refactor: parallelize merge and partition logic with obipipeline
Introduce the `obipipeline` dependency and refactor merge and partition logic to leverage parallel execution. Update `merge_partitions` to use rayon with dynamic memory budgeting and concurrency control via a pilot run. Refactor Pass 1 to concurrently read unitigs, filter kmers through a shared `LayeredMap`, and populate the graph safely. Simplify diagnostics to report total kmer counts and replace manual flags with graph length validation.
This commit is contained in:
+50
-174
@@ -2,11 +2,8 @@ use std::collections::HashMap;
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use std::fs;
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use std::io;
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use std::path::Path;
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use std::sync::atomic::{AtomicU64, Ordering};
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use std::sync::{Arc, Mutex};
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use obisys::{MemoryBudget, Reporter, Stage, available_memory_bytes, peak_rss_bytes, progress_bar, spinner};
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use rayon::prelude::*;
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use obisys::{Reporter, Stage, progress_bar, spinner};
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use tracing::{debug, info};
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use obilayeredmap::IndexMode;
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@@ -22,10 +19,9 @@ pub use obikpartitionner::MergeMode;
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#[derive(Debug)]
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struct PartStat {
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id: usize,
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unitig_bytes: u64, // sum of unitigs.bin across remaining sources
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g_len: usize, // actual new kmers inserted into GraphDeBruijn
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exp_at_acquire: f64, // expansion factor used to size the budget reservation
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id: usize,
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unitig_bytes: u64,
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g_len: usize,
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}
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// ── main merge entry point ────────────────────────────────────────────────────
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@@ -195,122 +191,48 @@ impl KmerIndex {
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let mut order: Vec<usize> = (0..n_partitions).collect();
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order.sort_unstable_by_key(|&i| std::cmp::Reverse(partition_sizes[i]));
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// ── Sequential pilot: worst partition → seed expansion factor ─────
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const FALLBACK_EXPANSION: u64 = 4_000; // 4× in fixed-point ×1000
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// ── First partition (largest) ─────────────────────────────────────
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let worst_id = order[0];
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let worst_bytes = partition_sizes[worst_id];
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let rss_before_pilot = peak_rss_bytes();
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let worst_g_len = dst_partition
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.merge_partition(worst_id, &srcs, mode, n_dst_genomes, block_bits, &evidence)
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.map_err(OKIError::Partition)?;
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let rss_after_pilot = peak_rss_bytes();
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pb.inc(1);
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let pilot_rss = rss_after_pilot.saturating_sub(rss_before_pilot);
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let seed_expansion = if worst_bytes > 0 && pilot_rss > 0 {
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pilot_rss * 1000 / worst_bytes
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} else {
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FALLBACK_EXPANSION
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};
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info!(
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"merge_partitions: pilot partition {} — {} unitig bytes → {} new kmers, \
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RSS delta {}, expansion {:.2}×",
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worst_id, worst_bytes, worst_g_len,
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fmt_bytes(pilot_rss),
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seed_expansion as f64 / 1000.0,
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"merge_partitions: first partition {} — {} unitig bytes → {} new kmers",
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worst_id, fmt_bytes(worst_bytes), worst_g_len,
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);
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let part_stats: Arc<Mutex<Vec<PartStat>>> = Arc::new(Mutex::new({
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let mut v = Vec::with_capacity(n_partitions);
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v.push(PartStat {
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id: worst_id,
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unitig_bytes: worst_bytes,
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g_len: worst_g_len,
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exp_at_acquire: seed_expansion as f64 / 1000.0,
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});
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v
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}));
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let mut part_stats: Vec<PartStat> = Vec::with_capacity(n_partitions);
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part_stats.push(PartStat {
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id: worst_id,
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unitig_bytes: worst_bytes,
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g_len: worst_g_len,
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});
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let max_expansion = AtomicU64::new(seed_expansion);
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// ── Sequential remainder ──────────────────────────────────────────
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// One partition at a time; each partition uses an internal pipeline
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// (obipipeline) to parallelise file I/O and dst_map filtering.
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let _ = budget_fraction; // kept in signature for CLI compatibility
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for &i in &order[1..] {
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let ubytes = partition_sizes[i];
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debug!("partition {i}: start — {} unitig bytes", fmt_bytes(ubytes));
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// ── Parallel remainder under memory budget ────────────────────────
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let available = available_memory_bytes();
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let budget_bytes = (available as f64 * budget_fraction) as u64;
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let budget = Arc::new(MemoryBudget::new(budget_bytes));
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let g_len = dst_partition
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.merge_partition(i, &srcs, mode, n_dst_genomes, block_bits, &evidence)
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.map_err(OKIError::Partition)?;
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pb.inc(1);
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info!(
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"merge_partitions: available RAM {}, budget {:.0}% = {}",
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fmt_bytes(available),
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budget_fraction * 100.0,
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fmt_bytes(budget_bytes),
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);
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let errors: Vec<OKIError> = order[1..].into_par_iter()
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.filter_map(|&i| {
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let ubytes = partition_sizes[i];
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let exp = max_expansion.load(Ordering::Relaxed);
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let cost = ubytes * exp / 1000;
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budget.acquire(cost);
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debug!(
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"partition {i}: start — est. {} ({:.2}×), \
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{} workers active, {} budget remaining",
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fmt_bytes(cost),
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exp as f64 / 1000.0,
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budget.active(),
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fmt_bytes(budget.remaining()),
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);
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let result = dst_partition
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.merge_partition(i, &srcs, mode, n_dst_genomes, block_bits, &evidence);
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budget.release(cost);
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pb.inc(1);
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match result {
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Ok(g_len) => {
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let actual_exp = if ubytes > 0 {
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g_len as u64 * 16 * 1000 / ubytes
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} else {
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0
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};
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max_expansion.fetch_max(actual_exp, Ordering::Relaxed);
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debug!(
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"partition {i}: done — {} new kmers, actual {:.2}× \
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(estimated {:.2}×)",
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g_len,
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actual_exp as f64 / 1000.0,
