如何读取带有不支持类型的Spark的拼接？

import org.apache.spark.sql.types._
import org.apache.spark.sql.{SparkSession, UserDefinedType}

// 自定义解析器
class CustomParser extends UserDefinedType[String] {
  override def serialize(obj: String): String = {
    // 实现将不支持的类型转换为字符串的逻辑
    // 示例代码：将不支持的类型转换为空字符串
    ""
  }

  override def deserialize(datum: Any): String = {
    // 实现将字符串转换为不支持的类型的逻辑
    // 示例代码：将空字符串转换为null
    if (datum == null) {
      null
    } else {
      datum.toString
    }
  }

  override def typeName: String = "custom_type"
}

object Main {
  def main(args: Array[String]): Unit = {
    val spark = SparkSession.builder()
      .appName("CustomParserExample")
      .master("local")
      .getOrCreate()

    // 注册自定义解析器
    spark.udf.register("custom_parser", new CustomParser)

    // 创建示例数据
    val data = Seq(("value1", 123), ("value2", 456), ("value3", 789))
    val schema = StructType(Seq(
      StructField("col1", StringType, nullable = false),
      StructField("col2", IntegerType, nullable = false)
    ))
    val df = spark.createDataFrame(data).toDF("col1", "col2")

    // 使用自定义解析器进行列的转换
    val result = df.select($"col1", $"col2", callUDF("custom_parser", $"col1").as("parsed_col"))
    
    result.show()
    
    spark.stop()
  }
}