spark自定义UDF函数toDF导入报错的引用方法

这里自定义了一个转换大写的UDF函数，用scala建表时会出现toDF不能导入的问题，后面通过查看源码可以找知道toDF的使用方法
正确代码

import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession
object ScalaTest {
  def main(args: Array[String]): Unit = {
    val sparkConfig = new SparkConf().setMaster("local")
    val spark = SparkSession.builder().appName("test").config(sparkConfig).enableHiveSupport().getOrCreate()

    // 需使用隐式转化
    import spark.implicits._

    spark.udf.register("to_uppercase", (s: String) => s.toUpperCase())

    Seq((1, "zhangsan"), (2, "lisi"), (3, "xiaoming")).toDF("id", "name").createOrReplaceTempView("table_tmp")
    spark.sql("select id, to_uppercase(name) from table_tmp").show()
    spark.sql("select id, to_uppercase(name) new_name from table_tmp").show()
  }
}

输出结果：

+---+----------------------+
| id|UDF:to_uppercase(name)|
+---+----------------------+
|  1|              ZHANGSAN|
|  2|                  LISI|
|  3|              XIAOMING|
+---+----------------------+

+---+--------+
| id|new_name|
+---+--------+
|  1|ZHANGSAN|
|  2|    LISI|
|  3|XIAOMING|
+---+--------+

toDF()源码介绍

@InterfaceStability.Stable
case class DatasetHolder[T] private[sql](private val ds: Dataset[T]) {

  // This is declared with parentheses to prevent the Scala compiler from treating
  // `rdd.toDS("1")` as invoking this toDS and then apply on the returned Dataset.
  def toDS(): Dataset[T] = ds

  // This is declared with parentheses to prevent the Scala compiler from treating
  // `rdd.toDF("1")` as invoking this toDF and then apply on the returned Dataframe.
  def toDF(): Dataframe = ds.toDF()

  def toDF(colNames: String*): Dataframe = ds.toDF(colNames : _*)
}

再贴一个关于scala隐式讲解的链接Scala隐式详解