Github user tedyu commented on a diff in the pull request:
https://github.com/apache/spark/pull/9344#discussion_r44212241
--- Diff:
core/src/main/scala/org/apache/spark/memory/ExecutionMemoryPool.scala ---
@@ -0,0 +1,153 @@
+/*
+ * 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 javax.annotation.concurrent.GuardedBy
+
+import scala.collection.mutable
+
+import org.apache.spark.Logging
+
+/**
+ * Implements policies and bookkeeping for sharing a adjustable-sized pool
of memory between tasks.
+ *
+ * Tries to ensure that each task gets a reasonable share of memory,
instead of some task ramping up
+ * to a large amount first and then causing others to spill to disk
repeatedly.
+ *
+ * If there are N tasks, it ensures that each task can acquire at least 1
/ 2N of the memory
+ * before it has to spill, and at most 1 / N. Because N varies
dynamically, we keep track of the
+ * set of active tasks and redo the calculations of 1 / 2N and 1 / N in
waiting tasks whenever this
+ * set changes. This is all done by synchronizing access to mutable state
and using wait() and
+ * notifyAll() to signal changes to callers. Prior to Spark 1.6, this
arbitration of memory across
+ * tasks was performed by the ShuffleMemoryManager.
+ *
+ * @param lock a [[MemoryManager]] instance to synchronize on
+ * @param poolName a human-readable name for this pool, for use in log
messages
+ */
+class ExecutionMemoryPool(
+ lock: Object,
+ poolName: String
+ ) extends MemoryPool(lock) with Logging {
+
+ /**
+ * Map from taskAttemptId -> memory consumption in bytes
+ */
+ @GuardedBy("lock")
+ private val memoryForTask = new mutable.HashMap[Long, Long]()
+
+ override def memoryUsed: Long = lock.synchronized {
+ memoryForTask.values.sum
+ }
+
+ /**
+ * Returns the memory consumption, in bytes, for the given task.
+ */
+ def getMemoryUsageForTask(taskAttemptId: Long): Long = lock.synchronized
{
+ memoryForTask.getOrElse(taskAttemptId, 0L)
+ }
+
+ /**
+ * Try to acquire up to `numBytes` of memory for the given task and
return the number of bytes
+ * obtained, or 0 if none can be allocated.
+ *
+ * This call may block until there is enough free memory in some
situations, to make sure each
+ * task has a chance to ramp up to at least 1 / 2N of the total memory
pool (where N is the # of
+ * active tasks) before it is forced to spill. This can happen if the
number of tasks increase
+ * but an older task had a lot of memory already.
+ *
+ * @return the number of bytes granted to the task.
+ */
+ def acquireMemory(numBytes: Long, taskAttemptId: Long): Long =
lock.synchronized {
+ assert(numBytes > 0, s"invalid number of bytes requested: $numBytes")
+
+ // Add this task to the taskMemory map just so we can keep an accurate
count of the number
+ // of active tasks, to let other tasks ramp down their memory in calls
to `acquireMemory`
+ if (!memoryForTask.contains(taskAttemptId)) {
+ memoryForTask(taskAttemptId) = 0L
+ // This will later cause waiting tasks to wake up and check numTasks
again
+ lock.notifyAll()
+ }
+
+ // Keep looping until we're either sure that we don't want to grant
this request (because this
+ // task would have more than 1 / numActiveTasks of the memory) or we
have enough free
+ // memory to give it (we always let each task get at least 1 / (2 *
numActiveTasks)).
+ // TODO: simplify this to limit each task to its own slot
+ while (true) {
+ val numActiveTasks = memoryForTask.keys.size
+ val curMem = memoryForTask(taskAttemptId)
+
+ // How much we can grant this task; don't let it grow to more than 1
/ numActiveTasks;
+ // don't let it be negative
+ val maxToGrant =
+ math.min(numBytes, math.max(0, (poolSize / numActiveTasks) -
curMem))
+ // Only give it as much memory as is free, which might be none if it
reached 1 / numTasks
+ val toGrant = math.min(maxToGrant, memoryFree)
+
+ if (curMem < poolSize / (2 * numActiveTasks)) {
+ // We want to let each task get at least 1 / (2 * numActiveTasks)
before blocking;
+ // if we can't give it this much now, wait for other tasks to free
up memory
+ // (this happens if older tasks allocated lots of memory before N
grew)
+ if (memoryFree >= math.min(maxToGrant, poolSize / (2 *
numActiveTasks) - curMem)) {
+ memoryForTask(taskAttemptId) += toGrant
+ return toGrant
+ } else {
+ logInfo(
+ s"TID $taskAttemptId waiting for at least 1/2N of $poolName
pool to be free")
+ lock.wait()
+ }
+ } else {
+ memoryForTask(taskAttemptId) += toGrant
+ return toGrant
+ }
+ }
+ 0L // Never reached
+ }
+
+ /**
+ * Release `numBytes` of memory acquired by the given task.
+ */
+ def releaseMemory(numBytes: Long, taskAttemptId: Long): Unit =
lock.synchronized {
+ val curMem = memoryForTask.getOrElse(taskAttemptId, 0L)
+ var memoryToFree = if (curMem < numBytes) {
+ logWarning(
+ s"Internal error: release called on $numBytes bytes but task only
has $curMem bytes " +
+ s"of memory from the $poolName pool")
+ curMem
+ } else {
+ numBytes
+ }
+ if (memoryForTask.contains(taskAttemptId)) {
+ memoryForTask(taskAttemptId) -= memoryToFree
+ if (memoryForTask(taskAttemptId) <= 0) {
+ memoryForTask.remove(taskAttemptId)
+ }
+ }
--- End diff --
Should we log the case where memoryForTask doesn't contain taskAttemptId ?
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