Github user icexelloss commented on a diff in the pull request:

    https://github.com/apache/spark/pull/18732#discussion_r141953435
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/python/FlatMapGroupsInPandasExec.scala
 ---
    @@ -0,0 +1,95 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.sql.execution.python
    +
    +import scala.collection.JavaConverters._
    +
    +import org.apache.spark.TaskContext
    +import org.apache.spark.api.python.{ChainedPythonFunctions, PythonEvalType}
    +import org.apache.spark.rdd.RDD
    +import org.apache.spark.sql.catalyst.InternalRow
    +import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, 
AttributeSet, Expression, NamedExpression, SortOrder, UnsafeProjection}
    +import 
org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution, 
Distribution, Partitioning}
    +import org.apache.spark.sql.execution.{GroupedIterator, SparkPlan, 
UnaryExecNode}
    +
    +case class FlatMapGroupsInPandasExec(
    +    grouping: Seq[Expression],
    +    func: Expression,
    +    override val output: Seq[Attribute],
    +    override val child: SparkPlan
    +) extends UnaryExecNode {
    +
    +  val groupingAttributes: Seq[Attribute] = grouping.map {
    +    case ne: NamedExpression => ne.toAttribute
    +  }
    +
    +  private val pandasFunction = func.asInstanceOf[PythonUDF].func
    +
    +  override def outputPartitioning: Partitioning = child.outputPartitioning
    +
    +  override def producedAttributes: AttributeSet = AttributeSet(output)
    +
    +  override def requiredChildDistribution: Seq[Distribution] =
    +    ClusteredDistribution(groupingAttributes) :: Nil
    +
    +  override def requiredChildOrdering: Seq[Seq[SortOrder]] =
    +    Seq(groupingAttributes.map(SortOrder(_, Ascending)))
    +
    +  override protected def doExecute(): RDD[InternalRow] = {
    +    val inputRDD = child.execute()
    +
    +    val bufferSize = inputRDD.conf.getInt("spark.buffer.size", 65536)
    +    val reuseWorker = 
inputRDD.conf.getBoolean("spark.python.worker.reuse", defaultValue = true)
    +    val chainedFunc = Seq(ChainedPythonFunctions(Seq(pandasFunction)))
    +    val argOffsets = Array((0 until child.schema.length).toArray)
    +
    +    inputRDD.mapPartitionsInternal { iter =>
    +      val grouped = GroupedIterator(iter, groupingAttributes, child.output)
    --- End diff --
    
    Other places pass `groupingAttributes` to `GroupedIterator`. What's the 
difference between the two?


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