Push zkspuxlpumpw #27

Merged
coissac merged 2 commits from push-zkspuxlpumpw into main 2026-06-13 11:25:12 +00:00
6 changed files with 437 additions and 46 deletions
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- [Project domain](project_domain.md) — obikmer est pour la génomique (génomes individuels), pas la métagénomique - [Project domain](project_domain.md) — obikmer est pour la génomique (génomes individuels), pas la métagénomique
- [No architectural decisions without authorization](feedback_architectural_decisions.md) — toute décision architecturale (mémoire, algo, structure) requiert l'accord explicite de l'utilisateur avant toute action - [No architectural decisions without authorization](feedback_architectural_decisions.md) — toute décision architecturale (mémoire, algo, structure) requiert l'accord explicite de l'utilisateur avant toute action
- [Phases intra-partition parallèles](feedback_phases_parallelism.md) — graph build, compute_degrees, unitig traversal, MPHF utilisent Rayon — ne jamais les appeler "séquentielles"
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---
name: feedback-phases-parallelism
description: Les phases intra-partition (graph build, compute_degrees, unitig traversal, MPHF) utilisent toutes Rayon — elles ne sont PAS séquentielles
metadata:
type: feedback
---
Ne jamais qualifier les phases intra-partition de "séquentielles". Chaque phase (graph build, compute_degrees, unitig traversal, MPHF build) utilise Rayon en interne et s'exécute en parallèle sur plusieurs cœurs.
**Why:** L'utilisateur a corrigé ce point plusieurs fois. Le décrire comme "séquentiel" est une erreur factuelle qui fausse l'analyse de performance.
**How to apply:** Quand on analyse l'efficacité CPU ou les 25% manquants, chercher la cause dans le déséquilibre de charge entre partitions, la contention Rayon entre workers, ou la latence inter-partitions — pas dans une prétendue sérialisation des phases.
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#!/usr/bin/env python3
"""Parse obikmer merge debug log → Markdown performance report."""
import re
import sys
from datetime import datetime
from collections import defaultdict
from statistics import mean, median, stdev
ANSI = re.compile(r'\x1b\[[0-9;]*m')
def strip(s):
return ANSI.sub('', s)
def parse_ts(s):
return datetime.fromisoformat(s.replace('Z', '+00:00'))
def dur_s(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1e3
if s.endswith('µs'): return float(s[:-2]) / 1e6
if s.endswith('us'): return float(s[:-2]) / 1e6
if s.endswith('ns'): return float(s[:-2]) / 1e9
if s.endswith('s'): return float(s[:-1])
return float(s)
def fmt_s(s):
if s < 0.001: return f"{s*1e6:.0f}µs"
if s < 1: return f"{s*1e3:.0f}ms"
if s < 60: return f"{s:.2f}s"
return f"{s/60:.1f}min ({s:.0f}s)"
def fmt_rate(n, s):
if s <= 0: return ""
r = n / s
if r >= 1e9: return f"{r/1e9:.2f}G/s"
if r >= 1e6: return f"{r/1e6:.2f}M/s"
if r >= 1e3: return f"{r/1e3:.2f}K/s"
