[SPARK-22897][CORE]: Expose stageAttemptId in TaskContext

core/src/main/scala/org/apache/spark/TaskContext.scala

@@ -66,7 +66,7 @@ object TaskContext {
    * An empty task context that does not represent an actual task.  This is only used in tests.
    */
   private[spark] def empty(): TaskContextImpl = {
-    new TaskContextImpl(0, 0, 0, 0, null, new Properties, null)
+    new TaskContextImpl(0, 0, 0, 0, 0, null, new Properties, null)
   }
 }
 
@@ -150,6 +150,11 @@ abstract class TaskContext extends Serializable {
    */
   def stageId(): Int
 
+  /**
+   * An ID that is unique to the stage attempt that this task belongs to.
+   */
+  def stageAttemptId(): Int
+
   /**
    * The ID of the RDD partition that is computed by this task.
    */

core/src/main/scala/org/apache/spark/TaskContextImpl.scala

@@ -42,6 +42,7 @@ import org.apache.spark.util._
  */
 private[spark] class TaskContextImpl(
     val stageId: Int,
+    val stageAttemptId: Int,
     val partitionId: Int,
     override val taskAttemptId: Long,
     override val attemptNumber: Int,

core/src/main/scala/org/apache/spark/scheduler/Task.scala

@@ -79,6 +79,7 @@ private[spark] abstract class Task[T](
     SparkEnv.get.blockManager.registerTask(taskAttemptId)
     context = new TaskContextImpl(
       stageId,
+      stageAttemptId,
       partitionId,
       taskAttemptId,
       attemptNumber,

core/src/test/java/test/org/apache/spark/JavaTaskContextCompileCheck.java

@@ -38,6 +38,7 @@ public static void test() {
     tc.attemptNumber();
     tc.partitionId();
     tc.stageId();
+    tc.stageAttemptId();
     tc.taskAttemptId();
   }
 
@@ -51,6 +52,7 @@ public void onTaskCompletion(TaskContext context) {
       context.isCompleted();
       context.isInterrupted();
       context.stageId();
+      context.stageAttemptId();
       context.partitionId();
       context.addTaskCompletionListener(this);
     }

core/src/test/scala/org/apache/spark/ShuffleSuite.scala

@@ -363,14 +363,14 @@ abstract class ShuffleSuite extends SparkFunSuite with Matchers with LocalSparkC
 
     // first attempt -- its successful
     val writer1 = manager.getWriter[Int, Int](shuffleHandle, 0,
-      new TaskContextImpl(0, 0, 0L, 0, taskMemoryManager, new Properties, metricsSystem))
+      new TaskContextImpl(0, 0, 0, 0L, 0, taskMemoryManager, new Properties, metricsSystem))
     val data1 = (1 to 10).map { x => x -> x}
 
     // second attempt -- also successful.  We'll write out different data,
     // just to simulate the fact that the records may get written differently
     // depending on what gets spilled, what gets combined, etc.
     val writer2 = manager.getWriter[Int, Int](shuffleHandle, 0,
-      new TaskContextImpl(0, 0, 1L, 0, taskMemoryManager, new Properties, metricsSystem))
+      new TaskContextImpl(0, 0, 0, 1L, 0, taskMemoryManager, new Properties, metricsSystem))
     val data2 = (11 to 20).map { x => x -> x}
 
     // interleave writes of both attempts -- we want to test that both attempts can occur
@@ -398,7 +398,7 @@ abstract class ShuffleSuite extends SparkFunSuite with Matchers with LocalSparkC
     }
 
     val reader = manager.getReader[Int, Int](shuffleHandle, 0, 1,
-      new TaskContextImpl(1, 0, 2L, 0, taskMemoryManager, new Properties, metricsSystem))
+      new TaskContextImpl(1, 0, 0, 2L, 0, taskMemoryManager, new Properties, metricsSystem))
     val readData = reader.read().toIndexedSeq
     assert(readData === data1.toIndexedSeq || readData === data2.toIndexedSeq)
 

core/src/test/scala/org/apache/spark/memory/MemoryTestingUtils.scala

@@ -29,6 +29,7 @@ object MemoryTestingUtils {
     val taskMemoryManager = new TaskMemoryManager(env.memoryManager, 0)
     new TaskContextImpl(
       stageId = 0,
+      stageAttemptId = 0,
       partitionId = 0,
       taskAttemptId = 0,
       attemptNumber = 0,

core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala

@@ -29,6 +29,7 @@ import org.apache.spark.memory.TaskMemoryManager
 import org.apache.spark.metrics.source.JvmSource
 import org.apache.spark.network.util.JavaUtils
 import org.apache.spark.rdd.RDD
+import org.apache.spark.shuffle.FetchFailedException
 import org.apache.spark.util._
 
 class TaskContextSuite extends SparkFunSuite with BeforeAndAfter with LocalSparkContext {
@@ -158,6 +159,30 @@ class TaskContextSuite extends SparkFunSuite with BeforeAndAfter with LocalSpark
     assert(attemptIdsWithFailedTask.toSet === Set(0, 1))
   }
 
