Fengzdadi opened a new pull request, #102:
URL: https://github.com/apache/datasketches-go/pull/102
### Summary
This PR implements the core `VarOptItemsSketch[T]` for variance-optimal
weighted sampling, following the C++ and Java implementations exactly. ref #98
### Changes
#### `internal/family.go`
- Added `VarOptItems` family (ID=13, MaxPreLongs=4)
#### `sampling/varopt_items_sketch.go` (new file, ~520 lines)
- **VarOptItemsSketch[T] struct** with fields: k, n, h, m, r, totalWeightR,
data, weights
- **Update algorithm** matching C++/Java:
- Warmup mode (h ≤ k): stores all items directly
- Transition at h > k via `transitionFromWarmup()`
- `growCandidateSet()` / `downsampleCandidateSet()` for variance-optimal
sampling
- `chooseDeleteSlot()` / `chooseWeightedDeleteSlot()` for weighted random
selection
- **Min-heap operations**: `heapify()`, `siftUp()`, `siftDown()`
- **Go 1.23 iterator**: `Samples() iter.Seq2[T, float64]` for elegant range
iteration
#### `sampling/varopt_items_sketch_test.go` (new file, ~218 lines)
8 unit tests matching C++ test coverage:
- `TestVarOptItemsSketch_NewSketch` - constructor and k validation
- `TestVarOptItemsSketch_WarmupPhase` - exact mode behavior
- `TestVarOptItemsSketch_TransitionToEstimation` - h > k transition
- `TestVarOptItemsSketch_EstimationMode` - sampling mode invariants
- `TestVarOptItemsSketch_InvalidWeight` - negative/zero weight handling
- `TestVarOptItemsSketch_Reset` - reset state verification
- `TestVarOptItemsSketch_UniformWeights` - reservoir-like behavior
- `TestVarOptItemsSketch_CumulativeWeight` - weight sum preservation
(matches C++ test with `exp(5*N(0,1))` distribution and 1e-13 tolerance)
### API Usage
```go
sketch, _ := NewVarOptItemsSketch[string](256)
// Add weighted items
sketch.Update("item1", 1.5)
sketch.Update("item2", 3.0)
// Iterate samples with Go 1.23 range
for item, weight := range sketch.Samples() {
fmt.Printf("Item: %s, Weight: %f\n", item, weight)
}
```
### Note
The current implementation includes detailed comments for clarity. If the
reviewers prefer, we can simplify the comments.
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