mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-11-14 14:56:54 +00:00
feat(promql): add histogram_quantiles and share Go float formatting
Signed-off-by: Dennis Zhuang <killme2008@gmail.com>
This commit is contained in:
Dennis Zhuang
@@ -28,6 +28,7 @@ use datafusion::error::{DataFusionError, Result};
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use datatypes::series::MetricName;
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use datatypes::series::samples::{SampleRef, Series, SeriesSchema};
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use crate::go_format::format_float_f;
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use crate::grid_series::{GridSeriesBuilder, external};
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use crate::map::{drop_empty_labels, validate_float_series, validate_scalar};
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use crate::range_eval::quantile;
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@@ -316,7 +317,7 @@ pub fn count_values(
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Entry::Vacant(entry) => {
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let mut metric = series.metric.clone();
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metric
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.set(label, Arc::from(format_value(value)))
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.set(label, Arc::from(format_float_f(value)))
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.map_err(external)?;
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let metric = grouping.apply(&metric)?;
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let index = *group_index.entry(label_key(&metric)).or_insert_with(|| {
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@@ -348,57 +349,6 @@ pub fn count_values(
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Ok(output)
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}
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/// Go's `strconv.FormatFloat(value, 'f', -1, 64)`: the fewest significant digits that round-trip,
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/// in positional notation. When two candidates of that length are equally close, Go takes the
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/// even one while Rust's shortest formatting rounds up, so the digits are recomputed with Rust's
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/// exact formatting, which rounds half to even. The recomputed digits only count when they still
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/// parse back to `value`: just above a power of two the lower neighbour is half as far away, so
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/// the even candidate can name that neighbour, and only the other one round-trips.
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fn format_value(value: f64) -> String {
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match value {
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f64::INFINITY => return "+Inf".to_string(),
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f64::NEG_INFINITY => return "-Inf".to_string(),
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_ if value.is_nan() => return "NaN".to_string(),
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_ => {}
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}
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let shortest = format!("{value:e}");
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let mantissa = shortest.split_once('e').expect("exponent format").0;
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let significant = mantissa.chars().filter(char::is_ascii_digit).count();
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let exact = format!("{value:.precision$e}", precision = significant - 1);
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let digits = if exact.parse::<f64>() == Ok(value) {
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&exact
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} else {
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&shortest
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};
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let (mantissa, exponent) = digits.split_once('e').expect("exponent format");
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let exponent: i64 = exponent.parse().expect("integer exponent");
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let (sign, mantissa) = match mantissa.strip_prefix('-') {
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Some(unsigned) => ("-", unsigned),
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None => ("", mantissa),
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};
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let digits: String = mantissa.chars().filter(char::is_ascii_digit).collect();
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// The decimal point goes after `exponent + 1` digits.
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let point = exponent + 1;
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let mut out = String::from(sign);
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if point <= 0 {
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out.push_str("0.");
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out.extend(std::iter::repeat_n('0', (-point) as usize));
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out.push_str(digits.trim_end_matches('0'));
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} else if point as usize >= digits.len() {
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out.push_str(&digits);
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out.extend(std::iter::repeat_n('0', point as usize - digits.len()));
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} else {
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let (whole, fraction) = digits.split_at(point as usize);
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out.push_str(whole);
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let fraction = fraction.trim_end_matches('0');
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if !fraction.is_empty() {
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out.push('.');
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out.push_str(fraction);
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}
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}
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out
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}
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/// Schema validation is repeated because Series exposes its fields publicly.
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fn validate_input(schema: &SeriesSchema, input: &[Series], grouping: Grouping<'_>) -> Result<()> {
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if schema.eval_grid.is_none() {
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@@ -907,7 +907,7 @@ fn value_labels_format_like_go() {
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for line in include_str!("format_float_cases.txt").lines() {
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let (bits, expected) = line.split_once(' ').unwrap();
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let value = f64::from_bits(u64::from_str_radix(bits, 16).unwrap());
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assert_eq!(format_value(value), expected, "{bits}");
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assert_eq!(crate::go_format::format_float_f(value), expected, "{bits}");
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checked += 1;
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}
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assert!(checked > 2_400, "{checked}");
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@@ -916,7 +916,7 @@ fn value_labels_format_like_go() {
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(f64::INFINITY, "+Inf"),
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(f64::NEG_INFINITY, "-Inf"),
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] {
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assert_eq!(format_value(value), expected);
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assert_eq!(crate::go_format::format_float_f(value), expected);
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}
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}
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@@ -0,0 +1,129 @@
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// Copyright 2023 Greptime Team
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//! The shortest float formats of Go's `strconv`, which Prometheus writes label values in.
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#[cfg(test)]
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mod tests;
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/// Go's `strconv.FormatFloat(value, 'f', -1, 64)`, the form of `count_values` labels.
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pub(crate) fn format_float_f(value: f64) -> String {
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match special(value) {
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Some(text) => text.to_string(),
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None => {
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let (negative, digits, point) = shortest(value);
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positional(negative, &digits, point)
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}
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}
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}
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/// Prometheus `labels.FormatOpenMetricsFloat`, the form of `histogram_quantiles` labels: Go's
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/// shortest `'g'` format, with `.0` appended to an integer and `0`, `1` and `-1` written as
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/// `0.0`, `1.0` and `-1.0`.
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pub(crate) fn format_open_metrics_float(value: f64) -> String {
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if value == 1.0 {
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return "1.0".to_string();
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}
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if value == 0.0 {
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return "0.0".to_string();
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}
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if value == -1.0 {
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return "-1.0".to_string();
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}
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if let Some(text) = special(value) {
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return text.to_string();
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}
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let (negative, digits, point) = shortest(value);
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// The shortest `'g'` format switches to an exponent below 1e-4 and from 1e6 on.
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let exponent = point - 1;
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let mut text = if !(-4..6).contains(&exponent) {
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let mut text = String::from(if negative { "-" } else { "" });
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text.push_str(&digits[..1]);
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if digits.len() > 1 {
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text.push('.');
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text.push_str(&digits[1..]);
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}
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text.push_str(&format!(
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"e{}{:02}",
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if exponent < 0 { '-' } else { '+' },
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exponent.abs()
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));
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text
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} else {
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positional(negative, &digits, point)
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};
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if !text.contains(['e', '.']) {
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text.push_str(".0");
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}
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text
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}
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fn special(value: f64) -> Option<&'static str> {
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match value {
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f64::INFINITY => Some("+Inf"),
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f64::NEG_INFINITY => Some("-Inf"),
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_ if value.is_nan() => Some("NaN"),
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_ => None,
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}
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}
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/// The fewest significant digits of a finite `value` that round-trip, without trailing zeros, and
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/// the position of the decimal point among them: `value = ±0.digits × 10^point`. Zero is `"0"` at
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/// point 1.
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///
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/// When two candidates of that length are equally close, Go takes the even one while Rust's
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/// shortest formatting rounds up, so the digits are recomputed with Rust's exact formatting,
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/// which rounds half to even. The recomputed digits only count when they still parse back to
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/// `value`: just above a power of two the lower neighbour is half as far away, so the even
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/// candidate can name that neighbour, and only the other one round-trips.
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fn shortest(value: f64) -> (bool, String, i64) {
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let shortest = format!("{value:e}");
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let mantissa = shortest.split_once('e').expect("exponent format").0;
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let significant = mantissa.chars().filter(char::is_ascii_digit).count();
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let exact = format!("{value:.precision$e}", precision = significant - 1);
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let chosen = if exact.parse::<f64>() == Ok(value) {
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&exact
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} else {
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&shortest
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};
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let (mantissa, exponent) = chosen.split_once('e').expect("exponent format");
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let exponent: i64 = exponent.parse().expect("integer exponent");
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let (negative, mantissa) = match mantissa.strip_prefix('-') {
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Some(unsigned) => (true, unsigned),
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None => (false, mantissa),
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};
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let digits: String = mantissa.chars().filter(char::is_ascii_digit).collect();
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let trimmed = digits.trim_end_matches('0');
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let digits = if trimmed.is_empty() { "0" } else { trimmed };
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(negative, digits.to_string(), exponent + 1)
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}
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/// `±0.digits × 10^point` in positional notation without trailing fractional zeros.
