guiyanakuang commented on a change in pull request #34743:
URL: https://github.com/apache/spark/pull/34743#discussion_r762409383



##########
File path: core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
##########
@@ -259,21 +259,29 @@ private[spark] class TaskSetManager(
       loc match {
         case e: ExecutorCacheTaskLocation =>
           pendingTaskSetToAddTo.forExecutor.getOrElseUpdate(e.executorId, new 
ArrayBuffer) += index
+          pendingTaskSetToAddTo.forHost.getOrElseUpdate(loc.host, new 
ArrayBuffer) += index
         case e: HDFSCacheTaskLocation =>
           val exe = sched.getExecutorsAliveOnHost(loc.host)
           exe match {
             case Some(set) =>
               for (e <- set) {
                 pendingTaskSetToAddTo.forExecutor.getOrElseUpdate(e, new 
ArrayBuffer) += index
               }
+              pendingTaskSetToAddTo.forHost.getOrElseUpdate(loc.host, new 
ArrayBuffer) += index
               logInfo(s"Pending task $index has a cached location at ${e.host} 
" +
                 ", where there are executors " + set.mkString(","))
             case None => logDebug(s"Pending task $index has a cached location 
at ${e.host} " +
               ", but there are no executors alive there.")
           }
-        case _ =>
+        case _: HostTaskLocation =>
+          val exe = sched.getExecutorsAliveOnHost(loc.host)
+          exe match {
+            case Some(_) =>
+              pendingTaskSetToAddTo.forHost.getOrElseUpdate(loc.host, new 
ArrayBuffer) += index
+            case _ => logDebug(s"Pending task $index has a location at 
${loc.host} " +
+              ", but there are no executors alive there.")
+          }
       }
-      pendingTaskSetToAddTo.forHost.getOrElseUpdate(loc.host, new ArrayBuffer) 
+= index

Review comment:
       @mridulm, thanks for the detailed answer, I currently avoid task pending 
by setting spark.locality.wait.node to 0. In fact a permanent pending is 
possible, if there are not many resources, spark.locality.wait.node defaults to 
3s, and all remaining resources are tried within this time range, then there is 
no chance to get to the next TaskLocality, although 
`computeValidLocalityLevels` returns [ PROCESS_LOCAL, NODE_LOCAL, ANY].
   
   While setting spark.locality.wait.node to 0 eased my production 
environment's trouble, I think it would be better to treat the TaskLocation 
special in this case, as the current code also treats the HDFSCacheTaskLocation 
special
   
https://github.com/apache/spark/blob/030de1d09f121b167aaaa8237a2807f902c1e710/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala#L262-L272
   




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