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feat: integrate tracing and enhance bit matrix operations

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Add the `tracing` crate to `obidebruinj`, `obisys`, and resolve it in `Cargo.lock`. Replace `eprintln!` statements with structured `debug!` and `info!` macros. Introduce a `TracedBar` wrapper for progress bars and enhance the `Stage` lifecycle to emit structured events for timing, memory metrics, and swap warnings. Add a progress spinner for unitig degree computation. Extend `PersistentBitMatrix` with columnar bit-vector operations and parallel distance methods, enabling uniform distance computations across all storage layouts while replacing previous panics with dimension-based fallbacks.
This commit is contained in:
Eric Coissac
2026-06-08 19:48:17 +02:00
parent 3f47e22083
commit 09d9e21744
8 changed files with 405 additions and 41 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/Cargo.lock
Generated
+2
View File
@@ -1490,6 +1490,7 @@ dependencies = [
"obifastwrite",
"obikseq",
"rayon",
"tracing",
"xxhash-rust",
]
@@ -1666,6 +1667,7 @@ dependencies = [
"indicatif",
"libc",
"sysinfo",
"tracing",
]
[[package]]
src/obicompactvec/src/bitmatrix.rs
+126 -10
View File
@@ -163,6 +163,108 @@ impl PackedBitMatrix {
(self.mmap[self.data_offsets[c] + (slot >> 3)] >> (slot & 7)) & 1 != 0
}).collect()
}
#[inline]
fn col_bytes(&self, c: usize) -> &[u8] {
let start = self.data_offsets[c];
let len = (self.n_rows + 7) / 8;
&self.mmap[start..start + len]
}
fn count_ones_col(&self, c: usize) -> u64 {
let bytes = self.col_bytes(c);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let mut n: u64 = bytes[..full].iter().map(|b| b.count_ones() as u64).sum();
if rem > 0 { n += (bytes[full] & ((1u8 << rem) - 1)).count_ones() as u64; }
n
}
fn pair_op(&self, i: usize, j: usize, and_or: bool) -> u64 {
let ai = self.col_bytes(i);
let aj = self.col_bytes(j);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let mut n: u64 = ai[..full].iter().zip(aj[..full].iter())
.map(|(a, b)| if and_or { a & b } else { a ^ b }.count_ones() as u64)
.sum();
if rem > 0 {
let mask = (1u8 << rem) - 1;
let last = if and_or { ai[full] & aj[full] } else { ai[full] ^ aj[full] };
n += (last & mask).count_ones() as u64;
}
n
}
fn partial_jaccard_col(&self, i: usize, j: usize) -> (u64, u64) {
let ai = self.col_bytes(i);
let aj = self.col_bytes(j);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let (mut inter, mut union) = ai[..full].iter().zip(aj[..full].iter())
.fold((0u64, 0u64), |(inter, union), (a, b)| {
(inter + (a & b).count_ones() as u64,
union + (a | b).count_ones() as u64)
});
if rem > 0 {
let mask = (1u8 << rem) - 1;
inter += ((ai[full] & aj[full]) & mask).count_ones() as u64;
union += ((ai[full] | aj[full]) & mask).count_ones() as u64;
}
(inter, union)
}
pub(crate) fn count_ones(&self) -> Array1<u64> {
Array1::from_vec(
(0..self.n_cols).into_par_iter().map(|c| self.count_ones_col(c)).collect()
)
}
pub(crate) fn jaccard_dist_matrix(&self) -> Array2<f64> {
let n = self.n_cols;
let results: Vec<(usize, usize, f64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| {
let (inter, union) = self.partial_jaccard_col(i, j);
let d = if union == 0 { 0.0 } else { 1.0 - inter as f64 / union as f64 };
(i, j, d)
})
.collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
pub(crate) fn hamming_dist_matrix(&self) -> Array2<u64> {
let n = self.n_cols;
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| (i, j, self.pair_op(i, j, false)))
.collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
pub(crate) fn partial_jaccard_dist_matrix(&self) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols;
let results: Vec<(usize, usize, u64, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| { let (inter, union) = self.partial_jaccard_col(i, j); (i, j, inter, union) })
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
}
(inter_m, union_m)
}
pub(crate) fn partial_hamming_dist_matrix(&self) -> Array2<u64> {
let n = self.n_cols;
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| (i, j, self.pair_op(i, j, false)))
.collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
}
/// Build `presence/matrix.pbmx` from existing `col_*.pbiv` files.