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fn positional(negative: bool, digits: &str, point: i64) -> String {
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let mut out = String::from(if negative { "-" } else { "" });
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if point <= 0 {
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out.push_str("0.");
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out.extend(std::iter::repeat_n('0', (-point) as usize));
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out.push_str(digits);
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} else if point as usize >= digits.len() {
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out.push_str(digits);
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out.extend(std::iter::repeat_n('0', point as usize - digits.len()));
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} else {
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let (whole, fraction) = digits.split_at(point as usize);
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out.push_str(whole);
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out.push('.');
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out.push_str(fraction);
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}
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out
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}
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@@ -0,0 +1,358 @@
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0 0.0
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8000000000000000 0.0
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||||
3ff0000000000000 1.0
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bff0000000000000 -1.0
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||||
3fe0000000000000 0.5
|
||||
3feccccccccccccd 0.9
|
||||
3fefae147ae147ae 0.99
|
||||
3feff7ced916872b 0.999
|
||||
3f1a36e2eb1c432d 0.0001
|
||||
3ee4f8b588e368f1 1e-05
|
||||
3f201f31f46ed246 0.000123
|
||||
40f869f000000000 99999.0
|
||||
40f86a0000000000 100000.0
|
||||
412e847e00000000 999999.0
|
||||
412e848000000000 1e+06
|
||||
4132d68700000000 1.234567e+06
|
||||
444b1ae4d6e2ef50 1e+21
|
||||
3e7ad7f29abcaf48 1e-07
|
||||
4000000000000000 2.0
|
||||
c004000000000000 -2.5
|
||||
1 5e-324
|
||||
7fefffffffffffff 1.7976931348623157e+308
|
||||
7ff8000000000001 NaN
|
||||
7ff0000000000000 +Inf
|
||||
fff0000000000000 -Inf
|
||||
3e0fffffffffffff 9.313225746154784e-10
|
||||
3e10000000000000 9.313225746154785e-10
|
||||
3e10000000000001 9.313225746154787e-10
|
||||
3e1fffffffffffff 1.8626451492309568e-09
|
||||
3e20000000000000 1.862645149230957e-09
|
||||
3e20000000000001 1.8626451492309574e-09
|
||||
3e2fffffffffffff 3.7252902984619136e-09
|
||||
3e30000000000000 3.725290298461914e-09
|
||||
3e30000000000001 3.725290298461915e-09
|
||||
3e3fffffffffffff 7.450580596923827e-09
|
||||
3e40000000000000 7.450580596923828e-09
|
||||
3e40000000000001 7.45058059692383e-09
|
||||
3e4fffffffffffff 1.4901161193847655e-08
|
||||
3e50000000000000 1.4901161193847656e-08
|
||||
3e50000000000001 1.490116119384766e-08
|
||||
3e5fffffffffffff 2.980232238769531e-08
|
||||
3e60000000000000 2.9802322387695312e-08
|
||||
3e60000000000001 2.980232238769532e-08
|
||||
3e6fffffffffffff 5.960464477539062e-08
|
||||
3e70000000000000 5.960464477539063e-08
|
||||
3e70000000000001 5.960464477539064e-08
|
||||
3e7fffffffffffff 1.1920928955078124e-07
|
||||
3e80000000000000 1.1920928955078125e-07
|
||||
3e80000000000001 1.1920928955078128e-07
|
||||
3e8fffffffffffff 2.3841857910156247e-07
|
||||
3e90000000000000 2.384185791015625e-07
|
||||
3e90000000000001 2.3841857910156255e-07
|
||||
3e9fffffffffffff 4.7683715820312495e-07
|
||||
3ea0000000000000 4.76837158203125e-07
|
||||
3ea0000000000001 4.768371582031251e-07
|
||||
3eafffffffffffff 9.536743164062499e-07
|
||||
3eb0000000000000 9.5367431640625e-07
|
||||
3eb0000000000001 9.536743164062502e-07
|
||||
3ebfffffffffffff 1.9073486328124998e-06
|
||||
3ec0000000000000 1.9073486328125e-06
|
||||
3ec0000000000001 1.9073486328125004e-06
|
||||
3ecfffffffffffff 3.8146972656249996e-06
|
||||
3ed0000000000000 3.814697265625e-06
|
||||
3ed0000000000001 3.814697265625001e-06
|
||||
3edfffffffffffff 7.629394531249999e-06
|
||||
3ee0000000000000 7.62939453125e-06
|
||||
3ee0000000000001 7.629394531250002e-06
|
||||
3eefffffffffffff 1.5258789062499998e-05
|
||||
3ef0000000000000 1.52587890625e-05
|
||||
3ef0000000000001 1.5258789062500003e-05
|
||||
3effffffffffffff 3.0517578124999997e-05
|
||||
3f00000000000000 3.0517578125e-05
|
||||
3f00000000000001 3.051757812500001e-05
|
||||
3f0fffffffffffff 6.103515624999999e-05
|
||||
3f10000000000000 6.103515625e-05
|
||||
3f10000000000001 6.103515625000001e-05
|
||||
3f1fffffffffffff 0.00012207031249999999
|
||||
3f20000000000000 0.0001220703125
|
||||
3f20000000000001 0.00012207031250000003
|
||||
3f2fffffffffffff 0.00024414062499999997
|
||||
3f30000000000000 0.000244140625
|
||||
3f30000000000001 0.00024414062500000005
|
||||
3f3fffffffffffff 0.00048828124999999995
|
||||
3f40000000000000 0.00048828125
|
||||
3f40000000000001 0.0004882812500000001
|
||||
3f4fffffffffffff 0.0009765624999999999
|
||||
3f50000000000000 0.0009765625
|
||||
3f50000000000001 0.0009765625000000002
|
||||
3f5fffffffffffff 0.0019531249999999998
|
||||
3f60000000000000 0.001953125
|
||||
3f60000000000001 0.0019531250000000004
|
||||
3f6fffffffffffff 0.0039062499999999996
|
||||
3f70000000000000 0.00390625
|
||||
3f70000000000001 0.003906250000000001
|
||||
3f7fffffffffffff 0.007812499999999999
|
||||
3f80000000000000 0.0078125
|
||||
3f80000000000001 0.007812500000000002
|
||||
3f8fffffffffffff 0.015624999999999998
|
||||
3f90000000000000 0.015625
|
||||
3f90000000000001 0.015625000000000003
|
||||
3f9fffffffffffff 0.031249999999999997
|
||||
3fa0000000000000 0.03125
|
||||
3fa0000000000001 0.03125000000000001
|
||||
3fafffffffffffff 0.06249999999999999
|
||||
3fb0000000000000 0.0625
|
||||
3fb0000000000001 0.06250000000000001
|
||||
3fbfffffffffffff 0.12499999999999999
|
||||
3fc0000000000000 0.125
|
||||
3fc0000000000001 0.12500000000000003
|
||||
3fcfffffffffffff 0.24999999999999997
|
||||
3fd0000000000000 0.25
|
||||
3fd0000000000001 0.25000000000000006
|
||||
3fdfffffffffffff 0.49999999999999994
|
||||
3fe0000000000000 0.5
|
||||
3fe0000000000001 0.5000000000000001
|
||||
3fefffffffffffff 0.9999999999999999
|
||||
3ff0000000000000 1.0
|
||||
3ff0000000000001 1.0000000000000002
|
||||
3fffffffffffffff 1.9999999999999998
|
||||
4000000000000000 2.0
|
||||
4000000000000001 2.0000000000000004
|
||||
400fffffffffffff 3.9999999999999996
|
||||
4010000000000000 4.0
|
||||
4010000000000001 4.000000000000001
|
||||
401fffffffffffff 7.999999999999999
|
||||
4020000000000000 8.0
|
||||
4020000000000001 8.000000000000002
|
||||
402fffffffffffff 15.999999999999998
|
||||
4030000000000000 16.0
|
||||
4030000000000001 16.000000000000004
|
||||
403fffffffffffff 31.999999999999996
|
||||
4040000000000000 32.0
|
||||
4040000000000001 32.00000000000001
|
||||
404fffffffffffff 63.99999999999999
|
||||
4050000000000000 64.0
|
||||
4050000000000001 64.00000000000001
|
||||
405fffffffffffff 127.99999999999999
|
||||
4060000000000000 128.0
|
||||
4060000000000001 128.00000000000003
|
||||
406fffffffffffff 255.99999999999997
|
||||
4070000000000000 256.0
|
||||
4070000000000001 256.00000000000006
|
||||
407fffffffffffff 511.99999999999994
|
||||
4080000000000000 512.0
|
||||
4080000000000001 512.0000000000001
|
||||
408fffffffffffff 1023.9999999999999
|
||||
4090000000000000 1024.0
|
||||
4090000000000001 1024.0000000000002
|
||||
409fffffffffffff 2047.9999999999998
|
||||
40a0000000000000 2048.0
|
||||
40a0000000000001 2048.0000000000005
|
||||
40afffffffffffff 4095.9999999999995
|
||||
40b0000000000000 4096.0
|
||||
40b0000000000001 4096.000000000001
|
||||
40bfffffffffffff 8191.999999999999
|
||||
40c0000000000000 8192.0
|
||||
40c0000000000001 8192.000000000002
|
||||
40cfffffffffffff 16383.999999999998
|
||||
40d0000000000000 16384.0
|
||||
40d0000000000001 16384.000000000004
|
||||
40dfffffffffffff 32767.999999999996
|
||||
40e0000000000000 32768.0
|
||||
40e0000000000001 32768.00000000001
|
||||
40efffffffffffff 65535.99999999999
|
||||
40f0000000000000 65536.0
|
||||
40f0000000000001 65536.00000000001
|
||||
40ffffffffffffff 131071.99999999999
|
||||
4100000000000000 131072.0
|
||||
4100000000000001 131072.00000000003
|
||||
410fffffffffffff 262143.99999999997
|
||||
4110000000000000 262144.0
|
||||
4110000000000001 262144.00000000006
|
||||
411fffffffffffff 524287.99999999994
|
||||
4120000000000000 524288.0
|
||||
