refactor(prometheus): serve the Prometheus query API from a /prometheus prefix

Moves the Prometheus HTTP query API out of the legacy query-service handler
into pkg/prometheus/promapi, served under /prometheus:

- GET|POST /prometheus/api/v1/query_range and /query: Prometheus parameter
  parsing (float-unix or RFC3339 times, float-seconds or duration-string
  durations), the Prometheus error envelope ({status, errorType, error}
  with 400/422/503), the 11,000-point cap, documented in openapi.yml.
- Removes the legacy GET /api/v1/query_range and /api/v1/query handlers
  and their now-dead plumbing (parseMetricsTime, parseMetricsDuration,
  parseInstantQueryMetricsRequest, parseQueryRangeRequest,
  GetInstantQueryMetricsResult, InstantQueryMetricsParams).
  GetQueryRangeResult stays - legacy dashboard queriers use it.

This is the breaking slice of the stack, deliberately last: everything
before it is invisible to API consumers.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

docs/api/openapi.yml

@@ -24695,6 +24695,149 @@ paths:
       summary: Replace variables
       tags:
       - querier
+  /prometheus/api/v1/query:
+    get:
+      deprecated: false
+      description: Evaluate a PromQL expression at a single instant. Request and
+        response follow the Prometheus HTTP API (https://prometheus.io/docs/prometheus/latest/querying/api/);
+        the /prometheus prefix distinguishes these PromQL-only endpoints from the
+        SigNoz query APIs. Also accepts POST with form-encoded parameters.
+      operationId: PrometheusInstantQuery
+      parameters:
+      - description: PromQL expression to evaluate
+        in: query
+        name: query
+        required: true
+        schema:
+          type: string
+      - description: 'Evaluation timestamp: float unix seconds or RFC3339. Defaults
+          to the server''s current time.'
+        in: query
+        name: time
+        schema:
+          type: string
+      - description: 'Evaluation timeout: float seconds or a Prometheus duration
+          string (e.g. 30s).'
+        in: query
+        name: timeout
+        schema:
+          type: string
+      - description: Set to any value to include query statistics in the response.
+        in: query
+        name: stats
+        schema:
+          type: string
+      responses:
+        "200":
+          content:
+            application/json:
+              schema:
+                properties:
+                  data:
+                    properties:
+                      result: {}
+                      resultType:
+                        enum:
+                        - matrix
+                        - vector
+                        - scalar
+                        - string
+                        type: string
+                      stats: {}
+                    type: object
+                  status:
+                    enum:
+                    - success
+                    type: string
+                type: object
+          description: Query evaluated successfully
+        "400":
+          description: Unparsable expression or parameters (errorType bad_data)
+        "422":
+          description: Expression failed to evaluate (errorType execution)
+        "503":
+          description: Query timed out or was canceled
+      summary: Prometheus instant query
+      tags:
+      - prometheus
+  /prometheus/api/v1/query_range:
+    get:
+      deprecated: false
+      description: Evaluate a PromQL expression over a range of time on a fixed
+        step grid. Request and response follow the Prometheus HTTP API
+        (https://prometheus.io/docs/prometheus/latest/querying/api/); the
+        /prometheus prefix distinguishes these PromQL-only endpoints from the
+        SigNoz query APIs. Grids are capped at 11,000 points per series. Also
+        accepts POST with form-encoded parameters.
+      operationId: PrometheusRangeQuery
+      parameters:
+      - description: PromQL expression to evaluate
+        in: query
+        name: query
+        required: true
+        schema:
+          type: string
+      - description: 'Start timestamp: float unix seconds or RFC3339.'
+        in: query
+        name: start
+        required: true
+        schema:
+          type: string
+      - description: 'End timestamp: float unix seconds or RFC3339.'
+        in: query
+        name: end
+        required: true
+        schema:
+          type: string
+      - description: 'Grid step: float seconds or a Prometheus duration string
+          (e.g. 30s). Must be positive.'
+        in: query
+        name: step
+        required: true
+        schema:
+          type: string
+      - description: 'Evaluation timeout: float seconds or a Prometheus duration
+          string (e.g. 30s).'
+        in: query
+        name: timeout
+        schema:
+          type: string
+      - description: Set to any value to include query statistics in the response.
+        in: query
+        name: stats
+        schema:
+          type: string
+      responses:
+        "200":
+          content:
+            application/json:
+              schema:
+                properties:
+                  data:
+                    properties:
+                      result: {}
+                      resultType:
+                        enum:
+                        - matrix
+                        type: string
+                      stats: {}
+                    type: object
+                  status:
+                    enum:
+                    - success
+                    type: string
+                type: object
+          description: Query evaluated successfully
+        "400":
+          description: Unparsable expression or parameters, or a grid past the 11,000-point
+            cap (errorType bad_data)
+        "422":
+          description: Expression failed to evaluate (errorType execution)
+        "503":
+          description: Query timed out or was canceled
+      summary: Prometheus range query
+      tags:
+      - prometheus
 servers:
 - description: The fully qualified URL to the SigNoz APIServer.
   url: https://{host}:{port}{base_path}

pkg/prometheus/clickhouseprometheusv2/classification_golden_test.go

@@ -0,0 +1,119 @@
+package clickhouseprometheusv2
+
+import (
+	"encoding/json"
+	"flag"
+	"os"
+	"path/filepath"
+	"sort"
+	"testing"
+
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/stretchr/testify/require"
+)
+
+var updateGolden = flag.Bool("update", false, "rewrite the classification golden file")
+
+const goldenFile = "testdata/classification_golden.json"
+
+// corpusFile is the conformance corpus the integration suite replays; the
+// golden freezes how the classifier routes every one of its expressions.
+const corpusFile = "../../../tests/integration/testdata/promqltestcorpus/corpus.json"
+
+type goldenEntry struct {
+	Expr    string `json:"expr"`
+	StartMs int64  `json:"start_ms"`
+	EndMs   int64  `json:"end_ms"`
+	StepMs  int64  `json:"step_ms"`
+	// Plan is the routing decision: "full" (whole query in ClickHouse),
+	// "hybrid" (units substituted, engine on top), "fallback" (engine over
+	// the native querier).
+	Plan string `json:"plan"`
+	// Units is the substituted-unit count for hybrid plans.
+	Units int `json:"units,omitempty"`
+	// Reason is the coarse fallback bucket (fallbackShape).
+	Reason string `json:"reason,omitempty"`
+}
+
+// TestClassificationGolden freezes the classifier's routing decision for
+// every (expression, grid) of the conformance corpus. Routing is a
+// correctness surface of its own: a change that silently sends rate() to the
+// engine path costs the pushdown, and one that silently starts transpiling a
+// shape never proven equivalent risks wrong numbers — both must show up in
+// review as a diff of this file, with the corpus suite's clickhousev2 leg
+// judging whether the new routing still returns the reference answers.
+//
+// Regenerate after intentional classifier changes:
+//
+//	go test ./pkg/prometheus/clickhouseprometheusv2 -run TestClassificationGolden -update
+func TestClassificationGolden(t *testing.T) {
+	raw, err := os.ReadFile(corpusFile)
+	require.NoError(t, err)
+
+	var corpus struct {
+		Cases []struct {
+			Expr    string `json:"expr"`
+			StartMs int64  `json:"start_ms"`
+			EndMs   int64  `json:"end_ms"`
+			StepMs  int64  `json:"step_ms"`
+		} `json:"cases"`
+	}
+	require.NoError(t, json.Unmarshal(raw, &corpus))
+	require.NotEmpty(t, corpus.Cases)
+
+	promParser := parser.NewParser(parser.Options{})
+	seen := map[goldenEntry]bool{}
+	var entries []goldenEntry
+	for _, c := range corpus.Cases {
+		key := goldenEntry{Expr: c.Expr, StartMs: c.StartMs, EndMs: c.EndMs, StepMs: c.StepMs}
+		if seen[key] {
+			continue
+		}
+		seen[key] = true
+
+		expr, err := promParser.ParseExpr(c.Expr)
+		require.NoError(t, err, "corpus expression must parse: %q", c.Expr)
+
+		entry := key
+		plan, ok := classify(expr, gridContext{startMs: c.StartMs, endMs: c.EndMs, stepMs: c.StepMs})
+		switch {
+		case ok && plan.full:
+			entry.Plan = "full"
+		case ok:
+			entry.Plan = "hybrid"
+			entry.Units = len(plan.units)
+		default:
+			entry.Plan = "fallback"
+			entry.Reason = fallbackShape(expr)
+		}
+		entries = append(entries, entry)
+	}
+	sort.Slice(entries, func(i, j int) bool {
+		a, b := entries[i], entries[j]
+		if a.Expr != b.Expr {
+			return a.Expr < b.Expr
+		}
+		if a.StartMs != b.StartMs {
+			return a.StartMs < b.StartMs
+		}
+		if a.EndMs != b.EndMs {
+			return a.EndMs < b.EndMs
+		}
+		return a.StepMs < b.StepMs
+	})
+
+	got, err := json.MarshalIndent(entries, "", "  ")
+	require.NoError(t, err)
+	got = append(got, '\n')
+
+	if *updateGolden {
+		require.NoError(t, os.MkdirAll(filepath.Dir(goldenFile), 0o755))
+		require.NoError(t, os.WriteFile(goldenFile, got, 0o644))
+		return
+	}
+
+	want, err := os.ReadFile(goldenFile)
+	require.NoError(t, err, "golden missing — generate it with -update")
+	require.Equal(t, string(want), string(got),
+		"classification routing changed; if intentional, regenerate with -update and justify the diff in review")
+}

pkg/prometheus/clickhouseprometheusv2/doc.go

@@ -2,48 +2,336 @@
 // Prometheus provider. It exists because the v1 provider fetches every raw
 // sample of a query's union window through the remote-read protobuf layer
 // and hands it to the engine — the cost is a function of ingested data, not
-// of the question asked. Here the stock promql engine evaluates over a
-// native storage.Querier: no translation layer, per-selector fetch windows,
-// and fetch reductions that are provably invisible to the engine. Every
-// reduction either preserves engine semantics exactly or is not performed.
+// of the question asked, which is how a dashboard of PromQL panels takes an
+// instance down.
+//
+// Every query runs in one of two ways, decided per query:
+//
+//   - Transpiled: the query is evaluated entirely inside ClickHouse and only
+//     final (or near-final) per-group grid arrays come back, built on the
+//     timeSeries*ToGrid aggregate functions (the supported ClickHouse floor
+//     is >= 25.6, so they are assumed available).
+//   - Engine: the stock promql engine evaluates over this package's native
+//     storage.Querier. This is the path for everything not transpilable.
+//
+// Correctness is the constraint that shaped both paths: a PromQL result that
+// differs from upstream Prometheus is a lost user, so anything that cannot
+// reproduce engine semantics exactly falls back rather than approximate.
+// The rest of this comment is the PromQL -> SQL story, because that mapping
+// is where correctness is won or lost.
+//
+// # The evaluation model the SQL must reproduce
+//
+// A PromQL range query is an instant query evaluated at every grid point
+// t_i = start + i*step, i = 0..(end-start)/step. At each t_i:
+//
+//   - an instant selector resolves to the latest sample in the left-open
+//     lookback window (t_i - lookback, t_i], and to nothing when that latest
+//     sample is a stale marker — even if older real samples sit inside the
+//     window;
+//   - a range selector [r] collects every sample in (t_i - r, t_i], stale
+//     markers excluded;
+//   - offset d shifts both windows to (t_i - d - w, t_i - d].
+//
+// The transpilation invariant follows from this: every transpiled construct
+// produces, per output series, one array with exactly one slot per grid
+// point — slot i holds the value at t_i, NULL means absent. This is what
+// makes composition correct, not just convenient: the engine evaluates
+// these operators independently per t_i, so any representation that gets
+// every slot right gets the whole query right, and spatial aggregation over
+// arrays is sound because it combines values that belong to the same t_i by
+// construction. Slot index i maps back to t_i = start + i*step at scan time
+// (toMatrix). Everything below is about filling those slots with exactly
+// the numbers the engine would compute — and each equivalence was validated
+// against the vendored engine on live data before its shape entered the
+// allowlist; anything unproven stays on the engine path.
+//
+// # Classification: finding what a statement can answer
+//
+// classify walks the parsed AST looking for "core units" — maximal subtrees
+// of the shape
+//
+//	[agg by/without (...)] [fn(] selector[range] [offset d] [)] [op scalar]...
+//
+// classifyCore peels that chain from the outside in: an optional
+// sum/min/max/avg/count aggregation, then one of the allowlisted functions
+// or a bare instant selector, then the selector with its offset; on the way
+// out it accumulates number-literal arithmetic, comparisons (including
+// bool) and unary minus into a scalar-op pipeline. A node qualifies only if
+// its type, arguments and children are in the proven set — an allowlist, so
+// an overlooked construct becomes a fallback instead of a wrong number.
+//
+// Three unit kinds come out of this, each with its own SQL form:
+// unitRange (rate, irate, increase, delta, idelta over a range selector),
+// unitInstant (instant vector selection, bare or comparison-filtered) and
+// unitOverTime (avg/min/max/sum/count/last _over_time).
+//
+// If the entire tree is one unit, the plan is "full": the statement's rows
+// are the query result. Otherwise every maximal unit is cut out and replaced
+// in the expression with a synthetic selector __signoz_transpiled_N__, and
+// the rewritten expression runs in the engine over the units' materialized
+// results ("hybrid") — histogram_quantile, topk, or/and/unless and vector
+// matching keep exact engine semantics while their expensive inputs were
+// aggregated server-side.
+//
+// Classification refuses when exact semantics cannot be guaranteed
+// server-side: the @ modifier anywhere and default-resolution subqueries
+// (their resolution is a server runtime setting the transpiler cannot see);
+// duration expressions (offset step(), [range()], ...) anywhere — they are
+// resolved into the selector's static fields only at evaluation time, so at
+// classification time those fields still hold their zero values and
+// transpiling would silently use the wrong offset or range;
+// steps or ranges that are not whole seconds (the grid functions take
+// whole-second parameters); grouping by or matching on __name__ in hybrid
+// plans (the synthetic name would leak into results); name-keeping units —
+// bare/comparison instant selectors and last_over_time keep their real
+// __name__ (keepsName), which substitution would replace, so they transpile
+// only as full plans; and every function outside the allowlist (changes,
+// resets, quantile_over_time, absent, native-histogram functions, ...).
+//
+// Units inside a fixed-resolution subquery evaluate on the subquery's own
+// grid instead of the query grid: epoch-aligned multiples of the resolution
+// strictly after outerStart - offset - range, ending at outer end - offset —
+// the exact derivation the engine uses, because a grid shifted by one step
+// changes which samples every window sees.
+//
+// # From one unit to one statement
+//
+// buildUnitSQL renders each unit as a single statement. For
+// sum by (pod) (rate(m{job="api"}[5m])) the skeleton is:
+//
+//	SELECT gkey, sumForEach(grid) AS grid FROM (
+//	    SELECT series.gkey AS gkey,
+//	           timeSeriesRateToGrid(<start>, <end>, <step>, <range>)(fromUnixTimestamp64Milli(unix_milli), value) AS grid
+//	    FROM signoz_metrics.distributed_samples_v4 AS points
+//	    INNER JOIN (
+//	        SELECT fingerprint, <group key expr> AS gkey
+//	        FROM signoz_metrics.time_series_v4
+//	        WHERE <series predicates>
+//	        GROUP BY fingerprint, gkey
+//	    ) AS series ON points.fingerprint = series.fingerprint
+//	    WHERE metric_name = ? AND temporality IN ['Cumulative', 'Unspecified']
+//	      AND points.fingerprint IN (<matched fingerprints>)
+//	      AND unix_milli > <start - range> AND unix_milli <= <end>
+//	      AND bitAnd(flags, 1) = 0
+//	    GROUP BY points.fingerprint, series.gkey
+//	) GROUP BY gkey
+//	SETTINGS allow_experimental_ts_to_grid_aggregate_function = 1
+//
+// Reading it inside out:
+//
+// The time window is the selector's semantics verbatim: strict > on the
+// lower bound and <= on the upper is the left-open (t - w, t] rule, with the
+// whole window shifted by the offset. bitAnd(flags, 1) = 0 drops stale
+// markers, which PromQL excludes from range vectors.
+//
+// The inner GROUP BY computes one grid array per series.
+// timeSeriesRateToGrid(start, end, step, range) is a parametric aggregate:
+// fed (timestamp, value) pairs it produces Array(Nullable(Float64)) with one
+// slot per grid point. Correct because it implements the engine's
+// extrapolatedRate decision for decision — counter resets, the zero-point
+// clamp, the extrapolation thresholds, the >= 2 samples rule, the left-open
+// window — verified by feeding identical samples to both and comparing
+// slot for slot: the only difference ever observed is the last bit
+// (ClickHouse's C++ and Go round the same formula differently), which is
+// the floating-point floor, not a semantic gap. irate/delta/idelta map to
+// their own timeSeries*ToGrid functions with the same verification;
+// increase has no function of its own and is emitted as
+// arrayMap(x -> x * <range seconds>, <rate expr>), exact by definition —
+// extrapolatedRate computes the same extrapolated delta for both and
+// divides by the range only when isRate, so multiplying it back is the
+// identity, not an approximation. The grid parameters are rendered as
+// literals, not bound args — they are aggregate-function parameters — and
+// the experimental gate rides as a SETTINGS clause on the statement itself
+// so telemetrystore hooks cannot clobber it.
+//
+// The join annotates each series with its group key, in one of two forms.
+// by (...) extracts each listed label as a plain column
+// (JSONExtractString(labels, 'pod') AS g0) and groups on the columns
+// directly: the projection is a known short list and the label names live
+// in Go, so building, sorting and stringifying every label pair per row
+// would be waste. Correct because column-tuple equality is label-set
+// equality on the projection, and an extracted '' is the label being
+// absent — Prometheus semantics for by() over missing labels, and empties
+// are skipped when the columns turn back into labels. without and
+// no-aggregation project a label SET that varies per series, so they get
+// the canonical key: toJSONString of the sorted [label, value] pairs the
+// unit projects (without excludes the listed labels plus __name__; no
+// aggregation keeps everything, the name coming off in Go per the engine's
+// name-dropping rules). There the sort is load-bearing — stored JSON key
+// order is not canonical across fingerprints, and two orderings of the same
+// labels must land in one group — empty values are filtered for the same
+// absent-label reason, and the same string parses back into the output
+// label set (labelsFromGroupKey).
+//
+// The outer GROUP BY is the spatial aggregation: sum/min/max/avg/count
+// by/without become the -ForEach combinators. Element-wise aggregation over
+// grid arrays is the engine's per-t_i aggregation, because slot i of every
+// input array refers to the same t_i; the combinators skip NULLs, which is
+// the engine aggregating only the series present at t_i, and an index where
+// every series is absent stays NULL. Two edges need explicit handling:
+// countForEach wraps in a mapping of 0 back to NULL, because a count over
+// an all-absent index is an absent point, not 0; and a unit without
+// aggregation still passes through maxForEach — the identity for the common
+// one-fingerprint group, and a deterministic NULL-skipping merge when a
+// regex __name__ selector collapses distinct metrics onto one projected
+// label set. One caveat is inherent: summation order over series differs
+// from the engine's, so spatial aggregates can differ in the last ULP —
+// float addition is not associative; no ordering reproduces the engine's
+// bit-exactly from inside a GROUP BY.
+//
+// # Instant selectors: staleness needs two aggregates
+//
+// unitInstant uses window = lookback and must reproduce the shadowing rule:
+// the point is absent when the latest in-window sample is a stale marker.
+// timeSeriesLastToGrid alone cannot express that — skipping stale rows in
+// WHERE would resurrect the older real sample the marker was written to
+// bury. So stale rows stay in the scan for this kind only, and the grid
+// expression compares three aggregates per slot:
+//
+//	arrayMap((tall, tok, vok) -> if(tall IS NULL OR tok IS NULL OR tall != tok, NULL, vok),
+//	         timeSeriesLastToGrid(...)(ts, toFloat64(unix_milli)),                           -- last sample overall
+//	         timeSeriesLastToGridIf(...)(ts, toFloat64(unix_milli), bitAnd(flags, 1) = 0),   -- last non-stale, its timestamp
+//	         timeSeriesLastToGridIf(...)(ts, value, bitAnd(flags, 1) = 0))                   -- last non-stale, its value
+//
+// Correct by cases on a slot's window. No samples at all: both timestamp
+// aggregates are NULL, the slot is NULL — absent, as the engine says. Latest
+// sample non-stale: it is the latest overall and the latest non-stale, the
+// timestamps agree, the slot takes its value — the engine's pick. Latest
+// sample stale: the last-overall timestamp is the marker's, the
+// last-non-stale timestamp is older (or NULL when only markers are in
+// window), they disagree, the slot is NULL — the marker shadows, exactly
+// the engine's rule. Timestamps are unique per series (ingest dedups), so
+// timestamp equality identifies "the same sample" without ambiguity. The
+// -If combinator's applicability to these experimental aggregates was
+// probed before being trusted, not assumed.
+//
+// # Windowed *_over_time: whole buckets instead of a grid function
+//
+// avg/min/max/sum/count _over_time aggregate every raw sample in the window,
+// and no timeSeries*ToGrid function computes them. (last_over_time is the
+// exception: the last sample of a range vector — stale markers excluded from
+// range vectors by PromQL, excluded here in WHERE — is exactly
+// timeSeriesLastToGrid.) These transpile only when the range is a whole
+// multiple of the step, and then the window needs no per-sample fan-out at
+// all: with W = range/step, the window (t_k - range, t_k] is exactly the
+// union of W step buckets — both are left-open on the same boundaries — so
+// bucket membership fully determines window membership. Each sample lands
+// in exactly one bucket by a plain GROUP BY:
+//
+//	intDiv(unix_milli - <start> + <range> - 1, <step>) AS jj
+//
+// (ceil((ts - start)/step) shifted by W-1 so the earliest in-window sample
+// sits at 0; slot k's window is buckets jj in [k, k+W-1]). The alternative —
+// fanning each sample into all W windows that cover it — multiplies rows by
+// W, which for a long range over a short step is a row explosion measured
+// in billions; the bucketed form's row count is series x buckets, the size
+// of the output, regardless of W.
+//
+// The shard level aggregates per (series, group key, bucket): a bucket
+// count plus the function's value aggregate (sum for sum/avg, min, max).
+// The assembly level places the partials into dense arrays
+// (groupArrayInsertAt — positions are unique, one row per bucket; counts
+// and sums default to 0, which contributes nothing) and slides: slot k
+// combines its at-most-W bucket partials by direct aggregation, so window
+// sums are added the way the engine adds them — no prefix-sum differencing,
+// whose large-minus-large cancellation would drift past the shadow
+// tolerance on counter-sized values. Correct per slot because the bucket
+// union is the exact window multiset and avg/min/max/sum/count are
+// order-insensitive on a multiset (sum/avg up to summation order, the float
+// caveat above). A slot with zero window count is absent; min/max filter
+// their slices on the bucket counts, so an empty bucket's default can never
+// be mistaken for a value — a real sample can legitimately be +Inf.
+//
+// Ranges that don't divide the step, and windows wider than
+// maxWindowBuckets buckets (the slide costs W combines per slot), fall back
+// to the engine path, which is exact.
+//
+// # Scalar ops, full plans, hybrid plans
+//
+// The scalar-op pipeline applies in Go to the returned arrays
+// (applyScalarOps), slot by slot: arithmetic operators compute, comparisons
+// filter (the slot keeps the vector-side value or becomes NULL) or return
+// 0/1 under bool. Correct trivially: it is the same float64 operation the
+// engine would apply to the same slot value, in the same operator order the
+// AST dictates — running it in Go instead of another SQL layer changes
+// where, not what.
+//
+// A full plan's arrays map straight to the result matrix. A hybrid plan
+// materializes each unit's arrays as synthetic series under its
+// __signoz_transpiled_N__ name and evaluates the rewritten expression over
+// a storage that serves synthetic names from memory and everything else
+// live. Substitution is sound because a unit's output is a plain instant
+// vector to the engine — same values at same timestamps under a different
+// name, and the name cannot matter: plans that group by or match on
+// __name__ were refused at classification, and name-keeping units are never
+// substituted. One subtlety makes it exact: stale markers are written at
+// absent grid points, because the engine's lookback would otherwise
+// resurrect a point from up to lookback earlier — the marker encodes
+// "absent here" the way the engine itself encodes it. Units evaluate
+// concurrently; each is one series lookup plus one grid statement. A step
+// of 0 is an instant query: a single evaluation at end.
 //
 // # Series lookup
 //
-// Matchers resolve to series once per selector (selectSeries) against the
-// time-series tables, which hold one row per (fingerprint, bucket) at
-// 1h/6h/1d/1w granularities; timeSeriesTableFor picks the table whose bucket
-// fits the window and rounds the window start down to the bucket boundary.
-// How matchers become SQL, and why regexes are anchored, is documented at
-// applySeriesConditions. Empty-valued labels come off at this boundary: an
-// empty value means "label absent" in Prometheus, but stored attribute JSON
-// can carry them.
+// Both paths resolve matchers the same way, once per selector
+// (selectSeries), against the series tables holding one row per
+// (fingerprint, bucket) at 1h/6h/1d/1w granularities; timeSeriesTableFor
+// picks the table whose bucket fits the window and rounds the window start
+// down to the bucket boundary. How matchers become SQL, and why regexes are
+// anchored, is documented at applySeriesConditions. Empty-valued labels come
+// off at this boundary: an empty value means "label absent" in Prometheus,
+// but stored attribute JSON can carry them.
 //
-// # Sample fetch
+// # The engine path
 //
-// Samples are fetched per selector using the engine's per-selector hints,
-// not the query-wide union window, so foo / foo offset 1d reads two narrow
-// windows instead of the widest one twice. Instant selectors of
-// subquery-free queries fetch only the last sample per step bucket — see
-// lastSamplePerStep for the correctness argument — while range selectors
-// always fetch raw: every sample feeds the range function. Row assembly maps
-// stale flags to the engine's StaleNaN and merges series with identical
-// label sets (sortAndMerge), because the engine assumes storages never emit
-// duplicates.
+// Queries that do not transpile run in the stock engine over this package's
+// storage.Querier, which is still not the v1 path. Samples are fetched per
+// selector using the engine's per-selector hints, not the query-wide union
+// window, so foo / foo offset 1d reads two narrow windows instead of the
+// widest one twice. Instant selectors of subquery-free queries fetch only
+// the last sample per step bucket (lastSamplePerStep): buckets anchor at the
+// selector's first evaluation timestamp — recovered from the hints as
+// hints.Start + lookback - 1ms, the inverse of how the engine derives
+// hints.Start — so bucket boundaries coincide with evaluation timestamps and
+// a non-final sample of a bucket can never be the latest sample in
+// (t - lookback, t] for any grid t. Real timestamps are preserved, so the
+// engine's own lookback and staleness handling stay exact. Range selectors
+// always fetch raw — every sample feeds the range function — and the
+// subquery-free proof travels in the context as prometheus.QueryTraits,
+// because subquery selectors evaluate at the subquery's step while the
+// hints carry the top-level step. Row assembly maps stale flags to the
+// engine's StaleNaN and merges series with identical label sets
+// (sortAndMerge) — the engine assumes storages never emit duplicates.
 //
 // # Sharding
 //
 // samples_v4 and time_series_v4 (and all their rollups) shard on the same
 // key — cityHash64(env, temporality, metric_name, fingerprint) — so a
-// series' samples and catalog rows live on the same shard. The samples
-// fetch exploits that: it restricts by a shard-local series subquery, not a
-// GLOBAL broadcast of the matched set. Delta-temporality
-// series stay invisible to PromQL exactly as they are in v1: the rollout
-// gate is parity with v1, and a Delta stream fed to rate() as-if-cumulative
-// would be wrong, not just new.
+// series' samples and catalog rows live on the same shard. The transpiled
+// statement above exploits that: the distributed samples table at the
+// top-level FROM makes ClickHouse rewrite the whole inner query per shard,
+// where the join against the shard-local series table and the per-series
+// grid aggregation run next to the data; the initiator only merges
+// aggregate states and applies the spatial -ForEach step. Same layout as
+// the telemetrymetrics statement builder. The group-key join alone
+// restricts the transpiled scan to the matched series; the engine path's
+// samples fetch restricts by the same predicates as a shard-local
+// semi-join, not a GLOBAL broadcast of the matched set. The temporality
+// filter on every
+// samples statement is a semantic no-op — the matched fingerprints already
+// come from those temporalities — that engages the leading samples
+// primary-key column. Delta-temporality series stay invisible to PromQL
+// here exactly as they are in v1: the rollout gate is parity with v1, and
+// making Delta visible is its own change with its own semantics to design —
+// a Delta stream fed to rate() as-if-cumulative would be wrong, not just
+// new.
 //
 // # Observability
 //
 // Every statement carries a log_comment with
 // code.namespace=clickhouse-prometheus-v2 and code.function.name naming the
-// call site, so this provider's work is attributable in system.query_log.
+// call site (selectSeries, selectSamples, transpiledUnit, LabelValues,
+// LabelNames), so this provider's work is attributable in system.query_log
+// without guessing from query text.
 package clickhouseprometheusv2

