scala - Spark UDAF : How to get value from input by column field name in UDAF (User-Defined Aggregation Function)?

Question

我正在尝试使用 Spark UDAF 将两个现有列汇总到一个新列中。大多数关于 Spark UDAF 的教程都使用索引来获取输入行每一列中的值。像这样:

input.getAs[String](1)

，它用在我的更新方法中(override def update(buffer: MutableAggregationBuffer, input: Row): Unit)。它也适用于我的情况。但是我想使用该列的字段名称来获取该值。像这样:

input.getAs[String](ColumnNames.BehaviorType)

，其中 ColumnNames.BehaviorType 是对象中定义的 String 对象:

 /**
    * Column names in the original dataset
    */
  object ColumnNames {
    val JobSeekerID = "JobSeekerID"
    val JobID = "JobID"
    val Date = "Date"
    val BehaviorType = "BehaviorType"
  }

这次不行了。我得到以下异常:

java.lang.IllegalArgumentException: Field "BehaviorType" does not exist. at org.apache.spark.sql.types.StructType$$anonfun$fieldIndex$1.apply(StructType.scala:292) ... at org.apache.spark.sql.Row$class.getAs(Row.scala:333) at org.apache.spark.sql.catalyst.expressions.GenericRow.getAs(rows.scala:165) at com.recsys.UserBehaviorRecordsUDAF.update(UserBehaviorRecordsUDAF.scala:44)

部分相关代码段:

这是我的 UDAF 的一部分:

class UserBehaviorRecordsUDAF extends UserDefinedAggregateFunction {


  override def inputSchema: StructType = StructType(
    StructField("JobID", IntegerType) ::
      StructField("BehaviorType", StringType) :: Nil)

  override def update(buffer: MutableAggregationBuffer, input: Row): Unit = {
    println("XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX")
    println(input.schema.treeString)
    println
    println(input.mkString(","))
    println
    println(this.inputSchema.treeString)
//    println
//    println(bufferSchema.treeString)

    input.getAs[String](ColumnNames.BehaviorType) match { //ColumnNames.BehaviorType //1 //TODO WHY??
      case BehaviourTypes.viewed_job =>
        buffer(0) =
          buffer.getAs[Seq[Int]](0) :+ //Array[Int]  //TODO WHY??
          input.getAs[Int](0) //ColumnNames.JobID
      case BehaviourTypes.bookmarked_job =>
        buffer(1) =
          buffer.getAs[Seq[Int]](1) :+ //Array[Int]
            input.getAs[Int](0)//ColumnNames.JobID
      case BehaviourTypes.applied_job =>
        buffer(2) =
          buffer.getAs[Seq[Int]](2) :+  //Array[Int]
            input.getAs[Int](0) //ColumnNames.JobID
    }
  }

以下是调用UDAF的部分代码:

val ubrUDAF = new UserBehaviorRecordsUDAF

val userProfileDF = userBehaviorDS
  .groupBy(ColumnNames.JobSeekerID)
  .agg(
    ubrUDAF(
      userBehaviorDS.col(ColumnNames.JobID), //userBehaviorDS.col(ColumnNames.JobID)
      userBehaviorDS.col(ColumnNames.BehaviorType) //userBehaviorDS.col(ColumnNames.BehaviorType)
    ).as("profile str"))

输入行的模式中的字段名称似乎没有传递到 UDAF 中:

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
root
 |-- input0: integer (nullable = true)
 |-- input1: string (nullable = true)


30917,viewed_job

root
 |-- JobID: integer (nullable = true)
 |-- BehaviorType: string (nullable = true)

我的代码有什么问题？

Answer 1

我还想在我的更新方法中使用我的 inputSchema 中的字段名称来创建可维护的代码。

import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
class MyUDAF extends UserDefinedAggregateFunction {
  def update(buffer: MutableAggregationBuffer, input: Row) = {
    val inputWSchema = new GenericRowWithSchema(input.toSeq.toArray, inputSchema)

最终切换到 Aggregator，运行时间缩短了一半。