4120000000000001 524288.0000000001
|
||||
412fffffffffffff 1.0485759999999999e+06
|
||||
4130000000000000 1.048576e+06
|
||||
4130000000000001 1.0485760000000002e+06
|
||||
413fffffffffffff 2.0971519999999998e+06
|
||||
4140000000000000 2.097152e+06
|
||||
4140000000000001 2.0971520000000005e+06
|
||||
414fffffffffffff 4.1943039999999995e+06
|
||||
4150000000000000 4.194304e+06
|
||||
4150000000000001 4.194304000000001e+06
|
||||
415fffffffffffff 8.388607999999999e+06
|
||||
4160000000000000 8.388608e+06
|
||||
4160000000000001 8.388608000000002e+06
|
||||
416fffffffffffff 1.6777215999999998e+07
|
||||
4170000000000000 1.6777216e+07
|
||||
4170000000000001 1.6777216000000004e+07
|
||||
417fffffffffffff 3.3554431999999996e+07
|
||||
4180000000000000 3.3554432e+07
|
||||
4180000000000001 3.355443200000001e+07
|
||||
418fffffffffffff 6.710886399999999e+07
|
||||
4190000000000000 6.7108864e+07
|
||||
4190000000000001 6.710886400000001e+07
|
||||
419fffffffffffff 1.3421772799999999e+08
|
||||
41a0000000000000 1.34217728e+08
|
||||
41a0000000000001 1.3421772800000003e+08
|
||||
41afffffffffffff 2.6843545599999997e+08
|
||||
41b0000000000000 2.68435456e+08
|
||||
41b0000000000001 2.6843545600000006e+08
|
||||
41bfffffffffffff 5.3687091199999994e+08
|
||||
41c0000000000000 5.36870912e+08
|
||||
41c0000000000001 5.368709120000001e+08
|
||||
41cfffffffffffff 1.0737418239999999e+09
|
||||
41d0000000000000 1.073741824e+09
|
||||
41d0000000000001 1.0737418240000002e+09
|
||||
3e65822107fcfd52 4.0062361426977984e-08
|
||||
bfd04dc76695721d -0.2547472478670743
|
||||
3dda858149c6e2d1 9.648466959782995e-11
|
||||
c276cb397916001e -1.5663811505600073e+12
|
||||
40197f48392907a0 6.374298947457561
|
||||
40b27cc6f3875d04 4732.777153454026
|
||||
be2cffa2ba517936 -3.3758786482808152e-09
|
||||
c27621587cb3ad0b -1.5207796437068152e+12
|
||||
c06a768b7c4e0b68 -211.70452704661443
|
||||
424c3f2525632186 2.426369665982619e+11
|
||||
41f2070f169c1121 4.839240041754182e+09
|
||||
bd8bd268b68e6a3f -3.162985000843313e-12
|
||||
c0b4c47f2cdf5b8a -5316.496778449868
|
||||
3ea4502fc5d6d268 6.053813980584764e-07
|
||||
c1034c367674cb74 -158086.80783995579
|
||||
3f8c8b35bb9457d8 0.013937396800013532
|
||||
c00419db794209ff -2.5126256440428274
|
||||
c1e4b7a55a25e0cb -2.7806379051836905e+09
|
||||
3e72b02936d4ff9b 6.961870520783569e-08
|
||||
40d442fd5ad145f4 20747.958668058694
|
||||
be4d968d3f71f8cb -1.3778029368671855e-08
|
||||
be06e3cafccae224 -6.661813267564451e-10
|
||||
c169d9f17d9e8fbc -1.3553547925605647e+07
|
||||
420403def63a5b6f 1.0745536199294645e+10
|
||||
4221017fbc897d06 3.651979629274419e+10
|
||||
c265a315724c7af1 -7.434432395238419e+11
|
||||
41ca71f52257bb7d 8.873518766854092e+08
|
||||
40bb9ca8be8e9981 7068.659157669522
|
||||
be33fac825416fed -4.651866964628022e-09
|
||||
41b9f7676678e7aa 4.356442624722849e+08
|
||||
3ef7830356aa6b86 2.2422570888562812e-05
|
||||
4228f8bd3e99b0a8 5.362618350084503e+10
|
||||
403a156ae58348b0 26.083662361671202
|
||||
bfa0a1e9406aec9d -0.03248528395985171
|
||||
bd9d8e9fa5ead0bd -6.720511814114512e-12
|
||||
40408e4b738b6829 33.11167759234406
|
||||
41b780ea967cd710 3.943246304876566e+08
|
||||
bfb9c16725fd3d7f -0.10060734441252882
|
||||
411f01c926fbf29b 508018.2880704791
|
||||
bf12787c2bf3394b -7.045991786755916e-05
|
||||
c16ed31f1cb9e6c6 -1.616101689769305e+07
|
||||
c0e92d0169a39144 -51560.04414537785
|
||||
c02b5389421657ff -13.663156571605212
|
||||
3f7e91e98b02c917 0.007463371541393002
|
||||
4052560383d17909 73.34396453338935
|
||||
c1a58fbeaf635d47 -1.8087099969407102e+08
|
||||
bfc03382be14186f -0.1265719822042146
|
||||
bdb7ae24e9174548 -2.1537062557132775e-11
|
||||
41f5855807b73658 5.7769657554507675e+09
|
||||
beb2a18da250bf34 -1.1104981549984584e-06
|
||||
bedb3641fe3dea79 -6.487833136388005e-06
|
||||
c1eb36dbc9b344e9 -3.652640333602162e+09
|
||||
40f5cb471941e52a 89268.44366635816
|
||||
c080d6326b40eabc -538.7746186324725
|
||||
bd82aafe336eacca -2.1222992129454815e-12
|
||||
c0ef278a67149b9c -63804.325083068776
|
||||
bf1c44bf5a5ffefb -0.0001078359406108085
|
||||
bf6d29286f00f02b -0.0035596646994502565
|
||||
bdbfafc3545836c4 -2.8818771389702537e-11
|
||||
bd7f325712f4128d -1.7733237396191494e-12
|
||||
c05e3e3e4a305605 -120.97255186767877
|
||||
bfeca80d72521a90 -0.8955142243219871
|
||||
3f85f26283efc6c6 0.01071621861590034
|
||||
411cfc5dc1540864 474903.4387971221
|
||||
bfbb185b70ab53ba -0.1058404111930277
|
||||
413fb024878d4063 2.076708529499077e+06
|
||||
c274d6353cb62f07 -1.4318905455069392e+12
|
||||
40b900fb4ffbf3a9 6400.981689211833
|
||||
3fd796b83f190476 0.36857420122038975
|
||||
3f89c820f5c353cf 0.012588746547786215
|
||||
bf1c9b582d230176 -0.00010912633595961348
|
||||
3f0b626c3f1d7427 5.223172037347622e-05
|
||||
c1b98e40b01aa47d -4.287530721040724e+08
|
||||
bf40e7ac7417bf38 -0.0005158989007991504
|
||||
c0fa23eb55ece0ea -107070.70847785813
|
||||
c144a3c813d346b5 -2.705296154885138e+06
|
||||
420cfdbc6db30e37 1.556450859838194e+10
|
||||
bffaedf1a6e222f5 -1.6830917853241634
|
||||
bdaa7d712e166bdf -1.2046261072190693e-11
|
||||
bd9166a221898f34 -3.956509186266304e-12
|
||||
41f29c7719af53ba 4.995903898957941e+09
|
||||
c257d70a133c9673 -4.0956803813035077e+11
|
||||
3e03f10e0f212551 5.803775500632443e-10
|
||||
bdd09a3e6f241c57 -6.039959833086004e-11
|
||||
3def70ff3be70cb0 2.2876625416160384e-10
|
||||
3e0b4e8e20f31127 7.947341135001321e-10
|
||||
c101aa87289cbd2c -144720.89483020583
|
||||
c1a30cf840a79c3b -1.5980854432736382e+08
|
||||
c1f2cee10365790c -5.048766518342052e+09
|
||||
4241f57b0bb131e8 1.542658517463899e+11
|
||||
41644786139efcca 1.0632240613157649e+07
|
||||
c10c4694a54af747 -231634.5807093924
|
||||
3fb93fb09f6c47ac 0.09862808124697037
|
||||
410283b654043a66 151670.7910236895
|
||||
3f955397b4926431 0.020826692959051655
|
||||
c2770eb58f0d2558 -1.584496439506334e+12
|
||||
c2574b9d7f803594 -4.0021144320083716e+11
|
||||
c1798c4033fe2656 -2.678886724954828e+07
|
||||
bdda20af6b41292d -9.505193404385634e-11
|
||||
bd9d5ac882093298 -6.6744682973325806e-12
|
||||
c10fbff5b2d5a113 -260094.71232152786
|
||||
3ea8e96f5b8e56a9 7.42431146882456e-07
|
||||
3d98fa6e04f9ce92 5.679394522162092e-12
|
||||
bfb82947a67e52b1 -0.09437988104611851
|
||||
3f819e7792417fc3 0.008603033209681038
|
||||
3ef67230b027b7e0 2.1406226560154065e-05
|
||||
410bdd8f44c9ab40 228273.908587778
|
||||
bdaddb0efd7a84af -1.3576799338601639e-11
|
||||
bfde7f03e3abff4a -0.476502392135434
|
||||
be3c374d736e41cc -6.569555391781771e-09
|
||||
bd8fd8d37b3ccebc -3.6205821004411243e-12
|
||||
bf015dbd315ae6af -3.312333698830599e-05
|
||||
bef0a23119ea0f2f -1.58630006077541e-05
|
||||
4147e80684a6bfdc 3.1334530363387894e+06
|
||||
418ffa8aa44a03a4 6.706414853613976e+07
|
||||
41b39bb8b580c8ba 3.2897246950306284e+08
|
||||
c13b6a22b648e604 -1.7966427120498428e+06
|
||||
c235fcdd893a310f -9.443669023419164e+10
|
||||
421ec18437f5198b 3.3023921661274944e+10
|
||||
bf8ae37ae39d02db -0.013129196234900877
|
||||
bef95e8cca599392 -2.4194083968604218e-05
|
||||
3dcad1bdc176163d 4.8784025588835895e-11
|
||||
3f1df0dcf9f95ede 0.00011421536191258015
|
||||
c1757d0f8a928585 -2.2532344660771865e+07
|
||||
c0a5dcfd887953e8 -2798.4951818385052
|
||||
c1ad00c4e533e9a3 -2.4329483460139188e+08
|
||||
be189b251dba77ae -1.432259747359515e-09
|
||||
c0faea4753b428d7 -110244.45793548539
|
||||
3f1888203391860a 9.358116666782087e-05
|
||||
c07eccfcba9075b0 -492.81170135907723
|
||||
c1a9bf542b517f2b -2.1598466165917334e+08
|
||||
be6f489bc56ba9c3 -5.827029585742761e-08
|
||||
c07aeee5fdde63b1 -430.9311503111922
|
||||
bdbff35e51e90a1f -2.905895413133007e-11
|
||||
c08585e696d511e1 -688.7375923772889
|
||||
3e1584aa5403510d 1.2525254861511635e-09
|
||||
425175c897a14c51 2.9996209728519244e+11
|
||||
bfefb52e3298237e -0.9908667553109891
|
||||
3ece74d4b80f63d4 3.630682329430478e-06
|
||||
be56a526ee438107 -2.108991638348143e-08
|
||||
3e7365a824bf7034 7.225981696286206e-08
|
||||
405b24ce99aa99ff 108.57510987911517
|
||||
bd8f8f5522164965 -3.5879444088569995e-12
|
||||
c11bb2a14ccdd7af -453800.3250039769
|
||||
be24ed37e9a7b972 -2.4361808796334138e-09
|
||||
bec4827163240d09 -2.444928008606154e-06
|
||||
c1c39851da458093 -6.574990605429863e+08
|
||||
3e46091f323f491a 1.0261140888290476e-08
|
||||
bdaa570dd2d99eb9 -1.197807008879946e-11
|
||||
40f265b33b61e4f4 75355.2019976562
|
||||
@@ -0,0 +1,29 @@
|
||||
// Copyright 2023 Greptime Team
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
use crate::go_format::format_open_metrics_float;
|
||||
|
||||
/// Prometheus `labels.FormatOpenMetricsFloat`; `open_metrics_cases.txt` comes from promql-compat
|
||||
/// `narthex-golden-formatfloat -openmetrics` as `<hex bits> <formatted>`.