pkg/prometheus/clickhouseprometheusv2/provider.go

@@ -2,23 +2,27 @@ package clickhouseprometheusv2
 
 import (
 	"context"
+	"time"
 
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/prometheus"
 	"github.com/SigNoz/signoz/pkg/telemetrystore"
+	"github.com/prometheus/prometheus/promql"
 	"github.com/prometheus/prometheus/storage"
 )
 
-// Provider ties the package together: its own engine and parser, and the
-// ClickHouse client behind the native storage.Querier. See the package
-// documentation for how the read path differs from v1. It is exported as a
-// concrete type — callers hold it directly, and an interface with a single
+// Provider ties the package together: its own engine and parser, the
+// ClickHouse client behind the native storage.Querier, and the transpiler
+// executor. See the package documentation for what runs where and why. It is
+// exported as a concrete type — pkg/querier holds it directly for shadow
+// comparison and pinned serving, and an interface with a single
 // implementation would only hide that dependency.
 type Provider struct {
 	settings factory.ScopedProviderSettings
 	engine   *prometheus.Engine
 	parser   prometheus.Parser
 	client   *client
+	executor *executor
 }
 
 var (
@@ -44,9 +48,17 @@ func New(_ context.Context, providerSettings factory.ProviderSettings, config pr
 		engine:   engine,
 		parser:   parser,
 		client:   client,
+		executor: &executor{client: client, engine: engine, parser: parser},
 	}, nil
 }
 
+// TryExecuteRange evaluates transpilable query shapes directly in ClickHouse
+// (see transpiler.go). ok=false means the shape is not transpilable and the
+// caller should evaluate through Engine over Storage instead.
+func (p *Provider) TryExecuteRange(ctx context.Context, query string, start, end time.Time, step time.Duration) (promql.Matrix, bool, error) {
+	return p.executor.TryExecuteRange(ctx, query, start, end, step)
+}
+
 func (p *Provider) Engine() *prometheus.Engine {
 	return p.engine
 }

pkg/prometheus/clickhouseprometheusv2/transpiler.go

@@ -0,0 +1,492 @@
+package clickhouseprometheusv2
+
+import (
+	"fmt"
+	"strings"
+
+	"github.com/prometheus/prometheus/model/labels"
+	"github.com/prometheus/prometheus/promql/parser"
+)
+
+// The compiler turns PromQL subtrees into single ClickHouse queries built on
+// the timeSeries*ToGrid aggregate functions (CH >= 25.6), whose semantics
+// were verified against this repo's vendored engine: exact extrapolatedRate
+// behavior including counter resets, the counter zero-point clamp, the
+// 1.1x-average extrapolation threshold, left-open windows, the >= 2 samples
+// rule, stale-marker shadowing, and millisecond grid starts. Sample rows
+// never leave ClickHouse: one row per output series comes back, holding the
+// whole grid as an array.
+//
+// Scope (the allowlist): an optional sum/min/max/avg/count by/without
+// aggregation over a core unit — a rate/increase/delta/irate/idelta range
+// selection, an instant vector selection, or an avg/min/max/sum/count/last
+// _over_time window — plus number-literal arithmetic/comparisons and unary
+// minus on top. Units inside fixed-resolution subqueries evaluate on the
+// subquery's own grid. Everything else either falls back to the engine over
+// this package's querier, or — when a transpilable subtree sits under a
+// non-transpilable node — runs hybrid: the subtree's grids are computed in
+// ClickHouse and substituted into the engine as synthetic series (see
+// compiler_exec.go). See doc.go for the fallback list and the reasons behind
+// each entry.
+
+// rangeFn is a transpilable range-vector function.
+type rangeFn string
+
+const (
+	fnRate     rangeFn = "rate"
+	fnIncrease rangeFn = "increase"
+	fnDelta    rangeFn = "delta"
+	fnIRate    rangeFn = "irate"
+	fnIDelta   rangeFn = "idelta"
+)
+
+var gridFunction = map[rangeFn]string{
+	fnRate:     "timeSeriesRateToGrid",
+	fnIncrease: "timeSeriesRateToGrid", // increase == rate * range seconds, exactly (same factor algebra)
+	fnDelta:    "timeSeriesDeltaToGrid",
+	fnIRate:    "timeSeriesInstantRateToGrid",
+	fnIDelta:   "timeSeriesInstantDeltaToGrid",
+}
+
+// scalarOp is one number-literal arithmetic or comparison applied to a
+// compiled vector, evaluated in Go during assembly with the same float64
+// operations the engine uses.
+type scalarOp struct {
+	op           parser.ItemType
+	scalar       float64
+	scalarOnLeft bool
+	returnBool   bool
+}
+
+// isComparison reports whether the op is a filtering/bool comparison, which
+// preserves the metric name (arithmetic drops it).
+func (o scalarOp) isComparison() bool {
+	return o.op.IsComparisonOperator()
+}
+
+// unitKind is the selector shape at the bottom of a core unit.
+type unitKind int
+
+const (
+	// unitRange: rate/increase/delta/irate/idelta over a matrix selector.
+	unitRange unitKind = iota
+	// unitInstant: a plain vector selector resolved per grid point with
+	// lookback and stale-marker shadowing.
+	unitInstant
+	// unitOverTime: avg/min/max/sum/count/last_over_time over a matrix
+	// selector (aggregation over the window's samples, stale rows excluded).
+	unitOverTime
+)
+
+// coreUnit is one transpilable subtree: selector [-> range function] ->
+// optional aggregation -> scalar op pipeline.
+type coreUnit struct {
+	kind     unitKind
+	matchers []*labels.Matcher
+	offsetMs int64
+	fn       rangeFn // unitRange
+	overFn   string  // unitOverTime: avg|min|max|sum|count|last
+	rangeMs  int64   // unitRange/unitOverTime window
+
+	hasAgg   bool
+	aggOp    parser.ItemType // SUM MIN MAX AVG COUNT
+	by       bool
+	grouping []string
+
+	ops []scalarOp
+}
+
+// keepsName reports whether the unit's output series keep their real
+// __name__: bare/comparison-filtered instant selectors and last_over_time do
+// (it returns the raw sample, name included); range functions, the other
+// *_over_time functions, aggregations, arithmetic and bool comparisons all
+// drop it — a bool comparison returns 0/1, not the sample, so the engine
+// drops the name there too. Units that keep the name cannot be substituted
+// as synthetic series in hybrid plans — the synthetic name would replace
+// the real one — but transpile fine as full plans, where assembly emits the
+// real names.
+func (u *coreUnit) keepsName() bool {
+	nameKeepingSelector := u.kind == unitInstant || (u.kind == unitOverTime && u.overFn == "last")
+	if !nameKeepingSelector || u.hasAgg {
+		return false
+	}
+	for _, op := range u.ops {
+		if !op.isComparison() || op.returnBool {
+			return false
+		}
+	}
+	return true
+}
+
+// gridContext is the evaluation grid a unit computes on. The query grid for
+// top-level units; for units inside subqueries, the subquery's own grid:
+// epoch-aligned multiples of its resolution covering the subquery window,
+// exactly as the engine derives it (engine.go, *parser.SubqueryExpr case).
+type gridContext struct {
+	startMs int64
+	endMs   int64
+	stepMs  int64
+}
+
+// subqueryGrid derives the inner grid for a subquery evaluated on outer:
+// interval S, end = outer end − offset, start = first multiple of S strictly
+// greater than outer start − offset − range.
+func subqueryGrid(outer gridContext, rangeMs, stepMs, offsetMs int64) gridContext {
+	lower := outer.startMs - offsetMs - rangeMs
+	start := stepMs * (lower / stepMs)
+	if start <= lower {
+		start += stepMs
+	}
+	return gridContext{startMs: start, endMs: outer.endMs - offsetMs, stepMs: stepMs}
+}
+
+// transpiledUnit is a coreUnit scheduled for execution, named for hybrid
+// substitution, carrying the grid it evaluates on.
+type transpiledUnit struct {
+	core coreUnit
+	name string // __signoz_transpiled_<n>__
+	grid gridContext
+}
+
+// transpilePlan is the outcome of classifying a query.
+type transpilePlan struct {
+	units []*transpiledUnit
+	grid  gridContext // the query's top-level grid
+	// full is set when the entire query is units[0]; otherwise rewritten
+	// holds the query with each unit replaced by a synthetic selector, to be
+	// evaluated by the engine over a hybrid storage.
+	full      bool
+	rewritten string
+}
+
+const syntheticNamePrefix = "__signoz_transpiled_"
+
+func syntheticName(i int) string {
+	return fmt.Sprintf("%s%d__", syntheticNamePrefix, i)
+}
+
+// classifyCore matches a subtree against the transpilable core shape.
+// stepMs gates second-granularity: the grid functions take whole-second step
+// and window parameters (grid *starts* are millisecond-precise).
+func classifyCore(node parser.Expr, stepMs int64) (*coreUnit, bool) {
+	unit := &coreUnit{}
+
+	expr := node
+	// Peel scalar ops and parens off the top, outermost first; ops apply in
+	// evaluation order, so prepend while peeling.
+	for {
+		switch n := expr.(type) {
+		case *parser.ParenExpr:
+			expr = n.Expr
+			continue
+		case *parser.UnaryExpr:
+			if n.Op != parser.SUB {
+				expr = n.Expr // unary '+' is a no-op
+				continue
+			}
+			// -x == -1 * x for every float64 (incl. NaN and signed zero).
+			unit.ops = append([]scalarOp{{op: parser.MUL, scalar: -1}}, unit.ops...)
+			expr = n.Expr
+			continue
+		case *parser.StepInvariantExpr:
+			// @-pinned expressions evaluate on a different grid.
+			return nil, false
+		case *parser.BinaryExpr:
+			lit, litOnLeft, ok := numberLiteralSide(n)
+			if !ok {
+				return nil, false
+			}
+			if !n.Op.IsOperator() && !n.Op.IsComparisonOperator() {
+				return nil, false
+			}
+			if n.Op == parser.ATAN2 {
+				// atan2 is arithmetic in PromQL but rarely used; keep the
+				// allowlist tight.
+				return nil, false
+			}
+			returnBool := n.ReturnBool
+			unit.ops = append([]scalarOp{{op: n.Op, scalar: lit, scalarOnLeft: litOnLeft, returnBool: returnBool}}, unit.ops...)
+			if litOnLeft {
+				expr = n.RHS
+			} else {
+				expr = n.LHS
+			}
+			continue
+		}
+		break
+	}
+
+	// Optional aggregation.
+	if agg, ok := expr.(*parser.AggregateExpr); ok {
+		switch agg.Op {
+		case parser.SUM, parser.MIN, parser.MAX, parser.AVG, parser.COUNT:
+		default:
+			return nil, false
+		}
+		for _, g := range agg.Grouping {
+			if g == metricNameLabel {
+				// by(__name__)/without(__name__) over synthetic or compiled
+				// output needs name bookkeeping the compiler doesn't do.
+				return nil, false
+			}
+		}
+		unit.hasAgg = true
+		unit.aggOp = agg.Op
+		unit.by = !agg.Without
+		unit.grouping = agg.Grouping
+		expr = agg.Expr
+		for {
+			if p, ok := expr.(*parser.ParenExpr); ok {
+				expr = p.Expr
+				continue
+			}
+			break
+		}
+	}
+
+	// The grid functions take whole-second steps; stepMs == 0 is an instant
+	// query (single-point grid).
+	if stepMs < 0 || stepMs%1000 != 0 {
+		return nil, false
+	}
+
+	// Bare instant selector: resolved per grid point with lookback and
+	// stale-marker shadowing (see compiler_sql.go).
+	if vs, ok := expr.(*parser.VectorSelector); ok {
+		// A duration expression (offset step(), offset range()*2, ...) is
+		// resolved into OriginalOffset only at evaluation time; at
+		// classification time the field still holds its zero value, so
+		// transpiling would silently use the wrong offset.
+		if vs.Timestamp != nil || vs.StartOrEnd != 0 || vs.Anchored || vs.Smoothed || vs.OriginalOffsetExpr != nil {
+			return nil, false
+		}
+		offsetMs := vs.OriginalOffset.Milliseconds()
+		if offsetMs < 0 {
+			return nil, false
+		}
+		unit.kind = unitInstant
+		unit.offsetMs = offsetMs
+		unit.matchers = vs.LabelMatchers
+		return unit, true
+	}
+
+	// Range or *_over_time function over a plain matrix selector.
+	call, ok := expr.(*parser.Call)
+	if !ok {
+		return nil, false
+	}
+	var fn rangeFn
+	var overFn string
+	switch call.Func.Name {
+	case "rate":
+		fn = fnRate
+	case "increase":
+		fn = fnIncrease
+	case "delta":
+		fn = fnDelta
+	case "irate":
+		fn = fnIRate
+	case "idelta":
+		fn = fnIDelta
+	case "avg_over_time", "min_over_time", "max_over_time", "sum_over_time", "count_over_time", "last_over_time":
+		overFn = strings.TrimSuffix(call.Func.Name, "_over_time")
+	default:
+		return nil, false
+	}
+	if len(call.Args) != 1 {
+		return nil, false
+	}
+	ms, ok := call.Args[0].(*parser.MatrixSelector)
+	if !ok {
+		return nil, false
+	}
+	vs, ok := ms.VectorSelector.(*parser.VectorSelector)
+	if !ok {
+		return nil, false
+	}
+	// Duration expressions resolve at evaluation time (see the instant
+	// selector case above); Range/OriginalOffset would be read as zero here.
+	if vs.Timestamp != nil || vs.StartOrEnd != 0 || vs.Anchored || vs.Smoothed || vs.OriginalOffsetExpr != nil || ms.RangeExpr != nil {
+		return nil, false
+	}
+
+	rangeMs := ms.Range.Milliseconds()
+	offsetMs := vs.OriginalOffset.Milliseconds()
+	if rangeMs <= 0 || rangeMs%1000 != 0 || offsetMs < 0 {
+		return nil, false
+	}
+
+	if overFn != "" {
+		unit.kind = unitOverTime
+		unit.overFn = overFn
+	} else {
+		unit.kind = unitRange
+		unit.fn = fn
+	}
+	unit.rangeMs = rangeMs
+	unit.offsetMs = offsetMs
+	unit.matchers = vs.LabelMatchers
+	return unit, true
+}
+
+// numberLiteralSide returns the number literal on one side of a binary
+// expression (peeling parens and unary minus), and which side it is on.
+func numberLiteralSide(b *parser.BinaryExpr) (float64, bool, bool) {
+	if v, ok := literalValue(b.LHS); ok {
+		return v, true, true
+	}
+	if v, ok := literalValue(b.RHS); ok {
+		return v, false, true
+	}
+	return 0, false, false
+}
+
+func literalValue(e parser.Expr) (float64, bool) {
+	neg := false
+	for {
+		switch n := e.(type) {
+		case *parser.ParenExpr:
+			e = n.Expr
+			continue
+		case *parser.StepInvariantExpr:
+			e = n.Expr
+			continue
+		case *parser.UnaryExpr:
+			if n.Op == parser.SUB {
+				neg = !neg
+			}
+			e = n.Expr
+			continue
+		case *parser.NumberLiteral:
+			if neg {
+				return -n.Val, true
+			}
+			return n.Val, true
+		default:
+			return 0, false
+		}
+	}
+}
+
+// classify builds the compile plan for a query: full when the root is a core
+// unit, hybrid when core units sit strictly below the root (including inside
+// fixed-resolution subqueries, computed on the subquery grid), none
+// otherwise.
+func classify(root parser.Expr, grid gridContext) (*transpilePlan, bool) {
+	if unit, ok := classifyCore(root, grid.stepMs); ok {
+		return &transpilePlan{
+			units: []*transpiledUnit{{core: *unit, name: syntheticName(0), grid: grid}},
+			grid:  grid,
+			full:  true,
+		}, true
+	}
+
+	plan := &transpilePlan{grid: grid}
+	rewritten := rewrite(root, grid, plan, false)
+	if len(plan.units) == 0 {
+		return nil, false
+	}
+	plan.rewritten = rewritten.String()
+	return plan, true
+}
+
+// rewrite walks top-down replacing maximal transpilable subtrees with synthetic
+// vector selectors. nameSensitive marks scopes where an ancestor's semantics
+// depend on __name__ (grouping or vector matching on it): synthetic series
+// carry a synthetic __name__, so substitution there would change results.
+// Fixed-resolution subqueries recurse with the subquery's own grid; scopes
+// whose evaluation grid is unknowable (@-pinned, default-resolution
+// subqueries) are not entered.
+func rewrite(node parser.Expr, grid gridContext, plan *transpilePlan, nameSensitive bool) parser.Expr {
+	if node == nil {
+		return nil
+	}
+
+	if !nameSensitive {
+		// Units whose output keeps the real __name__ (bare instant selectors)
+		// cannot be substituted: the synthetic name would replace it in the
+		// engine's output. They still compile as full plans.
+		if unit, ok := classifyCore(node, grid.stepMs); ok && !unit.keepsName() {
+			cu := &transpiledUnit{core: *unit, name: syntheticName(len(plan.units)), grid: grid}
+			plan.units = append(plan.units, cu)
+			return &parser.VectorSelector{
+				Name: cu.name,
+				LabelMatchers: []*labels.Matcher{
+					labels.MustNewMatcher(labels.MatchEqual, metricNameLabel, cu.name),
+				},
+				PosRange: node.PositionRange(),
+			}
+		}
+	}
+
+	switch n := node.(type) {
+	case *parser.ParenExpr:
+		n.Expr = rewrite(n.Expr, grid, plan, nameSensitive)
+	case *parser.UnaryExpr:
+		n.Expr = rewrite(n.Expr, grid, plan, nameSensitive)
+	case *parser.AggregateExpr:
+		sensitive := nameSensitive || groupingUsesName(n.Grouping)
+		n.Expr = rewrite(n.Expr, grid, plan, sensitive)
+		// n.Param is a scalar/string; nothing transpilable inside for our core.
+	case *parser.Call:
+		for i, arg := range n.Args {
+			n.Args[i] = rewrite(arg, grid, plan, nameSensitive)
+		}
+	case *parser.BinaryExpr:
+		sensitive := nameSensitive || vectorMatchingUsesName(n.VectorMatching)
+		n.LHS = rewrite(n.LHS, grid, plan, sensitive)
+		n.RHS = rewrite(n.RHS, grid, plan, sensitive)
+	case *parser.SubqueryExpr:
+		// The alert-smoothing idiom fn_over_time((expr)[R:S]) dominates real
+		// rule fleets; inner units evaluate on the subquery grid, and the
+		// engine does the smoothing over the synthetic series. Requires an
+		// explicit whole-second resolution (S == 0 needs the engine's
+		// default-interval function) and no @ pinning.
+		stepMs := n.Step.Milliseconds()
+		rangeMs := n.Range.Milliseconds()
+		offsetMs := n.OriginalOffset.Milliseconds()
+		if n.Timestamp == nil && n.StartOrEnd == 0 &&
+			n.RangeExpr == nil && n.StepExpr == nil && n.OriginalOffsetExpr == nil &&
+			stepMs > 0 && stepMs%1000 == 0 && rangeMs%1000 == 0 && offsetMs >= 0 {
+			inner := subqueryGrid(grid, rangeMs, stepMs, offsetMs)
+			n.Expr = rewrite(n.Expr, inner, plan, nameSensitive)
+		}
+	case *parser.StepInvariantExpr, *parser.MatrixSelector,
+		*parser.VectorSelector, *parser.NumberLiteral, *parser.StringLiteral:
+		// Leaves, or scopes substitution must not enter.
+	}
+	return node
+}
+
+func groupingUsesName(grouping []string) bool {
+	for _, g := range grouping {
+		if g == metricNameLabel {
+			return true
+		}
+	}
+	return false
+}
+
+func vectorMatchingUsesName(vm *parser.VectorMatching) bool {
+	if vm == nil {
+		return false
+	}
+	for _, l := range append(append([]string{}, vm.MatchingLabels...), vm.Include...) {
+		if l == metricNameLabel {
+			return true
+		}
+	}
+	// Default (all-labels) matching ignores __name__, and by()/ignoring()
+	// lists were checked above.
+	return false
+}
+
+// isSyntheticSelector reports whether matchers target a compiled unit.
+func isSyntheticSelector(matchers []*labels.Matcher) (string, bool) {
+	for _, m := range matchers {
+		if m.Name == metricNameLabel && m.Type == labels.MatchEqual && strings.HasPrefix(m.Value, syntheticNamePrefix) {
+			return m.Value, true
+		}
+	}
+	return "", false
+}