+  test("TaskContext.stageAttemptId getter") {
+    sc = new SparkContext("local[1,2]", "test")
+
+    // Check stage attemptIds are 0 for initial stage
+    val stageAttemptIds = sc.parallelize(Seq(1, 2), 2).mapPartitions { _ =>
+      Seq(TaskContext.get().stageAttemptId()).iterator
+    }.collect()
+    assert(stageAttemptIds.toSet === Set(0))
+
+    // Check stage attemptIds that are resubmitted when tasks have FetchFailedException
+    val stageAttemptIdsWithFailedStage =
+      sc.parallelize(Seq(1, 2, 3, 4), 4).repartition(1).mapPartitions { _ =>
+      val stageAttemptId = TaskContext.get().stageAttemptId()
+      if (stageAttemptId < 2) {
+        // Throw FetchFailedException to explicitly trigger stage resubmission. A normal exception
+        // will only trigger task resubmission in the same stage.
+        throw new FetchFailedException(null, 0, 0, 0, "Fake")
+      }
+      Seq(stageAttemptId).iterator
+    }.collect()
+
+    assert(stageAttemptIdsWithFailedStage.toSet === Set(2))
+  }
+
   test("accumulators are updated on exception failures") {
     // This means use 1 core and 4 max task failures
     sc = new SparkContext("local[1,4]", "test")
@@ -190,7 +215,7 @@ class TaskContextSuite extends SparkFunSuite with BeforeAndAfter with LocalSpark
     // accumulator updates from it.
     val taskMetrics = TaskMetrics.empty
     val task = new Task[Int](0, 0, 0) {
-      context = new TaskContextImpl(0, 0, 0L, 0,
+      context = new TaskContextImpl(0, 0, 0, 0L, 0,
         new TaskMemoryManager(SparkEnv.get.memoryManager, 0L),
         new Properties,
         SparkEnv.get.metricsSystem,
@@ -213,7 +238,7 @@ class TaskContextSuite extends SparkFunSuite with BeforeAndAfter with LocalSpark
     // accumulator updates from it.
     val taskMetrics = TaskMetrics.registered
     val task = new Task[Int](0, 0, 0) {
-      context = new TaskContextImpl(0, 0, 0L, 0,
+      context = new TaskContextImpl(0, 0, 0, 0L, 0,
         new TaskMemoryManager(SparkEnv.get.memoryManager, 0L),
         new Properties,
         SparkEnv.get.metricsSystem,

core/src/test/scala/org/apache/spark/storage/BlockInfoManagerSuite.scala

@@ -62,7 +62,7 @@ class BlockInfoManagerSuite extends SparkFunSuite with BeforeAndAfterEach {
   private def withTaskId[T](taskAttemptId: Long)(block: => T): T = {
     try {
       TaskContext.setTaskContext(
-        new TaskContextImpl(0, 0, taskAttemptId, 0, null, new Properties, null))
+        new TaskContextImpl(0, 0, 0, taskAttemptId, 0, null, new Properties, null))
       block
     } finally {
       TaskContext.unset()

project/MimaExcludes.scala

@@ -36,6 +36,9 @@ object MimaExcludes {
 
   // Exclude rules for 2.3.x
   lazy val v23excludes = v22excludes ++ Seq(
+    // [SPARK-22897] Expose stageAttemptId in TaskContext
+    ProblemFilters.exclude[ReversedMissingMethodProblem]("org.apache.spark.TaskContext.stageAttemptId"),
+
     // SPARK-22789: Map-only continuous processing execution
     ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.streaming.StreamingQueryManager.startQuery$default$8"),
     ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.sql.streaming.StreamingQueryManager.startQuery$default$6"),

sql/core/src/test/scala/org/apache/spark/sql/execution/UnsafeFixedWidthAggregationMapSuite.scala

@@ -70,6 +70,7 @@ class UnsafeFixedWidthAggregationMapSuite
 
       TaskContext.setTaskContext(new TaskContextImpl(
         stageId = 0,
+        stageAttemptId = 0,
         partitionId = 0,
         taskAttemptId = Random.nextInt(10000),
         attemptNumber = 0,

sql/core/src/test/scala/org/apache/spark/sql/execution/UnsafeKVExternalSorterSuite.scala

@@ -116,6 +116,7 @@ class UnsafeKVExternalSorterSuite extends SparkFunSuite with SharedSQLContext {
     val taskMemMgr = new TaskMemoryManager(memoryManager, 0)
     TaskContext.setTaskContext(new TaskContextImpl(
       stageId = 0,
+      stageAttemptId = 0,
       partitionId = 0,
       taskAttemptId = 98456,
       attemptNumber = 0,

sql/core/src/test/scala/org/apache/spark/sql/execution/UnsafeRowSerializerSuite.scala

@@ -114,7 +114,7 @@ class UnsafeRowSerializerSuite extends SparkFunSuite with LocalSparkContext {
         (i, converter(Row(i)))
       }
       val taskMemoryManager = new TaskMemoryManager(sc.env.memoryManager, 0)
-      val taskContext = new TaskContextImpl(0, 0, 0, 0, taskMemoryManager, new Properties, null)
+      val taskContext = new TaskContextImpl(0, 0, 0, 0, 0, taskMemoryManager, new Properties, null)
 
       val sorter = new ExternalSorter[Int, UnsafeRow, UnsafeRow](
         taskContext,

sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/SortBasedAggregationStoreSuite.scala

@@ -35,7 +35,8 @@ class SortBasedAggregationStoreSuite  extends SparkFunSuite with LocalSparkConte
     val conf = new SparkConf()
     sc = new SparkContext("local[2, 4]", "test", conf)
     val taskManager = new TaskMemoryManager(new TestMemoryManager(conf), 0)
-    TaskContext.setTaskContext(new TaskContextImpl(0, 0, 0, 0, taskManager, new Properties, null))
+    TaskContext.setTaskContext(
+      new TaskContextImpl(0, 0, 0, 0, 0, taskManager, new Properties, null))
   }
 
   override def afterAll(): Unit = TaskContext.unset()