|
||||
#[test]
|
||||
fn open_metrics_floats_format_like_prometheus() {
|
||||
let mut checked = 0;
|
||||
for line in include_str!("open_metrics_cases.txt").lines() {
|
||||
let (bits, expected) = line.split_once(' ').unwrap();
|
||||
let value = f64::from_bits(u64::from_str_radix(bits, 16).unwrap());
|
||||
assert_eq!(format_open_metrics_float(value), expected, "{bits}");
|
||||
checked += 1;
|
||||
}
|
||||
assert!(checked > 300, "{checked}");
|
||||
}
|
||||
@@ -40,9 +40,10 @@ use datatypes::series::time::{TimeAxis, union_positions};
|
||||
pub(crate) use aggregate::sum_or_avg;
|
||||
pub use aggregate::{HistogramAggregate, aggregate_histograms};
|
||||
|
||||
use crate::go_format::format_open_metrics_float;
|
||||
use crate::go_sort;
|
||||
use crate::grid_series::{
|
||||
GridSeriesBuilder, LabelSet, METADATA_LABELS, label_set, merge_same_labelset,
|
||||
GridSeriesBuilder, LabelSet, METADATA_LABELS, external, label_set, merge_same_labelset,
|
||||
};
|
||||
|
||||
const BUCKET_LABEL: &str = "le";
|
||||
@@ -56,6 +57,30 @@ pub enum HistogramFunction {
|
||||
Fraction { lower: f64, upper: f64 },
|
||||
}
|
||||
|
||||
/// `histogram_quantiles(v, label, q...)`: [`evaluate_histograms`] with `Quantile(q)` for each
|
||||
/// `q`, each result labelled with `label` set to `q` as Prometheus' `FormatOpenMetricsFloat`
|
||||
/// writes it. Results that then share a label set merge as [`merge_same_labelset`] does, so a
|
||||
/// repeated `q`, or a `label` that overwrites the label telling two histograms apart, fails at a
|
||||
/// point both hold.
|
||||
pub fn histogram_quantiles(
|
||||
label: &str,
|
||||
quantiles: &[f64],
|
||||
schema: &Arc<SeriesSchema>,
|
||||
series: &[Series],
|
||||
) -> Result<Vec<Series>> {
|
||||
let mut output = Vec::new();
|
||||
for &quantile in quantiles {
|
||||
let value: Arc<str> = Arc::from(format_open_metrics_float(quantile));
|
||||
for mut result in
|
||||
evaluate_histograms(HistogramFunction::Quantile(quantile), schema, series)?
|
||||
{
|
||||
result.metric.set(label, value.clone()).map_err(external)?;
|
||||
output.push(result);
|
||||
}
|
||||
}
|
||||
merge_same_labelset(schema, output)
|
||||
}
|
||||
|
||||
/// Evaluates `function` over the classic and native histograms in `series`.
|
||||
///
|
||||
/// Float series with the same labels other than `le` form a classic histogram; a float series
|
||||
|
||||
@@ -0,0 +1,425 @@
|
||||
# Generated by promql-compat cmd/narthex-golden-histogram built for amd64 (Prometheus
|
||||
# v3.15.0 engine, seed 1, 30 cases per function). Each case lists its operation and
|
||||
# tab-separated arguments, the grid, the input series and either the result series or
|
||||
# the error. Points are `grid index:hex bits`.
|
||||
case quantiles quantile 3fd0000000000000
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x ; 0:4026000000000000 1:4018000000000000
|
||||
series __name__=a_bucket|job=x|le=abc ; 0:404f000000000000 1:4057c00000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:403c000000000000 1:403c000000000000
|
||||
series __name__=a_bucket|job=y|le=0.1 ; 0:4051500000000000 1:4053b00000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:4058e00000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:405d300000000000 1:4069600000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:4065580000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:406c280000000000 1:4074240000000000
|
||||
series __name__=b_bucket|job=z|le=0.25 ; 0:404ba00000000000 1:4040200000000000
|
||||
series __name__=b_bucket|job=z|le=2.5 ; 0:4060580000000000 1:405a100000000000
|
||||
series __name__=b_bucket|job=z|le=inf ; 0:4065680000000000 1:4065180000000000
|
||||
result job=x|quantile=0.25 ; 0:7ff8000000000001 1:7ff8000000000001
|
||||
result job=y|quantile=0.25 ; 0:3fb4d13c711ede2d 1:3fbcf601dab51b18
|
||||
result job=z|quantile=0.25 ; 0:3fc8cbdf90cbdf91 1:3fe1f00000000000
|
||||
end
|
||||
case quantiles quantile bfe0000000000000,3fefae147ae147ae
|
||||
grid 100000 10000 5
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4024000000000000 1:4035000000000000 2:4000000000000000 3:4028000000000000 4:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=abc ; 1:4047800000000000 4:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=1e400 ; 0:0 1:4053800000000000 2:4052800000000000 3:7ff8000000000001 4:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:4044800000000000 1:4057800000000000 3:7ff8000000000001 4:7ff0000000000000
|
||||
series __name__=a_bucket|job=y ; 0:404a400000000000 1:4041400000000000 2:4017000000000000 3:4058600000000000 4:4050d00000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:405d800000000000 1:404de00000000000 2:405a700000000000 3:405db00000000000 4:405ad00000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 2:4063c80000000000 3:406af00000000000 4:4072440000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:406fd80000000000 1:4066280000000000 3:406c180000000000 4:4074440000000000
|
||||
series __name__=b_bucket|job=y ; 0:404f800000000000 2:4058300000000000
|
||||
series __name__=b_bucket|job=y|le=0 ; 0:4061480000000000 1:4064700000000000 2:4066800000000000 3:4058600000000000 4:4051900000000000
|
||||
series __name__=b_bucket|job=y|le=1 ; 0:4069300000000000 1:406ee00000000000 2:406a600000000000 3:4066180000000000 4:405a400000000000
|
||||
series __name__=b_bucket|job=y|le=+Inf ; 0:406a680000000000 2:4072380000000000 3:406b600000000000 4:4063680000000000
|
||||
series __name__=b_bucket|job=z|le=0.25 ; 0:4014000000000000 1:4020000000000000 2:4031000000000000 3:4043800000000000 4:4028000000000000
|
||||
series __name__=b_bucket|job=z|le=2.5 ; 0:4048000000000000 1:40200000000001c2 2:4030ffffffff4515 3:4055400000000000 4:4028000000000000
|
||||
series __name__=b_bucket|job=z|le=inf ; 1:40200000000001c2 2:4030ffffffff4336 3:405c400000000000 4:4028000000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 0,bfe0000000000000
|
||||
grid 100000 10000 3
|
||||
series __name__=a_bucket|job=x|le=0.1 ; 0:403e000000000000 1:4028000000000000 2:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:404c800000000000 1:4041000000000000 2:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4055400000000000 1:4045000000000000 2:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:4060000000000000 1:4056000000000000 2:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:7ff8000000000001 1:7ff0000000000000 2:7ff0000000000000
|
||||
series __name__=b_bucket|job=y|le=0.1 ; 0:4041800000000000 1:4038000000000000 2:4048000000000000
|
||||
series __name__=b_bucket|job=y|le=0.5 ; 0:4043000000000000 1:4037fffffffffd5c
|
||||
series __name__=b_bucket|job=y|le=1 ; 0:4054000000000000 1:4037ffffffffffff
|
||||
series __name__=b_bucket|job=y|le=5 ; 0:4053ffffffff2419 1:40380000000107e1 2:40553fffffff165b
|
||||
series __name__=b_bucket|job=y|le=+Inf ; 0:4054000000000000 2:40557fffffff165b
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:0 1:0 2:0
|
||||
series __name__=b_bucket|job=z|le=1.0 ; 0:0 2:0
|
||||
series __name__=b_bucket|job=z|le=2 ; 1:1 2:1a56e1fc2f8f359
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:1 1:1 2:0
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile bfe0000000000000,bfe0000000000000
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:402a000000000000 2:4010000000000000 3:4033000000000000 4:401c000000000000
|
||||
series __name__=a_bucket|job=y|le=2 ; 0:4035000000000000 1:4040ffffffff4515 2:4010000000000000 3:403d000000000000 4:401c000000000000 5:4056800000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:4034ffffffff191a 1:404a7fffffff4515 2:4047000000000000 4:401c000000000000 5:4058400000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4057c00000000000 1:4039800000000000 3:4028800000000000 4:404f600000000000 5:4044600000000000
|
||||
series __name__=b_bucket|job=z|le=2 ; 0:4065c00000000000 1:4055d00000000000 2:4060200000000000 3:4057500000000000 4:405f300000000000 5:4059600000000000
|
||||
series __name__=b_bucket|job=z|le=5 ; 0:4070e80000000000 1:405a900000000000 2:4069e80000000000 3:4062580000000000 4:4065500000000000 5:4062780000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile 3fd0000000000000,3ff8000000000000,3fe0000000000000
|
||||
grid 100000 10000 8
|
||||
series __name__=b_bucket|job=z ; 0:4044c00000000000 1:402e000000000000 2:4021000000000000 3:4048e00000000000 4:404ea00000000000 5:4056c00000000000 6:404ce00000000000 7:4047e00000000000
|
||||
series __name__=b_bucket|job=z|le=2.5 ; 1:403dc00000000000 2:4049000000000000 3:4050800000000000 4:4055b00000000000 5:4061300000000000 6:4055d00000000000
