VectorUDT 用法 [英] VectorUDT usage

问题描述

我必须获取数据类型并进行大小写匹配并将其转换为某种所需的格式.但是 org.apache.spark.ml.linalg.VectorUDT 的用法显示 VectorUDT 是 private.另外我特别需要使用 org.apache.spark.ml.linalg.VectorUDT 而不是 org.apache.spark.mllib.linalg.VectorUDT.有人可以建议如何解决这个问题吗?

I have to get the datatype and do a case match and convert it to some required format. But the usage of org.apache.spark.ml.linalg.VectorUDT is showing VectorUDT is private. Also I specifically need to use org.apache.spark.ml.linalg.VectorUDT and not org.apache.spark.mllib.linalg.VectorUDT. Can someone suggest how to go about this?

推荐答案

对于 org.apache.spark.ml.linalg 类型，您应该使用 org.apache.spark.ml 指定架构.linalg.SQLDataTypes 提供私有 UDT 类型的单例实例:

For org.apache.spark.ml.linalg types you should specify schema using org.apache.spark.ml.linalg.SQLDataTypes which provide singleton instances of the private UDT types:

• MatrixType 用于矩阵 (org.apache.spark.ml.linalg.Matrix).

scala> org.apache.spark.ml.linalg.SQLDataTypes.MatrixType.getClass
res0: Class[_ <: org.apache.spark.sql.types.DataType] = class org.apache.spark.ml.linalg.MatrixUDT

VectorType 用于矢量 (org.apache.spark.ml.linalg.Vector).

scala> org.apache.spark.ml.linalg.SQLDataTypes.VectorType.getClass
res1: Class[_ <: org.apache.spark.sql.types.DataType] = class org.apache.spark.ml.linalg.VectorUDT

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