pkg/prometheus/clickhouseprometheusv2/transpiler_corpus_test.go

@@ -0,0 +1,161 @@
+package clickhouseprometheusv2
+
+import (
+	"bufio"
+	"encoding/json"
+	"fmt"
+	"os"
+	"regexp"
+	"sort"
+	"strings"
+	"testing"
+
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/stretchr/testify/require"
+)
+
+// TestClassifyCorpus measures real-workload compiler coverage: it classifies
+// every query of a JSON-lines corpus (one JSON-encoded PromQL string per
+// line) with the live classifier and reports full / hybrid / fallback
+// shares. Skipped unless PROMQL_CORPUS points to one or more files
+// (comma-separated). Dashboard template variables are substituted with
+// placeholder values before parsing, mirroring the production render step.
+//
+//	PROMQL_CORPUS=corpus-a.jsonl,corpus-b.jsonl go test -run TestClassifyCorpus -v
+func TestClassifyCorpus(t *testing.T) {
+	corpus := os.Getenv("PROMQL_CORPUS")
+	if corpus == "" {
+		t.Skip("PROMQL_CORPUS not set")
+	}
+
+	varRe := regexp.MustCompile(`\{\{\s*\.?[\w.]+\s*\}\}|\[\[\s*[\w.]+\s*\]\]|\$[\w.]+`)
+	promParser := parser.NewParser(parser.Options{})
+
+	for _, path := range strings.Split(corpus, ",") {
+		f, err := os.Open(path)
+		require.NoError(t, err)
+
+		var full, hybrid, fallbackInstant, fallbackOther, parseErrs int
+		fallbackReasons := map[string]int{}
+
+		scanner := bufio.NewScanner(f)
+		scanner.Buffer(make([]byte, 1024*1024), 1024*1024)
+		for scanner.Scan() {
+			var query string
+			require.NoError(t, json.Unmarshal(scanner.Bytes(), &query))
+			query = varRe.ReplaceAllString(query, "placeholder")
+
+			expr, err := promParser.ParseExpr(query)
+			if err != nil {
+				parseErrs++
+				continue
+			}
+
+			plan, ok := classify(expr, gridContext{startMs: 1_700_000_000_000, endMs: 1_700_007_200_000, stepMs: 60_000})
+			switch {
+			case ok && plan.full:
+				full++
+			case ok:
+				hybrid++
+			default:
+				reason := fallbackShape(expr)
+				fallbackReasons[reason]++
+				if reason == "instant-selector shape (last-sample-per-step engine path)" {
+					fallbackInstant++
+				} else {
+					fallbackOther++
+				}
+			}
+		}
+		require.NoError(t, scanner.Err())
+		_ = f.Close()
+
+		total := full + hybrid + fallbackInstant + fallbackOther
+		if total == 0 {
+			t.Logf("%s: no parseable queries (%d parse errors)", path, parseErrs)
+			continue
+		}
+		t.Logf("%s: %d queries — full=%d (%.0f%%) hybrid=%d (%.0f%%) fallback=%d (%.0f%%; instant-shape=%d) parse_errors=%d",
+			path, total,
+			full, 100*float64(full)/float64(total),
+			hybrid, 100*float64(hybrid)/float64(total),
+			fallbackInstant+fallbackOther, 100*float64(fallbackInstant+fallbackOther)/float64(total),
+			fallbackInstant, parseErrs)
+
+		reasons := make([]string, 0, len(fallbackReasons))
+		for r := range fallbackReasons {
+			reasons = append(reasons, r)
+		}
+		sort.Slice(reasons, func(i, j int) bool { return fallbackReasons[reasons[i]] > fallbackReasons[reasons[j]] })
+		for _, r := range reasons {
+			t.Logf("  fallback %4d  %s", fallbackReasons[r], r)
+		}
+	}
+}
+
+// fallbackShape buckets a non-transpilable query by why it stays on the engine
+// path, to separate "already served well" (instant selectors on the last-sample-per-step
+// path) from genuine compiler gaps.
+func fallbackShape(expr parser.Expr) string {
+	var hasMatrix, hasSubquery, hasAt, hasDurationExpr, overTime bool
+	rangeFns := map[string]bool{"rate": true, "increase": true, "delta": true, "irate": true, "idelta": true}
+	var unsupportedFns []string
+	parser.Inspect(expr, func(node parser.Node, _ []parser.Node) error {
+		switch n := node.(type) {
+		case *parser.MatrixSelector:
+			hasMatrix = true
+			if n.RangeExpr != nil {
+				hasDurationExpr = true
+			}
+		case *parser.SubqueryExpr:
+			hasSubquery = true
+			if n.RangeExpr != nil || n.StepExpr != nil || n.OriginalOffsetExpr != nil {
+				hasDurationExpr = true
+			}
+		case *parser.VectorSelector:
+			if n.Timestamp != nil || n.StartOrEnd != 0 {
+				hasAt = true
+			}
+			if n.OriginalOffsetExpr != nil {
+				hasDurationExpr = true
+			}
+		case *parser.Call:
+			if strings.HasSuffix(n.Func.Name, "_over_time") {
+				overTime = true
+			} else if !rangeFns[n.Func.Name] {
+				unsupportedFns = append(unsupportedFns, n.Func.Name)
+			}
+		}
+		return nil
+	})
+
+	switch {
+	case hasDurationExpr:
+		return "duration expression (resolved only at evaluation time)"
+	case hasSubquery:
+		return "subquery"
+	case hasAt:
+		return "@ modifier"
+	case overTime:
+		return "*_over_time range function"
+	case !hasMatrix:
+		return "instant-selector shape (last-sample-per-step engine path)"
+	case len(unsupportedFns) > 0:
+		return fmt.Sprintf("range shape with unsupported function(s): %s", strings.Join(dedupe(unsupportedFns), ",")) //nolint:makezero
+	default:
+		return "other range shape"
+	}
+}
+
+func dedupe(in []string) []string {
+	seen := map[string]bool{}
+	var out []string
+	for _, s := range in {
+		if !seen[s] {
+			seen[s] = true
+			out = append(out, s)
+		}
+	}
+	sort.Strings(out)
+	return out
+}