|
||||
series __name__=b_bucket|job=z|le=inf ; 0:4064180000000000 1:4056c00000000000 2:4060400000000000 3:4064100000000000 5:406bf00000000000 6:4057d00000000000 7:4051e00000000000
|
||||
result job=z|quantile=0.25 ; 0:7ff8000000000001 1:3ffe969696969696 2:3ffa000000000000 3:3ff851745d1745d1 4:7ff8000000000001 5:3ff04129e4129e41 6:3fe5d574a1601779 7:7ff8000000000001
|
||||
result job=z|quantile=0.5 ; 0:7ff8000000000001 1:4004000000000000 2:4004000000000000 3:4004000000000000 4:7ff8000000000001 5:40004129e4129e41 6:3ff5d574a1601779 7:7ff8000000000001
|
||||
result job=z|quantile=1.5 ; 0:7ff0000000000000 1:7ff0000000000000 2:7ff0000000000000 3:7ff0000000000000 4:7ff0000000000000 5:7ff0000000000000 6:7ff0000000000000 7:7ff0000000000000
|
||||
end
|
||||
case quantiles quantile 3ff8000000000000,3ff0000000000000
|
||||
grid 100000 10000 5
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 1:4052600000000000 3:404b000000000000 4:404fe00000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 1:0 2:0 3:0
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:404e800000000000 1:4052000000000000 2:4029800000000000 3:4054b00000000000 4:4052900000000000
|
||||
series __name__=b_bucket|job=z|le=abc ; 2:4056900000000000 3:4062380000000000 4:405f200000000000
|
||||
series __name__=b_bucket|job=z|le=1e400 ; 0:4053900000000000 1:4062f00000000000 2:405e800000000000 3:4064380000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4063080000000000 1:4067680000000000 2:4064480000000000 4:406ee80000000000
|
||||
result job=x|quantile=1.0 ; 1:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001
|
||||
result job=x|quantile=1.5 ; 1:7ff0000000000000 3:7ff0000000000000 4:7ff0000000000000
|
||||
result job=y|quantile=1.0 ; 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001
|
||||
result job=y|quantile=1.5 ; 1:7ff0000000000000 2:7ff0000000000000 3:7ff0000000000000
|
||||
result job=z|quantile=1.0 ; 0:3ff0000000000000 1:3ff0000000000000 2:3ff0000000000000 3:7ff8000000000001 4:3ff0000000000000
|
||||
result job=z|quantile=1.5 ; 0:7ff0000000000000 1:7ff0000000000000 2:7ff0000000000000 3:7ff0000000000000 4:7ff0000000000000
|
||||
end
|
||||
case quantiles quantile 3ff0000000000000
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x ; 0:4026000000000000 1:4040800000000000
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:7ff8000000000001 1:7ff0000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:7ff8000000000001 1:7ff8000000000001
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:7ff8000000000001 1:7ff8000000000001
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:7ff8000000000001
|
||||
result job=x|quantile=1.0 ; 0:4014000000000000 1:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 3feccccccccccccd,3feccccccccccccd,3fe0000000000000
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4024000000000000 1:4010000000000000
|
||||
series __name__=a_bucket|job=x|le=2 ; 0:4008000000000000 1:4058800000000000
|
||||
series __name__=a_bucket|job=x|le=5 ;
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile 3fefae147ae147ae,3fd0000000000000,3ff0000000000000
|
||||
grid 100000 10000 7
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 1:4047000000000000 2:4010000000000000 3:4024000000000000 4:4022000000000000 5:4047800000000000 6:4033000000000000
|
||||
series __name__=b_bucket|job=y|le=1 ; 0:4053000000000000 1:404d000000000000 2:4026000000000000 3:4054800000000000 4:4055400000000000 5:4050000000000000 6:403d000000000000
|
||||
series __name__=b_bucket|job=y|le=2 ; 0:4054400000000000 1:4045000000000000 2:402a000000000000 3:4032000000000000 4:403d000000000000 5:4054800000000000 6:4055400000000000
|
||||
series __name__=b_bucket|job=y|le=5 ; 0:4057800000000000 1:4056800000000000 2:4038000000000000 3:403a000000000000 4:404f800000000000 5:404a000000000000 6:4055000000000000
|
||||
result job=x|quantile=0.25 ; 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=x|quantile=0.99 ; 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=x|quantile=1.0 ; 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=y|quantile=0.25 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=y|quantile=0.99 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=y|quantile=1.0 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 0,3ff0000000000000,0
|
||||
grid 100000 10000 7
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4045000000000000 1:4034000000000000 2:403a000000000000 3:4056000000000000 5:401c000000000000
|
||||
series __name__=a_bucket|job=x|le=1.0 ; 0:4024000000000000 1:4044000000000000 2:4008000000000000 3:4054400000000000 4:4039000000000000 5:4055800000000000 6:4052c00000000000
|
||||
series __name__=a_bucket|job=x|le=2 ; 0:404b800000000000 1:4042800000000000 3:4055c00000000000 4:4018000000000000 5:404b800000000000 6:4054c00000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:4045800000000000 1:4054800000000000 2:4050400000000000 3:4043000000000000 4:4050800000000000
|
||||
series __name__=a_bucket|job=y|le=0.1 ; 0:4056900000000000 1:403bc00000000000 2:4035800000000000 3:403b400000000000 4:402f000000000000 5:4052600000000000 6:4047600000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:4063f00000000000 1:4045800000000000 2:405a100000000000 3:4057d00000000000 5:4061080000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:4069e00000000000 1:405ab00000000000 3:4066400000000000 6:4053200000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:4072180000000000 2:406b780000000000 3:406d000000000000 4:4067080000000000 5:4070700000000000 6:405a500000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:4074b00000000000 1:4067680000000000 2:4073c80000000000 3:4072340000000000 4:4069000000000000 5:4070e80000000000 6:4062c80000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 0
|
||||
grid 100000 10000 2
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4055300000000000 1:4036400000000000
|
||||
series __name__=b_bucket|job=z|le=2 ; 0:4062280000000000 1:4047800000000000
|
||||
series __name__=b_bucket|job=z|le=5 ; 1:404e600000000000
|
||||
result job=0.0 ; 0:7ff8000000000001 1:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 3feccccccccccccd,bfe0000000000000
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:0 1:0 4:0 5:0
|
||||
series __name__=b_bucket|job=z|le=0.25 ; 0:4031000000000000 1:404e000000000000 3:4047800000000000 4:402c000000000000 5:4053400000000000
|
||||
series __name__=b_bucket|job=z|le=2.5 ; 0:404a800000000000 1:4058c00000000000 2:4033000000000000 3:4058000000000000 4:4054c00000000000 5:4048000000000000
|
||||
series __name__=b_bucket|job=z ; 0:4055000000000000 1:404c000000000000 3:3ff0000000000000 4:4035000000000000 5:4045000000000000
|
||||
result job=x|quantile=-0.5 ; 0:fff0000000000000 1:fff0000000000000 4:fff0000000000000 5:fff0000000000000
|
||||
result job=x|quantile=0.9 ; 0:7ff8000000000001 1:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001
|
||||
result job=z|quantile=-0.5 ; 0:fff0000000000000 1:fff0000000000000 2:fff0000000000000 3:fff0000000000000 4:fff0000000000000 5:fff0000000000000
|
||||
result job=z|quantile=0.9 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001
|
||||
end
|
||||
case quantiles job 3fefae147ae147ae,3fefae147ae147ae
|
||||
grid 100000 10000 8
|
||||
series __name__=a_bucket|job=x ; 0:4050f00000000000 1:4047000000000000 2:4057500000000000 3:404aa00000000000 4:4025000000000000 5:4050c00000000000 6:4055500000000000 7:402b800000000000
|
||||
series __name__=a_bucket|job=x|le=1.0 ; 0:4059b00000000000 1:405ac00000000000 3:405e200000000000 4:4056a00000000000 5:4064280000000000 6:4064200000000000 7:4048600000000000
|
||||
series __name__=a_bucket|job=x|le=2 ; 0:4061d80000000000 1:405c000000000000 2:4062180000000000 4:4066180000000000 5:406fe00000000000 6:406fa80000000000 7:404b000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:4065380000000000 1:4061800000000000 2:4064080000000000 3:4066180000000000 4:4067080000000000 5:4075340000000000 6:4071f40000000000 7:4051b00000000000
|
||||
series __name__=b_bucket|job=y|le=-1 ; 0:3ff0000000000000 1:4010000000000000 2:4010000000000000 4:c014000000000000 5:c014000000000000 6:4028000000000000 7:403d000000000000
|
||||
series __name__=b_bucket|job=y|le=0 ; 0:0 1:403d000000000000 2:c014000000000000 3:4055000000000000 4:4032000000000000 5:403e000000000000 6:c014000000000000 7:4043800000000000
|
||||
series __name__=b_bucket|job=y|le=1 ; 1:4048000000000000 2:4008000000000000 3:405d400000000000 4:4040800000000000 5:4045000000000000 6:c014000000000000 7:4053c00000000000
