Consolidate EngineSnapshot's impl blocks into snapshot/mod.rs
They were scattered across filter/metrics/params/query/sort.rs by an earlier file-splitting pass. Files can be split as much as needed, but a single type's impl should never be split across files — so all 15 impl EngineSnapshot blocks now live in mod.rs, while each submodule keeps its own types, free helper functions, and tests. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TeyhRfMYjMditek6geDRoQ
This commit is contained in:
Hugh Kaznowski
co-authored by
Claude Sonnet 5
Claude Sonnet 5
parent
7df6026a21
commit
1b2f690278
+10
-184
@@ -2,15 +2,15 @@
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//! stats, declaration listing, bucket-value listing, and PromQL evaluation.
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use crate::api::dto::{
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BucketValueDto, LogEntryDto, MetricDeclarationDto, ParamDeclarationDto, PromqlSeriesDto,
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BucketValueDto, LogEntryDto, MetricDeclarationDto, ParamDeclarationDto,
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StatsDto, TimelineBucketDto,
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};
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use crate::consts::{DEFAULT_TIMELINE_BUCKET_MS, MERGE_WINDOW_MS};
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use crate::engine::data_value::{DataValue, MetricPrimitiveKind};
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use crate::engine::data_value::DataValue;
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use crate::engine::index_key::IndexKey;
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use crate::engine::message::{EngineQuery, EngineResponse};
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use crate::engine::metric_primitive::{MetricPrimitive, Number};
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use crate::engine::promql::{AggOp, LabelMatcher, PromqlQuery};
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use crate::engine::promql::{LabelMatcher, PromqlQuery};
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use crate::engine::rate;
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#[cfg(test)]
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use crate::engine::snapshot::sort::SortHelperIndexEntry;
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@@ -263,7 +263,7 @@ pub(super) fn handle_query_inner(
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}
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}
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fn coerce_to_f64(value: &MetricPrimitive) -> f64 {
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pub(crate) fn coerce_to_f64(value: &MetricPrimitive) -> f64 {
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match value {
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MetricPrimitive::Number(n) => match n {
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Number::Int(v) => *v as f64,
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@@ -282,7 +282,7 @@ fn coerce_to_f64(value: &MetricPrimitive) -> f64 {
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}
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}
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fn matches_label_matchers(
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pub(crate) fn matches_label_matchers(
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labels: &BTreeMap<String, MetricPrimitive>,
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matchers: &[LabelMatcher],
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) -> bool {
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@@ -291,7 +291,7 @@ fn matches_label_matchers(
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})
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}
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fn project_labels(
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pub(crate) fn project_labels(
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labels: &BTreeMap<String, String>,
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by_labels: &[String],
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) -> BTreeMap<String, String> {
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@@ -301,7 +301,7 @@ fn project_labels(
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.collect()
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}
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fn windowed_rate_series(
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pub(crate) fn windowed_rate_series(
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points: &[(i64, f64)],
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range_ms: i64,
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start_ms: Option<i64>,
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@@ -329,7 +329,7 @@ fn windowed_rate_series(
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series
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}
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fn merge_series_windowed(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i64, f64)> {
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pub(crate) fn merge_series_windowed(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i64, f64)> {
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if sub_series.len() <= 1 {
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return sub_series.first().cloned().unwrap_or_default();
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}
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@@ -350,7 +350,7 @@ fn merge_series_windowed(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i
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.collect()
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}
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fn merge_series_locf(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i64, f64)> {
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pub(crate) fn merge_series_locf(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i64, f64)> {
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let mut all_timestamps: std::collections::BTreeSet<i64> = std::collections::BTreeSet::new();
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for points in sub_series {
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all_timestamps.extend(points.iter().map(|(ts, _)| *ts));
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@@ -373,184 +373,10 @@ fn merge_series_locf(sub_series: &[Vec<(i64, f64)>], is_avg: bool) -> Vec<(i64,
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.collect()
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}
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fn ottyl_reserved_numeric_value_fn(metric_name: &str) -> Option<fn(u64, i64) -> f64> {
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pub(crate) fn ottyl_reserved_numeric_value_fn(metric_name: &str) -> Option<fn(u64, i64) -> f64> {
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match metric_name {
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"ottyl_seq" => Some(|sequence, _timestamp_ms| sequence as f64),
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"ottyl_ts" => Some(|_sequence, timestamp_ms| timestamp_ms as f64),
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_ => None,
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}
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}
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impl EngineSnapshot {
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pub(crate) fn evaluate_promql(
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&self,
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parsed: &PromqlQuery,
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start_ms: Option<i64>,
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end_ms: Option<i64>,
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) -> Result<Vec<PromqlSeriesDto>, String> {
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if parsed.metric_name == "ottyl_fmt" {
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return Err(
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"'ottyl_fmt' is a categorical value (json/logfmt/none), not a number, so it can't be \
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used in a dashboard PromQL query; filter on it in the search bar instead, e.g. \
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ottyl_fmt==json"
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.to_string(),
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);
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}
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if ottyl_reserved_numeric_value_fn(&parsed.metric_name).is_none()
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&& !self.index.contains_key(&IndexKey::MetricDeclaration { name: parsed.metric_name.clone() })
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&& self.bucket_values(&parsed.metric_name, None).next().is_none()
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{
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return Err(format!(
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"unknown metric \"{}\": no declaration or recorded data for it (was it deleted?)",
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parsed.metric_name
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));
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}
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if matches!(parsed.agg, Some(AggOp::Sum) | Some(AggOp::Avg))
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&& !parsed.inner_rate
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&& self.declared_value_kind(&parsed.metric_name) == Some(MetricPrimitiveKind::String)
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{
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return Err(format!(
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"cannot sum/avg a string-typed metric \"{}\"; use count() or a numeric-typed metric",
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parsed.metric_name
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));
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}
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let mut series_points: BTreeMap<BTreeMap<String, String>, Vec<(i64, f64)>> = BTreeMap::new();
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if let Some(reserved_value) = ottyl_reserved_numeric_value_fn(&parsed.metric_name) {
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let no_labels: BTreeMap<String, MetricPrimitive> = BTreeMap::new();
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if matches_label_matchers(&no_labels, &parsed.matchers) {
