[to be discussed] Spark clustering planner should support skipping clustering groups where number of input and output file slices are same

### Feature Description

**What the feature achieves:**
Add a new clustering config, where if enabled, `org.apache.hudi.table.action.cluster.strategy.PartitionAwareClusteringPlanStrategy#buildClusteringGroupsForPartition` will not emit a clustering group if the number of input and output file slices are the same.

**Why this feature is needed:**
For our use case we use an execution class similar to `org.apache.hudi.client.clustering.run.strategy.SparkBinaryCopyClusteringExecutionStrategy` as a clustering execution class to merge smaller files together into one large file. We set `hoodie.clustering.plan.strategy.target.file.max.bytes` to the target output file size value. But there are scenarios where clustering groups with just one input & output file slice are created. For example, if a partition has these files
```
file1: 800 MB
file2: 800 MB
file3: 200 MB
```
and we cluster with target file size/clustering group size of 1 GB, then we will emit clustering groups
`([file1], 1), ([file2, file3], 2)` and we want to not execute the first group.

Adding the above config would achieve this.
We can upstream our internal implementation once we reach consensus

### User Experience

**How users will use this feature:**
- Configuration changes needed
- API changes
- Usage examples

### Hudi RFC Requirements

**RFC PR link:** (if applicable)

**Why RFC is/isn't needed:**
- Does this change public interfaces/APIs? (Yes/No)
- Does this change storage format? (Yes/No)
- Justification:

Start with org.apache.hudi.table.action.cluster.strategy.PartitionAwareClusteringPlanStrategy#buildClusteringGroupsForPartition and trace how clustering configuration reaches group creation. Review SparkBinaryCopyClusteringExecutionStrategy for the intended execution context. Done means consensus on the new configuration and API/RFC requirements, with groups skipped when input and output file-slice counts match.

Written by the indexing model from the issue text.