return f"{r:.0f}/s"
def pct(a, b):
return f"{100*a/b:.1f}%" if b else ""
def stats_row(label, values, unit="s", fmt=fmt_s):
if not values: return f"| {label} | — | — | — | — | — |"
mn, mx, med, av = min(values), max(values), median(values), mean(values)
sd = stdev(values) if len(values) > 1 else 0
return f"| {label} | {fmt(mn)} | {fmt(med)} | {fmt(av)} | {fmt(mx)} | {fmt(sd)} |"
# ── patterns ──────────────────────────────────────────────────────────────────
TS = r'(\d{4}-\d{2}-\d{2}T[\d:.]+Z)'
pats = {
'graph_done': re.compile(TS + r'.*partition (\d+): de Bruijn graph done — (\d+) new kmers'),
'trav_start': re.compile(TS + r'.*partition (\d+): unitig traversal start — (\d+) nodes'),
'trav_closing': re.compile(TS + r'.*partition (\d+): unitig writer closing'),
'trav_closed': re.compile(TS + r'.*partition (\d+): unitig writer closed'),
'graph_dropped': re.compile(TS + r'.*partition (\d+): graph dropped — starting MPHF build \((\d+) unitigs\)'),
'mphf_done': re.compile(TS + r'.*partition (\d+): MPHF build done'),
'mphf_open': re.compile(TS + r'.*partition (\d+): MPHF open in ([\d.]+)s'),
'bld_ready': re.compile(TS + r'.*partition (\d+): builders ready in ([\d.]+)s'),
'pass2_done': re.compile(TS + r'.*partition (\d+): pass2 pipeline done in ([\d.]+)s'),
'bld_closed': re.compile(TS + r'.*partition (\d+): builders closed in ([\d.]+)s'),
'part_done': re.compile(TS + r'.*partition (\d+): done in ([\d.]+)s — (\d+) new kmers'),
'worker': re.compile(TS + r'.*activated worker (\d+).*efficiency (\d+)%.*gain vs prev (\d+)%'),
'worker_poll': re.compile(TS + r'.*activated worker (\d+) \(poll\).*efficiency (\d+)%'),
'compute_deg': re.compile(TS + r'.*partition (\d+): compute_degrees in ([\d.]+)s — (\d+) nodes'),
'stage_done': re.compile(TS + r'.*done stage=merge_partitions wall_secs=([\d.]+)'),
'workers_rep': re.compile(r'workers spawned: (\d+) / (\d+)'),
}
# ── parse ─────────────────────────────────────────────────────────────────────
P = defaultdict(dict) # partition_id → timing dict
workers_ev = []
wall_total = None
workers_final = (None, None)
with open(sys.argv[1]) as f:
for raw in f:
line = strip(raw)
m = pats['graph_done'].search(line)
if m:
pid = int(m.group(2))
P[pid]['n_kmers'] = int(m.group(3))
P[pid]['graph_done_ts'] = parse_ts(m.group(1))
continue
m = pats['trav_start'].search(line)
if m:
pid = int(m.group(2))
P[pid]['trav_start_ts'] = parse_ts(m.group(1))
P[pid]['n_nodes'] = int(m.group(3))
continue
m = pats['trav_closing'].search(line)
if m:
pid = int(m.group(2))
P[pid]['trav_closing_ts'] = parse_ts(m.group(1))
continue
m = pats['trav_closed'].search(line)
if m:
pid = int(m.group(2))
P[pid]['trav_closed_ts'] = parse_ts(m.group(1))
continue
m = pats['graph_dropped'].search(line)
if m:
pid = int(m.group(2))
P[pid]['drop_ts'] = parse_ts(m.group(1))
P[pid]['n_unitigs'] = int(m.group(3))
continue
m = pats['mphf_done'].search(line)
if m:
pid = int(m.group(2))
P[pid]['mphf_done_ts'] = parse_ts(m.group(1))