|
||||
series __name__=b_bucket|job=y|le=+Inf ; 0:c014000000000000 1:4052000000000000 2:7ff0000000000000 3:4060800000000000 4:7ff0000000000000 5:404c000000000000 6:4044800000000000 7:4056000000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4053c00000000000 2:403f400000000000 3:4048a00000000000 4:4008000000000000 5:4052400000000000 6:404ec00000000000 7:4055600000000000
|
||||
series __name__=b_bucket|job=z|le=abc ; 0:405be00000000000 1:4059a00000000000 2:4059d00000000000 3:4054c00000000000 4:402d800000000000 5:4055b00000000000 6:4060680000000000 7:4057a00000000000
|
||||
series __name__=b_bucket|job=z|le=1e400 ; 0:4063500000000000 1:4065580000000000 2:4061600000000000 3:405ae00000000000 4:4049200000000000 5:4059c00000000000 6:4067900000000000 7:405d900000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:406c480000000000 1:4070800000000000 2:406d200000000000 3:4060400000000000 4:404ba00000000000 6:406a580000000000 7:4062c00000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 7ff8000000000001
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=x|le=0.1 ; 0:4053900000000000 1:402b000000000000 2:4045400000000000 4:4020000000000000 5:4053000000000000
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:405a400000000000 1:4048e00000000000 2:404aa00000000000 3:405e700000000000 4:4041600000000000 5:405e100000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:405d400000000000 1:4053000000000000 2:4054f00000000000 3:4067800000000000 5:405e500000000000
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:4069480000000000 1:4058200000000000 2:4064480000000000 3:4068d80000000000 4:4057f00000000000 5:4068c80000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:4070ec0000000000 2:4069000000000000 3:4071b40000000000 5:406a080000000000
|
||||
series __name__=b_bucket|job=z|le=0.25 ; 0:4046000000000000 1:403e000000000000 3:403c000000000000 4:403b000000000000 5:4045800000000000
|
||||
series __name__=b_bucket|job=z|le=2.5 ; 0:4053400000000000 1:4045000000000000 2:40390000000112e1 3:404e000000000000 4:403b000000000000 5:40457ffffffffda3
|
||||
series __name__=b_bucket|job=z|le=inf ; 0:40533fffffff2c58 1:4051000000000000 3:404dfffffffffcb3 5:40457ffffffffda3
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile 3fd0000000000000
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x|le=-1 ; 0:4048800000000000
|
||||
series __name__=a_bucket|job=x|le=0 ; 0:4055800000000000 1:4034000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4056800000000000 1:0
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:c014000000000000 1:4036000000000000
|
||||
result job=x|quantile=0.25 ; 0:bff0000000000000 1:0
|
||||
end
|
||||
case quantiles job 3fefae147ae147ae,3fd0000000000000
|
||||
grid 100000 10000 7
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4026000000000000 1:403a000000000000 5:4043000000000000 6:4000000000000000
|
||||
series __name__=a_bucket|job=x|le=2 ; 0:4046800000000000 1:4051800000000000 2:402e000000000000 3:4014000000000000 4:4040000000000000 5:403f000000000000 6:4041000000000000
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:4030000000000000 1:4028000000000000 2:4052400000000000 3:4056400000000000 4:4041800000000000 5:4055800000000000 6:4050000000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 1:4041800000000000 2:4056e00000000000 3:4048000000000000 4:4052c00000000000 5:4042a00000000000 6:401d000000000000
|
||||
series __name__=a_bucket|job=y|le=2 ; 1:4046800000000000 2:4062180000000000 3:404e400000000000 4:4065800000000000 5:4050e00000000000 6:4056e00000000000
|
||||
series __name__=a_bucket|job=y ; 0:405de00000000000 2:4068180000000000 3:4050000000000000 4:4069700000000000 5:4063d00000000000 6:4066980000000000
|
||||
series __name__=b_bucket|job=z|le=-1 ; 0:4014000000000000 1:4000000000000000 2:402c000000000000 3:403d000000000000 4:7ff8000000000001 5:3ff0000000000000 6:4043800000000000
|
||||
series __name__=b_bucket|job=z|le=0 ; 0:4039000000000000 1:4028000000000000 2:403f000000000000 4:7ff8000000000001 6:c014000000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:0 1:7ff0000000000000 2:4041800000000000 3:0 4:7ff8000000000001 5:c014000000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:7ff0000000000000 1:7ff0000000000000 4:7ff8000000000001 5:7ff0000000000000 6:4046000000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile 3feccccccccccccd
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x ; 0:0
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:0 1:0
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:0 1:0
|
||||
series __name__=a_bucket|job=x|le=5 ; 1:0
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:1a56e1fc2f8f359 1:0
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 1:4058800000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:0 1:0
|
||||
series __name__=b_bucket|job=z|le=abc ; 1:0
|
||||
series __name__=b_bucket|job=z|le=1e400 ; 0:0 1:1a56e1fc2f8f359
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 1:0
|
||||
result job=x|quantile=0.9 ; 0:3ff0000000000000 1:7ff8000000000001
|
||||
result job=y|quantile=0.9 ; 1:7ff8000000000001
|
||||
result job=z|quantile=0.9 ; 0:7ff8000000000001 1:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 3ff0000000000000
|
||||
grid 100000 10000 4
|
||||
series __name__=a_bucket|job=x|le=-1 ; 0:4045000000000000 1:4048800000000000 2:4036000000000000
|
||||
series __name__=a_bucket|job=x ; 0:4046800000000000 1:4053400000000000 2:4058c00000000000 3:4057800000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4051c00000000000 1:4044000000000000 2:4058c00000000000 3:403e000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:4018000000000000 1:4048000000000000 2:4041800000000000
|
||||
series __name__=a_bucket|job=y|le=0.1 ; 0:4022000000000000 2:402e000000000000 3:4042800000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:4024000000000000 2:4043800000000000 3:4042800000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:4023ffffffff2419 1:404a000000000000 2:4043800000000000 3:40427fffffff3497
|
||||
series __name__=a_bucket|job=y ; 0:4032ffffffff920c 1:404a000000000000 2:404380000000d668 3:40427fffffff3497
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:4032ffffffff920c 1:404a000000011de0 2:404380000000d443 3:40437fffffff3497
|
||||
series __name__=b_bucket|job=z|le=0.1 ; 0:7ff0000000000000 1:c014000000000000 2:4043000000000000 3:4008000000000000
|
||||
series __name__=b_bucket|job=z|le=0.5 ; 1:4030000000000000 2:4055800000000000 3:0
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:7ff0000000000000 1:4050400000000000 2:0 3:4037000000000000
|
||||
series __name__=b_bucket|job=z|le=5 ; 1:405a400000000000 2:403f000000000000 3:404b000000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:7ff8000000000001 1:4060600000000000 2:4041800000000000 3:7ff8000000000001
|
||||
result job=x|quantile=1.0 ; 0:3ff0000000000000 1:bff0000000000000 2:3ff0000000000000 3:7ff8000000000001
|
||||
result job=y|quantile=1.0 ; 0:3ff0000000000000 1:3ff0000000000000 2:3ff0000000000000 3:3ff0000000000000
|
||||
result job=z|quantile=1.0 ; 0:3ff0000000000000 1:4014000000000000 2:3fe0000000000000 3:4014000000000000
|
||||
end
|
||||
case quantiles quantile 3fefae147ae147ae
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=y|le=-1 ; 0:4051100000000000 1:4043800000000000 2:4050000000000000 4:4054300000000000 5:4055000000000000
|
||||
series __name__=a_bucket|job=y|le=0 ; 1:4047600000000000 2:4059a00000000000 3:405e000000000000 4:4055f00000000000 5:405a200000000000
|
||||
series __name__=a_bucket|job=y ; 0:4068e80000000000 1:4060900000000000 2:405fd00000000000 3:4063c00000000000 4:4061000000000000 5:4067b80000000000
|
||||
series __name__=b_bucket|job=z|le=-1 ; 0:4055000000000000 2:404a800000000000 3:4052000000000000 4:4024000000000000 5:4051400000000000
|
||||
series __name__=b_bucket|job=z|le=0 ; 1:4010000000000000 2:4053000000000000 3:4044800000000000 5:4032000000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4053c00000000000 1:4024000000000000 2:404a000000000000 3:4047000000000000 4:403e000000000000 5:4047000000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:404c000000000000 1:403d000000000000 2:3ff0000000000000 3:4054400000000000 4:404a000000000000 5:4024000000000000
|
||||
result job=y|quantile=0.99 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001
|
||||
result job=z|quantile=0.99 ; 0:bff0000000000000 1:3ff0000000000000 2:bfa0eb1324f3fad0 3:3ff0000000000000 4:3ff0000000000000 5:bff0000000000000
