[SPARK-49783][YARN] Fix resource leak of yarn allocator

### What changes were proposed in this pull request?

Fix the resource leak of yarn allocator

### Why are the changes needed?

When the target < running containers number, the assigned containers from the resource manager will be skipped, but these containers are not released by invoking the amClient.releaseAssignedContainer , that will make these containers reserved into the Yarn resourceManager at least 10 minutes. And so, the cluster resource will be wasted at a high ratio.

And this will reflect that the vcore * seconds statistics from yarn side will be greater than the result from the spark event logs.

From my statistics, the cluster resource waste ratio is ~25% if the spark jobs are exclusive in this cluster.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

In our internal hadoop cluster

### Was this patch authored or co-authored using generative AI tooling?

No

Closes #48238 from zuston/patch-1.

Authored-by: Junfan Zhang <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>

Author: zuston

resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala

@@ -820,6 +820,7 @@ private[yarn] class YarnAllocator(
         logInfo(log"Skip launching executorRunnable as running executors count: " +
           log"${MDC(LogKeys.COUNT, rpRunningExecs)} reached target executors count: " +
           log"${MDC(LogKeys.NUM_EXECUTOR_TARGET, getOrUpdateTargetNumExecutorsForRPId(rpId))}.")
+        internalReleaseContainer(container)
       }
     }
   }