[VL][Delta] Track native Delta writer improvements and optimization support

## Goal

Track Delta-only work to improve native Gluten/Velox support for Delta writer and table optimization paths.

This issue is organized by feature-sized work areas. Each top-level task should map to one reviewable PR or a small stack of tightly related PRs.

## Related Work

- [x] #11419 Delta write native statistics tracker to eliminate C2R overhead
- [ ] #12016 Delta native partitioned layout accounting
- [ ] #12024 Delta OPTIMIZE compaction command transaction offload

## Feature Tracks

- [ ] **OPTIMIZE Compaction**

Native support for Delta `OPTIMIZE` compaction/bin-packing command paths.

Scope:

- offload `OPTIMIZE` command transactions through GlutenOptimisticTransaction
- cover path-based and table-name `OPTIMIZE` forms
- cover `OPTIMIZE ... WHERE` partition predicates
- keep OPTIMIZE read/shuffle/write native where supported
- validate returned OPTIMIZE metrics and file statistics
- benchmark compaction on small-file Delta tables

Related PR:

- #12024 Delta OPTIMIZE compaction command transaction offload

Expected coverage:

- path-based `OPTIMIZE`
- table-name `OPTIMIZE`
- `OPTIMIZE ... WHERE partition_predicate`
- native-write-disabled fallback
- data correctness before and after compaction
- Delta log add/remove-file metadata correctness

- [ ] **Optimized Write**

Native support and correctness hardening for Delta optimized write paths.

Scope:

- verify native behavior when `delta.autoOptimize.optimizeWrite` is enabled
- verify native behavior when `spark.databricks.delta.optimizeWrite.enabled` is enabled
- verify DataFrameWriter option `optimizeWrite` behavior
- cover non-partitioned optimized writes
- cover partitioned optimized writes
- validate output file sizing and partition layout metadata
- reduce unnecessary columnar-to-row transitions in write, stats, and commit paths

Related PRs:

- #11419 native Delta write statistics tracker
- #12016 native partitioned layout accounting

Expected coverage:

- non-partitioned append and overwrite
- partitioned append and overwrite
- optimized-write table property, SQL conf, and writer option
- partition values in add-file metadata
- min/max/nullCount stats in add-file metadata
- native and fallback plan assertions

- [ ] **OPTIMIZE ZORDER**

Native support for Delta ZORDER layout operations.

Scope:

- add native support for Delta ZORDER expressions such as `InterleaveBits`
- add native support for `RangePartitionId`
- keep ZORDER read/shuffle/sort/write native where supported
- improve fallback diagnostics when ZORDER cannot stay native
- validate ZORDER output correctness and Delta log metadata
- benchmark ZORDER on larger Delta layout workloads

Expected coverage:

- `OPTIMIZE ... ZORDER BY (...)`
- `OPTIMIZE ... WHERE ... ZORDER BY (...)`
- single-column and multi-column ZORDER
- native expression coverage for ZORDER planning
- data correctness and Delta log metadata after ZORDER

- [ ] **Data Skipping Stats**

Correctness coverage for Delta data-skipping metadata generated by native write and optimization paths.

Scope:

- verify native Delta writes preserve min/max/nullCount stats
- verify stats behavior with partition columns
- verify stats behavior with `delta.dataSkippingNumIndexedCols`
- verify stats remain usable after native writes, optimized writes, and OPTIMIZE

Expected coverage:

- stats in Delta add-file JSON
- partitioned and non-partitioned tables
- columns inside and outside the indexed stats range
- queries that rely on data skipping after native writes

- [ ] **Auto Compaction**

Native behavior and correctness coverage for Delta auto compaction after successful writes.

Scope:

- investigate whether post-commit auto compaction runs through native write paths
- cover table property `delta.autoOptimize.autoCompact`
- cover session config `spark.databricks.delta.autoCompact.enabled`
- validate partition selection, file stats, and commit metadata after auto compaction

Expected coverage:

- auto compaction on non-partitioned tables
- auto compaction on partitioned tables
- minimum-file threshold behavior
- native/fallback diagnostics for post-commit compaction work

- [ ] **Delta Checkpoints And Log Compaction**

Evaluate whether there is meaningful Gluten/Velox execution work in Delta checkpoint and log compaction paths.

Scope:

- evaluate Delta multi-part checkpoint write paths
- evaluate Delta log compaction paths
- only open implementation PRs if there is execution work beyond Delta log metadata handling

Expected coverage:

- clear investigation result
- follow-up issue or PR only if native execution can add value

- [ ] **Performance And Diagnostics**

Benchmark and explain remaining overhead after native execution improvements.

Scope:

- profile stage time for native execution versus Delta planning/log/listing/commit overhead
- benchmark non-partitioned Delta writes
- benchmark partitioned Delta writes
- benchmark Delta optimized writes
- benchmark Delta OPTIMIZE compaction
- benchmark Delta OPTIMIZE ZORDER after native ZORDER expression support lands
- use larger Delta datasets where write volume dominates fixed planning and commit overhead

Expected coverage:

- before/after numbers for each feature track
- stage-level breakdown when native speedup is hidden by fixed overhead
- clear fallback diagnostics for unsupported pieces

## Boundaries

- Keep each PR reviewable and focused
- Prefer correctness tests before benchmark-only changes
- Split command offload, native expression support, metadata correctness, and benchmark work into separate patches where practical

Start by choosing one feature track and reading its related issues, especially #12016, #12024, and #11419. Narrow the work to a focused implementation or investigation; done means a reviewable PR with the stated correctness coverage, fallback behavior, or benchmark results for that track.

Written by the indexing model from the issue text.