# Code Refinement Summary

This document summarizes the code refinements made to address observations from the code review of the `simplify-pyarrow-dataset-module` implementation.

## Changes Made

### 1. Cleanup Imports in `io.py`
**File**: `src/fsspeckit/datasets/pyarrow/io.py`

**Issue**: Duplicate imports found at lines 430-433 within the `merge()` method:
```python
import pyarrow as pa
import pyarrow.compute as pc  # Duplicate
import pyarrow.dataset as ds  # Duplicate
import pyarrow.parquet as pq  # Duplicate
```

**Resolution**: Removed the duplicate imports. The initial imports at lines 395-397 remain and are sufficient for the entire method.

**Impact**: Improved code readability and eliminated redundant import statements.

---

### 2. Formalize Deprecation of `_create_string_key_array`
**Files Modified**:
- `src/fsspeckit/datasets/pyarrow/dataset.py`
- `src/fsspeckit/datasets/pyarrow/io.py`

**Issue**: The `_create_string_key_array` function was retained as an alias for backward compatibility, but internal code should use the new naming convention (`_create_fallback_key_array`).

**Resolution**:
- Converted the alias from a simple assignment to a function that emits a `DeprecationWarning`:
  ```python
  def _create_string_key_array(*args, **kwargs):
      """Deprecated alias for _create_fallback_key_array."""
      import warnings
      warnings.warn(
          "_create_string_key_array is deprecated and will be removed in a future version. "
          "Use _create_fallback_key_array directly instead.",
          DeprecationWarning,
          stacklevel=2
      )
      return _create_fallback_key_array(*args, **kwargs)
  ```

- Replaced internal usages with `_create_fallback_key_array`:
  - `dataset.py:1380`: Changed `source_keys = _create_string_key_array(...)` to `_create_fallback_key_array(...)`
  - `dataset.py:1386`: Changed `chunk_keys = _create_string_key_array(...)` to `_create_fallback_key_array(...)`
  - `io.py:414`: Updated import to use `_create_fallback_key_array`

**Impact**:
- External callers using the old alias will receive a deprecation warning
- Internal code now consistently uses the new naming convention
- Maintains backward compatibility while signaling future removal

---

### 3. Performance Investigation: `AdaptiveKeyTracker`
**File Created**: `scripts/benchmark_adaptive_key_tracker.py`

**Issue**: The `AdaptiveKeyTracker` uses `to_pylist()` calls in loops (e.g., for key insertion and membership checks), which may be costly for very large source tables (10M+ rows).

**Resolution**: Created a comprehensive benchmark script to evaluate:
- `to_pylist()` conversion time for different dataset sizes
- `AdaptiveKeyTracker` insertion time
- Membership check performance
- Comparison with vectorized PyArrow operations

**Benchmark Features**:
- Tests with configurable row counts (default: 1M, 5M, 10M)
- Measures individual operation times (to_pylist, tracker insertion, membership checks)
- Calculates memory overhead (bytes per key)
- Optional vectorized operations benchmark for comparison

**Usage**:
```bash
# Run with default sizes (1M, 5M, 10M rows)
python scripts/benchmark_adaptive_key_tracker.py

# Run with custom sizes
python scripts/benchmark_adaptive_key_tracker.py --rows 100000 250000 500000

# Include vectorized operations comparison
python scripts/benchmark_adaptive_key_tracker.py --rows 1000000 --vectorized
```

**Status**: The benchmark script has been created but not yet executed in this environment due to PyArrow not being available. Future execution should be done in a development or CI environment with the full project dependencies installed.

**Expected Outcomes**:
- If `to_pylist()` + tracker insertion time is < 10% of total merge time for 10M rows: Acceptable performance
- If > 20%: Consider optimizing the tracker to work directly with PyArrow arrays without materializing to Python lists
- Vectorized operations benchmark will provide context on the performance gap between Python list-based and vectorized approaches

---

## Verification Checklist

- [x] Duplicate imports removed from `io.py`
- [x] Deprecation warning added to `_create_string_key_array`
- [x] Internal usages replaced with `_create_fallback_key_array`
- [x] Import updated in `io.py`
- [x] Performance benchmark script created
- [ ] Benchmark executed with PyArrow environment (pending)
- [ ] Performance analysis completed (pending benchmark execution)

---

## Next Steps

1. **Execute Benchmark**: Run the benchmark script in an environment with PyArrow installed to gather performance data.

2. **Analyze Results**: Based on benchmark results:
   - If performance is acceptable: Document findings and close the task
   - If performance is suboptimal: Create a follow-up plan to optimize `AdaptiveKeyTracker` to work directly with PyArrow arrays

3. **Documentation**: Consider adding the benchmark script to the project's test suite or CI pipeline to catch performance regressions in the future.

---

## Files Changed

| File | Lines Changed | Type |
|------|---------------|------|
| `src/fsspeckit/datasets/pyarrow/io.py` | 4 lines removed | Cleanup |
| `src/fsspeckit/datasets/pyarrow/dataset.py` | 13 lines modified | Refactor |
| `scripts/benchmark_adaptive_key_tracker.py` | 199 lines (new file) | New |