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for (sequence, timestamp, _text) in self.logs_range() {
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let timestamp_ms = timestamp.as_millis();
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if start_ms.is_none_or(|start| timestamp_ms >= start)
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&& end_ms.is_none_or(|end| timestamp_ms <= end)
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{
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series_points
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.entry(BTreeMap::new())
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.or_default()
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.push((timestamp_ms, reserved_value(sequence, timestamp_ms)));
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}
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}
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}
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} else {
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for (labels, (_, timestamp, value)) in self.bucket_values(&parsed.metric_name, None)
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.filter(|(labels, _)| matches_label_matchers(labels, &parsed.matchers))
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.filter(|(_, (_, timestamp, _))| {
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start_ms.is_none_or(|start| timestamp.as_millis() >= start)
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&& end_ms.is_none_or(|end| timestamp.as_millis() <= end)
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})
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{
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let display_labels: BTreeMap<String, String> =
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labels.iter().map(|(name, value)| (name.clone(), value.to_string())).collect();
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series_points
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.entry(display_labels)
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.or_default()
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.push((timestamp.as_millis(), coerce_to_f64(value)));
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}
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}
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for points in series_points.values_mut() {
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points.sort_by_key(|(timestamp_ms, _)| *timestamp_ms);
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}
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Ok(match parsed.agg {
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None => series_points
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.into_iter()
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.map(|(labels, points)| PromqlSeriesDto { labels, points })
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.collect(),
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Some(AggOp::Count) => {
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let mut groups: BTreeMap<BTreeMap<String, String>, Vec<Vec<(i64, f64)>>> = BTreeMap::new();
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for (labels, points) in series_points {
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let count_points: Vec<(i64, f64)> =
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points.iter().map(|(timestamp_ms, _)| (*timestamp_ms, 1.0)).collect();
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let group_key = project_labels(&labels, &parsed.by_labels);
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groups.entry(group_key).or_default().push(count_points);
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}
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groups
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.into_iter()
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.map(|(group_labels, sub_series)| {
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let points = merge_series_windowed(&sub_series, false);
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PromqlSeriesDto { labels: group_labels, points }
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})
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.collect()
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}
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Some(AggOp::Sum) | Some(AggOp::Avg) => {
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let is_avg = parsed.agg == Some(AggOp::Avg);
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let rate_range_ms = parsed
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.inner_rate
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.then(|| parsed.range.expect("inner rate() always carries a range").as_millis() as i64);
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let mut groups: BTreeMap<BTreeMap<String, String>, Vec<Vec<(i64, f64)>>> = BTreeMap::new();
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for (labels, points) in series_points {
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let points = match rate_range_ms {
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Some(range_ms) => windowed_rate_series(&points, range_ms, start_ms, end_ms),
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None => points,
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};
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let group_key = project_labels(&labels, &parsed.by_labels);
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groups.entry(group_key).or_default().push(points);
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}
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groups
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.into_iter()
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.map(|(group_labels, sub_series)| {
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let points = if rate_range_ms.is_some() {
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merge_series_locf(&sub_series, is_avg)
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} else {
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merge_series_windowed(&sub_series, is_avg)
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};
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PromqlSeriesDto { labels: group_labels, points }
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})
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.collect()
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}
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Some(AggOp::Rate) => {
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let range_ms = parsed.range.expect("rate() always carries a range").as_millis() as i64;
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series_points
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.into_iter()
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.map(|(labels, points)| PromqlSeriesDto {
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labels,
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points: windowed_rate_series(&points, range_ms, start_ms, end_ms),
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})
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.collect()
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}
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Some(AggOp::Gauge) => {
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series_points
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.into_iter()
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.filter_map(|(labels, points)| {
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let last = *points.last()?;
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Some(PromqlSeriesDto { labels, points: vec![last] })
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})
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.collect()
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}
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Some(AggOp::Histogram) => {
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let bucket_width =
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parsed.bucket_width.expect("histogram() always carries a bucket width");
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let last_ts = series_points
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.values()
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.flat_map(|points| points.iter().map(|(ts, _)| *ts))
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.max()
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.unwrap_or(0);
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let mut groups: BTreeMap<BTreeMap<String, String>, Vec<&(i64, f64)>> = BTreeMap::new();
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for (labels, points) in &series_points {
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let group_key = project_labels(labels, &parsed.by_labels);
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groups.entry(group_key).or_default().extend(points.iter());
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}
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groups
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.into_iter()
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.flat_map(|(group_labels, points)| {
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let mut counts: BTreeMap<i64, u64> = BTreeMap::new();
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for (_, value) in points {
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let bucket_index = (value / bucket_width).floor() as i64;
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*counts.entry(bucket_index).or_insert(0) += 1;
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}
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counts.into_iter().map(move |(bucket_index, count)| {
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let upper_bound = (bucket_index + 1) as f64 * bucket_width;
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let mut labels = group_labels.clone();
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labels.insert("le".to_string(), upper_bound.to_string());
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PromqlSeriesDto { labels, points: vec![(last_ts, count as f64)] }
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})
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})
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.collect()
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}
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})
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}
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}
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