@@ -282,36 +384,50 @@ impl PersistentBitMatrix {
pub fn count_ones(&self) -> Array1<u64> {
match self {
Self::Columnar(m) => m.count_ones(),
_ => panic!("count_ones() only available on Columnar PersistentBitMatrix"),
Self::Columnar(m) => m.count_ones(),
Self::Packed(m) => m.count_ones(),
Self::Implicit { n_rows, n_cols } => Array1::from_elem(*n_cols, *n_rows as u64),
}
}
pub fn jaccard_dist_matrix(&self) -> Array2<f64> {
match self {
Self::Columnar(m) => m.jaccard_dist_matrix(),
_ => panic!("jaccard_dist_matrix() only available on Columnar PersistentBitMatrix"),
Self::Columnar(m) => m.jaccard_dist_matrix(),
Self::Packed(m) => m.jaccard_dist_matrix(),
Self::Implicit { n_cols, .. } => Array2::zeros((*n_cols, *n_cols)),
}
}
pub fn hamming_dist_matrix(&self) -> Array2<u64> {
match self {
Self::Columnar(m) => m.hamming_dist_matrix(),
_ => panic!("hamming_dist_matrix() only available on Columnar PersistentBitMatrix"),
Self::Columnar(m) => m.hamming_dist_matrix(),
Self::Packed(m) => m.hamming_dist_matrix(),
Self::Implicit { n_cols, .. } => Array2::zeros((*n_cols, *n_cols)),
}
}
pub fn partial_jaccard_dist_matrix(&self) -> (Array2<u64>, Array2<u64>) {
match self {
Self::Columnar(m) => m.partial_jaccard_dist_matrix(),
_ => panic!("partial_jaccard_dist_matrix() only available on Columnar PersistentBitMatrix"),
Self::Columnar(m) => m.partial_jaccard_dist_matrix(),
Self::Packed(m) => m.partial_jaccard_dist_matrix(),
Self::Implicit { n_rows, n_cols } => {
let v = *n_rows as u64;
let n = *n_cols;
let mut inter = Array2::zeros((n, n));
let mut union = Array2::zeros((n, n));
for i in 0..n { for j in 0..n {
inter[[i, j]] = v; union[[i, j]] = v;
}}
(inter, union)
}
}
}
pub fn partial_hamming_dist_matrix(&self) -> Array2<u64> {
match self {
Self::Columnar(m) => m.partial_hamming_dist_matrix(),
_ => panic!("partial_hamming_dist_matrix() only available on Columnar PersistentBitMatrix"),
Self::Columnar(m) => m.partial_hamming_dist_matrix(),
Self::Packed(m) => m.partial_hamming_dist_matrix(),
Self::Implicit { n_cols, .. } => Array2::zeros((*n_cols, *n_cols)),
}
}
src/obicompactvec/src/intmatrix.rs
+169 -17
View File
@@ -266,6 +266,161 @@ impl PackedCompactIntMatrix {
pub(crate) fn row(&self, slot: usize) -> Box<[u32]> {
(0..self.n_cols).map(|c| self.get(c, slot)).collect()
}
pub(crate) fn sum(&self) -> Array1<u64> {
Array1::from_vec(
(0..self.n_cols).into_par_iter()
.map(|c| (0..self.n_rows).map(|s| self.get(c, s) as u64).sum())
.collect()
)
}
// ── Pair primitives ───────────────────────────────────────────────────────
fn pair_partial_bray(&self, i: usize, j: usize) -> u64 {
(0..self.n_rows).map(|s| self.get(i, s).min(self.get(j, s)) as u64).sum()
}
fn pair_partial_euclidean(&self, i: usize, j: usize) -> f64 {
(0..self.n_rows).map(|s| {
let d = self.get(i, s) as f64 - self.get(j, s) as f64;
d * d
}).sum()
}
fn pair_partial_threshold_jaccard(&self, i: usize, j: usize, t: u32) -> (u64, u64) {
let (mut inter, mut union) = (0u64, 0u64);
for s in 0..self.n_rows {
let a = self.get(i, s) >= t;
let b = self.get(j, s) >= t;
if a && b { inter += 1; }
if a || b { union += 1; }
}
(inter, union)
}
fn pair_partial_relfreq_bray(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
(self.get(i, s) as f64 / si).min(self.get(j, s) as f64 / sj)
}).sum()
}