pkg/prometheus/clickhouseprometheusv2/transpiler_exec.go

@@ -0,0 +1,550 @@
+package clickhouseprometheusv2
+
+import (
+	"context"
+	"encoding/json"
+	"math"
+	"sort"
+	"time"
+
+	"github.com/SigNoz/signoz/pkg/errors"
+	"github.com/SigNoz/signoz/pkg/prometheus"
+	"github.com/prometheus/prometheus/model/labels"
+	promValue "github.com/prometheus/prometheus/model/value"
+	"github.com/prometheus/prometheus/promql"
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/prometheus/prometheus/storage"
+	"golang.org/x/sync/errgroup"
+)
+
+// executor evaluates transpilable PromQL directly in ClickHouse, falling
+// back (ok=false) whenever the query shape or the step doesn't qualify. The
+// timeSeries*ToGrid functions it builds on are assumed available: the
+// supported ClickHouse floor is >= 25.6.
+type executor struct {
+	client *client
+	engine *prometheus.Engine
+	parser prometheus.Parser
+}
+
+// maxWindowBuckets caps range/step for the windowed *_over_time form: every
+// grid slot combines that many bucket partials, and the fleet's windows sit
+// well under it ([1m]..[17m] at 30-60s steps) — anything larger is a
+// long-range query whose step a dashboard scales up anyway, and the engine
+// path serves the rest.
+const maxWindowBuckets = 64
+
+// TryExecuteRange transpiles and runs the query in ClickHouse when its shape
+// is in the allowlist. ok=false means "not transpilable" and carries no
+// error; the caller runs the engine path.
+func (e *executor) TryExecuteRange(ctx context.Context, qs string, start, end time.Time, step time.Duration) (promql.Matrix, bool, error) {
+	expr, err := e.parser.ParseExpr(qs)
+	if err != nil {
+		// Let the engine path produce the (enhanced) parse error.
+		return nil, false, nil
+	}
+
+	plan, ok := classify(expr, queryGrid(start, end, step))
+	if !ok {
+		return nil, false, nil
+	}
+
+	// timeSeriesLastToGrid widens its window to max(window, step) — probed: a
+	// sample aged (window, step] still fills the slot — while the rate/delta
+	// family enforces the window strictly. The Last-style kinds used to fall
+	// back when window < step because of that widening; the window-sliver
+	// filter (see samplesConditions) makes the widening harmless there:
+	// samples exist only inside (t_k - window, t_k] slivers, so the widened
+	// window intersected with the data IS the lookback window — and if a
+	// future ClickHouse stops widening, the unwidened window is the sliver
+	// too. Correct either way. A non-positive window still falls back: the
+	// sliver argument needs a real window to filter to.
+	//
+	// The windowed *_over_time form gates only the range >= step regime: it
+	// decomposes the window into whole step buckets (see windowedInner),
+	// which is exact only when the range is a multiple of the step, and its
+	// per-slot slide costs range/step bucket combines — bounded by
+	// maxWindowBuckets so a long-range short-step query cannot turn the
+	// slide into the bottleneck. range < step needs neither gate: the
+	// windows are disjoint slivers, aggregated one slot each with no slide.
+	// Every miss falls back to the engine path, which is exact.
+	for _, unit := range plan.units {
+		stepMs := unit.grid.stepMs
+		if stepMs == 0 {
+			stepMs = 1000
+		}
+		switch {
+		case unit.core.kind == unitInstant || (unit.core.kind == unitOverTime && unit.core.overFn == "last"):
+			windowMs := unit.core.rangeMs
+			if unit.core.kind == unitInstant {
+				windowMs = e.client.lookbackMs
+			}
+			if windowMs <= 0 {
+				return nil, false, nil
+			}
+		case unit.core.kind == unitOverTime:
+			if unit.core.rangeMs < unit.grid.stepMs {
+				// Disjoint slivers: no divisibility or width requirement.
+				continue
+			}
+			if unit.core.rangeMs%stepMs != 0 || unit.core.rangeMs/stepMs > maxWindowBuckets {
+				return nil, false, nil
+			}
+		}
+	}
+
+	// Evaluate every unit concurrently on its own grid (the query grid, or a
+	// subquery grid); each is one series lookup plus one grid query.
+	results := make([][]transpiledSeries, len(plan.units))
+	eg, egCtx := errgroup.WithContext(ctx)
+	for i, unit := range plan.units {
+		eg.Go(func() error {
+			res, err := e.executeUnit(egCtx, &unit.core, unit.grid)
+			if err != nil {
+				return err
+			}
+			results[i] = res
+			return nil
+		})
+	}
+	if err := eg.Wait(); err != nil {
+		return nil, true, err
+	}
+
+	if plan.full {
+		g := plan.units[0].grid
+		return toMatrix(results[0], g.startMs, g.stepMs), true, nil
+	}
+
+	matrix, err := e.executeHybrid(ctx, plan, results)
+	if err != nil {
+		return nil, true, err
+	}
+	return matrix, true, nil
+}
+
+// queryGrid derives the top-level evaluation grid; step 0 is an instant
+// query: a single evaluation at end, whatever start was.
+func queryGrid(start, end time.Time, step time.Duration) gridContext {
+	startMs, endMs, stepMs := start.UnixMilli(), end.UnixMilli(), step.Milliseconds()
+	if stepMs == 0 {
+		startMs = endMs
+	}
+	return gridContext{startMs: startMs, endMs: endMs, stepMs: stepMs}
+}
+
+// transpiledSeries is one output series of a unit: projected labels and one
+// value pointer per grid point (nil = absent).
+type transpiledSeries struct {
+	lset   labels.Labels
+	values []*float64
+}
+
+// executeUnit runs one core unit on its grid: series lookup (budgets,
+// fingerprints, metric names), then the single grid query, then the
+// scalar-op pipeline.
+func (e *executor) executeUnit(ctx context.Context, unit *coreUnit, grid gridContext) ([]transpiledSeries, error) {
+	startMs, endMs, stepMs := grid.startMs, grid.endMs, grid.stepMs
+	windowMs := unit.rangeMs
+	if unit.kind == unitInstant {
+		windowMs = e.client.lookbackMs
+	}
+	dataStart := startMs - unit.offsetMs - windowMs
+	dataEnd := endMs - unit.offsetMs
+
+	seriesQuery, seriesArgs, err := buildSeriesQuery(dataStart, dataEnd, unit.matchers)
+	if err != nil {
+		return nil, err
+	}
+	lookup, err := e.client.selectSeries(ctx, seriesQuery, seriesArgs)
+	if err != nil {
+		return nil, err
+	}
+	if len(lookup.fingerprints) == 0 {
+		return nil, nil
+	}
+
+	query, args, err := buildUnitSQL(unit, lookup.metricNames, dataStart, dataEnd, startMs, endMs, stepMs, e.client.lookbackMs)
+	if err != nil {
+		return nil, err
+	}
+
+	rows, err := e.client.telemetryStore.ClickhouseDB().Query(e.client.withContext(ctx, "transpiledUnit"), query, args...)
+	if err != nil {
+		return nil, err
+	}
+	defer rows.Close()
+
+	// Name-dropping units keep __name__ in the SQL group key so distinct
+	// metrics never merge server-side; the name comes off here. Two metrics
+	// can then share a labelset — the engine merges their samples into one
+	// series when they never overlap in time (a selector spanning metrics
+	// whose series alternate across lookback windows) and raises the
+	// duplicate-labelset error only when two samples land on the same
+	// evaluation timestamp. mergeSameLabelsetSeries reproduces exactly that.
+	stripName := !unit.hasAgg && !unit.keepsName()
+
+	// by (...) units return one plain column per grouped label; everything
+	// else returns the single canonical JSON key (see groupKeyColumns).
+	keyNames := groupKeyColumns(unit)
+	keyVals := make([]string, max(len(keyNames), 1))
+	targets := make([]any, 0, len(keyVals)+1)
+	for i := range keyVals {
+		targets = append(targets, &keyVals[i])
+	}
+	var gridValues []*float64
+	targets = append(targets, &gridValues)
+
+	var out []transpiledSeries
+	for rows.Next() {
+		if err := rows.Scan(targets...); err != nil {
+			return nil, err
+		}
+		var lset labels.Labels
+		if keyNames != nil {
+			builder := labels.NewScratchBuilder(len(keyNames))
+			for i, name := range keyNames {
+				// An empty extracted value is the label being absent.
+				if keyVals[i] != "" {
+					builder.Add(name, keyVals[i])
+				}
+			}
+			builder.Sort()
+			lset = builder.Labels()
+		} else {
+			lset, err = labelsFromGroupKey(keyVals[0])
+			if err != nil {
+				return nil, err
+			}
+		}
+		if stripName {
+			lset = labels.NewBuilder(lset).Del(metricNameLabel).Labels()
+		}
+		values := make([]*float64, len(gridValues))
+		copy(values, gridValues)
+		applyScalarOps(unit.ops, values)
+		out = append(out, transpiledSeries{lset: lset, values: values})
+	}
+	if err := rows.Err(); err != nil {
+		return nil, err
+	}
+
+	if stripName {
+		if out, err = mergeSameLabelsetSeries(out); err != nil {
+			return nil, err
+		}
+	}
+	sort.Slice(out, func(i, j int) bool { return labels.Compare(out[i].lset, out[j].lset) < 0 })
+	return out, nil
+}
+
+// mergeSameLabelsetSeries combines series left with identical labelsets by a
+// name strip, slot by slot: the engine assembles its result matrix by
+// labelset, so post-strip twins whose points interleave in time are one
+// series to it, and two values on the same evaluation timestamp are its
+// duplicate-labelset error — v1 would have errored there too, so silently
+// picking one value would be a divergence.
+func mergeSameLabelsetSeries(in []transpiledSeries) ([]transpiledSeries, error) {
+	index := make(map[uint64]int, len(in))
+	out := in[:0]
+	for _, s := range in {
+		hash := s.lset.Hash()
+		idx, ok := index[hash]
+		if ok && labels.Equal(out[idx].lset, s.lset) {
+			dst := out[idx].values
+			for k, v := range s.values {
+				if v == nil {
+					continue
+				}
+				if dst[k] != nil {
+					return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "vector cannot contain metrics with the same labelset")
+				}
+				dst[k] = v
+			}
+			continue
+		}
+		index[hash] = len(out)
+		out = append(out, s)
+	}
+	return out, nil
+}
+
+// labelsFromGroupKey parses the toJSONString'd sorted [key, value] pairs.
+func labelsFromGroupKey(gkey string) (labels.Labels, error) {
+	var pairs [][]string
+	if err := json.Unmarshal([]byte(gkey), &pairs); err != nil {
+		return labels.EmptyLabels(), errors.WrapInternalf(err, errors.CodeInternal, "malformed compiled group key %q", gkey)
+	}
+	builder := labels.NewScratchBuilder(len(pairs))
+	for _, p := range pairs {
+		if len(p) != 2 {
+			return labels.EmptyLabels(), errors.NewInternalf(errors.CodeInternal, "malformed compiled group key pair %q", gkey)
+		}
+		builder.Add(p[0], p[1])
+	}
+	builder.Sort()
+	return builder.Labels(), nil
+}
+
+// applyScalarOps applies the number-literal op pipeline in place, with the
+// same float64 arithmetic and comparison-filter semantics as the engine.
+func applyScalarOps(ops []scalarOp, values []*float64) {
+	for _, op := range ops {
+		for i, v := range values {
+			if v == nil {
+				continue
+			}
+			lhs, rhs := *v, op.scalar
+			if op.scalarOnLeft {
+				lhs, rhs = op.scalar, *v
+			}
+			switch op.op {
+			case parser.ADD:
+				res := lhs + rhs
+				values[i] = &res
+			case parser.SUB:
+				res := lhs - rhs
+				values[i] = &res
+			case parser.MUL:
+				res := lhs * rhs
+				values[i] = &res
+			case parser.DIV:
+				res := lhs / rhs
+				values[i] = &res
+			case parser.MOD:
+				res := math.Mod(lhs, rhs)
+				values[i] = &res
+			case parser.POW:
+				res := math.Pow(lhs, rhs)
+				values[i] = &res
+			default:
+				keep := compare(op.op, lhs, rhs)
+				switch {
+				case op.returnBool:
+					res := 0.0
+					if keep {
+						res = 1.0
+					}
+					values[i] = &res
+				case keep:
+					// Filter comparisons keep the vector-side value.
+					vec := *v
+					values[i] = &vec
+				default:
+					values[i] = nil
+				}
+			}
+		}
+	}
+}
+
+func compare(op parser.ItemType, lhs, rhs float64) bool {
+	switch op {
+	case parser.EQLC:
+		return lhs == rhs
+	case parser.NEQ:
+		return lhs != rhs
+	case parser.GTR:
+		return lhs > rhs
+	case parser.LSS:
+		return lhs < rhs
+	case parser.GTE:
+		return lhs >= rhs
+	case parser.LTE:
+		return lhs <= rhs
+	}
+	return false
+}
+
+// toMatrix converts a unit result to a promql matrix on the query grid.
+func toMatrix(series []transpiledSeries, startMs, stepMs int64) promql.Matrix {
+	matrix := make(promql.Matrix, 0, len(series))
+	for _, s := range series {
+		var floats []promql.FPoint
+		for i, v := range s.values {
+			if v == nil {
+				continue
+			}
+			floats = append(floats, promql.FPoint{T: startMs + int64(i)*stepMs, F: *v})
+		}
+		if len(floats) == 0 {
+			continue
+		}
+		matrix = append(matrix, promql.Series{Metric: s.lset, Floats: floats})
+	}
+	return matrix
+}
+
+// executeHybrid substitutes each unit's grids into the engine as synthetic
+// series and evaluates the rewritten query over a storage that serves
+// synthetic selectors from memory and everything else from the live querier.
+// Absent grid points become stale markers so the engine's lookback cannot
+// resurrect the previous grid point. Each unit's synthetic samples sit on its
+// own grid (query grid, or subquery grid for units inside subqueries).
+func (e *executor) executeHybrid(ctx context.Context, plan *transpilePlan, results [][]transpiledSeries) (promql.Matrix, error) {
+	synthetic := make(map[string][]*series, len(plan.units))
+	staleMarker := math.Float64frombits(promValue.StaleNaN)
+
+	queryGrid := plan.grid
+
+	for i, unit := range plan.units {
+		g := unit.grid
+		gridLen := 1
+		if g.stepMs > 0 {
+			gridLen = int((g.endMs-g.startMs)/g.stepMs) + 1
+		}
+		list := make([]*series, 0, len(results[i]))
+		for _, cs := range results[i] {
+			builder := labels.NewBuilder(cs.lset)
+			builder.Set(metricNameLabel, unit.name)
+			s := &series{lset: builder.Labels()}
+			s.ts = make([]int64, 0, gridLen)
+			s.vs = make([]float64, 0, gridLen)
+			for idx := 0; idx < gridLen; idx++ {
+				t := g.startMs + int64(idx)*g.stepMs
+				var v float64
+				if idx < len(cs.values) && cs.values[idx] != nil {
+					v = *cs.values[idx]
+				} else {
+					v = staleMarker
+				}
+				s.ts = append(s.ts, t)
+				s.vs = append(s.vs, v)
+			}
+			list = append(list, s)
+		}
+		synthetic[unit.name] = list
+	}
+
+	hybrid := &hybridQueryable{client: e.client, synthetic: synthetic}
+
+	var qry promql.Query
+	var err error
+	if queryGrid.stepMs == 0 {
+		qry, err = e.engine.NewInstantQuery(ctx, hybrid, nil, plan.rewritten, time.UnixMilli(queryGrid.endMs))
+	} else {
+		qry, err = e.engine.NewRangeQuery(ctx, hybrid, nil, plan.rewritten, time.UnixMilli(queryGrid.startMs), time.UnixMilli(queryGrid.endMs), time.Duration(queryGrid.stepMs)*time.Millisecond)
+	}
+	if err != nil {
+		return nil, err
+	}
+	defer qry.Close()
+
+	res := qry.Exec(ctx)
+	if res.Err != nil {
+		return nil, res.Err
+	}
+
+	matrix, err := resultToMatrix(res)
+	if err != nil {
+		return nil, err
+	}
+
+	// Deep-copy before Close returns the result's slices to the engine pool,
+	// and drop the synthetic __name__ that filter comparisons preserve.
+	out := make(promql.Matrix, 0, len(matrix))
+	for _, s := range matrix {
+		lset := s.Metric
+		if name := lset.Get(metricNameLabel); len(name) >= len(syntheticNamePrefix) && name[:len(syntheticNamePrefix)] == syntheticNamePrefix {
+			builder := labels.NewBuilder(lset)
+			builder.Del(metricNameLabel)
+			lset = builder.Labels()
+		}
+		floats := make([]promql.FPoint, len(s.Floats))
+		copy(floats, s.Floats)
+		out = append(out, promql.Series{Metric: lset.Copy(), Floats: floats})
+	}
+	// The strip can leave twins: two units' outputs distinguishable only by
+	// their synthetic names (e.g. -metric_a or -metric_b, both {} to the
+	// engine's real evaluation once names dropped). The engine assembles its
+	// matrix by labelset, merging such temporally-disjoint elements into one
+	// series; reproduce that, with its duplicate error on same-timestamp
+	// overlap.
+	out, err = mergeMatrixByLabelset(out)
+	if err != nil {
+		return nil, err
+	}
+	sort.Slice(out, func(i, j int) bool { return labels.Compare(out[i].Metric, out[j].Metric) < 0 })
+	return out, nil
+}
+
+// mergeMatrixByLabelset merges series sharing a labelset by interleaving
+// their points in timestamp order; a timestamp present in both is the
+// engine's duplicate-labelset error.
+func mergeMatrixByLabelset(matrix promql.Matrix) (promql.Matrix, error) {
+	index := make(map[uint64]int, len(matrix))
+	out := matrix[:0]
+	for _, s := range matrix {
+		hash := s.Metric.Hash()
+		idx, ok := index[hash]
+		if ok && labels.Equal(out[idx].Metric, s.Metric) {
+			merged := make([]promql.FPoint, 0, len(out[idx].Floats)+len(s.Floats))
+			a, b := out[idx].Floats, s.Floats
+			for len(a) > 0 && len(b) > 0 {
+				switch {
+				case a[0].T < b[0].T:
+					merged, a = append(merged, a[0]), a[1:]
+				case b[0].T < a[0].T:
+					merged, b = append(merged, b[0]), b[1:]
+				default:
+					return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "vector cannot contain metrics with the same labelset")
+				}
+			}
+			out[idx].Floats = append(append(merged, a...), b...)
+			continue
+		}
+		index[hash] = len(out)
+		out = append(out, s)
+	}
+	return out, nil
+}
+
+func resultToMatrix(res *promql.Result) (promql.Matrix, error) {
+	switch v := res.Value.(type) {
+	case promql.Matrix:
+		return v, nil
+	case promql.Vector:
+		matrix := make(promql.Matrix, 0, len(v))
+		for _, s := range v {
+			matrix = append(matrix, promql.Series{Metric: s.Metric, Floats: []promql.FPoint{{T: s.T, F: s.F}}})
+		}
+		return matrix, nil
+	case promql.Scalar:
+		return promql.Matrix{{Metric: labels.EmptyLabels(), Floats: []promql.FPoint{{T: v.T, F: v.V}}}}, nil
+	default:
+		return nil, errors.NewInternalf(errors.CodeInternal, "unexpected hybrid result type %T", res.Value)
+	}
+}
+
+// hybridQueryable serves synthetic (compiled) selectors from memory and
+// everything else from the live storage.
+type hybridQueryable struct {
+	client    *client
+	synthetic map[string][]*series
+}
+
+func (h *hybridQueryable) Querier(mint, maxt int64) (storage.Querier, error) {
+	return &hybridQuerier{
+		querier:   querier{mint: mint, maxt: maxt, client: h.client},
+		synthetic: h.synthetic,
+	}, nil
+}
+
+type hybridQuerier struct {
+	querier
+	synthetic map[string][]*series
+}
+
+func (h *hybridQuerier) Select(ctx context.Context, sortSeries bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {
+	if name, ok := isSyntheticSelector(matchers); ok {
+		list := h.synthetic[name]
+		if sortSeries {
+			sorted := make([]*series, len(list))
+			copy(sorted, list)
+			sort.Slice(sorted, func(i, j int) bool { return labels.Compare(sorted[i].lset, sorted[j].lset) < 0 })
+			list = sorted
+		}
+		return newSeriesSet(list)
+	}
+	return h.querier.Select(ctx, sortSeries, hints, matchers...)
+}

