In MapReduce, we sometimes kill a task's JVM before it naturally shuts down if we want to launch other tasks (look in JvmManager$JvmManagerForType.reapJvm). This behavior means that if the map task process is in the middle of doing some cleanup/finalization after the task is done, it might be interrupted/killed without giving it a chance.
In the Microsoft's Hadoop Service, after a Map/Reduce task is done and during closing file systems in a special shutdown hook, we're typically uploading storage (ASV in our context) usage metrics to Microsoft Azure Tables. So if this kill happens these metrics get lost. The impact is that for many MR jobs we don't see accurate metrics reported most of the time.