baohe-zhang commented on a change in pull request #28412:
URL: https://github.com/apache/spark/pull/28412#discussion_r440907281



##########
File path: 
core/src/main/scala/org/apache/spark/deploy/history/HistoryServerMemoryManager.scala
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@@ -0,0 +1,82 @@
+/*
+ * 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.deploy.history
+
+import java.util.concurrent.atomic.AtomicLong
+
+import scala.collection.mutable.HashMap
+
+import org.apache.spark.SparkConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.internal.config.History._
+import org.apache.spark.util.Utils
+
+/**
+ * A class used to keep track of in-memory store usage by the SHS.
+ */
+private class HistoryServerMemoryManager(
+    conf: SparkConf) extends Logging {
+
+  private val maxUsage = conf.get(MAX_IN_MEMORY_STORE_USAGE)
+  private val currentUsage = new AtomicLong(0L)
+  private val active = new HashMap[(String, Option[String]), Long]()
+
+  def initialize(): Unit = {
+    logInfo("Initialized memory manager: " +
+      s"current usage = ${Utils.bytesToString(currentUsage.get())}, " +
+      s"max usage = ${Utils.bytesToString(maxUsage)}")
+  }
+
+  def lease(
+      appId: String,
+      attemptId: Option[String],
+      eventLogSize: Long,
+      isCompressed: Boolean): Unit = {
+    val memoryUsage = approximateMemoryUsage(eventLogSize, isCompressed)
+    if (memoryUsage + currentUsage.get > maxUsage) {
+      throw new RuntimeException("Not enough memory to create hybrid store " +
+        s"for app $appId / $attemptId.")
+    }
+    active.synchronized {
+      active(appId -> attemptId) = memoryUsage
+    }
+    currentUsage.addAndGet(memoryUsage)
+    logInfo(s"Leasing ${Utils.bytesToString(memoryUsage)} memory usage for " +
+      s"app $appId / $attemptId")
+  }
+
+  def release(appId: String, attemptId: Option[String]): Unit = {
+    val memoryUsage = active.synchronized { active.remove(appId -> attemptId) }
+
+    memoryUsage match {
+      case Some(m) =>
+        currentUsage.addAndGet(-m)
+        logInfo(s"Released ${Utils.bytesToString(m)} memory usage for " +
+          s"app $appId / $attemptId")
+      case None =>
+    }
+  }
+
+  private def approximateMemoryUsage(eventLogSize: Long, isCompressed: 
Boolean): Long = {
+    if (isCompressed) {
+      eventLogSize * 2

Review comment:
       This memory usage approximation follows the way we estimate disk usage 
in HistoryServerDiskManager. In disk manager, we estimate the disk usage based 
on the log file size. I did some experiments to compare the memory usage of 
hybridStore (measured through org.apache.spark.util.SizeEstimator) and the disk 
usage of levelDB on a set of log files. I found they are similar. So I think if 
disk usage approximation works, this kind of memory usage approximation should 
work.




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