# 098 — No histogram_quantile()-style percentile query

## Summary

The PromQL layer's `histogram()` op buckets raw sample values by a
fixed width and returns per-bucket counts — it's unrelated to
Prometheus's classic histogram bucket/quantile model, and there's no
way to ask for p50/p95/p99 out of a metric today.

## Where

- `src/engine/promql.rs:9-16` — `AggOp::Histogram` is one of the six
  supported ops.
- `src/engine/snapshot/mod.rs:1002` onward — `Histogram` evaluation:
  buckets values by `bucket_width` into counts, grouped by
  `by_labels`. This answers "how many samples fell in each bucket",
  not "what value is the Nth percentile".
- No `histogram_quantile()` function or equivalent exists anywhere in
  `promql.rs`'s parser (`parse_query`, `:261-324` recognizes only
  `sum`, `avg`, `count`, `rate`, `histogram`, `gauge`).
- Depends on ticket 097 (gauge/counter semantics) for the broader
  question of whether a metric needs a declared "this holds raw
  observations for quantile purposes" flag, but quantile computation
  itself doesn't strictly require that — it can operate on whatever
  raw values are already stored in a metric's buckets.

## Scope

- Decide the quantile computation model: interpolate over the raw
  stored sample values in a bucket/window (simplest, exact for the
  data actually retained) vs. building a genuine bucketed-histogram
  representation with configurable bucket boundaries (closer to
  Prometheus's classic histograms, more work, needed only if retained
  raw values are later dropped in favor of pre-aggregated buckets).
- Add a `histogram_quantile(p, metric[range])`-shaped PromQL construct
  (or extend `histogram()` with a quantile argument) to
  `promql.rs`'s parser and `AggOp`, plus an evaluator in
  `snapshot/mod.rs` alongside the existing `Histogram` handling.
- Add dashboard/panel UI support for selecting a quantile once the
  query-language side exists (`webapp/src/components/Dashboards.tsx`
  or wherever panel query construction lives).