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test(promql): benchmark quantile selection across value shapes

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Signed-off-by: discord9 <55937128+discord9@users.noreply.github.com>
This commit is contained in:
discord9
2026-09-10 12:31:31 +08:00
parent 13e98e9afa
commit 7d880ff12e
1 changed files with 53 additions and 0 deletions
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src/promql/benches/bench_range_fn.rs
+53
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@@ -238,6 +238,40 @@ fn make_quantile_input(num_points: usize, window_size: u32) -> Vec<ColumnarValue
]
}
fn make_quantile_input_with_values(
num_points: usize,
window_size: u32,
values: Vec<f64>,
) -> Vec<ColumnarValue> {
let (ts_range, val_range, _) = build_sliding_ranges(num_points, window_size, values, 0);
vec![
ColumnarValue::Array(Arc::new(ts_range.into_dict())),
ColumnarValue::Array(Arc::new(val_range.into_dict())),
ColumnarValue::Scalar(ScalarValue::Float64(Some(0.9))),
]
}
fn build_descending_values(num_points: usize) -> Vec<f64> {
(0..num_points).map(|i| (num_points - i) as f64).collect()
}
fn build_pseudorandom_values(num_points: usize) -> Vec<f64> {
let mut state = 0x9E37_79B9_7F4A_7C15_u64;
(0..num_points)
.map(|_| {
state = state
.wrapping_mul(6_364_136_223_846_793_005)
.wrapping_add(1);
(state >> 11) as f64 / (1_u64 << 53) as f64
})
.collect()
}
fn build_low_cardinality_values(num_points: usize) -> Vec<f64> {
const VALUES: [f64; 4] = [-2.0, 0.0, 1.0, 4.0];
(0..num_points).map(|i| VALUES[i % VALUES.len()]).collect()
}
fn make_predict_linear_input(num_points: usize, window_size: u32) -> Vec<ColumnarValue> {
let (ts_range, val_range, _) =
build_sliding_ranges(num_points, window_size, build_default_values(num_points), 0);
@@ -460,6 +494,25 @@ fn bench_range_functions(c: &mut Criterion) {
);
}
// --- quantile_over_time (value-shape matrix) ---
let quantile_shape_params = [
("descending", build_descending_values(4_096)),
("pseudorandom", build_pseudorandom_values(4_096)),
("low_cardinality", build_low_cardinality_values(4_096)),
("gauge", build_gauge_values(4_096)),
];
for (shape, values) in quantile_shape_params {
for w in [60, 360] {
let prepared =
PreparedUdfCall::new(make_quantile_input_with_values(4_096, w, values.clone()));
group.bench_with_input(
BenchmarkId::new("quantile_over_time", format!("{shape}_n4096_w{w}")),
&w,
|b, _| b.iter(|| invoke_prepared(&quantile_udf, &prepared)),
);
}
}
// --- predict_linear ---
let predict_udf = PredictLinear::scalar_udf();
for &(n, w) in params {