fn pair_partial_relfreq_euclidean(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
let d = self.get(i, s) as f64 / si - self.get(j, s) as f64 / sj;
d * d
}).sum()
}
fn pair_partial_hellinger(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
let d = (self.get(i, s) as f64 / si).sqrt() - (self.get(j, s) as f64 / sj).sqrt();
d * d
}).sum()
}
// ── Matrix methods ────────────────────────────────────────────────────────
fn pairwise<T>(&self, f: impl Fn(usize, usize) -> T + Sync) -> Array2<T>
where T: Clone + Default + Send {
let n = self.n_cols;
let results: Vec<(usize, usize, T)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| { let w = v.clone(); (i, j, v, w) }))
}
fn pairwise_u64(&self, f: impl Fn(usize, usize) -> u64 + Sync) -> Array2<u64> {
let n = self.n_cols;
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
pub(crate) fn partial_bray_dist_matrix(&self) -> Array2<u64> {
self.pairwise_u64(|i, j| self.pair_partial_bray(i, j))
}
pub(crate) fn bray_dist_matrix(&self) -> Array2<f64> {
let col_sums = self.sum();
let sum_min = self.partial_bray_dist_matrix();
let n = self.n_cols;
let mut m = Array2::zeros((n, n));
for i in 0..n { for j in 0..n {
if i != j {
let denom = col_sums[i] + col_sums[j];
m[[i, j]] = if denom == 0 { 0.0 }
else { 1.0 - 2.0 * sum_min[[i, j]] as f64 / denom as f64 };
}
}}
m
}
pub(crate) fn partial_euclidean_dist_matrix(&self) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_euclidean(i, j))
}
pub(crate) fn euclidean_dist_matrix(&self) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_euclidean(i, j).sqrt())
}
pub(crate) fn partial_threshold_jaccard_dist_matrix(&self, t: u32) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols;
let results: Vec<(usize, usize, u64, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| { let (inter, union) = self.pair_partial_threshold_jaccard(i, j, t); (i, j, inter, union) })
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
}
(inter_m, union_m)
}
pub(crate) fn jaccard_dist_matrix(&self) -> Array2<f64> {
self.pairwise(|i, j| {
let (inter, union) = self.pair_partial_threshold_jaccard(i, j, 1);
if union == 0 { 0.0 } else { 1.0 - inter as f64 / union as f64 }
})
}
pub(crate) fn threshold_jaccard_dist_matrix(&self, t: u32) -> Array2<f64> {
self.pairwise(|i, j| {
let (inter, union) = self.pair_partial_threshold_jaccard(i, j, t);
if union == 0 { 0.0 } else { 1.0 - inter as f64 / union as f64 }
})
}
pub(crate) fn partial_relfreq_bray_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_relfreq_bray(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
pub(crate) fn relfreq_bray_dist_matrix(&self) -> Array2<f64> {
let col_sums = self.sum();
self.partial_relfreq_bray_dist_matrix(&col_sums)
}
pub(crate) fn partial_relfreq_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_relfreq_euclidean(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
pub(crate) fn relfreq_euclidean_dist_matrix(&self) -> Array2<f64> {
let col_sums = self.sum();
self.partial_relfreq_euclidean_dist_matrix(&col_sums)
}
pub(crate) fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_hellinger(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
pub(crate) fn hellinger_dist_matrix(&self) -> Array2<f64> {
let col_sums = self.sum();
self.partial_hellinger_euclidean_dist_matrix(&col_sums)
}
}
/// Build `counts/matrix.pcmx` from existing `col_*.pciv` files.
