tgravescs commented on code in PR #44690:
URL: https://github.com/apache/spark/pull/44690#discussion_r1475468620


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core/src/main/scala/org/apache/spark/resource/ResourceAllocator.scala:
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@@ -20,6 +20,49 @@ package org.apache.spark.resource
 import scala.collection.mutable
 
 import org.apache.spark.SparkException
+import org.apache.spark.resource.ResourceAmountUtils.ONE_ENTIRE_RESOURCE
+
+private[spark] object ResourceAmountUtils {
+  /**
+   * Using "double" to do the resource calculation may encounter a problem of 
precision loss. Eg
+   *
+   * scala> val taskAmount = 1.0 / 9
+   * taskAmount: Double = 0.1111111111111111
+   *
+   * scala> var total = 1.0
+   * total: Double = 1.0
+   *
+   * scala> for (i <- 1 to 9 ) {
+   * |   if (total >= taskAmount) {
+   * |           total -= taskAmount
+   * |           println(s"assign $taskAmount for task $i, total left: $total")
+   * |   } else {
+   * |           println(s"ERROR Can't assign $taskAmount for task $i, total 
left: $total")
+   * |   }
+   * | }
+   * assign 0.1111111111111111 for task 1, total left: 0.8888888888888888
+   * assign 0.1111111111111111 for task 2, total left: 0.7777777777777777
+   * assign 0.1111111111111111 for task 3, total left: 0.6666666666666665
+   * assign 0.1111111111111111 for task 4, total left: 0.5555555555555554
+   * assign 0.1111111111111111 for task 5, total left: 0.44444444444444425
+   * assign 0.1111111111111111 for task 6, total left: 0.33333333333333315
+   * assign 0.1111111111111111 for task 7, total left: 0.22222222222222204
+   * assign 0.1111111111111111 for task 8, total left: 0.11111111111111094
+   * ERROR Can't assign 0.1111111111111111 for task 9, total left: 
0.11111111111111094
+   *
+   * So we multiply ONE_ENTIRE_RESOURCE to convert the double to long to avoid 
this limitation.
+   * Double can display up to 16 decimal places, so we set the factor to
+   * 10, 000, 000, 000, 000, 000L.
+   */
+  final val ONE_ENTIRE_RESOURCE: Long = 10000000000000000L

Review Comment:
   @srowen  what if your major concern here?  Are you seeing performance 
issues?  just more complex then you think is necessary?   i don't think its 
hacky, it might be overkill but I do agree its likely more then we need for 
precision.  I would go more then 100 though as 100 tasks per some resource 
seems unlikely but not impossible, 1000 - 10000 much more unlikely.  



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