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40 changes: 40 additions & 0 deletions core/src/main/scala/org/apache/spark/ContextAwareIterator.scala
Original file line number Diff line number Diff line change
@@ -0,0 +1,40 @@
/*
* 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

import org.apache.spark.annotation.DeveloperApi

/**
* :: DeveloperApi ::
* A TaskContext aware iterator.
*
* As the Python evaluation consumes the parent iterator in a separate thread,
* it could consume more data from the parent even after the task ends and the parent is closed.
* If an off-heap access exists in the parent iterator, it could cause segmentation fault
* which crashes the executor.
* Thus, we should use [[ContextAwareIterator]] to stop consuming after the task ends.
*/
@DeveloperApi
class ContextAwareIterator[+T](val context: TaskContext, val delegate: Iterator[T])
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Nice! Thank you for revising this consistently with InterruptibleIterator. Now, it looks much better.

extends Iterator[T] {

override def hasNext: Boolean =
!context.isCompleted() && !context.isInterrupted() && delegate.hasNext

override def next(): T = delegate.next()
}
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ import java.io.File

import scala.collection.mutable.ArrayBuffer

import org.apache.spark.{SparkEnv, TaskContext}
import org.apache.spark.{ContextAwareIterator, SparkEnv, TaskContext}
import org.apache.spark.api.python.ChainedPythonFunctions
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
Expand Down Expand Up @@ -89,6 +89,7 @@ trait EvalPythonExec extends UnaryExecNode {

inputRDD.mapPartitions { iter =>
val context = TaskContext.get()
val contextAwareIterator = new ContextAwareIterator(context, iter)

// The queue used to buffer input rows so we can drain it to
// combine input with output from Python.
Expand Down Expand Up @@ -120,7 +121,7 @@ trait EvalPythonExec extends UnaryExecNode {
}.toSeq)

// Add rows to queue to join later with the result.
val projectedRowIter = iter.map { inputRow =>
val projectedRowIter = contextAwareIterator.map { inputRow =>
queue.add(inputRow.asInstanceOf[UnsafeRow])
projection(inputRow)
}
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution.python

import scala.collection.JavaConverters._

import org.apache.spark.TaskContext
import org.apache.spark.{ContextAwareIterator, TaskContext}
import org.apache.spark.api.python.{ChainedPythonFunctions, PythonEvalType}
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
Expand Down Expand Up @@ -61,16 +61,17 @@ case class MapInPandasExec(
val pythonRunnerConf = ArrowUtils.getPythonRunnerConfMap(conf)
val outputTypes = child.schema

val context = TaskContext.get()
val contextAwareIterator = new ContextAwareIterator(context, inputIter)

// Here we wrap it via another row so that Python sides understand it
// as a DataFrame.
val wrappedIter = inputIter.map(InternalRow(_))
val wrappedIter = contextAwareIterator.map(InternalRow(_))

// DO NOT use iter.grouped(). See BatchIterator.
val batchIter =
if (batchSize > 0) new BatchIterator(wrappedIter, batchSize) else Iterator(wrappedIter)

val context = TaskContext.get()

val columnarBatchIter = new ArrowPythonRunner(
chainedFunc,
PythonEvalType.SQL_MAP_PANDAS_ITER_UDF,
Expand Down