Github user edwinalu commented on a diff in the pull request:
https://github.com/apache/spark/pull/21221#discussion_r198815695
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/PeakExecutorMetrics.scala ---
@@ -0,0 +1,127 @@
+/*
+ * 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.scheduler
+
+import org.apache.spark.executor.ExecutorMetrics
+import org.apache.spark.status.api.v1.PeakMemoryMetrics
+
+/**
+ * Records the peak values for executor level metrics. If
jvmUsedHeapMemory is -1, then no
+ * values have been recorded yet.
+ */
+private[spark] class PeakExecutorMetrics {
--- End diff --
With ExecutorMetrics removed, it seems useful to have a class for tracking
and setting peak metric values, that can be used by both EventLoggingListener
and AppStatusListener.
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