continue
m = pats['mphf_open'].search(line)
if m:
pid = int(m.group(2))
P[pid]['mphf_open_s'] = float(m.group(3))
continue
m = pats['bld_ready'].search(line)
if m:
pid = int(m.group(2))
P[pid]['bld_ready_s'] = float(m.group(3))
continue
m = pats['pass2_done'].search(line)
if m:
pid = int(m.group(2))
P[pid]['pass2_s'] = float(m.group(3))
continue
m = pats['bld_closed'].search(line)
if m:
pid = int(m.group(2))
P[pid]['bld_closed_s'] = float(m.group(3))
continue
m = pats['part_done'].search(line)
if m:
pid = int(m.group(2))
P[pid]['total_s'] = float(m.group(3))
P[pid]['done_ts'] = parse_ts(m.group(1))
continue
m = pats['worker'].search(line)
if m:
workers_ev.append({'n': int(m.group(2)), 'eff': int(m.group(3)),
'gain': int(m.group(4)), 'ts': parse_ts(m.group(1)), 'poll': False})
continue
m = pats['worker_poll'].search(line)
if m:
workers_ev.append({'n': int(m.group(2)), 'eff': int(m.group(3)),
'gain': None, 'ts': parse_ts(m.group(1)), 'poll': True})
continue
m = pats['compute_deg'].search(line)
if m:
pid = int(m.group(2))
P[pid]['cdeg_s'] = float(m.group(3))
P[pid]['n_nodes'] = P[pid].get('n_nodes') or int(m.group(4))
continue
m = pats['stage_done'].search(line)
if m:
wall_total = float(m.group(2))
continue
m = pats['workers_rep'].search(line)
if m:
workers_final = (int(m.group(1)), int(m.group(2)))
continue
# ── derive per-partition phases ───────────────────────────────────────────────
def tsdiff(p, k1, k2):
if k1 in p and k2 in p:
return (p[k2] - p[k1]).total_seconds()
return None
phases = {}
for pid, p in P.items():
row = {'pid': pid}
row['n_kmers'] = p.get('n_kmers', 0)
row['n_nodes'] = p.get('n_nodes', 0)
row['n_unitigs']= p.get('n_unitigs', 0)
row['total_s'] = p.get('total_s')
row['cdeg_s'] = p.get('cdeg_s')
row['mphf_open_s'] = p.get('mphf_open_s')
row['bld_ready_s'] = p.get('bld_ready_s')
row['pass2_s'] = p.get('pass2_s')
row['bld_closed_s'] = p.get('bld_closed_s')
# Traversal: trav_start → trav_closing (= writing all unitigs)
row['trav_s'] = tsdiff(p, 'trav_start_ts', 'trav_closing_ts')
# Writer close: trav_closing → trav_closed
row['close_s'] = tsdiff(p, 'trav_closing_ts', 'trav_closed_ts')
# Graph drop: trav_closed → drop_ts
row['drop_s'] = tsdiff(p, 'trav_closed_ts', 'drop_ts')
# MPHF build: drop_ts → mphf_done_ts
row['mphf_s'] = tsdiff(p, 'drop_ts', 'mphf_done_ts')
# After MPHF: mphf_done → done_ts
row['post_s'] = tsdiff(p, 'mphf_done_ts', 'done_ts')
# Graph build: total - known phases (rough estimate)
known = sum(v for v in [row['cdeg_s'], row['trav_s'], row['close_s'], row['drop_s'],
row['mphf_s'], row['mphf_open_s'], row['bld_ready_s'],
row['pass2_s'], row['bld_closed_s']] if v is not None)
row['graph_build_s'] = (row['total_s'] - known) if row['total_s'] else None
phases[pid] = row
# helpers
def collect(key):
return [r[key] for r in phases.values() if r.get(key) is not None]
def rate_stats(n_key, t_key):
"""Returns list of throughput values (items/s)."""