@@ -350,50 +505,47 @@ impl PersistentCompactIntMatrix {
}
pub fn sum(&self) -> Array1<u64> {
match self {
Self::Columnar(m) => m.sum(),
_ => panic!("sum() only available on Columnar PersistentCompactIntMatrix"),
}
match self { Self::Columnar(m) => m.sum(), Self::Packed(m) => m.sum() }
}
pub fn bray_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.bray_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.bray_dist_matrix(), Self::Packed(m) => m.bray_dist_matrix() }
}
pub fn relfreq_bray_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.relfreq_bray_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.relfreq_bray_dist_matrix(), Self::Packed(m) => m.relfreq_bray_dist_matrix() }
}
pub fn euclidean_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.euclidean_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.euclidean_dist_matrix(), Self::Packed(m) => m.euclidean_dist_matrix() }
}
pub fn relfreq_euclidean_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.relfreq_euclidean_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.relfreq_euclidean_dist_matrix(), Self::Packed(m) => m.relfreq_euclidean_dist_matrix() }
}
pub fn hellinger_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.hellinger_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.hellinger_dist_matrix(), Self::Packed(m) => m.hellinger_dist_matrix() }
}
pub fn jaccard_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.jaccard_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.jaccard_dist_matrix(), Self::Packed(m) => m.jaccard_dist_matrix() }
}
pub fn threshold_jaccard_dist_matrix(&self, threshold: u32) -> Array2<f64> {
match self { Self::Columnar(m) => m.threshold_jaccard_dist_matrix(threshold), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.threshold_jaccard_dist_matrix(threshold), Self::Packed(m) => m.threshold_jaccard_dist_matrix(threshold) }
}
pub fn partial_bray_dist_matrix(&self) -> Array2<u64> {
match self { Self::Columnar(m) => m.partial_bray_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_bray_dist_matrix(), Self::Packed(m) => m.partial_bray_dist_matrix() }
}
pub fn partial_euclidean_dist_matrix(&self) -> Array2<f64> {
match self { Self::Columnar(m) => m.partial_euclidean_dist_matrix(), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_euclidean_dist_matrix(), Self::Packed(m) => m.partial_euclidean_dist_matrix() }
}
pub fn partial_threshold_jaccard_dist_matrix(&self, threshold: u32) -> (Array2<u64>, Array2<u64>) {
match self { Self::Columnar(m) => m.partial_threshold_jaccard_dist_matrix(threshold), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_threshold_jaccard_dist_matrix(threshold), Self::Packed(m) => m.partial_threshold_jaccard_dist_matrix(threshold) }
}
pub fn partial_relfreq_bray_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
match self { Self::Columnar(m) => m.partial_relfreq_bray_dist_matrix(col_sums), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_relfreq_bray_dist_matrix(col_sums), Self::Packed(m) => m.partial_relfreq_bray_dist_matrix(col_sums) }
}
pub fn partial_relfreq_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
