perf!: delta-aware BnbMetric via SelectionView/compute_view

CHANGELOG.md

@@ -1,5 +1,6 @@
 # Unreleased
 
+- **Breaking:** The read-only query methods (`selected_value`, `input_weight`, `weight`, `excess` and its `rate_`/`absolute_`/`replacement_` variants, `is_target_met`/`is_target_met_with_drain`, `fee`, `drain_value`, `drain`, `effective_value`, `waste`, `is_selection_possible`) move off `CoinSelector` onto the new public `SelectionView`, obtained via `CoinSelector::compute_view()` (e.g. `cs.excess(..)` becomes `cs.compute_view().excess(..)`). `is_selection_possible` is renamed to `SelectionView::is_target_reachable`. `BnbMetric::{score, bound, drain}` now receive `&SelectionView` instead of `&CoinSelector`. During branch-and-bound the view's running aggregates are maintained incrementally (delta-aware), so metric evaluation is O(1) per query instead of O(|selected|) — a large speedup at scale.
 - **Breaking:** `BnbMetric`'s `score`, `bound`, and `drain` take the `target: Target` as a parameter, and `CoinSelector::run_bnb`/`bnb_solutions` gain a leading `target` argument. Consequently `LowestFee` and `Changeless` no longer store a `target` field. This removes the target that `Changeless<M>` previously had to keep in sync with its inner metric, and aligns the metric API with the rest of `CoinSelector`, where `target` is always passed in.
 - **Breaking:** `BnbMetric` metrics now decide the change output themselves. The trait gains a `drain(&mut self, cs) -> Drain` method; call it on a branch-and-bound solution (or the `LowestFee` metric directly) to get the change output the metric optimized against, instead of computing a separate `ChangePolicy`.
 - **Breaking:** `CoinSelector::run_bnb` now returns `(Ordf32, Drain)` instead of just `Ordf32`, handing back the change output the metric decided on for the winning selection.

Cargo.toml

@@ -29,3 +29,8 @@ criterion = "0.5"
 [[bench]]
 name = "coin_selector"
 harness = false
+
+# Enable debug symbols so profilers (perf, samply, flamegraph) can resolve
+# function names. No runtime cost.
+[profile.bench]
+debug = true

README.md

@@ -55,10 +55,10 @@ let candidates = vec![
 let mut coin_selector = CoinSelector::new(&candidates);
 coin_selector.select(0);
 
-assert!(!coin_selector.is_target_met(target), "we didn't select enough");
-println!("we didn't select enough yet we're missing: {}", coin_selector.missing(target));
+assert!(!coin_selector.compute_view().is_target_met(target), "we didn't select enough");
+println!("we didn't select enough yet we're missing: {}", coin_selector.compute_view().missing(target));
 coin_selector.select(1);
-assert!(coin_selector.is_target_met(target), "we should have enough now");
+assert!(coin_selector.compute_view().is_target_met(target), "we should have enough now");
 
 // Now we need to know if we need a change output to drain the excess if we overshot too much
 //
@@ -67,7 +67,7 @@ assert!(coin_selector.is_target_met(target), "we should have enough now");
 let drain_weights = DrainWeights::TR_KEYSPEND; 
 // Our policy is to only add a change output if the value is over 1_000 sats
 let change_policy = ChangePolicy::min_value(drain_weights, 1_000);
-let change = coin_selector.drain(target, change_policy);
+let change = coin_selector.compute_view().drain(target, change_policy);
 if change.is_some() {
     println!("We need to add our change output to the transaction with {} value", change.value);
 } else {
@@ -153,7 +153,7 @@ let change = match coin_selector.run_bnb(target, metric, 100_000) {
         // fall back to naive selection
         coin_selector.select_until_target_met(target).expect("a selection was impossible!");
         // the metric still decides the change output for whatever we end up selecting
-        metric.drain(&coin_selector, target)
+        metric.drain(&coin_selector.compute_view(), target)
     }
     Ok((score, change)) => {
         println!("we found a solution with score {}", score);

benches/coin_selector.rs

@@ -1,10 +1,20 @@
 //! Benchmarks for `CoinSelector`.
 //!
-//! Two groups:
-//! - `clone`: direct cost of `CoinSelector::clone()`, the operation `Bitset`
-//!   was introduced to make cheap.
-//! - `run_bnb_lowest_fee`: end-to-end Branch-and-Bound throughput on a
-//!   deterministic synthetic pool using the `LowestFee` metric.
+//! Groups:
+//! - `new`: cost of `CoinSelector::new(candidates)` — allocations grow with
+//!   the candidate pool size. Bounds the cost of standing up a selector.
+//! - `clone`: cost of `CoinSelector::clone()`. The per-branch cost of BnB
+//!   exploration is dominated by this.
+//! - `compute_view`: cost of `CoinSelector::compute_view()` — walks the
+//!   selected bitset to build the cached aggregates. Scales with |selected|.
+//! - `run_bnb_lowest_fee`: end-to-end BnB throughput on a deterministic
+//!   synthetic pool using the `LowestFee` metric. BnB's search space is
+//!   exponential in pool size, so this caps at moderate `n` (BnB at 10M
+//!   candidates would take eons; real callers pre-filter / pre-group).
+//!
+//! Pool sizes target the spectrum from wallets (~1k UTXOs) to exchanges
+//! (~10M UTXOs). At the high end, this allocates hundreds of MB — adjust the
+//! `LARGE_N` list if your machine can't fit.
 //!
 //! Run with `cargo bench`. Filter with `cargo bench -- <pattern>`.
 