result = []
for r in phases.values():
n, t = r.get(n_key), r.get(t_key)
if n and t and t > 0:
result.append(n / t)
return result
# ── output ────────────────────────────────────────────────────────────────────
out = []
w = out.append
w("# obikmer merge — performance report\n")
# Run info
n_parts = len([r for r in phases.values() if r['n_kmers'] > 0])
n_empty = len([r for r in phases.values() if r['n_kmers'] == 0])
total_kmers = sum(r['n_kmers'] for r in phases.values())
w("## Run summary\n")
w(f"- **Partitions**: {len(phases)} total — {n_parts} non-empty, {n_empty} empty")
w(f"- **New kmers (total)**: {total_kmers:,}")
if wall_total:
w(f"- **merge_partitions wall time**: {fmt_s(wall_total)}")
if workers_final[0]:
w(f"- **Workers spawned**: {workers_final[0]} / {workers_final[1]} (max)")
w("")
# Worker spawn timeline
if workers_ev:
w("## Worker activation\n")
w("| Time | Worker # | Trigger | Efficiency | Gain vs prev |")
w("|------|----------|---------|------------|--------------|")
t0 = workers_ev[0]['ts']
for e in workers_ev:
elapsed = fmt_s((e['ts'] - t0).total_seconds())
trigger = "poll (timeout)" if e['poll'] else "partition done"
gain = f"{e['gain']}%" if e.get('gain') is not None else ""
w(f"| +{elapsed} | {e['n']} | {trigger} | {e['eff']}% | {gain} |")
w("")
# Phase breakdown table
w("## Phase timing statistics\n")
w("Columns: min | median | mean | max | stdev\n")
w("| Phase | min | median | mean | max | stdev |")
w("|-------|-----|--------|------|-----|-------|")
w(stats_row("Graph build (estimated)", collect('graph_build_s')))
w(stats_row("compute_degrees", collect('cdeg_s')))
w(stats_row("Unitig traversal", collect('trav_s')))
w(stats_row("Writer close (uw.close)", collect('close_s')))
w(stats_row("Graph drop", collect('drop_s')))
w(stats_row("MPHF build", collect('mphf_s')))
w(stats_row("MPHF open", collect('mphf_open_s')))
w(stats_row("Builders ready", collect('bld_ready_s')))
w(stats_row("Pass2 pipeline", collect('pass2_s')))
w(stats_row("Builders close", collect('bld_closed_s')))
w(stats_row("Post-MPHF (residual)", collect('post_s')))
w(stats_row("**Total per partition**", collect('total_s')))
w("")
# Throughput
w("## Throughput by phase\n")
w("| Phase | metric | min | median | mean | max |")
w("|-------|--------|-----|--------|------|-----|")
def rate_row(label, rates):
if not rates: return f"| {label} | — | — | — | — | — |"
f = lambda x: fmt_rate(x, 1)
mn, med, av, mx = min(rates), median(rates), mean(rates), max(rates)
return f"| {label} | nodes/s | {f(mn)} | {f(med)} | {f(av)} | {f(mx)} |"
w(rate_row("compute_degrees", rate_stats('n_nodes', 'cdeg_s')))
w(rate_row("Unitig traversal", rate_stats('n_nodes', 'trav_s')))
w(rate_row("MPHF build", rate_stats('n_unitigs', 'mphf_s')))
w("")
# Top 10 slowest partitions
w("## Top 10 slowest partitions\n")
w("| Partition | nodes | unitigs | total | trav | MPHF | graph build |")
w("|-----------|-------|---------|-------|------|------|-------------|")
sorted_parts = sorted(phases.values(), key=lambda r: r['total_s'] or 0, reverse=True)
for r in sorted_parts[:10]:
pid = r['pid']
def f(k): return fmt_s(r[k]) if r.get(k) is not None else ""
nodes = f"{r['n_nodes']/1e6:.1f}M" if r['n_nodes'] else ""
unitigs = f"{r['n_unitigs']/1e6:.1f}M" if r['n_unitigs'] else ""
w(f"| {pid} | {nodes} | {unitigs} | {f('total_s')} | {f('trav_s')} | {f('mphf_s')} | {f('graph_build_s')} |")
w("")
# Phase share of total time (for non-empty partitions with full data)
complete = [r for r in phases.values()
if all(r.get(k) is not None
for k in ('total_s','trav_s','close_s','drop_s','mphf_s',
'mphf_open_s','bld_ready_s','pass2_s','bld_closed_s'))
and r['total_s'] and r['total_s'] > 0]
if complete:
w("## Phase share of total time (mean across complete partitions)\n")
total_mean = mean(r['total_s'] for r in complete)
w(f"_Based on {len(complete)} partitions with full timing data. Mean total: {fmt_s(total_mean)}_\n")
w("| Phase | mean time | share |")
w("|-------|-----------|-------|")
for label, key in [