match self { Self::Columnar(m) => m.partial_relfreq_euclidean_dist_matrix(col_sums), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_relfreq_euclidean_dist_matrix(col_sums), Self::Packed(m) => m.partial_relfreq_euclidean_dist_matrix(col_sums) }
}
pub fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
match self { Self::Columnar(m) => m.partial_hellinger_euclidean_dist_matrix(col_sums), _ => panic!("Columnar only") }
match self { Self::Columnar(m) => m.partial_hellinger_euclidean_dist_matrix(col_sums), Self::Packed(m) => m.partial_hellinger_euclidean_dist_matrix(col_sums) }
}
pub fn append_column(dir: &Path, value_of: impl Fn(usize) -> u32) -> io::Result<()> {
src/obidebruinj/Cargo.toml
+1
View File
@@ -10,6 +10,7 @@ ahash = "0.8"
hashbrown = { version = "0.14", features = ["rayon"] }
rayon = "1"
xxhash-rust = { version = "0.8.15", features = ["xxh3", "const_xxh3"] }
tracing = "0.1"
[features]
test-utils = []
src/obidebruinj/src/debruijn.rs
+8 -7
View File
@@ -2,10 +2,11 @@
use hashbrown::HashMap;
use obikseq::k;
use obikseq::{CanonicalKmer, Sequence};
use rayon::prelude::*;
use rayon::iter::{IntoParallelRefIterator, ParallelIterator};
use std::fmt;
use std::sync::atomic::{AtomicU8, Ordering};
use xxhash_rust::xxh3::Xxh3Builder;
use tracing::{debug, info};
// ── Types ─────────────────────────────────────────────────────────────────────
@@ -379,7 +380,7 @@ impl GraphDeBruijn {
});
let n = n_new.load(Ordering::Relaxed);
eprintln!("[for_each_unitig] pass {}: {} starts", pass, n);
debug!("[for_each_unitig] pass {}: {} starts", pass, n);
n_chains.fetch_add(n, Ordering::Relaxed);
pass += 1;
if n == 0 {
@@ -410,11 +411,11 @@ impl GraphDeBruijn {
}
}
eprintln!(
"[for_each_unitig] chains={} phase2={} total={}",
n_chains.load(Ordering::Relaxed),
n2.load(Ordering::Relaxed),
n_chains.load(Ordering::Relaxed) + n2.load(Ordering::Relaxed),
info!(
chains = n_chains.load(Ordering::Relaxed),
phase2 = n2.load(Ordering::Relaxed),
total = n_chains.load(Ordering::Relaxed) + n2.load(Ordering::Relaxed),
"unitig traversal complete"
);
}
src/obikmer/src/cmd/unitig.rs
+3 -1
View File
@@ -65,9 +65,11 @@ pub fn run(args: UnitigArgs) {
info!("unitig: {} distinct k-mers", g.len());
// ── Phase 2 : compute degrees (in-memory, no progress needed) ────────────
// ── Phase 2 : compute degrees ─────────────────────────────────────────────
let pb = spinner("degrees");
let stage = Stage::start("compute degrees");
g.compute_degrees_and_mark_starts();
pb.finish_and_clear();
rep.push(stage.stop());
// ── Phase 3 : enumerate unitigs and write as FASTA ───────────────────────
src/obisys/Cargo.toml
+1
View File
@@ -7,3 +7,4 @@ edition = "2024"
libc = "0.2"
sysinfo = "0.33"
indicatif = "0.17"
tracing = "0.1"
src/obisys/src/lib.rs
+95 -6
View File
@@ -1,13 +1,79 @@
use std::fmt;
use std::sync::atomic::{AtomicU64, Ordering};
use std::time::{Duration, Instant};
use indicatif::{ProgressBar, ProgressStyle};
use tracing::{info, warn};
const BRAILLE: &[&str] = &["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"];
// ── TracedBar ──────────────────────────────────────────────────────────────────
/// Wrapper around `ProgressBar` that emits `tracing` events when stderr is not
/// a TTY (e.g. HPC job logs): every 10% for bounded bars, every ~10 s for
/// spinners (throttled on `set_message`).
