[SPARK-22827][CORE] Avoid throwing OutOfMemoryError in case of exception in spill

## What changes were proposed in this pull request?
Currently, the task memory manager throws an OutofMemory error when there is an IO exception happens in spill() - https://github.com/apache/spark/blob/master/core/src/main/java/org/apache/spark/memory/TaskMemoryManager.java#L194. Similarly there any many other places in code when if a task is not able to acquire memory due to an exception we throw an OutofMemory error which kills the entire executor and hence failing all the tasks that are running on that executor instead of just failing one single task.

## How was this patch tested?

Unit tests

Author: Sital Kedia <[email protected]>

Closes apache#20014 from sitalkedia/skedia/upstream_SPARK-22827.

Author: Sital Kedia

core/src/main/java/org/apache/spark/memory/MemoryConsumer.java

@@ -88,7 +88,7 @@ public void spill() throws IOException {
    * `LongArray` is too large to fit in a single page. The caller side should take care of these
    * two exceptions, or make sure the `size` is small enough that won't trigger exceptions.
    *
-   * @throws OutOfMemoryError
+   * @throws SparkOutOfMemoryError
    * @throws TooLargePageException
    */
   public LongArray allocateArray(long size) {
@@ -154,6 +154,6 @@ private void throwOom(final MemoryBlock page, final long required) {
       taskMemoryManager.freePage(page, this);
     }
     taskMemoryManager.showMemoryUsage();
-    throw new OutOfMemoryError("Unable to acquire " + required + " bytes of memory, got " + got);
+    throw new SparkOutOfMemoryError("Unable to acquire " + required + " bytes of memory, got " + got);
   }
 }

core/src/main/java/org/apache/spark/memory/SparkOutOfMemoryError.java

@@ -0,0 +1,36 @@
+/*
+ * 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.memory;
+
+import org.apache.spark.annotation.Private;
+
+/**
+ * This exception is thrown when a task can not acquire memory from the Memory manager.
+ * Instead of throwing {@link OutOfMemoryError}, which kills the executor,
+ * we should use throw this exception, which just kills the current task.
+ */
+@Private
+public final class SparkOutOfMemoryError extends OutOfMemoryError {
+
+    public SparkOutOfMemoryError(String s) {
+        super(s);
+    }
+
+    public SparkOutOfMemoryError(OutOfMemoryError e) {
+        super(e.getMessage());
+    }
+}

core/src/main/java/org/apache/spark/memory/TaskMemoryManager.java

@@ -192,7 +192,7 @@ public long acquireExecutionMemory(long required, MemoryConsumer consumer) {
             throw new RuntimeException(e.getMessage());
           } catch (IOException e) {
             logger.error("error while calling spill() on " + c, e);
-            throw new OutOfMemoryError("error while calling spill() on " + c + " : "
+            throw new SparkOutOfMemoryError("error while calling spill() on " + c + " : "
               + e.getMessage());
           }
         }
@@ -213,7 +213,7 @@ public long acquireExecutionMemory(long required, MemoryConsumer consumer) {
           throw new RuntimeException(e.getMessage());
         } catch (IOException e) {
           logger.error("error while calling spill() on " + consumer, e);
-          throw new OutOfMemoryError("error while calling spill() on " + consumer + " : "
+          throw new SparkOutOfMemoryError("error while calling spill() on " + consumer + " : "
             + e.getMessage());
         }
       }

core/src/main/java/org/apache/spark/shuffle/sort/ShuffleExternalSorter.java

@@ -33,6 +33,7 @@
 import org.apache.spark.executor.ShuffleWriteMetrics;
 import org.apache.spark.internal.config.package$;
 import org.apache.spark.memory.MemoryConsumer;
+import org.apache.spark.memory.SparkOutOfMemoryError;
 import org.apache.spark.memory.TaskMemoryManager;
 import org.apache.spark.memory.TooLargePageException;
 import org.apache.spark.serializer.DummySerializerInstance;
@@ -337,7 +338,7 @@ private void growPointerArrayIfNecessary() throws IOException {
         // The pointer array is too big to fix in a single page, spill.
         spill();
         return;
-      } catch (OutOfMemoryError e) {
+      } catch (SparkOutOfMemoryError e) {
         // should have trigger spilling
         if (!inMemSorter.hasSpaceForAnotherRecord()) {
           logger.error("Unable to grow the pointer array");

core/src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeExternalSorter.java

@@ -25,6 +25,7 @@
 import java.util.function.Supplier;
 
 import com.google.common.annotations.VisibleForTesting;
+import org.apache.spark.memory.SparkOutOfMemoryError;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
@@ -349,7 +350,7 @@ private void growPointerArrayIfNecessary() throws IOException {
         // The pointer array is too big to fix in a single page, spill.
         spill();
         return;
-      } catch (OutOfMemoryError e) {
+      } catch (SparkOutOfMemoryError e) {
         // should have trigger spilling
         if (!inMemSorter.hasSpaceForAnotherRecord()) {
           logger.error("Unable to grow the pointer array");

core/src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeInMemorySorter.java

@@ -24,6 +24,7 @@
 
 import org.apache.spark.TaskContext;
 import org.apache.spark.memory.MemoryConsumer;
+import org.apache.spark.memory.SparkOutOfMemoryError;
 import org.apache.spark.memory.TaskMemoryManager;
 import org.apache.spark.unsafe.Platform;
 import org.apache.spark.unsafe.UnsafeAlignedOffset;
@@ -212,7 +213,7 @@ public boolean hasSpaceForAnotherRecord() {
 
   public void expandPointerArray(LongArray newArray) {
     if (newArray.size() < array.size()) {
-      throw new OutOfMemoryError("Not enough memory to grow pointer array");
+      throw new SparkOutOfMemoryError("Not enough memory to grow pointer array");
     }
     Platform.copyMemory(
       array.getBaseObject(),

core/src/main/scala/org/apache/spark/executor/Executor.scala

@@ -35,7 +35,7 @@ import com.google.common.util.concurrent.ThreadFactoryBuilder
 import org.apache.spark._
 import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.internal.Logging
-import org.apache.spark.memory.TaskMemoryManager
+import org.apache.spark.memory.{SparkOutOfMemoryError, TaskMemoryManager}
 import org.apache.spark.rpc.RpcTimeout
 import org.apache.spark.scheduler.{DirectTaskResult, IndirectTaskResult, Task, TaskDescription}
 import org.apache.spark.shuffle.FetchFailedException
@@ -553,10 +553,9 @@ private[spark] class Executor(
 
           // Don't forcibly exit unless the exception was inherently fatal, to avoid
           // stopping other tasks unnecessarily.
-          if (Utils.isFatalError(t)) {
+          if (!t.isInstanceOf[SparkOutOfMemoryError] && Utils.isFatalError(t)) {
             uncaughtExceptionHandler.uncaughtException(Thread.currentThread(), t)
           }
-
       } finally {
         runningTasks.remove(taskId)
       }

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregationIterator.scala

@@ -19,6 +19,7 @@ package org.apache.spark.sql.execution.aggregate
 
 import org.apache.spark.TaskContext
 import org.apache.spark.internal.Logging
+import org.apache.spark.memory.SparkOutOfMemoryError
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.aggregate._
@@ -205,7 +206,7 @@ class TungstenAggregationIterator(
           buffer = hashMap.getAggregationBufferFromUnsafeRow(groupingKey)
           if (buffer == null) {
             // failed to allocate the first page
-            throw new OutOfMemoryError("No enough memory for aggregation")
+            throw new SparkOutOfMemoryError("No enough memory for aggregation")
           }
         }
         processRow(buffer, newInput)