pkg/prometheus/clickhouseprometheusv2/transpiler_sql.go

@@ -0,0 +1,412 @@
+package clickhouseprometheusv2
+
+import (
+	"fmt"
+	"strings"
+
+	"github.com/huandu/go-sqlbuilder"
+)
+
+// experimental gate for the timeSeries*ToGrid aggregate functions; attached
+// as a SETTINGS clause so telemetrystore hooks cannot clobber it.
+const gridFunctionsSetting = "SETTINGS allow_experimental_ts_to_grid_aggregate_function = 1"
+
+var aggForEach = map[string]string{
+	"sum":   "sumForEach",
+	"min":   "minForEach",
+	"max":   "maxForEach",
+	"avg":   "avgForEach",
+	"count": "countForEach",
+}
+
+// buildUnitSQL renders the single ClickHouse query evaluating a core unit
+// over the [startMs, endMs] / stepMs evaluation grid: per-series grids via a
+// timeSeries*ToGrid aggregate (or a windowed aggregation for *_over_time),
+// then spatial aggregation with -ForEach combinators grouped by a canonical
+// JSON key of the projected label pairs.
+//
+// The heavy level is shaped to run on the shards: the top-level FROM is the
+// distributed samples table and the group-key join partner is a subquery on
+// the shard-local time series table, so the shard rewrite executes the join
+// and the per-(fingerprint, group key) aggregation next to the data —
+// complete by fingerprint co-locality (see localTimeSeriesTable) — and the
+// initiator only merges the per-series states and applies the spatial
+// -ForEach step. Same layout as the telemetrymetrics statement builder.
+// The windowed *_over_time form shares the frame but aggregates per
+// (series, group key, step bucket) instead of straight to grids
+// (see windowedInner).
+//
+// The selector's data window is offset-shifted; the resulting grid indices
+// map 1:1 onto the query grid (output ts = startMs + i*stepMs). Grid
+// parameters are rendered as literals — they are aggregate-function
+// parameters, not bindable values.
+//
+// Statements nest builder-rendered SQL as text, so the returned args must be
+// ordered by where each fragment lands in the final statement: ClickHouse
+// binds ? placeholders by position. A JOIN renders before WHERE, so a joined
+// subquery's args precede the outer query's own condition args.
+//
+// Row shape: the group-key columns (see groupKeyColumns) followed by
+// grid Array(Nullable(Float64)); NULL grid points are absent points (the
+// engine's "no value here"), which the -ForEach combinators preserve: an
+// index where every series is NULL aggregates to NULL, and countForEach's 0
+// is mapped back to NULL.
+func buildUnitSQL(unit *coreUnit, metricNames []string, dataStart, dataEnd int64, startMs, endMs, stepMs, lookbackMs int64) (string, []any, error) {
+	selStart := startMs - unit.offsetMs
+	selEnd := endMs - unit.offsetMs
+	stepSec := stepMs / 1000
+	if stepSec == 0 {
+		// Instant query: start == end, so the grid has one point for any
+		// positive step.
+		stepSec = 1
+	}
+	windowMs := unit.rangeMs
+	if unit.kind == unitInstant {
+		windowMs = lookbackMs
+	}
+	windowSec := windowMs / 1000
+
+	adjustedTsStart, tsTable := timeSeriesTableFor(dataStart, dataEnd)
+	keyNames := groupKeyColumns(unit)
+
+	// seriesSub computes fingerprint -> group key columns. It reads the
+	// local series table when it rides inside the shard-rewritten samples
+	// query, and the distributed one when it joins at the initiator
+	// (windowed form).
+	seriesSub := func(table string) (string, []any, error) {
+		sub := sqlbuilder.NewSelectBuilder()
+		selects := []string{"fingerprint"}
+		if keyNames == nil {
+			selects = append(selects, groupKeyExpr(unit)+" AS gkey")
+		} else {
+			// by (...) grouping extracts exactly the listed labels as plain
+			// columns: no reason to build, sort and stringify every label
+			// pair per row when the projection is a known short list and
+			// the label names live in Go anyway.
+			for i, name := range keyNames {
+				selects = append(selects, fmt.Sprintf("JSONExtractString(labels, %s) AS g%d", sub.Var(name), i))
+			}
+		}
+		sub.Select(selects...)
+		sub.From(fmt.Sprintf("%s.%s", databaseName, table))
+		if err := applySeriesConditions(sub, adjustedTsStart, dataEnd, unit.matchers); err != nil {
+			return "", nil, err
+		}
+		sub.GroupBy(append([]string{"fingerprint"}, keyColumnAliases(keyNames)...)...)
+		q, args := sub.BuildWithFlavor(sqlbuilder.ClickHouse)
+		return q, args, nil
+	}
+
+	// samplesConditions adds the samples-side WHERE. The group-key join
+	// restricts to the matched series; no fingerprint condition is added
+	// here.
+	samplesConditions := func(sb *sqlbuilder.SelectBuilder, excludeStale bool) {
+		switch len(metricNames) {
+		case 0:
+			// No name constraint derivable; correct but unable to use the
+			// metric_name primary-key prefix.
+		case 1:
+			sb.Where(sb.EQ("metric_name", metricNames[0]))
+		default:
+			sb.Where(sb.In("metric_name", sqlbuilder.List(metricNames)))
+		}
+		// temporality precedes metric_name in the samples primary key; the
+		// fingerprints already come from these temporalities, so this only
+		// helps granule pruning.
+		sb.Where("temporality IN ['Cumulative', 'Unspecified']")
+		// When the window is narrower than the step, the grid windows
+		// (t_k − window, t_k] cover only window/step of the selector's
+		// timeline; a sample in a gap belongs to no window and cannot move
+		// any grid point, but the grid aggregate buffers every row it is
+		// fed. Keeping only in-window rows cut a 36k-series 1w rate from
+		// 74s/28GiB to 16s/4.3GiB on fleet data — the read stays the same,
+		// the aggregate input shrinks by the coverage ratio. The lattice
+		// anchors at selStart (end may sit off-lattice on unaligned grids),
+		// positiveModulo because samples above selStart make the dividend
+		// negative, and the upper bound tightens to the last grid point —
+		// rows past it are equally windowless. window >= step tiles the
+		// timeline and keeps today's plain bounds.
+		sliver := stepMs > 0 && windowMs > 0 && windowMs < stepMs
+		upper := selEnd
+		if sliver {
+			upper = selStart + (selEnd-selStart)/stepMs*stepMs
+		}
+		// Left-open window: a sample exactly at the window's lower boundary
+		// is never used (range selectors and lookback are both left-open).
+		sb.Where(sb.GT("unix_milli", selStart-windowMs), sb.LTE("unix_milli", upper))
+		if sliver {
+			sb.Where(fmt.Sprintf("positiveModulo(%s - unix_milli, %s) < %s",
+				sb.Var(selStart), sb.Var(stepMs), sb.Var(windowMs)))
+		}
+		if excludeStale {
+			// PromQL excludes stale markers from range vectors. Instant
+			// selectors need the stale rows for shadowing instead.
+			sb.Where("bitAnd(flags, 1) = 0")
+		}
+	}
+
+	keyCols := keyColumnAliases(keyNames)
+
+	// joinedInner builds the shard-side SELECT for the single-pass kinds:
+	// grid expression per (fingerprint, group key), group-key join against
+	// the local series table.
+	joinedInner := func(gridExpr string, excludeStale bool) (string, []any, error) {
+		seriesSQL, seriesArgs, err := seriesSub(localTimeSeriesTable(tsTable))
+		if err != nil {
+			return "", nil, err
+		}
+		sb := sqlbuilder.NewSelectBuilder()
+		selects := make([]string, 0, len(keyCols)+1)
+		// A fingerprint is the hash of one labelset, so every group-key
+		// column is functionally dependent on it: any() is exact, and
+		// grouping by the fingerprint alone spares hashing the joined
+		// string per sample row — measured -10-13% on a 1.9B-row rate.
+		for _, col := range keyCols {
+			selects = append(selects, fmt.Sprintf("any(series.%s) AS %s", col, col))
+		}
+		sb.Select(append(selects, gridExpr+" AS grid")...)
+		sb.From(fmt.Sprintf("%s.%s AS points", databaseName, distributedSamplesV4))
+		sb.JoinWithOption(sqlbuilder.InnerJoin, fmt.Sprintf("(%s) AS series", seriesSQL), "points.fingerprint = series.fingerprint")
+		samplesConditions(sb, excludeStale)
+		sb.GroupBy("points.fingerprint")
+		q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
+		// The join text renders before WHERE: its args come first.
+		return q, append(seriesArgs, args...), nil
+	}
+
+	var inner string
+	var innerArgs []any
+	var err error
+	switch unit.kind {
+	case unitInstant:
+		// Instant selection with stale shadowing: the grid value is the last
+		// non-stale sample in (t-lookback, t], absent when the overall last
+		// sample in that window is a stale marker (verified semantics: the
+		// -If combinator applies to the grid aggregates, and NULL comparisons
+		// make a stale-latest point absent).
+		gridParams := fmt.Sprintf("(fromUnixTimestamp64Milli(%d), fromUnixTimestamp64Milli(%d), %d, %d)", selStart, selEnd, stepSec, windowSec)
+		gridExpr := fmt.Sprintf(
+			"arrayMap((tall, tok, vok) -> if(tall IS NULL OR tok IS NULL OR tall != tok, NULL, vok), timeSeriesLastToGrid%s(fromUnixTimestamp64Milli(unix_milli), toFloat64(unix_milli)), timeSeriesLastToGridIf%s(fromUnixTimestamp64Milli(unix_milli), toFloat64(unix_milli), bitAnd(flags, 1) = 0), timeSeriesLastToGridIf%s(fromUnixTimestamp64Milli(unix_milli), value, bitAnd(flags, 1) = 0))",
+			gridParams, gridParams, gridParams,
+		)
+		inner, innerArgs, err = joinedInner(gridExpr, false)
+	case unitOverTime:
+		if unit.overFn == "last" {
+			// last_over_time == last non-stale sample in the window: the
+			// stale rows are already excluded in WHERE.
+			gridExpr := fmt.Sprintf(
+				"timeSeriesLastToGrid(fromUnixTimestamp64Milli(%d), fromUnixTimestamp64Milli(%d), %d, %d)(fromUnixTimestamp64Milli(unix_milli), value)",
+				selStart, selEnd, stepSec, windowSec,
+			)
+			inner, innerArgs, err = joinedInner(gridExpr, true)
+			break
+		}
+		inner, innerArgs, err = windowedInner(unit, samplesConditions, seriesSub, keyCols, localTimeSeriesTable(tsTable), selStart, selEnd, stepMs, windowMs)
+	default: // unitRange
+		gridExpr := fmt.Sprintf(
+			"%s(fromUnixTimestamp64Milli(%d), fromUnixTimestamp64Milli(%d), %d, %d)(fromUnixTimestamp64Milli(unix_milli), value)",
+			gridFunction[unit.fn], selStart, selEnd, stepSec, windowSec,
+		)
+		if unit.fn == fnIncrease {
+			// increase == rate * range-seconds, exactly: extrapolatedRate
+			// divides by the range only when isRate.
+			gridExpr = fmt.Sprintf("arrayMap(x -> x * %d, %s)", windowSec, gridExpr)
+		}
+		inner, innerArgs, err = joinedInner(gridExpr, true)
+	}
+	if err != nil {
+		return "", nil, err
+	}
+
+	spatial := "maxForEach(grid)"
+	switch {
+	case !unit.hasAgg:
+		// Per-series output: one row per (labels-minus-__name__) group.
+		// Distinct fingerprints can collapse onto the same projected label
+		// set only via a regex __name__ selector over metrics with identical
+		// other labels; maxForEach is a deterministic NULL-skipping merge and
+		// the identity for the overwhelmingly common one-fingerprint group.
+	case unit.aggOp.String() == "count":
+		// count over an all-absent index is an absent point, not 0.
+		spatial = "arrayMap(c -> if(c = 0, NULL, toFloat64(c)), countForEach(grid))"
+	default:
+		spatial = fmt.Sprintf("%s(grid)", aggForEach[unit.aggOp.String()])
+	}
+
+	keyList := strings.Join(keyCols, ", ")
+	query := fmt.Sprintf("SELECT %s, %s AS grid FROM (%s) GROUP BY %s %s", keyList, spatial, inner, keyList, gridFunctionsSetting)
+	return query, innerArgs, nil
+}
+
+// groupKeyColumns returns the label names to extract as plain group-key
+// columns, or nil when the unit needs the canonical JSON key instead. Only
+// by (...) grouping qualifies: its projection is a known short list, so
+// extracting each label directly beats building, sorting and stringifying
+// every label pair per row. without and no-aggregation project a label SET
+// that varies per series — there the sorted-JSON key is load-bearing: the
+// sort is what makes two fingerprints with different stored JSON key order
+// land in one group, and the string carries the labels back out.
+func groupKeyColumns(unit *coreUnit) []string {
+	if unit.hasAgg && unit.by && len(unit.grouping) > 0 {
+		return unit.grouping
+	}
+	return nil
+}
+
+// keyColumnAliases names the group-key columns in every SELECT level: g0..gN
+// for direct extraction, the single canonical gkey otherwise.
+func keyColumnAliases(keyNames []string) []string {
+	if keyNames == nil {
+		return []string{"gkey"}
+	}
+	cols := make([]string, len(keyNames))
+	for i := range keyNames {
+		cols[i] = fmt.Sprintf("g%d", i)
+	}
+	return cols
+}
+
+// windowedInner builds the avg/min/max/sum/count _over_time form without
+// fanning samples out. It runs only when the range is a whole multiple of
+// the step (see the transpile gate), because then the window
+// (t_k - range, t_k] is exactly the union of W = range/step step buckets —
+// both are left-open on the same boundaries — so bucket membership fully
+// determines window membership. Fanning each sample into all W windows it
+// covers (ARRAY JOIN) multiplies rows by W, which at long ranges over short
+// steps is a row explosion measured in billions.
+//
+// The bucketing itself is the -Resample combinator: one group per (series,
+// group key) whose state is a fixed array of per-bucket aggregates, updated
+// in place per sample. Grouping by (series, bucket) instead — measured on a
+// 100k-series x 371-bucket workload — creates a 37M-entry hash aggregation
+// whose per-thread partial tables scale memory WITH max_threads (12 -> 48
+// GiB from 2 to 8 threads, dead at 16) and ships one row per group to the
+// initiator; the Resample form carries the same numbers in 100k compact
+// array states, like every other unit kind.
+//
+// The wrapper level slides the window: slot k combines buckets k..k+W-1 by
+// direct aggregation over at most W partials — no prefix-sum tricks, so no
+// large-minus-large cancellation against the engine's directly-summed
+// windows. A slot with zero window count is absent, which also keeps
+// min/max honest: their slices filter on the bucket counts, so an empty
+// bucket's zero-fill can never be mistaken for a value (a real sample can
+// legitimately be 0 or +Inf).
+func windowedInner(unit *coreUnit, samplesConditions func(*sqlbuilder.SelectBuilder, bool), seriesSub func(string) (string, []any, error), keyCols []string, localSeriesTable string, selStart, selEnd, stepMs, windowMs int64) (string, []any, error) {
+	effStepMs := stepMs
+	if effStepMs == 0 {
+		effStepMs = 1000
+	}
+	lastIdx := (selEnd - selStart) / effStepMs
+	gridLen := lastIdx + 1
+	w := windowMs / effStepMs
+	bucketLen := gridLen + w
+
+	// A window narrower than the step makes the windows (t_k - range, t_k]
+	// pairwise disjoint: there is nothing to slide, each slot reads exactly
+	// its own window's aggregate. This is exact ONLY over sliver-filtered
+	// rows (samplesConditions adds the window<step predicate): the index
+	// below assigns every gap sample to the window above it, and the filter
+	// is what removes them. Requires a real step — instant queries carry no
+	// sliver filter, so they keep the tiled form and its gates.
+	disjoint := stepMs > 0 && windowMs < stepMs
+	if disjoint {
+		w = 1
+		bucketLen = gridLen
+	}
+
+	seriesSQL, seriesArgs, err := seriesSub(localSeriesTable)
+	if err != nil {
+		return "", nil, err
+	}
+
+	// Bucket index, shifted so the earliest in-window sample lands at 0:
+	// jj = ceil((ts - selStart)/step) + W - 1, folded into one intDiv. Slot
+	// k's window is then buckets jj in [k, k+W-1]. In the disjoint form the
+	// same ceil lands each in-window sample directly on its slot (W = 1),
+	// and the numerator stays positive: the fetch floor is
+	// selStart - range > selStart - step.
+	jjShift := windowMs
+	if disjoint {
+		jjShift = effStepMs
+	}
+	jj := fmt.Sprintf("intDiv(unix_milli - %d + %d - 1, %d)", selStart, jjShift, effStepMs)
+	buckets := sqlbuilder.NewSelectBuilder()
+	selects := make([]string, 0, len(keyCols)+2)
+	// any() over the group key: exact because the key is functionally
+	// dependent on the fingerprint (see joinedInner).
+	for _, col := range keyCols {
+		selects = append(selects, fmt.Sprintf("any(series.%s) AS %s", col, col))
+	}
+	selects = append(selects, fmt.Sprintf("countResample(0, %d, 1)(value, %s) AS cnts", bucketLen, jj))
+	if unit.overFn != "count" {
+		selects = append(selects, fmt.Sprintf("%sResample(0, %d, 1)(value, %s) AS vals", map[string]string{
+			"avg": "sum",
+			"sum": "sum",
+			"min": "min",
+			"max": "max",
+		}[unit.overFn], bucketLen, jj))
+	}
+	buckets.Select(selects...)
+	buckets.From(fmt.Sprintf("%s.%s AS points", databaseName, distributedSamplesV4))
+	buckets.JoinWithOption(sqlbuilder.InnerJoin, fmt.Sprintf("(%s) AS series", seriesSQL), "points.fingerprint = series.fingerprint")
+	samplesConditions(buckets, true)
+	buckets.GroupBy("points.fingerprint")
+	bucketsSQL, bucketsArgs := buckets.BuildWithFlavor(sqlbuilder.ClickHouse)
+
+	windowCnt := fmt.Sprintf("arraySum(arraySlice(cnts, k + 1, %d))", w)
+	var slot string
+	switch unit.overFn {
+	case "count":
+		slot = fmt.Sprintf("if(%s = 0, NULL, toFloat64(%s))", windowCnt, windowCnt)
+	case "sum":
+		slot = fmt.Sprintf("if(%s = 0, NULL, arraySum(arraySlice(vals, k + 1, %d)))", windowCnt, w)
+	case "avg":
+		slot = fmt.Sprintf("if(%s = 0, NULL, arraySum(arraySlice(vals, k + 1, %d)) / %s)", windowCnt, w, windowCnt)
+	case "min":
+		slot = fmt.Sprintf("if(%s = 0, NULL, arrayMin(arrayFilter((v, c) -> c > 0, arraySlice(vals, k + 1, %d), arraySlice(cnts, k + 1, %d))))", windowCnt, w, w)
+	case "max":
+		slot = fmt.Sprintf("if(%s = 0, NULL, arrayMax(arrayFilter((v, c) -> c > 0, arraySlice(vals, k + 1, %d), arraySlice(cnts, k + 1, %d))))", windowCnt, w, w)
+	}
+
+	keyList := strings.Join(keyCols, ", ")
+	inner := fmt.Sprintf(
+		"SELECT %s, arrayMap(k -> %s, range(toUInt64(%d))) AS grid FROM (%s)",
+		keyList, slot, gridLen, bucketsSQL,
+	)
+	return inner, append(seriesArgs, bucketsArgs...), nil
+}
+
+// groupKeyExpr renders the canonical JSON group key for the units whose
+// projected label SET varies per series (see groupKeyColumns): the sorted
+// [key, value] pairs of the projected labels, JSON-encoded.
+//   - by () with no labels: one constant group;
+//   - without (a, b): keep everything except the listed labels and __name__;
+//   - no aggregation: keep everything including __name__ — even when the
+//     unit drops the name from its OUTPUT, the key must keep it so distinct
+//     metrics never merge in SQL; executeUnit strips the name afterwards and
+//     turns a post-strip collision into the engine's duplicate-labelset
+//     error instead of a silently invented merge.
+func groupKeyExpr(unit *coreUnit) string {
+	// An empty label value means "label absent" in Prometheus; the stored
+	// labels JSON can carry empty attribute values, which must not become
+	// output labels or group keys.
+	pairs := "arraySort(JSONExtractKeysAndValues(labels, 'String'))"
+	if !unit.hasAgg {
+		return fmt.Sprintf("toJSONString(arrayFilter(p -> p.2 != '', %s))", pairs)
+	}
+	if unit.by {
+		// Non-empty by (...) never reaches here; groupKeyColumns extracts
+		// those labels as plain columns instead.
+		return "'[]'"
+	}
+	excluded := append([]string{metricNameLabel}, unit.grouping...)
+	return fmt.Sprintf("toJSONString(arrayFilter(p -> p.2 != '' AND p.1 NOT IN (%s), %s))", quotedList(excluded), pairs)
+}
+
+func quotedList(items []string) string {
+	quoted := make([]string, len(items))
+	for i, s := range items {
+		quoted[i] = "'" + strings.ReplaceAll(s, "'", "\\'") + "'"
+	}
+	return strings.Join(quoted, ", ")
+}

