢!
您可以使用 vectorAssembler
:
import org.apache.spark.ml.linalg.Vector
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.ml.feature.VectorAssembler
val df = Seq((1,2),(3,4)).toDF("col1","col2")
val va = new VectorAssembler().setInputCols(Array("col1","col2")).setOutputCol("vector")
val row0 = va.transform(df).select("vector").collect()(0).getAs[Vector](0)
val vector0 = Vectors.fromML(row0)
// vector0: org.apache.spark.mllib.linalg.Vector = [1.0,2.0]