Spark UnaryTransformer 实现因 scala.MatchError 而失败

Question

我正在 Spark 1.6.2 中实现 UnaryTransformer。使用这个界面：

class myUT(override val uid: String) extends UnaryTransformer[Seq[String], Seq[String], myUT] {
...
override protected def createTransformFunc: Seq[String] => Seq[String] = {
   _ => _.map(x => x + "s")
}

这编译得很好，但在运行时返回一个错误：

17/07/21 22:29:33 WARN TaskSetManager: Lost task 0.3 in stage 0.0 (TID 3, myhost.com.au): scala.MatchError: ArrayBuffer(<contents of my array>) (of class scala.collection.mutable.ArrayBuffer)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:295)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:294)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:401)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:51)
    at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:49)

接下来我尝试的是替换

_ => _.map(x => x + "s")

与

_ => _

所以，理论上这应该意味着数据完全没有变化！但我遇到的错误是：

17/07/21 22:11:59 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, myhost.com.au): scala.MatchError: WrappedArray(<contains of my array>) (of class scala.collection.mutable.WrappedArray$ofRef)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:295)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:294)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:401)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:51)
    at org.apache.spark.sql.execution.Project$$anonfun$1$$anonfun$apply$1.apply(basicOperators.scala:49)

所以看起来传出数据的类型无论如何都会发生变化。我该如何避免这种情况？

更新：接下来我尝试将 .toArray 添加到地图中。现在的错误是这样的：

[error] /sparkprj/src/main/scala/sp_txt.scala:43: polymorphic expression cannot be instantiated to expected type;
[error]  found   : [B >: String]Array[B]
[error]  required: Seq[String]
[error]                                           ).toArray

它可能会增加一些细节，但不会增加我的理解。在查看了一些 mllib UnaryTransformer 的示例后，我倾向于认为这是 Catalyst 中的一个错误。

Answer 1

myUT 类定义中的这一行不正确：

override protected def outputDataType: DataType = new ArrayType(StringType, true)

当我从 String->String 转换器复制这个类定义时，我将 DataType 定义为 StringType。我的错。