LuciferYang commented on a change in pull request #25309: 
[SPARK-28577][YARN]Ensure executorMemoryOverHead requested value not less than 
offHeapSize when offHeap enable
URL: https://github.com/apache/spark/pull/25309#discussion_r310153175
 
 

 ##########
 File path: 
resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala
 ##########
 @@ -184,4 +184,29 @@ object YarnSparkHadoopUtil {
     ConverterUtils.toContainerId(containerIdString)
   }
 
+  /**
+   * If MEMORY_OFFHEAP_ENABLED is true, we should ensure 
executorOverheadMemory requested value
+   * is not less than MEMORY_OFFHEAP_SIZE, otherwise the memory resource 
requested for executor
+   * may be not enough.
+   */
+  def executorMemoryOverheadRequested(sparkConf: SparkConf): Int = {
+    val executorMemory = sparkConf.get(EXECUTOR_MEMORY).toInt
+    val overhead = sparkConf.get(EXECUTOR_MEMORY_OVERHEAD).getOrElse(
+      math.max((MEMORY_OVERHEAD_FACTOR * executorMemory).toInt, 
MEMORY_OVERHEAD_MIN)).toInt
+    val offHeap = if (sparkConf.get(MEMORY_OFFHEAP_ENABLED)) {
+      val size =
+        sparkConf.getSizeAsMb(MEMORY_OFFHEAP_SIZE.key, 
MEMORY_OFFHEAP_SIZE.defaultValueString)
+      require(size > 0,
+        s"${MEMORY_OFFHEAP_SIZE.key} must be > 0 when 
${MEMORY_OFFHEAP_ENABLED.key} == true")
+      if (size > overhead) {
+        logWarning(s"The value of ${MEMORY_OFFHEAP_SIZE.key}(${size}MB) will 
be used as " +
+          s"executorMemoryOverhead to request resource to ensure that Executor 
has enough memory " +
+          s"to use. It is recommended that the configuration value of " +
+          s"${EXECUTOR_MEMORY_OVERHEAD.key} should be no less than 
${MEMORY_OFFHEAP_SIZE.key} " +
+          s"when ${MEMORY_OFFHEAP_ENABLED.key} is true.")
+      }
+      size
+    } else 0
+    math.max(overhead, offHeap).toInt
 
 Review comment:
   @tgravescs Agree with you, overhead should  be used to describe memory not 
use by Spark, like Netty used or JVM used as @jerryshao  said, and we should 
clearly describe it in the configuration document.
   
   So change to use `executorMemory + memoryOverhead + pysparkWorkerMemory + 
executorOffHeapMemory` to request resource?

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