@@ -15,6 +25,14 @@ use bdk_coin_select::{
 use criterion::{criterion_group, criterion_main, BatchSize, BenchmarkId, Criterion};
 use std::hint::black_box;
 
+/// Pool sizes for the O(n)-ish operations (new, clone, compute_view).
+///
+/// 1_024 ~ typical wallet, 1_048_576 ~ small exchange, 10_000_000 ~ very large
+/// exchange. The 10M case allocates ~320MB just for the `Candidate` slice and
+/// ~80MB for the selector's `candidate_order`; comment out if running on a
+/// memory-constrained host.
+const LARGE_N: &[usize] = &[64, 1_024, 16_384, 262_144, 1_048_576, 10_000_000];
+
 /// Deterministic synthetic pool of P2WPKH-shaped UTXOs.
 ///
 /// Values grow super-linearly so the pool resembles a real wallet's mix of
@@ -24,7 +42,7 @@ fn make_candidates(n: usize) -> Vec<Candidate> {
     (0..n)
         .map(|i| {
             let i = i as u64;
-            let value = 1_000 + i * 137 + i * i;
+            let value = 1_000 + i.wrapping_mul(137).wrapping_add(i.wrapping_mul(i));
             Candidate {
                 value,
                 weight: TXIN_BASE_WEIGHT + P2WPKH_SAT_W,
@@ -46,27 +64,72 @@ fn make_bnb_inputs(candidates: &[Candidate]) -> (Target, FeeRate) {
     (target, long_term_fr)
 }
 
+/// Number of selected candidates to use as a representative "sparse"
+/// selection (real wallets/exchanges typically select 1–100 UTXOs even from a
+/// huge pool).
+const SPARSE_SELECTED: usize = 100;
+
+fn select_sparse(selector: &mut CoinSelector<'_>, n: usize) {
+    let count = SPARSE_SELECTED.min(n);
+    if count == 0 {
+        return;
+    }
+    let stride = (n / count).max(1);
+    for i in (0..n).step_by(stride).take(count) {
+        selector.select(i);
+    }
+}
+
+fn bench_new(c: &mut Criterion) {
+    let mut group = c.benchmark_group("new");
+    group.sample_size(20);
+    for &n in LARGE_N {
+        let candidates = make_candidates(n);
+        group.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, _| {
+            b.iter(|| black_box(CoinSelector::new(&candidates)));
+        });
+    }
+    group.finish();
+}
+
 fn bench_coin_selector_clone(c: &mut Criterion) {
     let mut group = c.benchmark_group("clone");
-    for &n in &[64usize, 256, 1024, 4096] {
+    group.sample_size(20);
+    for &n in LARGE_N {
         let candidates = make_candidates(n);
         let mut selector = CoinSelector::new(&candidates);
-        // Select ~10% of candidates so `selected` is non-trivial to copy.
-        for i in (0..n).step_by(10) {
-            selector.select(i);
-        }
+        select_sparse(&mut selector, n);
         group.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, _| {
             b.iter(|| black_box(selector.clone()));
         });
     }
     group.finish();
 }
 
+fn bench_compute_view(c: &mut Criterion) {
+    let mut group = c.benchmark_group("compute_view");
+    group.sample_size(20);
+    for &n in LARGE_N {
+        let candidates = make_candidates(n);
+        let mut selector = CoinSelector::new(&candidates);
+        select_sparse(&mut selector, n);
+        group.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, _| {
+            b.iter(|| {
+                let view = selector.compute_view();
+                black_box(view.selected_value())
+            });
+        });
+    }
+    group.finish();
+}
+
 fn bench_run_bnb_lowest_fee(c: &mut Criterion) {
     let mut group = c.benchmark_group("run_bnb_lowest_fee");
-    // Cap iterations so the largest case fits in a benchmark sample.
-    group.sample_size(20);
-    for &n in &[20usize, 50, 100, 200] {
+    // BnB's search space is exponential. Capping `max_rounds` at 100k bounds
+    // the per-sample cost, but for large `n` we hit that cap and the work
+    // per round itself scales with the depth of the search tree.
+    group.sample_size(10);
+    for &n in &[20usize, 50, 100, 200, 500, 1000] {
         let candidates = make_candidates(n);
         let selector = CoinSelector::new(&candidates);
         let (target, long_term_feerate) = make_bnb_inputs(&candidates);
@@ -89,5 +152,11 @@ fn bench_run_bnb_lowest_fee(c: &mut Criterion) {
     group.finish();
 }
 
-criterion_group!(benches, bench_coin_selector_clone, bench_run_bnb_lowest_fee);
+criterion_group!(
+    benches,
+    bench_new,
+    bench_coin_selector_clone,
+    bench_compute_view,
+    bench_run_bnb_lowest_fee
+);
 criterion_main!(benches);