[SPARK-26736][SQL] Partition pruning through nondeterministic expressions in Hive tables

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

This PR intends to improve partition pruning for nondeterministic expressions in Hive tables:

Before this PR:
```
scala> sql("""create table test(id int) partitioned by (dt string)""")
scala> sql("""select * from test where dt='20190101' and rand() < 0.5""").explain()

== Physical Plan ==
*(1) Filter ((isnotnull(dt#19) AND (dt#19 = 20190101)) AND (rand(6515336563966543616) < 0.5))
+- Scan hive default.test [id#18, dt#19], HiveTableRelation `default`.`test`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, [id#18], [dt#19], Statistics(sizeInBytes=8.0 EiB)
```
After this PR:
```
== Physical Plan ==
*(1) Filter (rand(-9163956883277176328) < 0.5)
+- Scan hive default.test [id#0, dt#1], HiveTableRelation `default`.`test`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, [id#0], [dt#1], Statistics(sizeInBytes=8.0 EiB), [isnotnull(dt#1), (dt#1 = 20190101)]
```
This PR is the rework of #24118.

### Why are the changes needed?

For better performance.

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

No.

### How was this patch tested?

Unit tests added.

Closes #27219 from maropu/SPARK-26736.

Authored-by: Takeshi Yamamuro <[email protected]>
Signed-off-by: Takeshi Yamamuro <[email protected]>

Author: maropu

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala

@@ -252,7 +252,7 @@ private[hive] trait HiveStrategies {
    */
   object HiveTableScans extends Strategy {
     def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
-      case PhysicalOperation(projectList, predicates, relation: HiveTableRelation) =>
+      case ScanOperation(projectList, predicates, relation: HiveTableRelation) =>
         // Filter out all predicates that only deal with partition keys, these are given to the
         // hive table scan operator to be used for partition pruning.
         val partitionKeyIds = AttributeSet(relation.partitionCols)