[SPARK-45386][SQL][3.5] Fix correctness issue with persist using StorageLevel.NONE on Dataset

### What changes were proposed in this pull request?
Support for InMememoryTableScanExec in AQE was added in #39624, but this patch contained a bug when a Dataset is persisted using `StorageLevel.NONE`. Before that patch a query like:
```
import org.apache.spark.storage.StorageLevel
spark.createDataset(Seq(1, 2)).persist(StorageLevel.NONE).count()
```
would correctly return 2. But after that patch it incorrectly returns 0. This is because AQE incorrectly determines based on the runtime statistics that are collected here:
https://github.com/apache/spark/blob/eac5a8c7e6da94bb27e926fc9a681aed6582f7d3/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryRelation.scala#L294
that the input is empty. The problem is that the action that should make sure the statistics are collected here
https://github.com/apache/spark/blob/eac5a8c7e6da94bb27e926fc9a681aed6582f7d3/sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/QueryStageExec.scala#L285-L291
never use the iterator and when we have `StorageLevel.NONE` the persisting will also not use the iterator and we will not gather the correct statistics.

The proposed fix in the patch just make calling persist with StorageLevel.NONE a no-op. Changing the action since it always "emptied" the iterator would also work but seems like that would be unnecessary work in a lot of normal circumstances.

### Why are the changes needed?
The current code has a correctness issue.

### Does this PR introduce _any_ user-facing change?
Yes, fixes the correctness issue.

### How was this patch tested?
New and existing unit tests.

### Was this patch authored or co-authored using generative AI tooling?
No

Closes #43213 from eejbyfeldt/SPARK-45386-branch-3.5.

Authored-by: Emil Ejbyfeldt <eejbyfeldt@liveintent.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

Author: Emil Ejbyfeldt

sql/core/src/main/scala/org/apache/spark/sql/execution/CacheManager.scala

@@ -113,7 +113,9 @@ class CacheManager extends Logging with AdaptiveSparkPlanHelper {
       planToCache: LogicalPlan,
       tableName: Option[String],
       storageLevel: StorageLevel): Unit = {
-    if (lookupCachedData(planToCache).nonEmpty) {
+    if (storageLevel == StorageLevel.NONE) {
+      // Do nothing for StorageLevel.NONE since it will not actually cache any data.
+    } else if (lookupCachedData(planToCache).nonEmpty) {
       logWarning("Asked to cache already cached data.")
     } else {
       val sessionWithConfigsOff = getOrCloneSessionWithConfigsOff(spark)

sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala

@@ -45,6 +45,7 @@ import org.apache.spark.sql.functions._
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSparkSession
 import org.apache.spark.sql.types._
+import org.apache.spark.storage.StorageLevel
 
 case class TestDataPoint(x: Int, y: Double, s: String, t: TestDataPoint2)
 case class TestDataPoint2(x: Int, s: String)
@@ -2535,6 +2536,11 @@ class DatasetSuite extends QueryTest
 
     checkDataset(ds.filter(f(col("_1"))), Tuple1(ValueClass(2)))
   }
+
+  test("SPARK-45386: persist with StorageLevel.NONE should give correct count") {
+    val ds = Seq(1, 2).toDS().persist(StorageLevel.NONE)
+    assert(ds.count() == 2)
+  }
 }
 
 class DatasetLargeResultCollectingSuite extends QueryTest