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exp as f64 / 1000.0,
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);
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part_stats.lock().unwrap().push(PartStat {
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id: i,
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unitig_bytes: ubytes,
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g_len,
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exp_at_acquire: exp as f64 / 1000.0,
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});
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None
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}
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Err(e) => Some(OKIError::Partition(e)),
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}
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})
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.collect();
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pb.finish_and_clear();
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if let Some(e) = errors.into_iter().next() {
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return Err(e);
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debug!("partition {i}: done — {} new kmers", g_len);
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part_stats.push(PartStat { id: i, unitig_bytes: ubytes, g_len });
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}
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pb.finish_and_clear();
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// ── Diagnostic report ─────────────────────────────────────────────
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let stats = Arc::try_unwrap(part_stats).unwrap().into_inner().unwrap();
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print_merge_partition_report(
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&stats,
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available,
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budget_fraction,
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seed_expansion as f64 / 1000.0,
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max_expansion.load(Ordering::Relaxed) as f64 / 1000.0,
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budget.peak_active(),
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);
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print_merge_partition_report(&part_stats);
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rep.push(t.stop());
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}
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@@ -332,82 +254,36 @@ impl KmerIndex {
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// ── Diagnostic report ─────────────────────────────────────────────────────────
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fn print_merge_partition_report(
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stats: &[PartStat],
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available_ram: u64,
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budget_fraction: f64,
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seed_expansion: f64,
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final_expansion: f64,
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peak_active: usize,
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) {
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// Compute actual expansion per partition (skip empty partitions)
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let expansions: Vec<(usize, f64)> = stats
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.iter()
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.filter(|s| s.unitig_bytes > 0)
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.map(|s| (s.id, s.g_len as f64 * 16.0 / s.unitig_bytes as f64))
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.collect();
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fn print_merge_partition_report(stats: &[PartStat]) {
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let total_new: usize = stats.iter().map(|s| s.g_len).sum();
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let non_empty = stats.iter().filter(|s| s.unitig_bytes > 0).count();
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if expansions.is_empty() {
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if non_empty == 0 {
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info!("merge_partitions report: no data (all partitions empty)");
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return;
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}
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let mut sorted_exp: Vec<f64> = expansions.iter().map(|(_, e)| *e).collect();
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sorted_exp.sort_by(|a, b| a.partial_cmp(b).unwrap());
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let n = sorted_exp.len();
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let mean_exp = sorted_exp.iter().sum::<f64>() / n as f64;
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let median_exp = sorted_exp[n / 2];
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let max_exp = sorted_exp[n - 1];
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info!("─── merge_partitions memory report ───");
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info!("─── merge_partitions report ───");
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info!(
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" available RAM : {} budget {:.0}% = {}",
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fmt_bytes(available_ram),
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budget_fraction * 100.0,
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fmt_bytes((available_ram as f64 * budget_fraction) as u64),
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" {} partition(s) processed, {} total new kmers",
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non_empty, total_new,
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);
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info!(
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" expansion factor — seed: {:.2}× final max: {:.2}× \
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(mean: {:.2}× median: {:.2}× observed max: {:.2}×)",
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seed_expansion, final_expansion, mean_exp, median_exp, max_exp,
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);
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info!(" peak concurrent workers: {}", peak_active);
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// Histogram of actual expansion factors
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let min_e = sorted_exp[0];
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let max_e = sorted_exp[n - 1];
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let n_buckets = 8usize;
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let bucket_w = (max_e - min_e).max(0.01) / n_buckets as f64;
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let mut counts = vec![0usize; n_buckets];
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for &e in &sorted_exp {
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let b = (((e - min_e) / bucket_w) as usize).min(n_buckets - 1);
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counts[b] += 1;
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// Top 8 partitions by new-kmer count
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let mut by_new: Vec<&PartStat> = stats.iter().filter(|s| s.g_len > 0).collect();
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by_new.sort_by_key(|s| std::cmp::Reverse(s.g_len));
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if !by_new.is_empty() {
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info!(" top partitions by new kmers:");
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for s in by_new.iter().take(8) {
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info!(
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" partition {:4} : {}M new kmers ({} unitig bytes)",
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s.id,
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s.g_len / 1_000_000,
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fmt_bytes(s.unitig_bytes),
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);
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}
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}
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let max_count = *counts.iter().max().unwrap();
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info!(" expansion factor distribution ({} partitions with data):", n);
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for (i, &c) in counts.iter().enumerate() {
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let lo = min_e + i as f64 * bucket_w;
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let hi = min_e + (i + 1) as f64 * bucket_w;
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let bar = "█".repeat(if max_count > 0 { c * 30 / max_count } else { 0 });
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info!(" {:5.2}× – {:5.2}× │{:<30} {}", lo, hi, bar, c);
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}
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// Top 8 by actual expansion
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let mut by_exp: Vec<(usize, f64)> = expansions.clone();
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by_exp.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap());
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info!(" top partitions by actual expansion factor:");
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for (id, exp) in by_exp.iter().take(8) {
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let s = stats.iter().find(|s| s.id == *id).unwrap();
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info!(
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" partition {:4} : {:.2}× ({} unitigs → {}M kmers, \
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reserved at {:.2}×)",
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id, exp,
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fmt_bytes(s.unitig_bytes),
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s.g_len / 1_000_000,
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s.exp_at_acquire,
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);
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}
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info!("──────────────────────────────────────");
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info!("───────────────────────────────");
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}
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// ── helpers ───────────────────────────────────────────────────────────────────
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