|
||||
end
|
||||
case quantiles quantile 3fefae147ae147ae
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=y|le=0.25 ; 0:4057800000000000 2:404f000000000000 3:403e000000000000 4:403d000000000000 5:4056c00000000000
|
||||
series __name__=a_bucket|job=y|le=2.5 ; 0:4055400000000000 1:4053400000000000 2:404a800000000000 3:404f000000000000 4:4055400000000000 5:4050c00000000000
|
||||
series __name__=a_bucket|job=y|le=inf ; 0:4044800000000000 1:4034000000000000 2:4041000000000000 3:404f000000000000 4:404f000000000000 5:402a000000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4043800000000000 1:4022000000000000 3:4042800000000000 4:4026000000000000 5:403e000000000000
|
||||
result job=y|quantile=0.99 ; 0:3fcfae147ae147ae 1:4003cccccccccccd 2:3fcfae147ae147ae 3:4003a6b851eb851f 4:4003ba0ea0ea0ea1 5:3fcfae147ae147ae
|
||||
result job=z|quantile=0.99 ; 0:7ff8000000000001 1:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 7ff8000000000001
|
||||
grid 100000 10000 7
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:0 1:0 2:0 3:0 4:0 5:0
|
||||
series __name__=a_bucket|job=x|le=abc ; 0:0 1:0 2:1 3:1 4:0 5:0
|
||||
series __name__=a_bucket|job=x|le=1e400 ; 0:1a56e1fc2f8f359 1:0 2:0 3:0 4:1a56e1fc2f8f359 5:1 6:0
|
||||
series __name__=a_bucket|job=x ; 0:0 1:1a56e1fc2f8f359 2:0 3:0 4:1a56e1fc2f8f359 5:0 6:0
|
||||
series __name__=a_bucket|job=y ; 0:402a000000000000 1:4035000000000000 3:4044000000000000 4:403f000000000000 5:3ff0000000000000 6:4034000000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:404d000000000000 1:4046800000000000 2:4043000000000000 4:4042800000000000 5:4040000000000000 6:403a000000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:405a400000000000 1:4049800000000000 3:405e800000000000 4:404e000000000000 5:4042000000000000 6:4045800000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:7ff0000000000000 1:404c000000000000 2:0 3:4061000000000000 4:4059000000000000 5:0 6:4056400000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 1:4059000000000000 2:4020000000000000 3:4062a00000000000 4:405bc00000000000 5:c014000000000000 6:405e800000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:404b800000000000 2:4052400000000000 4:4044000000000000 5:4047800000000000 6:4050800000000000
|
||||
result job=x|quantile=NaN ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001
|
||||
result job=y|quantile=NaN ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
result job=z|quantile=NaN ; 0:7ff8000000000001 2:7ff8000000000001 4:7ff8000000000001 5:7ff8000000000001 6:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 3fefae147ae147ae,3fefae147ae147ae,7ff8000000000001
|
||||
grid 100000 10000 2
|
||||
series __name__=a_bucket|job=x|le=0.25 ; 0:403a000000000000 1:4030000000000000
|
||||
series __name__=a_bucket|job=x|le=2.5 ; 0:4039fffffffffd24
|
||||
series __name__=a_bucket|job=x|le=inf ; 0:404afffffffffe92 1:404d800000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:4046800000000000
|
||||
series __name__=a_bucket|job=y|le=1.0 ; 0:7ff0000000000000 1:4018000000000000
|
||||
series __name__=a_bucket|job=y|le=2 ; 0:7ff0000000000000 1:4046000000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:7ff0000000000000 1:404b800000000000
|
||||
series __name__=b_bucket|job=z|le=-1 ; 0:404b800000000000 1:4043e00000000000
|
||||
series __name__=b_bucket|job=z|le=0 ; 0:405ec00000000000 1:4060900000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4062f80000000000
|
||||
series __name__=b_bucket|job=z ; 0:406e400000000000 1:406a380000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile 3ff0000000000000,7ff8000000000001,3ff8000000000000
|
||||
grid 100000 10000 1
|
||||
series __name__=a_bucket|job=x|le=0.1 ; 0:403d000000000000
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:403d000000000330
|
||||
series __name__=a_bucket|job=x ;
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:404ffffffffffe13
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:404ffffffffffe13
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:4055000000000000
|
||||
series __name__=a_bucket|job=y|le=abc ; 0:404f800000000000
|
||||
series __name__=a_bucket|job=y|le=1e400 ;
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:4053000000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:404bc00000000000
|
||||
series __name__=b_bucket|job=z|le=1.0 ; 0:4058900000000000
|
||||
series __name__=b_bucket|job=z|le=2 ;
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4065480000000000
|
||||
result job=x|quantile=1.0 ; 0:4014000000000000
|
||||
result job=x|quantile=1.5 ; 0:7ff0000000000000
|
||||
result job=x|quantile=NaN ; 0:7ff8000000000001
|
||||
result job=y|quantile=1.0 ; 0:3ff0000000000000
|
||||
result job=y|quantile=1.5 ; 0:7ff0000000000000
|
||||
result job=y|quantile=NaN ; 0:7ff8000000000001
|
||||
result job=z|quantile=1.0 ; 0:3ff0000000000000
|
||||
result job=z|quantile=1.5 ; 0:7ff0000000000000
|
||||
result job=z|quantile=NaN ; 0:7ff8000000000001
|
||||
end
|
||||
case quantiles quantile 3fd0000000000000,bfe0000000000000,3fefae147ae147ae
|
||||
grid 100000 10000 6
|
||||
series __name__=a_bucket|job=x|le=-1 ; 0:4045000000000000 1:4042000000000000 2:4046000000000000 3:403d000000000000 4:3ff0000000000000
|
||||
series __name__=a_bucket|job=x ; 1:404e800000000000 3:403d000000000330 5:4038000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:405d400000000000 1:4057c00000000000 2:404fffffffff0e1c 3:403d000000000330
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 1:4057c00000010522 2:4057ffffffff870e 3:4041000000000198 4:4030000000000000 5:4048000000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:0 1:0 2:0 3:0 4:0
|
||||
series __name__=a_bucket|job=y|le=2 ; 0:1 2:1a56e1fc2f8f359 3:1 4:0 5:0
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:1a56e1fc2f8f359 1:0 2:0 3:1 4:0
|
||||
series __name__=b_bucket|job=y|le=-1 ; 0:402c000000000000 1:4018000000000000 2:4014000000000000 3:4047000000000000 4:4024000000000000 5:4031000000000000
|
||||
series __name__=b_bucket|job=y|le=0 ; 0:404a800000000000 2:4040800000000000 4:4031000000000000 5:404c800000000000
|
||||
series __name__=b_bucket|job=y|le=1 ; 0:404e800000000000 1:4055000000000000 2:4053400000000000 3:4046fffffffffd78 4:4040800000000000 5:404c800000000322
|
||||
series __name__=b_bucket|job=y|le=+Inf ; 1:4054ffffffff191a 2:4053400000000000 3:4057bffffffffebc 4:404080000000b56b 5:404c800000013c7e
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4037000000000000 1:4048e00000000000 2:4050800000000000 3:404d400000000000 4:4057800000000000
|
||||
series __name__=b_bucket|job=z|le=abc ; 0:405a500000000000 1:405ea00000000000 2:4062a00000000000 4:405f800000000000
|
||||
series __name__=b_bucket|job=z|le=1e400 ; 0:405eb00000000000 1:4067b80000000000 2:406d300000000000 3:406ab00000000000 4:4064b80000000000 5:4062800000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4061000000000000 1:406df00000000000 2:4070100000000000 3:4072040000000000 4:4065280000000000 5:4064880000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 3fe0000000000000,3ff0000000000000,bfe0000000000000
|
||||
grid 100000 10000 1
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4012000000000000
|
||||
series __name__=a_bucket|job=x ; 0:403d000000000000
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:4055f00000000000
|
||||
series __name__=b_bucket|job=z|le=1 ;
|
||||
series __name__=b_bucket|job=z|le=1.0 ; 0:4042000000000000
|
||||
series __name__=b_bucket|job=z|le=2 ; 0:404b000000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:404b000000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 3ff8000000000000,0
|
||||
grid 100000 10000 3
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4041800000000000 1:4024000000000000 2:4000000000000000
|
||||
series __name__=b_bucket|job=z|le=abc ; 0:40417fffffff3f96 1:402e000000000000 2:4000000000000000
|
||||
series __name__=b_bucket|job=z|le=1e400 ; 0:40527fffffff9fcb 1:4045000000000000 2:40000000000001c2
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:405dbfffffff9fcb 1:4044ffffffff191a 2:400000000000b1ae
|
||||
result job=0.0 ; 0:0 1:0 2:0
|
||||
result job=1.5 ; 0:7ff0000000000000 1:7ff0000000000000 2:7ff0000000000000
|
||||
end
|
||||
case quantiles quantile 3ff0000000000000,3fe0000000000000,3fefae147ae147ae
|
||||
grid 100000 10000 4
|
||||
series __name__=a_bucket|job=x|le=0.1 ; 0:c014000000000000 1:4026000000000000 2:4010000000000000 3:0