("Graph build", 'graph_build_s'),
("compute_degrees", 'cdeg_s'),
("Unitig traversal", 'trav_s'),
("Writer close", 'close_s'),
("Graph drop", 'drop_s'),
("MPHF build", 'mphf_s'),
("MPHF open", 'mphf_open_s'),
("Builders ready", 'bld_ready_s'),
("Pass2 pipeline", 'pass2_s'),
("Builders close", 'bld_closed_s'),
("Post-MPHF (residual)", 'post_s'),
]:
vals = [r[key] for r in complete]
m = mean(vals)
w(f"| {label} | {fmt_s(m)} | {pct(m, total_mean)} |")
w("")
print('\n'.join(out))
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@@ -7,8 +7,6 @@ use rayon::iter::{IntoParallelRefIterator, ParallelIterator};
use std::cell::RefCell; use std::cell::RefCell;
use std::fmt; use std::fmt;
use std::sync::atomic::{AtomicU8, Ordering}; use std::sync::atomic::{AtomicU8, Ordering};
use std::time::Instant;
use tracing::{debug, info};
use xxhash_rust::xxh3::Xxh3Builder; use xxhash_rust::xxh3::Xxh3Builder;
// ── Types ───────────────────────────────────────────────────────────────────── // ── Types ─────────────────────────────────────────────────────────────────────
@@ -285,7 +283,6 @@ impl GraphDeBruijn {
pub fn compute_degrees_and_mark_starts(&self) { pub fn compute_degrees_and_mark_starts(&self) {
// Pass 1: count right/left neighbors for each node // Pass 1: count right/left neighbors for each node
let t1 = Instant::now();
self.for_each_node(|kmer, atomic| { self.for_each_node(|kmer, atomic| {
let mut old = Node(atomic.load(Ordering::Relaxed)); let mut old = Node(atomic.load(Ordering::Relaxed));
if old.is_visited() { if old.is_visited() {
@@ -295,20 +292,13 @@ impl GraphDeBruijn {
} }
let (rc, rn) = count_neighbors(&kmer.right_canonical_neighbors(), &self.nodes); let (rc, rn) = count_neighbors(&kmer.right_canonical_neighbors(), &self.nodes);
let (lc, ln) = count_neighbors(&kmer.left_canonical_neighbors(), &self.nodes); let (lc, ln) = count_neighbors(&kmer.left_canonical_neighbors(), &self.nodes);
let mut node = Node(0); // reset all bits (visited=0, start=0) let mut node = Node(0);
node.set_right(rc, rn); node.set_right(rc, rn);
node.set_left(lc, ln); node.set_left(lc, ln);
atomic.store(node.0, Ordering::Relaxed); atomic.store(node.0, Ordering::Relaxed);
}); });
debug!(
"[compute_degrees] pass 1 (degrees): {:?} — {} nodes",
t1.elapsed(),
self.nodes.len()
);
// Pass 2: mark start nodes // Pass 2: mark start nodes
let t2 = Instant::now();
self.for_each_node(|kmer, atomic| { self.for_each_node(|kmer, atomic| {
let mut node = Node(atomic.load(Ordering::Relaxed)); let mut node = Node(atomic.load(Ordering::Relaxed));
if node.is_visited() { if node.is_visited() {
@@ -319,11 +309,6 @@ impl GraphDeBruijn {
atomic.store(node.0, Ordering::Relaxed); atomic.store(node.0, Ordering::Relaxed);
} }
}); });
debug!(
"[compute_degrees] pass 2 (starts): {:?} — {} nodes",
t2.elapsed(),
self.nodes.len()
);
} }
pub fn is_visited(&self, kmer: &CanonicalKmer) -> Option<bool> { pub fn is_visited(&self, kmer: &CanonicalKmer) -> Option<bool> {
@@ -391,7 +376,6 @@ impl GraphDeBruijn {
let n2 = std::sync::atomic::AtomicUsize::new(0); let n2 = std::sync::atomic::AtomicUsize::new(0);
// Boucle unique : traiter les starts, recalculer les arités, recommencer // Boucle unique : traiter les starts, recalculer les arités, recommencer
let mut pass = 0usize;
loop { loop {
let n_new = std::sync::atomic::AtomicUsize::new(0); let n_new = std::sync::atomic::AtomicUsize::new(0);
@@ -421,9 +405,7 @@ impl GraphDeBruijn {
}); });
let n = n_new.load(Ordering::Relaxed); let n = n_new.load(Ordering::Relaxed);
debug!("[for_each_unitig] pass {}: {} starts", pass, n);
n_chains.fetch_add(n, Ordering::Relaxed); n_chains.fetch_add(n, Ordering::Relaxed);
pass += 1;
if n == 0 { if n == 0 {
break; break;
} }
@@ -452,12 +434,6 @@ impl GraphDeBruijn {
} }
} }
debug!(
chains = n_chains.load(Ordering::Relaxed),
phase2 = n2.load(Ordering::Relaxed),
total = n_chains.load(Ordering::Relaxed) + n2.load(Ordering::Relaxed),
"unitig traversal complete"
);
} }
/// Merge `other` into `self`. /// Merge `other` into `self`.