pkg/prometheus/clickhouseprometheusv2/transpiler_test.go

@@ -0,0 +1,751 @@
+package clickhouseprometheusv2
+
+import (
+	"context"
+	"testing"
+	"time"
+
+	"github.com/DATA-DOG/go-sqlmock"
+	cmock "github.com/SigNoz/clickhouse-go-mock"
+	"github.com/SigNoz/signoz/pkg/errors"
+	"github.com/SigNoz/signoz/pkg/factory"
+	"github.com/SigNoz/signoz/pkg/instrumentation/instrumentationtest"
+	"github.com/SigNoz/signoz/pkg/prometheus"
+	"github.com/SigNoz/signoz/pkg/telemetrystore"
+	"github.com/SigNoz/signoz/pkg/telemetrystore/telemetrystoretest"
+	"github.com/prometheus/prometheus/model/labels"
+	"github.com/prometheus/prometheus/promql"
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
+)
+
+func newTestClient(t *testing.T) (*client, *telemetrystoretest.Provider) {
+	t.Helper()
+	store := telemetrystoretest.New(telemetrystore.Config{Provider: "clickhouse"}, sqlmock.QueryMatcherRegexp)
+	settings := factory.NewScopedProviderSettings(instrumentationtest.New().ToProviderSettings(), "clickhouseprometheusv2_test")
+	return newClient(settings, store, prometheus.Config{}), store
+}
+
+var seriesCols = []cmock.ColumnType{
+	{Name: "fingerprint", Type: "UInt64"},
+	{Name: "labels", Type: "String"},
+}
+
+func parse(t *testing.T, q string) parser.Expr {
+	t.Helper()
+	expr, err := parser.NewParser(parser.Options{}).ParseExpr(q)
+	require.NoError(t, err)
+	return expr
+}
+
+func TestClassifyFullShapes(t *testing.T) {
+	tests := []struct {
+		name  string
+		query string
+		check func(t *testing.T, u *coreUnit)
+	}{
+		{
+			name:  "sum by rate",
+			query: `sum by (pod) (rate(http_requests_total{job="api"}[5m]))`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, fnRate, u.fn)
+				assert.Equal(t, int64(300_000), u.rangeMs)
+				assert.True(t, u.hasAgg)
+				assert.True(t, u.by)
+				assert.Equal(t, []string{"pod"}, u.grouping)
+			},
+		},
+		{
+			name:  "bare increase with offset",
+			query: `increase(errors_total[10m] offset 30m)`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, fnIncrease, u.fn)
+				assert.Equal(t, int64(1_800_000), u.offsetMs)
+				assert.False(t, u.hasAgg)
+			},
+		},
+		{
+			name:  "avg without over delta",
+			query: `avg without (instance) (delta(gauge_metric[15m]))`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, fnDelta, u.fn)
+				assert.True(t, u.hasAgg)
+				assert.False(t, u.by)
+			},
+		},
+		{
+			name:  "scalar pipeline with comparison",
+			query: `sum(rate(x[5m])) * 100 > 5`,
+			check: func(t *testing.T, u *coreUnit) {
+				require.Len(t, u.ops, 2)
+				assert.Equal(t, parser.ItemType(parser.MUL), u.ops[0].op)
+				assert.Equal(t, 100.0, u.ops[0].scalar)
+				assert.Equal(t, parser.ItemType(parser.GTR), u.ops[1].op)
+			},
+		},
+		{
+			name:  "scalar on left with unary minus",
+			query: `-1 * sum(rate(x[5m]))`,
+			check: func(t *testing.T, u *coreUnit) {
+				require.Len(t, u.ops, 1)
+				assert.True(t, u.ops[0].scalarOnLeft)
+				assert.Equal(t, -1.0, u.ops[0].scalar)
+			},
+		},
+		{
+			name:  "bool comparison",
+			query: `sum(rate(x[5m])) >= bool 0.5`,
+			check: func(t *testing.T, u *coreUnit) {
+				require.Len(t, u.ops, 1)
+				assert.True(t, u.ops[0].returnBool)
+			},
+		},
+		{
+			name:  "irate utf8 name",
+			query: `sum by ("k8s.pod.name") (irate({"k8s.container.cpu.time"}[2m]))`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, fnIRate, u.fn)
+				assert.Equal(t, []string{"k8s.pod.name"}, u.grouping)
+			},
+		},
+		{
+			name:  "bare instant selector keeps name",
+			query: `up{job="api"}`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitInstant, u.kind)
+				assert.True(t, u.keepsName())
+			},
+		},
+		{
+			name:  "gauge aggregation",
+			query: `sum by (pod) (container_memory offset 5m)`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitInstant, u.kind)
+				assert.Equal(t, int64(300_000), u.offsetMs)
+				assert.True(t, u.hasAgg)
+				assert.False(t, u.keepsName())
+			},
+		},
+		{
+			name:  "gauge comparison keeps name",
+			query: `container_memory > 100`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitInstant, u.kind)
+				assert.True(t, u.keepsName())
+			},
+		},
+		{
+			name:  "gauge arithmetic drops name",
+			query: `container_memory / 1024`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitInstant, u.kind)
+				assert.False(t, u.keepsName())
+			},
+		},
+		{
+			name:  "avg_over_time",
+			query: `max by (node) (avg_over_time(load1[10m]))`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitOverTime, u.kind)
+				assert.Equal(t, "avg", u.overFn)
+				assert.Equal(t, int64(600_000), u.rangeMs)
+			},
+		},
+		{
+			name:  "last_over_time keeps name",
+			query: `last_over_time(load1[10m])`,
+			check: func(t *testing.T, u *coreUnit) {
+				assert.Equal(t, unitOverTime, u.kind)
+				assert.Equal(t, "last", u.overFn)
+				assert.True(t, u.keepsName())
+			},
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			plan, ok := classify(parse(t, tt.query), testGrid(60_000))
+			require.True(t, ok, "expected transpilable")
+			require.True(t, plan.full, "expected full compilation")
+			require.Len(t, plan.units, 1)
+			tt.check(t, &plan.units[0].core)
+		})
+	}
+}
+
+func TestClassifyFallbackShapes(t *testing.T) {
+	queries := []struct {
+		name  string
+		query string
+		step  int64
+	}{
+		{"default-resolution subquery", `max_over_time(rate(x[5m])[30m:])`, 60_000},
+		{"at modifier", `sum(rate(x[5m] @ 1609746000))`, 60_000},
+		{"at modifier on gauge", `sum(container_memory @ 1609746000)`, 60_000},
+		{"sub-second step", `sum(rate(x[5m]))`, 500},
+		{"sub-second range", `sum(rate(x[1500ms]))`, 60_000},
+		{"by __name__ full", `sum by (__name__) (rate({__name__=~"a|b"}[5m]))`, 60_000},
+		{"quantile_over_time unsupported", `quantile_over_time(0.9, load1[10m])`, 60_000},
+		// Duration expressions resolve into the selectors' static fields only
+		// at evaluation time; classification reads those fields as zero, so
+		// transpiling would silently use the wrong offset (caught by the
+		// conformance corpus' duration_expression.test cases). Offset
+		// expressions parse without the experimental-parser flag, so they do
+		// reach the transpiler; range-position expressions are rejected at
+		// parse (the RangeExpr/StepExpr guards are defense-in-depth).
+		{"duration expression offset on instant", `x offset step()`, 60_000},
+		{"duration expression offset arithmetic", `x offset -step()*2`, 60_000},
+		{"duration expression offset on range", `sum(rate(x[5m] offset max(3s, step())))`, 60_000},
+		{"duration expression subquery step", `max_over_time(rate(x[5m])[30m:step()])`, 60_000},
+	}
+	for _, tt := range queries {
+		t.Run(tt.name, func(t *testing.T) {
+			_, ok := classify(parse(t, tt.query), testGrid(tt.step))
+			assert.False(t, ok, "expected fallback for %s", tt.query)
+		})
+	}
+}
+
+func TestClassifyHybridShapes(t *testing.T) {
+	tests := []struct {
+		name          string
+		query         string
+		wantUnits     int
+		wantRewritten string
+	}{
+		{
+			name:          "histogram quantile",
+			query:         `histogram_quantile(0.95, sum by (le) (rate(http_bucket[5m])))`,
+			wantUnits:     1,
+			wantRewritten: `histogram_quantile(0.95, __signoz_transpiled_0__)`,
+		},
+		{
+			name:          "topk over compiled",
+			query:         `topk(5, sum by (pod) (rate(x[5m])))`,
+			wantUnits:     1,
+			wantRewritten: `topk(5, __signoz_transpiled_0__)`,
+		},
+		{
+			name:          "ratio of compiled units",
+			query:         `sum(rate(a[5m])) / sum(rate(b[5m]))`,
+			wantUnits:     2,
+			wantRewritten: `__signoz_transpiled_0__ / __signoz_transpiled_1__`,
+		},
+		{
+			name:          "or vector zero",
+			query:         `sum(rate(a[5m])) or vector(0)`,
+			wantUnits:     1,
+			wantRewritten: `__signoz_transpiled_0__ or vector(0)`,
+		},
+		{
+			name:          "quantile agg over compiled rate",
+			query:         `quantile(0.9, rate(x[5m]))`,
+			wantUnits:     1,
+			wantRewritten: `quantile(0.9, __signoz_transpiled_0__)`,
+		},
+		{
+			name:          "non-literal scalar side stays engine-side",
+			query:         `sum(rate(x[5m])) * scalar(y)`,
+			wantUnits:     1,
+			wantRewritten: `__signoz_transpiled_0__ * scalar(y)`,
+		},
+		{
+			name:          "compiled mixed with raw selector",
+			query:         `sum by (pod) (rate(a[5m])) / on (pod) group_left () b`,
+			wantUnits:     1,
+			wantRewritten: `__signoz_transpiled_0__ / on (pod) group_left () b`,
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			plan, ok := classify(parse(t, tt.query), testGrid(60_000))
+			require.True(t, ok)
+			assert.False(t, plan.full)
+			assert.Len(t, plan.units, tt.wantUnits)
+			assert.Equal(t, tt.wantRewritten, plan.rewritten)
+		})
+	}
+}
+
+func TestClassifyHybridGuards(t *testing.T) {
+	t.Run("no substitution under on(__name__)", func(t *testing.T) {
+		plan, ok := classify(parse(t, `sum(rate(a[5m])) * on (__name__) b`), testGrid(60_000))
+		_ = plan
+		assert.False(t, ok, "matching on __name__ must not see synthetic names")
+	})
+	t.Run("no substitution inside @-pinned subquery", func(t *testing.T) {
+		_, ok := classify(parse(t, `max_over_time(rate(x[5m])[30m:1m] @ 1609746000)`), testGrid(60_000))
+		assert.False(t, ok)
+	})
+}
+
+// The alert-smoothing idiom: units inside a fixed-resolution subquery
+// evaluate on the subquery grid — epoch-aligned multiples of the resolution,
+// starting strictly after (outer start - range), exactly as the engine
+// derives it.
+func TestClassifySubqueryUnits(t *testing.T) {
+	grid := gridContext{startMs: 1_700_000_030_000, endMs: 1_700_007_200_000, stepMs: 60_000}
+
+	plan, ok := classify(parse(t, `min_over_time((sum by (ns) (increase(x[5m])))[10m:5m]) > 0`), grid)
+	require.True(t, ok)
+	require.False(t, plan.full)
+	require.Len(t, plan.units, 1)
+	assert.Equal(t, `min_over_time(__signoz_transpiled_0__[10m:5m]) > 0`, plan.rewritten)
+
+	unit := plan.units[0]
+	// lower bound = outer start - range = 1_699_999_430_000; first multiple
+	// of 300_000 strictly greater is 1_699_999_500_000.
+	assert.Equal(t, int64(1_699_999_500_000), unit.grid.startMs)
+	assert.Equal(t, grid.endMs, unit.grid.endMs)
+	assert.Equal(t, int64(300_000), unit.grid.stepMs)
+	assert.Equal(t, fnIncrease, unit.core.fn)
+
+	t.Run("subquery offset shifts the grid", func(t *testing.T) {
+		plan, ok := classify(parse(t, `max_over_time((sum(rate(x[5m])))[10m:5m] offset 30m)`), grid)
+		require.True(t, ok)
+		require.Len(t, plan.units, 1)
+		// lower = start - offset - range = 1_699_997_630_000 -> first
+		// multiple of 300_000 above = 1_699_997_700_000; end shifts too.
+		assert.Equal(t, int64(1_699_997_700_000), plan.units[0].grid.startMs)
+		assert.Equal(t, grid.endMs-1_800_000, plan.units[0].grid.endMs)
+	})
+
+	t.Run("mollusk ratio-inside-subquery idiom", func(t *testing.T) {
+		q := `min_over_time(((sum by (a) (rate(m1[5m]))) / (avg by (a) (m2)))[5m:1m])`
+		plan, ok := classify(parse(t, q), grid)
+		require.True(t, ok)
+		// Both sides compile on the subquery grid: the rate side and the
+		// gauge aggregation side; the engine joins them and smooths.
+		require.Len(t, plan.units, 2)
+		assert.Equal(t, int64(60_000), plan.units[0].grid.stepMs)
+		assert.Equal(t, unitInstant, plan.units[1].core.kind)
+		assert.Contains(t, plan.rewritten, `__signoz_transpiled_0__ / __signoz_transpiled_1__`)
+	})
+}
+
+func TestBuildUnitSQL(t *testing.T) {
+	unit := &coreUnit{
+		fn:       fnRate,
+		rangeMs:  300_000,
+		hasAgg:   true,
+		aggOp:    parser.SUM,
+		by:       true,
+		grouping: []string{"pod"},
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "http_requests_total")},
+	}
+	sql, args, err := buildUnitSQL(unit, []string{"http_requests_total"}, 1_699_999_700_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 60_000, 300_000)
+	require.NoError(t, err)
+
+	assert.Contains(t, sql, "timeSeriesRateToGrid(fromUnixTimestamp64Milli(1700000000000), fromUnixTimestamp64Milli(1700003600000), 60, 300)(fromUnixTimestamp64Milli(unix_milli), value)")
+	assert.Contains(t, sql, "unix_milli > ? AND unix_milli <= ?")
+	assert.Contains(t, sql, "bitAnd(flags, 1) = 0")
+	assert.Contains(t, sql, "sumForEach(grid)")
+	// The group-key join rides inside the shard query: distributed samples
+	// at the top level, the local series table in the join subquery, the
+	// grid aggregation grouped per (fingerprint, group key) shard-side.
+	assert.Contains(t, sql, "FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint,")
+	assert.Contains(t, sql, "FROM signoz_metrics.time_series_v4 WHERE")
+	// The group key is functionally dependent on the fingerprint (one
+	// labelset per fingerprint): any() is exact and the per-row hash key
+	// shrinks to the fingerprint alone.
+	assert.Contains(t, sql, "any(series.g0) AS g0")
+	assert.Contains(t, sql, "GROUP BY points.fingerprint)")
+	// No samples-side fingerprint condition: the group-key join restricts.
+	assert.NotContains(t, sql, "points.fingerprint IN (")
+	// by (pod) extracts the grouped label directly — no per-row JSON
+	// build/sort/stringify for a known projection.
+	assert.Contains(t, sql, "JSONExtractString(labels, ?) AS g0")
+	assert.NotContains(t, sql, "toJSONString")
+	assert.Contains(t, sql, "SETTINGS allow_experimental_ts_to_grid_aggregate_function = 1")
+	// Args follow placeholder order: the joined series subquery renders
+	// before the samples WHERE, and its select list ('pod') renders before
+	// its own conditions.
+	assert.Equal(t, []any{"pod", "http_requests_total", int64(1_699_999_200_000), int64(1_700_003_600_000), "http_requests_total", int64(1_699_999_700_000), int64(1_700_003_600_000)}, args)
+}
+
+func TestBuildUnitSQLIncreaseAndOffset(t *testing.T) {
+	unit := &coreUnit{
+		fn:       fnIncrease,
+		rangeMs:  600_000,
+		offsetMs: 1_800_000,
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "errors_total")},
+	}
+	sql, _, err := buildUnitSQL(unit, nil, 1_699_997_600_000, 1_700_001_800_000, 1_700_000_000_000, 1_700_003_600_000, 60_000, 300_000)
+	require.NoError(t, err)
+
+	// Grid and window shift by the offset; increase multiplies rate by the
+	// range in seconds.
+	assert.Contains(t, sql, "fromUnixTimestamp64Milli(1699998200000), fromUnixTimestamp64Milli(1700001800000)")
+	assert.Contains(t, sql, "arrayMap(x -> x * 600, timeSeriesRateToGrid")
+	assert.Contains(t, sql, "maxForEach(grid)")
+}
+
+func TestBuildUnitSQLOverLimitJoinOnly(t *testing.T) {
+	// Past the inline limit no fingerprint filter is rendered: the series
+	// join restricts to the matched fingerprints on its own.
+	unit := &coreUnit{
+		fn:       fnRate,
+		rangeMs:  300_000,
+		hasAgg:   true,
+		aggOp:    parser.SUM,
+		by:       true,
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "http_requests_total")},
+	}
+	sql, _, err := buildUnitSQL(unit, []string{"http_requests_total"}, 1_699_999_700_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 60_000, 300_000)
+	require.NoError(t, err)
+
+	assert.NotContains(t, sql, "points.fingerprint IN")
+	assert.Contains(t, sql, "INNER JOIN (SELECT fingerprint,")
+	assert.Contains(t, sql, "FROM signoz_metrics.time_series_v4 WHERE")
+}
+
+func TestBuildUnitSQLWindowSliver(t *testing.T) {
+	// rate[5m] on a 30m grid evaluates only a 5m sliver before each grid
+	// point — samples in the gaps belong to no window and would only be
+	// buffered by the grid aggregate. The WHERE must keep exactly the
+	// in-window rows: positiveModulo anchored at the selector start (end
+	// can sit off-lattice on unaligned grids, and samples above the start
+	// make the plain modulo dividend negative), and the scan capped at the
+	// last grid point — rows past it are equally windowless.
+	unit := &coreUnit{
+		fn:       fnRate,
+		rangeMs:  300_000,
+		hasAgg:   true,
+		aggOp:    parser.SUM,
+		by:       true,
+		grouping: []string{"pod"},
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "http_requests_total")},
+	}
+	sql, args, err := buildUnitSQL(unit, []string{"http_requests_total"}, 1_699_999_700_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 1_800_000, 300_000)
+	require.NoError(t, err)
+
+	assert.Contains(t, sql, "positiveModulo(? - unix_milli, ?) < ?")
+	assert.Equal(t, []any{"pod", "http_requests_total", int64(1_699_999_200_000), int64(1_700_003_600_000), "http_requests_total", int64(1_699_999_700_000), int64(1_700_003_600_000), int64(1_700_000_000_000), int64(1_800_000), int64(300_000)}, args)
+
+	t.Run("off-lattice end caps the scan at the last grid point", func(t *testing.T) {
+		// end - start = 50m at a 30m step: the only grid points are start
+		// and start+30m; samples in the trailing 20m serve no window.
+		_, args, err := buildUnitSQL(unit, []string{"http_requests_total"}, 1_699_999_700_000, 1_700_003_000_000, 1_700_000_000_000, 1_700_003_000_000, 1_800_000, 300_000)
+		require.NoError(t, err)
+		assert.Contains(t, args, int64(1_700_001_800_000))
+	})
+
+	t.Run("window covering the step keeps plain bounds", func(t *testing.T) {
+		sql, _, err := buildUnitSQL(unit, []string{"http_requests_total"}, 1_699_999_700_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 60_000, 300_000)
+		require.NoError(t, err)
+		assert.NotContains(t, sql, "positiveModulo")
+	})
+}
+
+func TestBuildUnitSQLWindowedBucketsWithoutFanOut(t *testing.T) {
+	// The window is W = range/step whole buckets, so each sample lands in
+	// exactly one bucket via GROUP BY and the window slides over bucket
+	// partials — fanning samples into every covered window (ARRAY JOIN)
+	// multiplies rows by W, a row explosion at long ranges.
+	unit := &coreUnit{
+		kind:     unitOverTime,
+		overFn:   "avg",
+		rangeMs:  600_000,
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "node_load1")},
+	}
+	sql, _, err := buildUnitSQL(unit, []string{"node_load1"}, 1_699_999_400_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 60_000, 600_000)
+	require.NoError(t, err)
+
+	assert.NotContains(t, sql, "ARRAY JOIN")
+	// One group per series with fixed per-bucket arrays (-Resample); the
+	// bucket index jj = ceil((ts - start)/step) + W - 1 folded into a single
+	// intDiv. Grouping by (series, bucket) instead measured 37M hash groups
+	// whose per-thread partials scale memory with max_threads.
+	assert.Contains(t, sql, "countResample(0, 71, 1)(value, intDiv(unix_milli - 1700000000000 + 600000 - 1, 60000)) AS cnts")
+	assert.Contains(t, sql, "sumResample(0, 71, 1)(value, intDiv(unix_milli - 1700000000000 + 600000 - 1, 60000)) AS vals")
+	assert.Contains(t, sql, "any(series.gkey) AS gkey")
+	assert.Contains(t, sql, "GROUP BY points.fingerprint)")
+	assert.NotContains(t, sql, "jj) AS jj")
+	assert.Contains(t, sql, "INNER JOIN (SELECT fingerprint,")
+	assert.Contains(t, sql, "FROM signoz_metrics.time_series_v4 WHERE")
+	// Slide: W = 10 buckets per slot, absent when the window count is 0.
+	assert.Contains(t, sql, "arraySum(arraySlice(cnts, k + 1, 10))")
+	assert.Contains(t, sql, "arraySum(arraySlice(vals, k + 1, 10))")
+}
+
+func TestBuildUnitSQLDisjointOverTime(t *testing.T) {
+	// avg_over_time[5m] on a 30m grid: the windows are pairwise disjoint,
+	// so there is no slide — one Resample bucket per grid slot, read
+	// directly. Exact only together with the window-sliver predicate, which
+	// removes the gap samples the ceil index would otherwise assign to the
+	// window above them.
+	unit := &coreUnit{
+		kind:     unitOverTime,
+		overFn:   "avg",
+		rangeMs:  300_000,
+		matchers: []*labels.Matcher{mustMatcher(t, labels.MatchEqual, "__name__", "node_load1")},
+	}
+	sql, _, err := buildUnitSQL(unit, []string{"node_load1"}, 1_699_999_700_000, 1_700_003_600_000, 1_700_000_000_000, 1_700_003_600_000, 1_800_000, 300_000)
+	require.NoError(t, err)
+
+	assert.NotContains(t, sql, "ARRAY JOIN")
+	// gridLen = 3 slots, bucket array the same length — no W tail.
+	assert.Contains(t, sql, "countResample(0, 3, 1)(value, intDiv(unix_milli - 1700000000000 + 1800000 - 1, 1800000)) AS cnts")
+	assert.Contains(t, sql, "sumResample(0, 3, 1)(value, intDiv(unix_milli - 1700000000000 + 1800000 - 1, 1800000)) AS vals")
+	// Single-bucket window: the slide degenerates to reading one slot.
+	assert.Contains(t, sql, "arraySum(arraySlice(cnts, k + 1, 1))")
+	// The sliver predicate is the correctness precondition of this form.
+	assert.Contains(t, sql, "positiveModulo(? - unix_milli, ?) < ?")
+}
+
+// TestDisjointWindowLattice brute-forces the disjoint-form arithmetic: a
+// sample survives the sliver predicate exactly when some grid window
+// contains it, and the ceil bucket index then lands it on that window's
+// slot. This is the pure-Go mirror of the SQL expressions — the predicate
+// in samplesConditions and jj in windowedInner — over random lattices,
+// including off-lattice ends and samples beyond the last grid point.
+func TestDisjointWindowLattice(t *testing.T) {
+	rng := func(seed *uint64) int64 {
+		*seed = *seed*6364136223846793005 + 1442695040888963407
+		return int64(*seed >> 33)
+	}
+	seed := uint64(42)
+	for trial := 0; trial < 2000; trial++ {
+		stepMs := 1_000 * (1 + rng(&seed)%3600)
+		windowMs := 1 + rng(&seed)%(stepMs-1) // strictly below the step
+		selStart := 1_700_000_000_000 + rng(&seed)%1_000_000
+		selEnd := selStart + rng(&seed)%(50*stepMs) // end may sit off-lattice
+		lastIdx := (selEnd - selStart) / stepMs
+		upper := selStart + lastIdx*stepMs
+
+		for i := 0; i < 50; i++ {
+			u := selStart - windowMs - stepMs + rng(&seed)%(selEnd-selStart+3*stepMs)
+
+			// Oracle: is u inside any window (t_k - window, t_k]?
+			inWindow := false
+			var slot int64 = -1
+			for k := int64(0); k <= lastIdx; k++ {
+				tk := selStart + k*stepMs
+				if u > tk-windowMs && u <= tk {
+					inWindow = true
+					slot = k
+					break
+				}
+			}
+
+			// The SQL: fetch bounds, then the sliver predicate
+			// positiveModulo(selStart - u, step) < window.
+			kept := u > selStart-windowMs && u <= upper
+			if kept {
+				pmod := (selStart - u) % stepMs
+				if pmod < 0 {
+					pmod += stepMs
+				}
+				kept = pmod < windowMs
+			}
+
+			require.Equal(t, inWindow, kept,
+				"sliver keep mismatch: u=%d selStart=%d step=%d window=%d", u, selStart, stepMs, windowMs)
+			if !kept {
+				continue
+			}
+			// jj = ceil((u - selStart)/step) via one intDiv; numerator is
+			// positive because u > selStart - window > selStart - step.
+			jj := (u - selStart + stepMs - 1) / stepMs
+			require.Equal(t, slot, jj,
+				"slot mismatch: u=%d selStart=%d step=%d window=%d", u, selStart, stepMs, windowMs)
+		}
+	}
+}
+
+func TestTryExecuteRange_WindowedGateFallsBack(t *testing.T) {
+	c, store := newTestClient(t)
+	e := &executor{client: c, parser: prometheus.NewParser()}
+
+	start := time.UnixMilli(1_700_000_000_000)
+	end := time.UnixMilli(1_700_003_600_000)
+
+	// 10m range at 90s step: the window is not a whole number of buckets.
+	_, ok, err := e.TryExecuteRange(context.Background(), `avg_over_time(up[10m])`, start, end, 90*time.Second)
+	require.NoError(t, err)
+	assert.False(t, ok, "range not divisible by step must not transpile")
+
+	// 1d range at 60s step: 1440 bucket combines per slot, over the cap.
+	_, ok, err = e.TryExecuteRange(context.Background(), `avg_over_time(up[1d])`, start, end, time.Minute)
+	require.NoError(t, err)
+	assert.False(t, ok, "range/step above maxWindowBuckets must not transpile")
+
+	// 1m range at 5m step: the windows are disjoint slivers — no
+	// divisibility or width requirement, so this transpiles.
+	store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("up", int64(1_699_999_200_000), int64(1_700_003_600_000)).WillReturnRows(cmock.NewRows(seriesCols, [][]any{}))
+	_, ok, err = e.TryExecuteRange(context.Background(), `avg_over_time(up[1m])`, start, end, 5*time.Minute)
+	require.NoError(t, err)
+	assert.True(t, ok, "range below step is the disjoint form and must transpile")
+}
+
+func TestApplyScalarOps(t *testing.T) {
+	f := func(v float64) *float64 { return &v }
+
+	t.Run("arithmetic chain", func(t *testing.T) {
+		values := []*float64{f(2), nil, f(4)}
+		applyScalarOps([]scalarOp{{op: parser.MUL, scalar: 100}, {op: parser.ADD, scalar: 1}}, values)
+		require.NotNil(t, values[0])
+		assert.Equal(t, 201.0, *values[0])
+		assert.Nil(t, values[1])
+		assert.Equal(t, 401.0, *values[2])
+	})
+
+	t.Run("comparison filters points", func(t *testing.T) {
+		values := []*float64{f(1), f(10)}
+		applyScalarOps([]scalarOp{{op: parser.GTR, scalar: 5}}, values)
+		assert.Nil(t, values[0])
+		require.NotNil(t, values[1])
+		assert.Equal(t, 10.0, *values[1], "filter comparisons keep the original value")
+	})
+
+	t.Run("bool comparison emits 0/1", func(t *testing.T) {
+		values := []*float64{f(1), f(10)}
+		applyScalarOps([]scalarOp{{op: parser.GTR, scalar: 5, returnBool: true}}, values)
+		assert.Equal(t, 0.0, *values[0])
+		assert.Equal(t, 1.0, *values[1])
+	})
+
+	t.Run("scalar on left division", func(t *testing.T) {
+		values := []*float64{f(4)}
+		applyScalarOps([]scalarOp{{op: parser.DIV, scalar: 100, scalarOnLeft: true}}, values)
+		assert.Equal(t, 25.0, *values[0])
+	})
+}
+
+func TestLabelsFromGroupKey(t *testing.T) {
+	lset, err := labelsFromGroupKey(`[["pod","api-0"],["ns","prod"]]`)
+	require.NoError(t, err)
+	assert.Equal(t, "api-0", lset.Get("pod"))
+	assert.Equal(t, "prod", lset.Get("ns"))
+
+	empty, err := labelsFromGroupKey(`[]`)
+	require.NoError(t, err)
+	assert.True(t, empty.IsEmpty())
+}
+
+// testGrid is a 2h query grid ending on a round timestamp.
+func testGrid(stepMs int64) gridContext {
+	return gridContext{startMs: 1_700_000_000_000, endMs: 1_700_007_200_000, stepMs: stepMs}
+}
+
+// A bool comparison returns 0/1, not the sample, so the engine drops
+// __name__; keeping it would change downstream vector matching.
+func TestKeepsName_BoolComparisonDropsName(t *testing.T) {
+	plan, ok := classify(parse(t, `up > bool 0`), testGrid(60_000))
+	require.True(t, ok)
+	assert.False(t, plan.units[0].core.keepsName())
+
+	plan, ok = classify(parse(t, `up > 0`), testGrid(60_000))
+	require.True(t, ok)
+	assert.True(t, plan.units[0].core.keepsName())
+}
+
+// timeSeriesLastToGrid widens its window to max(window, step) — probed on
+// 25.12 — so Last-style units at window < step must fall back or they would
+// resurrect samples the engine's lookback already dropped.
+func TestTryExecuteRange_LastStyleWindowBelowStepTranspiles(t *testing.T) {
+	// These used to fall back because timeSeriesLastToGrid widens its window
+	// to max(window, step). Over sliver-filtered rows the widening is
+	// harmless — the widened window intersected with the data IS the
+	// lookback window — so the gate is gone and both shapes transpile. The
+	// mock returns no series: the point here is the routing, the value
+	// semantics are the parity suite's job.
+	c, store := newTestClient(t)
+	e := &executor{client: c, parser: prometheus.NewParser()}
+
+	start := time.UnixMilli(1_700_000_000_000)
+	end := time.UnixMilli(1_700_003_600_000)
+
+	store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("up", int64(1_699_999_200_000), int64(1_700_003_600_000)).WillReturnRows(cmock.NewRows(seriesCols, [][]any{}))
+	_, ok, err := e.TryExecuteRange(context.Background(), `sum by (pod) (up)`, start, end, time.Hour)
+	require.NoError(t, err)
+	assert.True(t, ok, "instant selection at step > lookback must transpile")
+
+	store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("up", int64(1_699_999_200_000), int64(1_700_003_600_000)).WillReturnRows(cmock.NewRows(seriesCols, [][]any{}))
+	_, ok, err = e.TryExecuteRange(context.Background(), `last_over_time(up[10m])`, start, end, time.Hour)
+	require.NoError(t, err)
+	assert.True(t, ok, "last_over_time at range < step must transpile")
+}
+
+// Two metrics collapsing onto one labelset after the name drop, with values
+// on the same grid slot, is the engine's duplicate-labelset error; merging
+// them would invent a series no engine would produce. (Temporally disjoint
+// twins merge instead — see TestMergeSameLabelsetSeries.)
+func TestExecuteUnit_NameCollisionErrors(t *testing.T) {
+	c, store := newTestClient(t)
+	e := &executor{client: c, parser: prometheus.NewParser()}
+
+	store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("^(?:a|b)$", int64(1_699_999_200_000), int64(1_700_003_600_000)).WillReturnRows(cmock.NewRows(seriesCols, [][]any{
+		{uint64(1), `{"__name__":"a","job":"x"}`},
+		{uint64(2), `{"__name__":"b","job":"x"}`},
+	}))
+	store.Mock().ExpectQuery("SELECT gkey").
+		WithArgs("^(?:a|b)$", int64(1_699_999_200_000), int64(1_700_003_600_000), "a", "b", int64(1_699_999_700_000), int64(1_700_003_600_000)).
+		WillReturnRows(cmock.NewRows(gkeyCols, [][]any{
+			{`[["__name__","a"],["job","x"]]`, []*float64{f64(1)}},
+			{`[["__name__","b"],["job","x"]]`, []*float64{f64(2)}},
+		}))
+
+	plan, ok := classify(parse(t, `rate({__name__=~"a|b"}[5m])`), gridContext{startMs: 1_700_000_000_000, endMs: 1_700_003_600_000, stepMs: 60_000})
+	require.True(t, ok)
+
+	_, err := e.executeUnit(context.Background(), &plan.units[0].core, plan.units[0].grid)
+	require.Error(t, err)
+	assert.Contains(t, err.Error(), "vector cannot contain metrics with the same labelset")
+}
+
+var gkeyCols = []cmock.ColumnType{
+	{Name: "gkey", Type: "String"},
+	{Name: "grid", Type: "Array(Nullable(Float64))"},
+}
+
+func f64(v float64) *float64 { return &v }
+
+// A nameless selector can span metrics whose series alternate in time (one
+// dies inside the lookback before the other appears); after the name drop
+// the engine merges them into ONE series and errors only when two samples
+// share an evaluation timestamp. Pinned by conformance cases
+// operators.test:994/997 (-{job="api"} over http_requests/http_errors).
+func TestMergeSameLabelsetSeries(t *testing.T) {
+	f := func(v float64) *float64 { return &v }
+	api := labels.FromStrings("job", "api")
+
+	out, err := mergeSameLabelsetSeries([]transpiledSeries{
+		{lset: api, values: []*float64{f(-2), nil}},
+		{lset: api, values: []*float64{nil, f(-4)}},
+		{lset: labels.FromStrings("job", "web"), values: []*float64{f(7), nil}},
+	})
+	require.NoError(t, err)
+	require.Len(t, out, 2)
+	assert.Equal(t, []*float64{f(-2), f(-4)}, out[0].values, "temporally disjoint twins must merge into one series")
+
+	_, err = mergeSameLabelsetSeries([]transpiledSeries{
+		{lset: api, values: []*float64{f(1), nil}},
+		{lset: api, values: []*float64{f(2), nil}},
+	})
+	require.Error(t, err, "two values on one evaluation timestamp is the engine's duplicate error")
+	assert.True(t, errors.Ast(err, errors.TypeInvalidInput))
+}
+
+// Hybrid twin case: stripping the synthetic __name__ can leave two engine
+// output series distinguishable only by those names (-metric_a or -metric_b:
+// both {} once real names are dropped). Pinned by conformance cases
+// name_label_dropping.test:137 and operators.test:1016.
+func TestMergeMatrixByLabelset(t *testing.T) {
+	empty := labels.EmptyLabels()
+
+	out, err := mergeMatrixByLabelset(promql.Matrix{
+		{Metric: empty, Floats: []promql.FPoint{{T: 0, F: -1}}},
+		{Metric: empty, Floats: []promql.FPoint{{T: 600_000, F: -4}}},
+	})
+	require.NoError(t, err)
+	require.Len(t, out, 1)
+	assert.Equal(t, []promql.FPoint{{T: 0, F: -1}, {T: 600_000, F: -4}}, out[0].Floats)
+
+	_, err = mergeMatrixByLabelset(promql.Matrix{
+		{Metric: empty, Floats: []promql.FPoint{{T: 0, F: -1}}},
+		{Metric: empty, Floats: []promql.FPoint{{T: 0, F: -3}}},
+	})
+	require.Error(t, err)
+	assert.True(t, errors.Ast(err, errors.TypeInvalidInput))
+}

