将结构传递给spark中的UDAF

import org.apache.spark.sql.expressions.{UserDefinedAggregateFunction, MutableAggregationBuffer}
import org.apache.spark.sql.types._
import org.apache.spark.sql.Row

// 定义一个自定义的聚合函数
class MyUDAF extends UserDefinedAggregateFunction {
  // 定义输入数据的结构
  def inputSchema: StructType = StructType(StructField("value", DoubleType) :: Nil)

  // 定义缓冲区的结构
  def bufferSchema: StructType = StructType(StructField("sum", DoubleType) :: Nil)

  // 定义返回结果的类型
  def dataType: DataType = DoubleType

  // 定义是否是确定性的
  def deterministic: Boolean = true

  // 初始化缓冲区的值
  def initialize(buffer: MutableAggregationBuffer): Unit = {
    buffer(0) = 0.0
  }

  // 更新缓冲区的值
  def update(buffer: MutableAggregationBuffer, input: Row): Unit = {
    val sum = buffer.getDouble(0)
    val value = input.getDouble(0)
    buffer(0) = sum + value
  }

  // 合并两个缓冲区的值
  def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit = {
    val sum1 = buffer1.getDouble(0)
    val sum2 = buffer2.getDouble(0)
    buffer1(0) = sum1 + sum2
  }

  // 计算最终的聚合结果
  def evaluate(buffer: Row): Any = {
    buffer.getDouble(0)
  }
}

// 使用自定义的聚合函数
val df = spark.range(10).toDF("value")
df.createOrReplaceTempView("myTable")
spark.udf.register("myUDAF", new MyUDAF)
spark.sql("SELECT myUDAF(value) FROM myTable").show()