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@@ -289,14 +289,39 @@ impl KmerIndex {
activate_tx.send(()).ok(); activate_tx.send(()).ok();
n_workers = 1; n_workers = 1;
const SPAWN_POLL: Duration = Duration::from_secs(10);
let mut completed = 0usize; let mut completed = 0usize;
while completed < n_partitions { while completed < n_partitions {
let (i, r, dur) = result_rx.recv().map_err(|_| { let result = result_rx.recv_timeout(SPAWN_POLL);
OKIError::Io(io::Error::new(
io::ErrorKind::UnexpectedEof, // On timeout: no partition finished yet, just check efficiency.
"worker channel closed", let (i, r, dur) = match result {
)) Ok(v) => v,
})?; Err(crossbeam_channel::RecvTimeoutError::Timeout) => {
if n_workers < max_workers {
let eff = cpu_sample.cpu_efficiency(n_cores);
if eff < SPAWN_THRESHOLD {
debug!(
"activated worker {} (poll) — efficiency {:.0}%",
n_workers + 1,
eff * 100.0,
);
efficiency_at_last_spawn = eff;
activate_tx.send(()).ok();
n_workers += 1;
cpu_sample = CpuSample::now();
}
}
continue;
}
Err(crossbeam_channel::RecvTimeoutError::Disconnected) => {
return Err(OKIError::Io(io::Error::new(
io::ErrorKind::UnexpectedEof,
"worker channel closed",
)));
}
};
let g_len = r.map_err(OKIError::Partition)?; let g_len = r.map_err(OKIError::Partition)?;
pb.inc(1); pb.inc(1);
debug!( debug!(
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@@ -304,27 +304,37 @@ impl KmerPartition {
let new_layer_dir = dst_index_dir.join(format!("layer_{new_layer_idx}")); let new_layer_dir = dst_index_dir.join(format!("layer_{new_layer_idx}"));
let n_new = if any_new { let n_new = if any_new {
let t_deg = std::time::Instant::now();
g.compute_degrees_and_mark_starts(); g.compute_degrees_and_mark_starts();
debug!("partition {i}: compute_degrees in {:.3}s — {} nodes",
t_deg.elapsed().as_secs_f64(), g.len());
fs::create_dir_all(&new_layer_dir)?; fs::create_dir_all(&new_layer_dir)?;
let mut uw = Layer::<()>::unitig_writer(&new_layer_dir).map_err(olm_to_sk)?; let mut uw = Layer::<()>::unitig_writer(&new_layer_dir).map_err(olm_to_sk)?;
debug!("partition {i}: unitig traversal start — {} nodes", g.len());
g.try_for_each_unitig(|unitig| { g.try_for_each_unitig(|unitig| {
uw.write(unitig) uw.write(unitig)
})?; })?;
debug!("partition {i}: unitig writer closing");
uw.close()?; uw.close()?;
debug!("partition {i}: unitig writer closed — dropping graph ({} nodes)", g.len());
let n = g.len(); let n = g.len();
drop(g); // release GraphDeBruijn before MPHF build drop(g);
debug!("partition {i}: graph dropped — starting MPHF build ({n} unitigs)");
Layer::<()>::build(&new_layer_dir, block_bits, evidence).map_err(olm_to_sk)?; Layer::<()>::build(&new_layer_dir, block_bits, evidence).map_err(olm_to_sk)?;
debug!("partition {i}: MPHF build done");
n n
} else { } else {
drop(g); drop(g);
0 0
}; };
let t_open = std::time::Instant::now();
let new_mphf: Option<Arc<MphfOnly>> = if any_new { let new_mphf: Option<Arc<MphfOnly>> = if any_new {
Some(Arc::new(MphfOnly::open(&new_layer_dir).map_err(olm_to_sk)?)) Some(Arc::new(MphfOnly::open(&new_layer_dir).map_err(olm_to_sk)?))