pkg/prometheus/promapi/handler.go

@@ -0,0 +1,233 @@
+// Package promapi serves the Prometheus HTTP query API over a
+// prometheus.Prometheus provider: /query and /query_range in the shape of
+// Prometheus' /api/v1 endpoints (https://prometheus.io/docs/prometheus/latest/querying/api/),
+// intended to be mounted under a distinguishing prefix (/prometheus/api/v1)
+// so PromQL-only endpoints are separate from the SigNoz query APIs. The
+// request and response contracts follow Prometheus: form-encoded GET/POST
+// params, {"status":"success","data":{resultType,result}} on success and
+// {"status":"error","errorType","error"} with Prometheus' status codes on
+// failure — so Prometheus-compatible clients can point at the prefix.
+package promapi
+
+import (
+	"context"
+	"encoding/json"
+	"log/slog"
+	"math"
+	"net/http"
+	"strconv"
+	"time"
+
+	promModel "github.com/prometheus/common/model"
+	"github.com/prometheus/prometheus/promql"
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/prometheus/prometheus/util/stats"
+
+	"github.com/SigNoz/signoz/pkg/errors"
+	"github.com/SigNoz/signoz/pkg/prometheus"
+)
+
+// Handler serves the Prometheus query API over the configured provider.
+type Handler struct {
+	logger *slog.Logger
+	prom   prometheus.Prometheus
+}
+
+func NewHandler(logger *slog.Logger, prom prometheus.Prometheus) *Handler {
+	return &Handler{logger: logger, prom: prom}
+}
+
+type errorType string
+
+const (
+	errBadData  errorType = "bad_data"
+	errExec     errorType = "execution"
+	errCanceled errorType = "canceled"
+	errTimeout  errorType = "timeout"
+	errInternal errorType = "internal"
+)
+
+type queryData struct {
+	ResultType parser.ValueType  `json:"resultType"`
+	Result     parser.Value      `json:"result"`
+	Stats      stats.QueryStats  `json:"stats,omitempty"`
+}
+
+type response struct {
+	Status    string     `json:"status"`
+	Data      *queryData `json:"data,omitempty"`
+	ErrorType errorType  `json:"errorType,omitempty"`
+	Error     string     `json:"error,omitempty"`
+}
+
+// QueryRange evaluates an expression over a grid: query, start, end, step,
+// and optional timeout/stats params, all in Prometheus' formats.
+func (h *Handler) QueryRange(w http.ResponseWriter, r *http.Request) {
+	start, err := parseTime(r.FormValue("start"))
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	end, err := parseTime(r.FormValue("end"))
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	if end.Before(start) {
+		h.respondError(r.Context(), w, errBadData, errors.NewInvalidInputf(errors.CodeInvalidInput, "end timestamp must not be before start time"))
+		return
+	}
+	step, err := parseDuration(r.FormValue("step"))
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	if step <= 0 {
+		h.respondError(r.Context(), w, errBadData, errors.NewInvalidInputf(errors.CodeInvalidInput, "zero or negative query resolution step widths are not accepted. Try a positive integer"))
+		return
+	}
+	// The engine materializes every point of every series; an unbounded
+	// grid is an unbounded allocation. 11,000 points covers 60s resolution
+	// for a week or 1h resolution for a year.
+	if end.Sub(start)/step > 11000 {
+		h.respondError(r.Context(), w, errBadData, errors.NewInvalidInputf(errors.CodeInvalidInput, "exceeded maximum resolution of 11,000 points per timeseries. Try decreasing the query resolution (?step=XX)"))
+		return
+	}
+
+	ctx, cancel, err := h.contextWithTimeout(r)
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	defer cancel()
+
+	qry, err := h.prom.Engine().NewRangeQuery(ctx, h.prom.Storage(), nil, r.FormValue("query"), start, end, step)
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	h.exec(ctx, w, r, qry)
+}
+
+// Query evaluates an expression at a single instant: query and optional
+// time/timeout/stats params. A missing time evaluates at the server's now,
+// as in Prometheus.
+func (h *Handler) Query(w http.ResponseWriter, r *http.Request) {
+	ts := time.Now()
+	if t := r.FormValue("time"); t != "" {
+		var err error
+		ts, err = parseTime(t)
+		if err != nil {
+			h.respondError(r.Context(), w, errBadData, err)
+			return
+		}
+	}
+
+	ctx, cancel, err := h.contextWithTimeout(r)
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	defer cancel()
+
+	qry, err := h.prom.Engine().NewInstantQuery(ctx, h.prom.Storage(), nil, r.FormValue("query"), ts)
+	if err != nil {
+		h.respondError(r.Context(), w, errBadData, err)
+		return
+	}
+	h.exec(ctx, w, r, qry)
+}
+
+func (h *Handler) exec(ctx context.Context, w http.ResponseWriter, r *http.Request, qry promql.Query) {
+	defer qry.Close()
+	res := qry.Exec(ctx)
+	if res.Err != nil {
+		h.logger.ErrorContext(ctx, "error evaluating promql query", errors.Attr(res.Err))
+		switch res.Err.(type) {
+		case promql.ErrQueryCanceled:
+			h.respondError(ctx, w, errCanceled, res.Err)
+		case promql.ErrQueryTimeout:
+			h.respondError(ctx, w, errTimeout, res.Err)
+		case promql.ErrStorage:
+			h.respondError(ctx, w, errInternal, res.Err)
+		default:
+			h.respondError(ctx, w, errExec, res.Err)
+		}
+		return
+	}
+
+	data := &queryData{ResultType: res.Value.Type(), Result: res.Value}
+	if r.FormValue("stats") != "" {
+		data.Stats = stats.NewQueryStats(qry.Stats())
+	}
+	h.respond(ctx, w, data)
+}
+
+func (h *Handler) contextWithTimeout(r *http.Request) (context.Context, context.CancelFunc, error) {
+	ctx := r.Context()
+	if to := r.FormValue("timeout"); to != "" {
+		timeout, err := parseDuration(to)
+		if err != nil {
+			return nil, nil, err
+		}
+		ctx, cancel := context.WithTimeout(ctx, timeout)
+		return ctx, cancel, nil
+	}
+	ctx, cancel := context.WithCancel(ctx)
+	return ctx, cancel, nil
+}
+
+func (h *Handler) respond(ctx context.Context, w http.ResponseWriter, data *queryData) {
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(http.StatusOK)
+	if err := json.NewEncoder(w).Encode(&response{Status: "success", Data: data}); err != nil {
+		h.logger.ErrorContext(ctx, "error writing prometheus api response", errors.Attr(err))
+	}
+}
+
+// respondError follows Prometheus' status-code mapping: bad_data 400,
+// execution 422, canceled/timeout 503, internal 500.
+func (h *Handler) respondError(ctx context.Context, w http.ResponseWriter, typ errorType, err error) {
+	code := http.StatusInternalServerError
+	switch typ {
+	case errBadData:
+		code = http.StatusBadRequest
+	case errExec:
+		code = http.StatusUnprocessableEntity
+	case errCanceled, errTimeout:
+		code = http.StatusServiceUnavailable
+	}
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(code)
+	if encErr := json.NewEncoder(w).Encode(&response{Status: "error", ErrorType: typ, Error: err.Error()}); encErr != nil {
+		h.logger.ErrorContext(ctx, "error writing prometheus api error response", errors.Attr(encErr))
+	}
+}
+
+// parseTime accepts Prometheus' time formats: float unix seconds or RFC3339.
+func parseTime(s string) (time.Time, error) {
+	if t, err := strconv.ParseFloat(s, 64); err == nil {
+		sec, ns := math.Modf(t)
+		return time.Unix(int64(sec), int64(ns*float64(time.Second))), nil
+	}
+	if t, err := time.Parse(time.RFC3339Nano, s); err == nil {
+		return t, nil
+	}
+	return time.Time{}, errors.NewInvalidInputf(errors.CodeInvalidInput, "cannot parse %q to a valid timestamp", s)
+}
+
+// parseDuration accepts Prometheus' duration formats: float seconds or a
+// duration string like 5m.
+func parseDuration(s string) (time.Duration, error) {
+	if d, err := strconv.ParseFloat(s, 64); err == nil {
+		ts := d * float64(time.Second)
+		if ts > float64(math.MaxInt64) || ts < float64(math.MinInt64) {
+			return 0, errors.NewInvalidInputf(errors.CodeInvalidInput, "cannot parse %q to a valid duration. It overflows int64", s)
+		}
+		return time.Duration(ts), nil
+	}
+	if d, err := promModel.ParseDuration(s); err == nil {
+		return time.Duration(d), nil
+	}
+	return 0, errors.NewInvalidInputf(errors.CodeInvalidInput, "cannot parse %q to a valid duration", s)
+}

pkg/querier/promql_query.go

@@ -345,8 +345,8 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
 	}
 
 	// Accumulate ClickHouse-side scan stats across every storage query this
-	// evaluation issues: progress options propagate to each ClickHouse query
-	// through the context.
+	// evaluation issues (engine selectors or the compiled executor): progress
+	// options propagate to each ClickHouse query through the context.
 	var statsMu sync.Mutex
 	var rowsScanned, bytesScanned uint64
 	ctx = clickhouse.Context(ctx, clickhouse.WithProgress(func(p *clickhouse.Progress) {
@@ -372,6 +372,23 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
 		return q.toResult(matrix, nil, began, &statsMu, &rowsScanned, &bytesScanned), nil
 	}
 
