zhenlineo commented on code in PR #40581:
URL: https://github.com/apache/spark/pull/40581#discussion_r1156523516
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connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
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@@ -482,27 +482,66 @@ class SparkConnectPlanner(val session: SparkSession) {
}
private def transformMapPartitions(rel: proto.MapPartitions): LogicalPlan = {
+ val baseRel = transformRelation(rel.getInput)
val commonUdf = rel.getFunc
- val pythonUdf = transformPythonUDF(commonUdf)
- val isBarrier = if (rel.hasIsBarrier) rel.getIsBarrier else false
- pythonUdf.evalType match {
- case PythonEvalType.SQL_MAP_PANDAS_ITER_UDF =>
- logical.MapInPandas(
- pythonUdf,
- pythonUdf.dataType.asInstanceOf[StructType].toAttributes,
- transformRelation(rel.getInput),
- isBarrier)
- case PythonEvalType.SQL_MAP_ARROW_ITER_UDF =>
- logical.PythonMapInArrow(
- pythonUdf,
- pythonUdf.dataType.asInstanceOf[StructType].toAttributes,
- transformRelation(rel.getInput),
- isBarrier)
+ commonUdf.getFunctionCase match {
+ case proto.CommonInlineUserDefinedFunction.FunctionCase.SCALAR_SCALA_UDF
=>
+ transformTypedMapPartitions(commonUdf, baseRel)
+ case proto.CommonInlineUserDefinedFunction.FunctionCase.PYTHON_UDF =>
+ val pythonUdf = transformPythonUDF(commonUdf)
+ val isBarrier = if (rel.hasIsBarrier) rel.getIsBarrier else false
+ pythonUdf.evalType match {
+ case PythonEvalType.SQL_MAP_PANDAS_ITER_UDF =>
+ logical.MapInPandas(
+ pythonUdf,
+ pythonUdf.dataType.asInstanceOf[StructType].toAttributes,
+ baseRel,
+ isBarrier)
+ case PythonEvalType.SQL_MAP_ARROW_ITER_UDF =>
+ logical.PythonMapInArrow(
+ pythonUdf,
+ pythonUdf.dataType.asInstanceOf[StructType].toAttributes,
+ baseRel,
+ isBarrier)
+ case _ =>
+ throw InvalidPlanInput(
+ s"Function with EvalType: ${pythonUdf.evalType} is not
supported")
+ }
case _ =>
- throw InvalidPlanInput(s"Function with EvalType: ${pythonUdf.evalType}
is not supported")
+ throw InvalidPlanInput(
+ s"Function with ID: ${commonUdf.getFunctionCase.getNumber} is not
supported")
}
}
+ private def generateObjAttr[T](enc: ExpressionEncoder[T]): Attribute = {
+ val dataType = enc.deserializer.dataType
+ val nullable = !enc.clsTag.runtimeClass.isPrimitive
+ AttributeReference("obj", dataType, nullable)()
+ }
+
+ private def transformTypedMapPartitions(
+ fun: proto.CommonInlineUserDefinedFunction,
+ child: LogicalPlan): LogicalPlan = {
+ val udf = fun.getScalarScalaUdf
+ val udfPacket =
Review Comment:
Now that I have the input and return types, can I use reflection to find the
encoders for them rather than use the encoders obtained from udfPacket?
I cannot easily test out using a `Person` class currently as I am missing
the class sync logic.
But in theory, if the class is synced to the server correctly, I should be
able to directly use reflection to find the Person encoders, right?
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