如何在spark编码器中映射cassandra数据类型？

import com.datastax.spark.connector.mapper.ColumnMapper
import com.datastax.spark.connector.types.TypeConverter
import com.datastax.spark.connector.types.TypeConverter.OptionToNullConverter

class MyColumnMapper extends ColumnMapper {

  override def map(columnName: String, columnType: String): TypeConverter[_] = {
    columnType match {
      case "text" => TypeConverter.StringConverter
      case "int" => TypeConverter.IntConverter
      case "bigint" => TypeConverter.LongConverter
      // 添加其他Cassandra数据类型的映射
      case _ => throw new IllegalArgumentException(s"Unsupported Cassandra data type: $columnType")
    }
  }
}

import com.datastax.spark.connector.cql.CassandraConnector
import org.apache.spark.{SparkConf, SparkContext}

object SparkCassandraMappingExample {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf()
      .setAppName("Spark Cassandra Mapping Example")
      .setMaster("local[2]")
      .set("spark.cassandra.connection.host", "localhost")
    val sc = new SparkContext(conf)

    // 创建自定义映射器
    val columnMapper = new MyColumnMapper

    // 应用自定义映射器
    CassandraConnector(conf).withColumnMapper(columnMapper).withSessionDo { session =>
      // 执行Spark操作，读取Cassandra数据
      val rdd = sc.cassandraTable("mykeyspace", "mytable")
      // 进行进一步的数据处理和分析
      // ...
    }

    sc.stop()
  }
}