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:4000000000000000 2:403e000000000000 3:403a000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:4038000000000000 1:4054000000000000 2:404a000000000000 3:4044800000000000
|
||||
series __name__=a_bucket|job=x|le=5 ; 1:4057000000000000 2:404b000000000000 3:4056000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:7ff8000000000001 1:4060400000000000 2:4055c00000000000 3:4061000000000000
|
||||
series __name__=a_bucket|job=y|le=0.1 ; 0:0 1:0 2:0 3:0
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:1 1:0 2:0 3:1
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:1 1:0 2:0 3:1
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:0 2:0 3:1
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:0 1:0 3:0
|
||||
result job=x|quantile=0.5 ; 0:3ff0000000000000 1:3fe9bd37a6f4de9c 2:3fe9d1745d1745d2 3:400a620ae4c415ca
|
||||
result job=x|quantile=0.99 ; 0:3ff0000000000000 1:4014000000000000 2:4014000000000000 3:4014000000000000
|
||||
result job=x|quantile=1.0 ; 0:3ff0000000000000 1:4014000000000000 2:4014000000000000 3:4014000000000000
|
||||
result job=y|quantile=0.5 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001
|
||||
result job=y|quantile=0.99 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001
|
||||
result job=y|quantile=1.0 ; 0:7ff8000000000001 1:7ff8000000000001 2:7ff8000000000001 3:7ff8000000000001
|
||||
end
|
||||
case quantiles job 3fefae147ae147ae
|
||||
grid 100000 10000 1
|
||||
series __name__=a_bucket|job=x|le=0.25 ; 0:4055e00000000000
|
||||
series __name__=a_bucket|job=x|le=2.5 ; 0:4059200000000000
|
||||
series __name__=a_bucket|job=x|le=inf ; 0:405b200000000000
|
||||
series __name__=a_bucket|job=y|le=1 ; 0:4051300000000000
|
||||
series __name__=a_bucket|job=y|le=2 ; 0:4057800000000000
|
||||
series __name__=a_bucket|job=y|le=5 ; 0:4058b00000000000
|
||||
series __name__=b_bucket|job=z|le=-1 ; 0:4051c00000000000
|
||||
series __name__=b_bucket|job=z|le=0 ; 0:4060400000000000
|
||||
series __name__=b_bucket|job=z|le=1 ; 0:4065280000000000
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4066880000000000
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles job 3fe0000000000000,3fe0000000000000
|
||||
grid 100000 10000 5
|
||||
series __name__=a_bucket|job=x|le=0.1 ; 0:4008000000000000 3:4022000000000000 4:403a000000000000
|
||||
series __name__=a_bucket|job=x|le=0.5 ; 0:4032000000000000 1:4053400000000000 3:40220000000001fa 4:4040000000000000
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:40320000000001fa 1:40533fffffff2c58 2:404200000000c5ea 3:404c80000000007e
|
||||
series __name__=a_bucket|job=x|le=5 ; 0:40320000000003f4 2:4042000000018bd4 4:4054000000000000
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 1:40533fffffff2c57 2:40420000000251be 3:404c7ffffffd8dc6 4:4053ffffffff2419
|
||||
series __name__=b_bucket|job=y|le=1 ; 0:4050c00000000000 2:4055500000000000 3:4044c00000000000 4:4047000000000000
|
||||
series __name__=b_bucket|job=y|le=1.0 ; 0:405b000000000000 1:405f400000000000 2:4066c00000000000 3:4054500000000000 4:404b800000000000
|
||||
series __name__=b_bucket|job=y|le=2 ; 0:405e400000000000 1:406a500000000000 2:406b980000000000 4:405d100000000000
|
||||
series __name__=b_bucket|job=y|le=+Inf ; 0:4060b80000000000 1:4072180000000000 2:406e400000000000 3:4067500000000000 4:4067580000000000
|
||||
series __name__=b_bucket|job=z|le=-1 ; 0:0 1:0 2:0 3:0 4:0
|
||||
series __name__=b_bucket|job=z|le=0 ; 0:1 1:0 3:1a56e1fc2f8f359 4:0
|
||||
series __name__=b_bucket|job=z ; 0:1 1:0 2:1a56e1fc2f8f359 3:0 4:0
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:0 1:1 3:0
|
||||
error vector cannot contain metrics with the same labelset
|
||||
end
|
||||
case quantiles quantile bfe0000000000000,0
|
||||
grid 100000 10000 8
|
||||
series __name__=a_bucket|job=x|le=1 ; 0:0 1:0 5:0 6:0
|
||||
series __name__=a_bucket|job=x ; 0:1a56e1fc2f8f359 1:0 2:0 3:0 4:0 5:0 6:0 7:1
|
||||
series __name__=a_bucket|job=x|le=2 ; 0:1 1:1a56e1fc2f8f359 2:0 3:1 4:0 5:0 6:1a56e1fc2f8f359 7:0
|
||||
series __name__=a_bucket|job=x|le=+Inf ; 0:0 1:0 2:1 3:0 4:1a56e1fc2f8f359 5:0 6:0 7:0
|
||||
series __name__=a_bucket|job=y|le=0.1 ; 0:403b000000000000 1:4040000000000000 2:4018000000000000 3:4008000000000000 4:4042000000000000 5:403c000000000000 6:4045800000000000 7:4032000000000000
|
||||
series __name__=a_bucket|job=y|le=0.5 ; 0:4052000000000000 1:404b800000000000 2:4017fffffffffd5c 3:4008000000000000 5:403c000000000000 6:4045800000000000 7:4032000000000000
|
||||
series __name__=a_bucket|job=y ; 0:405bc00000000000 1:404b800000012e5e 2:4017fffffffef57a 3:4030000000000000 4:4051400000000000 7:4045000000000000
|
||||
series __name__=a_bucket|job=y|le=+Inf ; 0:4061c0000000c32a 1:404e000000012e5e 2:402ffffffffef6cc 3:402ffffffffea028 4:405ac00000000000 5:40587fffffffff3b 6:40458000000004ba
|
||||
series __name__=b_bucket|job=z ; 0:4000000000000000 1:4043000000000000 2:402a000000000000 3:403c000000000000 4:4043800000000000 5:4043800000000000 6:4020000000000000 7:0
|
||||
series __name__=b_bucket|job=z|le=1.0 ; 0:4014000000000000 1:4050400000000000 2:402a000000000000 3:4046000000000000 4:4049800000000000 5:4055c00000000000 6:4039000000000000 7:403c000000000000
|
||||
series __name__=b_bucket|job=z|le=2 ; 0:4018000000000000 1:4056400000000000 2:402a0000000002db 3:4046000000000000 4:40497ffffffee7a0 5:405f800000000000 6:4038fffffffeed1f 7:403c0000000133dd
|
||||
series __name__=b_bucket|job=z|le=+Inf ; 0:4047800000000000 1:405640000000f4a4 2:40418000000000b7 3:404600000000f1e4 4:40497ffffffee7a0 5:405f800000000376 6:4038fffffffeed1f 7:403c000000000000
|
||||
result job=x|quantile=-0.5 ; 0:fff0000000000000 1:fff0000000000000 2:fff0000000000000 3:fff0000000000000 4:fff0000000000000 5:fff0000000000000 6:fff0000000000000 7:fff0000000000000
|
||||
result job=x|quantile=0.0 ; 0:7ff8000000000001 1:fff8000000000000 2:7ff8000000000001 3:0 4:fff8000000000000 5:7ff8000000000001 6:fff8000000000000 7:7ff8000000000001
|
||||
result job=y|quantile=-0.5 ; 0:fff0000000000000 1:fff0000000000000 2:fff0000000000000 3:fff0000000000000 4:fff0000000000000 5:fff0000000000000 6:fff0000000000000 7:fff0000000000000
|
||||
result job=y|quantile=0.0 ; 0:0 1:0 2:0 3:0 4:0 5:0 6:0 7:7ff8000000000001
|
||||
result job=z|quantile=-0.5 ; 0:fff0000000000000 1:fff0000000000000 2:fff0000000000000 3:fff0000000000000 4:fff0000000000000 5:fff0000000000000 6:fff0000000000000 7:fff0000000000000
|
||||
result job=z|quantile=0.0 ; 0:0 1:0 2:0 3:0 4:0 5:0 6:0 7:0
|
||||
end
|
||||
@@ -22,7 +22,7 @@ use datatypes::series::time::{EvalGrid, GridRange, GridSpec, TimeAxis};
|
||||
use super::float_histogram::{AddOutcome, FloatHistogram};
|
||||
use super::{
|
||||
HistogramAggregate, HistogramFunction, NativeHistogramFunction, aggregate_histograms,
|
||||
evaluate_histograms, map_native_histogram,
|
||||
evaluate_histograms, histogram_quantiles, map_native_histogram,
|
||||
};
|
||||
use crate::grid_series::merge_same_labelset;
|
||||
use crate::grid_series::reference::{
|
||||
@@ -127,6 +127,30 @@ fn classic_histograms_match_prometheus() {
|
||||
assert!(failed > 20, "{failed} failed");
|
||||
}
|
||||
|
||||
/// `histogram_quantiles` over classic histograms, evaluated by the Prometheus v3.15.0 engine with
|
||||
/// experimental functions enabled (promql-compat `narthex-golden-histogram -quantiles`).
|
||||
#[test]
|
||||
fn histogram_quantiles_match_prometheus() {
|
||||
let cases = golden_cases(include_str!("quantiles_cases.txt"));
|
||||
assert_eq!(cases.len(), 30);
|
||||
let mut failed = 0;
|
||||
for case in &cases {
|
||||
let schema = schema(case);
|
||||
let input: Vec<_> = case
|
||||
.inputs
|
||||
.iter()
|
||||
.filter_map(|(labels, points)| mixed_series(&schema, labels, points, &BTreeMap::new()))
|
||||
.collect();
|
||||
let quantiles: Vec<f64> = case.spec[2]
|
||||
.split(',')
|
||||
.map(|bits| f64::from_bits(u64::from_str_radix(bits, 16).unwrap()))
|
||||
.collect();
|
||||
let actual = histogram_quantiles(&case.spec[1], &quantiles, &schema, &input);
|
||||
failed += usize::from(assert_outcome(case, actual, &case.outcome));
|
||||
}
|
||||
assert!(failed > 5, "{failed} failed");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn native_histograms_match_prometheus() {
|
||||
let cases = golden_cases(include_str!("native_cases.txt"));
|
||||
|
||||
@@ -17,6 +17,7 @@ pub mod error;
|
||||
pub mod evaluated;
|
||||
pub mod extension_plan;
|
||||
pub mod functions;
|
||||
mod go_format;
|
||||
mod go_sort;
|
||||
#[cfg(test)]
|
||||
mod golden;
|
||||
|
||||
Reference in New Issue
Block a user