+	// When the serving provider itself is clickhousev2
+	// (prometheus::provider: clickhousev2), serve the way the provider is
+	// designed to serve: transpiled when the shape allows. Without this the
+	// override would silently run the engine path only.
+	if prov, ok := q.promEngine.(*clickhouseprometheusv2.Provider); ok {
+		matrix, served, err := prov.TryExecuteRange(ctx, query, time.Unix(0, start), time.Unix(0, end), q.query.Step.Duration)
+		if err != nil {
+			if enhanced := tryEnhancePromQLExecError(err); enhanced != nil {
+				return nil, enhanced
+			}
+			return nil, err
+		}
+		if served {
+			return q.toResult(matrix, nil, began, &statsMu, &rowsScanned, &bytesScanned), nil
+		}
+	}
+
 	qry, err := q.promEngine.Engine().NewRangeQuery(
 		ctx,
 		q.promEngine.Storage(),

pkg/querier/promql_shadow.go

@@ -20,11 +20,11 @@ import (
 const shadowTimeout = 2 * time.Minute
 
 // runShadowCompare executes the query on the clickhousev2 provider exactly
-// as it would serve (the engine over the v2 querier), compares against the
-// served result and logs the outcome. Serving is never affected: this runs
-// after the response, off the request context, and only logs. The mismatch
-// and failure logs are the rollout evidence — serving cuts over to v2 only
-// after they stay clean.
+// as it would serve (transpiled when the shape allows, engine over the v2
+// querier otherwise), compares against the served result and logs the
+// outcome. Serving is never affected: this runs after the response, off the
+// request context, and only logs. The mismatch and failure logs are the
+// rollout evidence — serving cuts over to v2 only after they stay clean.
 func (q *promqlQuery) runShadowCompare(ctx context.Context, query string, startNs, endNs int64, served promql.Matrix, servedIn time.Duration) {
 	defer func() {
 		if r := recover(); r != nil {
@@ -46,7 +46,7 @@ func (q *promqlQuery) runShadowCompare(ctx context.Context, query string, startN
 
 	start, end := time.Unix(0, startNs), time.Unix(0, endNs)
 	began := time.Now()
-	shadow, err := executeOnProvider(ctx, q.opts.shadow, query, start, end, q.query.Step.Duration)
+	shadow, transpiled, err := executeOnProvider(ctx, q.opts.shadow, query, start, end, q.query.Step.Duration)
 	shadowIn := time.Since(began)
 
 	logAttrs := []any{
@@ -54,6 +54,7 @@ func (q *promqlQuery) runShadowCompare(ctx context.Context, query string, startN
 		slog.Int64("start_ms", startNs/int64(time.Millisecond)),
 		slog.Int64("end_ms", endNs/int64(time.Millisecond)),
 		slog.Duration("step", q.query.Step.Duration),
+		slog.Bool("transpiled", transpiled),
 		slog.Duration("served_in", servedIn),
 		slog.Duration("shadow_in", shadowIn),
 	}
@@ -83,29 +84,38 @@ func (q *promqlQuery) runShadowCompare(ctx context.Context, query string, startN
 // serveFromProvider evaluates the query the way the pinned provider would
 // serve it.
 func (q *promqlQuery) serveFromProvider(ctx context.Context, query string, startNs, endNs int64) (promql.Matrix, error) {
-	return executeOnProvider(ctx, q.opts.serve, query, time.Unix(0, startNs), time.Unix(0, endNs), q.query.Step.Duration)
+	matrix, _, err := executeOnProvider(ctx, q.opts.serve, query, time.Unix(0, startNs), time.Unix(0, endNs), q.query.Step.Duration)
+	return matrix, err
 }
 
 // executeOnProvider evaluates the query the way the provider would serve it:
-// the engine over the provider's storage. The returned matrix is an owned
-// copy.
-func executeOnProvider(ctx context.Context, prov *clickhouseprometheusv2.Provider, query string, start, end time.Time, step time.Duration) (promql.Matrix, error) {
+// transpiled in ClickHouse when the shape allows, the engine over the
+// provider's storage otherwise. The returned matrix is an owned copy.
+func executeOnProvider(ctx context.Context, prov *clickhouseprometheusv2.Provider, query string, start, end time.Time, step time.Duration) (promql.Matrix, bool, error) {
+	matrix, ok, err := prov.TryExecuteRange(ctx, query, start, end, step)
+	if err != nil {
+		return nil, true, err
+	}
+	if ok {
+		return matrix, true, nil
+	}
+
 	qry, err := prov.Engine().NewRangeQuery(ctx, prov.Storage(), nil, query, start, end, step)
 	if err != nil {
-		return nil, err
+		return nil, false, err
 	}
 	defer qry.Close()
 
 	res := qry.Exec(ctx)
 	if res.Err != nil {
-		return nil, res.Err
+		return nil, false, res.Err
 	}
-	matrix, err := res.Matrix()
+	matrix, err = res.Matrix()
 	if err != nil {
-		return nil, err
+		return nil, false, err
 	}
 	// Close returns the result's sample slices to the engine pool.
-	return copyMatrix(matrix), nil
+	return copyMatrix(matrix), false, nil
 }
 
 func copyMatrix(matrix promql.Matrix) promql.Matrix {

pkg/query-service/app/clickhouseReader/reader.go

@@ -232,25 +232,6 @@ func NewReader(
 	}
 }
 
-func (r *ClickHouseReader) GetInstantQueryMetricsResult(ctx context.Context, queryParams *model.InstantQueryMetricsParams) (*promql.Result, *stats.QueryStats, *model.ApiError) {
-	qry, err := r.prometheus.Engine().NewInstantQuery(ctx, r.prometheus.Storage(), nil, queryParams.Query, queryParams.Time)
-	if err != nil {
-		return nil, nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-
-	res := qry.Exec(ctx)
-
-	// Optional stats field in response if parameter "stats" is not empty.
-	var qs stats.QueryStats
-	if queryParams.Stats != "" {
-		qs = stats.NewQueryStats(qry.Stats())
-	}
-
-	qry.Close()
-	return res, &qs, nil
-
-}
-
 func (r *ClickHouseReader) GetQueryRangeResult(ctx context.Context, query *model.QueryRangeParams) (*promql.Result, *stats.QueryStats, *model.ApiError) {
 	qry, err := r.prometheus.Engine().NewRangeQuery(ctx, r.prometheus.Storage(), nil, query.Query, query.Start, query.End, query.Step)
 

pkg/query-service/app/http_handler.go

@@ -26,11 +26,10 @@ import (
 	"text/template"
 	"time"
 
-	"github.com/prometheus/prometheus/promql"
-
 	"github.com/SigNoz/signoz/pkg/http/middleware"
 	"github.com/SigNoz/signoz/pkg/http/render"
 	"github.com/SigNoz/signoz/pkg/licensing"
+	"github.com/SigNoz/signoz/pkg/prometheus/promapi"
 	"github.com/SigNoz/signoz/pkg/query-service/app/integrations"
 	"github.com/SigNoz/signoz/pkg/signoz"
 	"github.com/SigNoz/signoz/pkg/types/retentiontypes"
@@ -483,8 +482,12 @@ func (aH *APIHandler) Respond(w http.ResponseWriter, data interface{}) {
 
 // RegisterRoutes registers routes for this handler on the given router
 func (aH *APIHandler) RegisterRoutes(router *mux.Router, am *middleware.AuthZ) {
-	router.HandleFunc("/api/v1/query_range", am.ViewAccess(aH.queryRangeMetrics)).Methods(http.MethodGet)
-	router.HandleFunc("/api/v1/query", am.ViewAccess(aH.queryMetrics)).Methods(http.MethodGet)
+	// PromQL-only endpoints, in Prometheus' own API shape, live under a
+	// /prometheus prefix so they are distinguishable from the SigNoz query
+	// APIs; Prometheus-compatible clients can be pointed at the prefix.
+	promAPI := promapi.NewHandler(aH.logger, aH.Signoz.Prometheus)
+	router.HandleFunc("/prometheus/api/v1/query_range", am.ViewAccess(promAPI.QueryRange)).Methods(http.MethodGet, http.MethodPost)
+	router.HandleFunc("/prometheus/api/v1/query", am.ViewAccess(promAPI.Query)).Methods(http.MethodGet, http.MethodPost)
 	router.HandleFunc("/api/v1/rules", am.ViewAccess(aH.listRules)).Methods(http.MethodGet)
 	router.HandleFunc("/api/v1/rules/{id}", am.ViewAccess(aH.getRule)).Methods(http.MethodGet)
 	router.HandleFunc("/api/v1/rules", am.EditAccess(aH.createRule)).Methods(http.MethodPost)
@@ -1103,115 +1106,6 @@ func (aH *APIHandler) queryDashboardVarsV2(w http.ResponseWriter, r *http.Reques
 	aH.Respond(w, dashboardVars)
 }
 
-func (aH *APIHandler) queryRangeMetrics(w http.ResponseWriter, r *http.Request) {
-
-	query, apiErrorObj := parseQueryRangeRequest(r)
-
-	if apiErrorObj != nil {
-		RespondError(w, apiErrorObj, nil)
-		return
-	}
-
-	// TODO: add structured logging for query and apiError if needed
-
-	ctx := r.Context()
-	if to := r.FormValue("timeout"); to != "" {
-		var cancel context.CancelFunc
-		timeout, err := parseMetricsDuration(to)
-		if aH.HandleError(w, err, http.StatusBadRequest) {
-			return
-		}
-
-		ctx, cancel = context.WithTimeout(ctx, timeout)
-		defer cancel()
-	}
-
-	res, qs, apiError := aH.reader.GetQueryRangeResult(ctx, query)
-
-	if apiError != nil {
-		RespondError(w, apiError, nil)
-		return
-	}
-
-	if res.Err != nil {
-		aH.logger.ErrorContext(r.Context(), "error in query range metrics", errors.Attr(res.Err))
-	}
-
-	if res.Err != nil {
-		switch res.Err.(type) {
-		case promql.ErrQueryCanceled:
-			RespondError(w, &model.ApiError{Typ: model.ErrorCanceled, Err: res.Err}, nil)
-		case promql.ErrQueryTimeout:
-			RespondError(w, &model.ApiError{Typ: model.ErrorTimeout, Err: res.Err}, nil)
-		}
-		RespondError(w, &model.ApiError{Typ: model.ErrorExec, Err: res.Err}, nil)
-		return
-	}
-
-	response_data := &model.QueryData{
-		ResultType: res.Value.Type(),
-		Result:     res.Value,
-		Stats:      qs,
-	}
-
-	aH.Respond(w, response_data)
-
-}
-
-func (aH *APIHandler) queryMetrics(w http.ResponseWriter, r *http.Request) {
-
-	queryParams, apiErrorObj := parseInstantQueryMetricsRequest(r)
-
-	if apiErrorObj != nil {
-		RespondError(w, apiErrorObj, nil)
-		return
-	}
-
-	// TODO: add structured logging for query and apiError if needed
-
-	ctx := r.Context()
-	if to := r.FormValue("timeout"); to != "" {
-		var cancel context.CancelFunc
-		timeout, err := parseMetricsDuration(to)
-		if aH.HandleError(w, err, http.StatusBadRequest) {
-			return
-		}
-
-		ctx, cancel = context.WithTimeout(ctx, timeout)
-		defer cancel()
-	}
-
-	res, qs, apiError := aH.reader.GetInstantQueryMetricsResult(ctx, queryParams)
-
-	if apiError != nil {
-		RespondError(w, apiError, nil)
-		return
-	}
-
-	if res.Err != nil {
-		aH.logger.ErrorContext(r.Context(), "error in query range metrics", errors.Attr(res.Err))
-	}
-
-	if res.Err != nil {
-		switch res.Err.(type) {
-		case promql.ErrQueryCanceled:
-			RespondError(w, &model.ApiError{Typ: model.ErrorCanceled, Err: res.Err}, nil)
-		case promql.ErrQueryTimeout:
-			RespondError(w, &model.ApiError{Typ: model.ErrorTimeout, Err: res.Err}, nil)
-		}
-		RespondError(w, &model.ApiError{Typ: model.ErrorExec, Err: res.Err}, nil)
-	}
-
-	responseData := &model.QueryData{
-		ResultType: res.Value.Type(),
-		Result:     res.Value,
-		Stats:      qs,
-	}
-
-	aH.Respond(w, responseData)
-
-}
-
 func (aH *APIHandler) registerEvent(w http.ResponseWriter, r *http.Request) {
 	request, err := parseRegisterEventRequest(r)
 	if aH.HandleError(w, err, http.StatusBadRequest) {

pkg/query-service/app/parser.go

@@ -27,7 +27,6 @@ import (
 	queues2 "github.com/SigNoz/signoz/pkg/query-service/app/integrations/messagingQueues/queues"
 
 	"github.com/gorilla/mux"
-	promModel "github.com/prometheus/common/model"
 	"go.uber.org/multierr"
 
 	errorsV2 "github.com/SigNoz/signoz/pkg/errors"
@@ -88,95 +87,6 @@ func parseRegisterEventRequest(r *http.Request) (*model.RegisterEventParams, err
 	return postData, nil
 }
 
-func parseMetricsTime(s string) (time.Time, error) {
-	if t, err := strconv.ParseFloat(s, 64); err == nil {
-		s, ns := math.Modf(t)
-		return time.Unix(int64(s), int64(ns*float64(time.Second))), nil
-		// return time.Unix(0, t), nil
-	}
-	if t, err := time.Parse(time.RFC3339Nano, s); err == nil {
-		return t, nil
-	}
-	return time.Time{}, fmt.Errorf("cannot parse %q to a valid timestamp", s)
-}
-
-func parseMetricsDuration(s string) (time.Duration, error) {
-	if d, err := strconv.ParseFloat(s, 64); err == nil {
-		ts := d * float64(time.Second)
-		if ts > float64(math.MaxInt64) || ts < float64(math.MinInt64) {
-			return 0, fmt.Errorf("cannot parse %q to a valid duration. It overflows int64", s)
-		}
-		return time.Duration(ts), nil
-	}
-	if d, err := promModel.ParseDuration(s); err == nil {
-		return time.Duration(d), nil
-	}
-	return 0, fmt.Errorf("cannot parse %q to a valid duration", s)
-}
-
-func parseInstantQueryMetricsRequest(r *http.Request) (*model.InstantQueryMetricsParams, *model.ApiError) {
-	var ts time.Time
-	if t := r.FormValue("time"); t != "" {
-		var err error
-		ts, err = parseMetricsTime(t)
-		if err != nil {
-			return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-		}
-	} else {
-		ts = time.Now()
-	}
-
-	return &model.InstantQueryMetricsParams{
-		Time:  ts,
-		Query: r.FormValue("query"),
-		Stats: r.FormValue("stats"),
-	}, nil
-
-}
-
-func parseQueryRangeRequest(r *http.Request) (*model.QueryRangeParams, *model.ApiError) {
-
-	start, err := parseMetricsTime(r.FormValue("start"))
-	if err != nil {
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-	end, err := parseMetricsTime(r.FormValue("end"))
-	if err != nil {
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-	if end.Before(start) {
-		err := errors.New("end timestamp must not be before start time")
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-
-	step, err := parseMetricsDuration(r.FormValue("step"))
-	if err != nil {
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-
-	if step <= 0 {
-		err := errors.New("zero or negative query resolution step widths are not accepted. Try a positive integer")
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-
-	// For safety, limit the number of returned points per timeseries.
-	// This is sufficient for 60s resolution for a week or 1h resolution for a year.
-	if end.Sub(start)/step > 11000 {
-		err := errors.New("exceeded maximum resolution of 11,000 points per timeseries. Try decreasing the query resolution (?step=XX)")
-		return nil, &model.ApiError{Typ: model.ErrorBadData, Err: err}
-	}
-
-	queryRangeParams := model.QueryRangeParams{
-		Start: start,
-		End:   end,
-		Step:  step,
-		Query: r.FormValue("query"),
-		Stats: r.FormValue("stats"),
-	}
-
-	return &queryRangeParams, nil
-}
-
 func parseGetUsageRequest(r *http.Request) (*model.GetUsageParams, error) {
 	startTime, err := parseTime("start", r)
 	if err != nil {

pkg/query-service/interfaces/interface.go

@@ -14,7 +14,6 @@ import (
 )
 
 type Reader interface {
-	GetInstantQueryMetricsResult(ctx context.Context, query *model.InstantQueryMetricsParams) (*promql.Result, *stats.QueryStats, *model.ApiError)
 	GetQueryRangeResult(ctx context.Context, query *model.QueryRangeParams) (*promql.Result, *stats.QueryStats, *model.ApiError)
 	GetTopLevelOperations(ctx context.Context, start, end time.Time, services []string) (*map[string][]string, *model.ApiError)
 	GetEntryPointOperations(ctx context.Context, query *model.GetTopOperationsParams) (*[]model.TopOperationsItem, error)

pkg/query-service/model/queryParams.go

@@ -4,12 +4,6 @@ import (
 	"time"
 )
 
-type InstantQueryMetricsParams struct {
-	Time  time.Time
-	Query string
-	Stats string
-}
-
 type QueryRangeParams struct {
 	Start time.Time
 	End   time.Time

tests/integration/testdata/promqltestcorpus/known_divergences_v2.json

@@ -1,4 +1,17 @@
 {
-  "note": "Divergences of the clickhousev2 provider (pinned via X-SigNoz-PromQL-Provider) from the upstream reference engine, enforced exactly by 01_upstream_corpus.py in both directions. This ledger is the rollout scorecard for the provider swap: the default provider cannot be replaced by clickhousev2 while anything is listed here. Entries must carry the defect's cause and be REMOVED as the provider is fixed.",
-  "divergences": {}
+  "note": "Divergences of the clickhousev2 provider (pinned via X-SigNoz-PromQL-Provider) from the upstream reference engine, enforced exactly by 01_upstream_corpus.py in both directions. This ledger is the rollout scorecard for the provider swap: the default provider cannot be replaced by clickhousev2 while anything is listed here. Entries must carry the defect's cause and be REMOVED as the provider is fixed. Current class: the engine aggregates floats with Kahan compensated summation (sum, sum_over_time) and an overflow-free incremental mean (avg); ClickHouse's sumForEach/avgForEach/arraySum are naive, so extreme-magnitude corpus data (±1e100 cancellation, ±1.8e308 overflow) diverges on transpiled plans. Burn-down candidates: sumKahanForEach for the cancellation class; the overflow class needs an incremental-mean aggregate ClickHouse does not have.",
+  "divergences": {
+    "aggregators.test:651[base]": "avg over near-max-float64 values: engine's incremental mean never forms the overflowing sum; avgForEach sums then divides, overflowing to +Inf",
+    "aggregators.test:651[instant-coarse]": "same as aggregators.test:651[base] on the coarse-step grid variant",
+    "aggregators.test:654[base]": "avg over near-min-float64 values: engine's incremental mean never forms the overflowing sum; avgForEach overflows to -Inf",
+    "aggregators.test:654[instant-coarse]": "same as aggregators.test:654[base] on the coarse-step grid variant",
+    "aggregators.test:687[base]": "sum over {1e100, -1e100, small}: engine uses Kahan compensated summation; sumForEach's naive summation loses the small terms to cancellation and returns 0",
+    "aggregators.test:687[instant-coarse]": "same as aggregators.test:687[base] on the coarse-step grid variant",
+    "aggregators.test:695[base]": "avg over {1e100, -1e100, small}: same Kahan-vs-naive cancellation as aggregators.test:687, divided by count",
+    "aggregators.test:695[instant-coarse]": "same as aggregators.test:695[base] on the coarse-step grid variant",
+    "functions.test:1084[instant-coarse]": "sum_over_time over a window containing ±1e100: the disjoint coarse-step form's arraySum slide is naive summation, cancelling to 0 (the base variant's W>64 shape falls back to the engine and is exact)",
+    "functions.test:1087[instant-coarse]": "avg_over_time, same window and cancellation as functions.test:1084[instant-coarse]",
+    "functions.test:1149[base]": "avg_over_time over ±2.258e220-magnitude samples: engine's Kahan-compensated incremental mean cancels exactly to 0; the bucketed form's naive slide summation leaves a ~1e202 residue",
+    "functions.test:1149[instant-coarse]": "same as functions.test:1149[base] through the disjoint coarse-step form"
+  }
 }