} else { } else {
None None
}; };
debug!("partition {i}: MPHF open in {:.3}s", t_open.elapsed().as_secs_f64());
// ── Prepare matrix directories for the new layer ────────────────────── // ── Prepare matrix directories for the new layer ──────────────────────
// Absent columns (dst genomes) are written via append_column (all-zero/false). // Absent columns (dst genomes) are written via append_column (all-zero/false).
@@ -379,6 +389,7 @@ impl KmerPartition {
vec![] vec![]
}; };
let t_builders = std::time::Instant::now();
// Builders for existing layers: n_src_total per layer. // Builders for existing layers: n_src_total per layer.
// Columns n_dst_genomes .. n_dst_genomes + n_src_total - 1. // Columns n_dst_genomes .. n_dst_genomes + n_src_total - 1.
let exist_builders: Vec<Vec<ColBuilder>> = (0..n_dst_layers) let exist_builders: Vec<Vec<ColBuilder>> = (0..n_dst_layers)
@@ -410,7 +421,10 @@ impl KmerPartition {
}) })
.collect::<SKResult<_>>()?; .collect::<SKResult<_>>()?;
debug!("partition {i}: builders ready in {:.3}s", t_builders.elapsed().as_secs_f64());
// ── Pass 2: fill builders (pipeline) ───────────────────────────────── // ── Pass 2: fill builders (pipeline) ─────────────────────────────────
let t_pass2 = std::time::Instant::now();
// Collect source items before the pipeline so load_meta errors propagate // Collect source items before the pipeline so load_meta errors propagate
// via ? before any worker thread is spawned. // via ? before any worker thread is spawned.
let mut pass2_items: Vec<(usize, usize, PathBuf)> = Vec::new(); let mut pass2_items: Vec<(usize, usize, PathBuf)> = Vec::new();
@@ -439,8 +453,18 @@ impl KmerPartition {
WriteBatch(Vec<(Option<usize>, usize, usize, u32)>), WriteBatch(Vec<(Option<usize>, usize, usize, u32)>),
} }
let builders = Arc::new(Mutex::new((exist_builders, new_src_builders))); let exist_locked: Vec<Vec<Arc<Mutex<ColBuilder>>>> = exist_builders
let builders_sink = Arc::clone(&builders); .into_iter()
.map(|layer| layer.into_iter().map(|b| Arc::new(Mutex::new(b))).collect())
.collect();
let new_locked: Vec<Arc<Mutex<ColBuilder>>> = new_src_builders
.into_iter()
.map(|b| Arc::new(Mutex::new(b)))
.collect();
let exist_sink: Vec<Vec<Arc<Mutex<ColBuilder>>>> = exist_locked.iter()
.map(|layer| layer.iter().map(Arc::clone).collect())
.collect();
let new_sink: Vec<Arc<Mutex<ColBuilder>>> = new_locked.iter().map(Arc::clone).collect();
let dst_map_t2 = Arc::clone(&dst_map); let dst_map_t2 = Arc::clone(&dst_map);
let new_mphf_t2 = new_mphf.clone(); let new_mphf_t2 = new_mphf.clone();
let pass2_err: Arc<Mutex<Option<String>>> = Arc::new(Mutex::new(None)); let pass2_err: Arc<Mutex<Option<String>>> = Arc::new(Mutex::new(None));
@@ -519,11 +543,10 @@ impl KmerPartition {
], ],
make_sink!(Pass2Data, { make_sink!(Pass2Data, {