pub struct TracedBar {
pb: ProgressBar,
label: String,
unit: String,
total: u64, // 0 for spinners
start: Instant, // creation time, for spinner throttling
last_pct: AtomicU64, // last emitted 10%-bucket (1..=10), 0 = none yet
last_log_ms: AtomicU64, // ms since `start` at last spinner log
}
impl TracedBar {
pub fn inc(&self, delta: u64) {
self.pb.inc(delta);
if self.pb.is_hidden() && self.total > 0 {
let pos = self.pb.position();
let pct10 = (pos * 10) / self.total; // 0..=10
let last = self.last_pct.load(Ordering::Relaxed);
if pct10 > last
&& self.last_pct
.compare_exchange(last, pct10, Ordering::Relaxed, Ordering::Relaxed)
.is_ok()
{
info!(
stage = %self.label,
progress = format_args!("{}%", pct10 * 10),
"{}/{} {}",
pos, self.total, self.unit
);
}
}
}
pub fn set_message(&self, msg: impl Into<String>) {
let msg = msg.into();
if self.pb.is_hidden() {
if self.total > 0 {
// bounded bar: always log (already rate-limited by 10% threshold in inc)
info!(stage = %self.label, "{msg}");
} else {
// spinner: throttle to ~10 s
let now_ms = self.start.elapsed().as_millis() as u64;
let last = self.last_log_ms.load(Ordering::Relaxed);
if now_ms >= last + 10_000
&& self.last_log_ms
.compare_exchange(last, now_ms, Ordering::Relaxed, Ordering::Relaxed)
.is_ok()
{
info!(stage = %self.label, "{msg}");
}
}
}
self.pb.set_message(msg);
}
pub fn finish_and_clear(&self) {
self.pb.finish_and_clear();
}
}
/// Spinner with the standard project look: `⠋ label — msg 0s`.
/// Caller updates the message with `pb.set_message(...)`.
pub fn spinner(label: &str) -> ProgressBar {
pub fn spinner(label: &str) -> TracedBar {
let pb = ProgressBar::new_spinner();
pb.set_style(
ProgressStyle::with_template(&format!("{{spinner}} {label} — {{msg}} {{elapsed}}"))
@@ -15,12 +81,15 @@ pub fn spinner(label: &str) -> ProgressBar {
.tick_strings(BRAILLE),
);
pb.enable_steady_tick(Duration::from_millis(100));
pb
TracedBar {
pb, label: label.to_string(), unit: String::new(), total: 0,
start: Instant::now(), last_pct: AtomicU64::new(0), last_log_ms: AtomicU64::new(0),
}
}
/// Progress bar with the standard project look:
/// `⠋ label — [████░░░░] pos/len unit elapsed`.
pub fn progress_bar(label: &str, n: u64, unit: &str) -> ProgressBar {
pub fn progress_bar(label: &str, n: u64, unit: &str) -> TracedBar {
let pb = ProgressBar::new(n);
pb.set_style(
ProgressStyle::with_template(&format!(
@@ -30,7 +99,10 @@ pub fn progress_bar(label: &str, n: u64, unit: &str) -> ProgressBar {
.tick_strings(BRAILLE),
);
pb.enable_steady_tick(Duration::from_millis(100));
pb
TracedBar {
pb, label: label.to_string(), unit: unit.to_string(), total: n,
start: Instant::now(), last_pct: AtomicU64::new(0), last_log_ms: AtomicU64::new(0),
}
}
use libc::{RUSAGE_SELF, getrusage, rusage, timeval};
@@ -83,13 +155,15 @@ pub struct Stage {
impl Stage {
pub fn start(label: impl Into<String>) -> Self {
Self { label: label.into(), wall: Instant::now(), ru: get_rusage() }
let label = label.into();
info!(stage = %label, "started");
Self { label, wall: Instant::now(), ru: get_rusage() }
}
pub fn stop(self) -> StageStats {
let wall_secs = self.wall.elapsed().as_secs_f64();
let end = get_rusage();
StageStats {
let stats = StageStats {
label: self.label,
wall_secs,
user_secs: tv_to_secs(end.ru_utime) - tv_to_secs(self.ru.ru_utime),
@@ -102,7 +176,22 @@ impl Stage {
in_blocks: delta(end.ru_inblock as i64, self.ru.ru_inblock as i64),
out_blocks: delta(end.ru_oublock as i64, self.ru.ru_oublock as i64),
swaps: delta(end.ru_nswap as i64, self.ru.ru_nswap as i64),
};
info!(
stage = %stats.label,
wall_secs = format_args!("{:.3}", stats.wall_secs),
rss = %fmt_bytes(stats.max_rss_bytes),
swaps = stats.swaps,
"done"
);
if stats.swaps > 0 {
warn!(
stage = %stats.label,
swaps = stats.swaps,
"working set exceeds available RAM"
);
}
stats
}
}