move |ops: Vec<(Option<usize>, usize, usize, u32)>| { move |ops: Vec<(Option<usize>, usize, usize, u32)>| {
let mut guard = builders_sink.lock().unwrap();
for (layer_opt, col, slot, val) in ops { for (layer_opt, col, slot, val) in ops {
match layer_opt { match layer_opt {
Some(l) => guard.0[l][col].set_val(slot, val), Some(l) => exist_sink[l][col].lock().unwrap().set_val(slot, val),
None => guard.1[col].set_val(slot, val), None => new_sink[col].lock().unwrap().set_val(slot, val),
} }
} }
} }
@@ -531,6 +554,7 @@ impl KmerPartition {
); );
WorkerPool::new(pipeline2, n_workers, capacity).run(); WorkerPool::new(pipeline2, n_workers, capacity).run();
debug!("partition {i}: pass2 pipeline done in {:.3}s", t_pass2.elapsed().as_secs_f64());
if let Some(msg) = Arc::try_unwrap(pass2_err) if let Some(msg) = Arc::try_unwrap(pass2_err)
.unwrap_or_else(|_| panic!("pass2: pass2_err not uniquely owned")) .unwrap_or_else(|_| panic!("pass2: pass2_err not uniquely owned"))
@@ -540,16 +564,16 @@ impl KmerPartition {
return Err(SKError::InvalidData { context: "merge pass2", detail: msg }); return Err(SKError::InvalidData { context: "merge pass2", detail: msg });
} }
let (exist_builders, new_src_builders) = Arc::try_unwrap(builders) let t_close = std::time::Instant::now();
.unwrap_or_else(|_| panic!("pass2: builders not uniquely owned after pipeline"))
.into_inner()
.unwrap_or_else(|e| e.into_inner());
// ── Close builders and update metadata ──────────────────────────────── // ── Close builders and update metadata ────────────────────────────────
for (l, builders) in exist_builders.into_iter().enumerate() { for (l, builders) in exist_locked.into_iter().enumerate() {
let layer_dir = dst_index_dir.join(format!("layer_{l}")); let layer_dir = dst_index_dir.join(format!("layer_{l}"));
for b in builders { for b in builders {
b.close()?; Arc::try_unwrap(b)
.unwrap_or_else(|_| panic!("pass2: exist_builder[{l}] not uniquely owned"))
.into_inner()
.unwrap_or_else(|e| e.into_inner())
.close()?;
} }
let n = dst_map.layer(l).n(); let n = dst_map.layer(l).n();
let data_dir = match mode { let data_dir = match mode {
@@ -559,8 +583,12 @@ impl KmerPartition {
write_matrix_meta(&data_dir, n, n_dst_genomes + n_src_total).map_err(SKError::Io)?; write_matrix_meta(&data_dir, n, n_dst_genomes + n_src_total).map_err(SKError::Io)?;
} }
for b in new_src_builders { for b in new_locked {
b.close()?; Arc::try_unwrap(b)
.unwrap_or_else(|_| panic!("pass2: new_builder not uniquely owned"))
.into_inner()
.unwrap_or_else(|e| e.into_inner())
.close()?;
} }
if any_new { if any_new {
let data_dir = match mode { let data_dir = match mode {
@@ -575,6 +603,8 @@ impl KmerPartition {
part_meta.save(&dst_index_dir).map_err(olm_to_sk)?; part_meta.save(&dst_index_dir).map_err(olm_to_sk)?;
} }
debug!("partition {i}: builders closed in {:.3}s", t_close.elapsed().as_secs_f64());
Ok(n_new) Ok(n_new)
} }
} }