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2 Commits

Author SHA1 Message Date
Srikanth Chekuri
7e52a79a57 Merge branch 'main' into issue-4293 2026-07-15 15:42:42 +05:30
srikanthccv
2522fe0bcf chore(promql): add clickhousev2 provider (push agg to CH) and shadow-compare promql behind a flag 2026-07-13 10:53:48 +05:30
57 changed files with 5076 additions and 4454 deletions

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@@ -58,6 +58,7 @@ jobs:
- rootuser
- serviceaccount
- querier_json_body
- promqlparity
- querier_skip_resource_fingerprint
- ttl
sqlstore-provider:

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@@ -2682,6 +2682,7 @@ components:
unit:
type: string
value:
format: double
type: number
required:
- value
@@ -3654,6 +3655,7 @@ components:
unit:
type: string
value:
format: double
type: number
required:
- value
@@ -3690,6 +3692,7 @@ components:
unit:
type: string
value:
format: double
type: number
required:
- value

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@@ -3395,6 +3395,7 @@ export interface DashboardtypesThresholdWithLabelDTO {
unit?: string;
/**
* @type number
* @format double
*/
value: number;
}
@@ -3922,6 +3923,7 @@ export interface DashboardtypesComparisonThresholdDTO {
unit?: string;
/**
* @type number
* @format double
*/
value: number;
}
@@ -4210,6 +4212,7 @@ export interface DashboardtypesTableThresholdDTO {
unit?: string;
/**
* @type number
* @format double
*/
value: number;
}

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@@ -15,6 +15,8 @@ var (
FeatureEnableAIObservability = featuretypes.MustNewName("enable_ai_observability")
FeatureEnableMetricsReduction = featuretypes.MustNewName("enable_metrics_reduction")
FeatureUseInfraMonitoringV2 = featuretypes.MustNewName("use_infra_monitoring_v2")
FeatureUsePrometheusClickhouseV2 = featuretypes.MustNewName("use_prometheus_clickhouse_v2")
)
func MustNewRegistry() featuretypes.Registry {
@@ -115,6 +117,14 @@ func MustNewRegistry() featuretypes.Registry {
DefaultVariant: featuretypes.MustNewName("disabled"),
Variants: featuretypes.NewBooleanVariants(),
},
&featuretypes.Feature{
Name: FeatureUsePrometheusClickhouseV2,
Kind: featuretypes.KindBoolean,
Stage: featuretypes.StageExperimental,
Description: "Runs PromQL queries on the clickhousev2 provider alongside the served engine result and logs any difference; serving is unaffected.",
DefaultVariant: featuretypes.MustNewName("disabled"),
Variants: featuretypes.NewBooleanVariants(),
},
)
if err != nil {
panic(err)

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@@ -0,0 +1,89 @@
package clickhouseprometheusv2
import (
"context"
"sync"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/util/annotations"
)
// statementRecorder collects the statements a PromQL evaluation would run.
// Safe for concurrent use: the engine may Select selectors concurrently.
type statementRecorder struct {
mu sync.Mutex
statements []prometheus.CapturedStatement
}
func (r *statementRecorder) record(query string, args []any) {
r.mu.Lock()
defer r.mu.Unlock()
r.statements = append(r.statements, prometheus.CapturedStatement{Query: query, Args: args})
}
func (r *statementRecorder) Statements() []prometheus.CapturedStatement {
r.mu.Lock()
defer r.mu.Unlock()
out := make([]prometheus.CapturedStatement, len(r.statements))
copy(out, r.statements)
return out
}
type captureQueryable struct {
client *client
recorder *statementRecorder
}
func (c *captureQueryable) Querier(mint, maxt int64) (storage.Querier, error) {
return &captureQuerier{
querier: querier{mint: mint, maxt: maxt, client: c.client},
recorder: c.recorder,
}, nil
}
// captureQuerier builds the same SQL as the live querier but records it and
// returns no data. The fingerprint filter always takes the subquery form:
// without executing the series lookup, the inline literal set is unknown.
type captureQuerier struct {
querier
recorder *statementRecorder
}
func (c *captureQuerier) Select(ctx context.Context, _ bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {
if rawQuery, ok := rawSQLQuery(matchers); ok {
c.recorder.record(rawQuery, nil)
return storage.EmptySeriesSet()
}
start, end := c.window(hints)
samplesQuery, args, err := buildSamplesQuery(start, end, metricNamesFromMatchers(matchers), nil, matchers, c.lastSamplePerStepFor(ctx, hints))
if err != nil {
return storage.ErrSeriesSet(err)
}
c.recorder.record(samplesQuery, args)
return storage.EmptySeriesSet()
}
func (c *captureQuerier) LabelValues(context.Context, string, *storage.LabelHints, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
return nil, nil, nil
}
func (c *captureQuerier) LabelNames(context.Context, *storage.LabelHints, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
return nil, nil, nil
}
// metricNamesFromMatchers extracts the statically known metric name, if any.
// The live path derives names from the matched series; the capture path has
// no execution results, so only a __name__ equality contributes.
func metricNamesFromMatchers(matchers []*labels.Matcher) []string {
for _, m := range matchers {
if m.Name == metricNameLabel && m.Type == labels.MatchEqual && m.Value != "" {
return []string{m.Value}
}
}
return nil
}

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@@ -0,0 +1,282 @@
package clickhouseprometheusv2
import (
"context"
"database/sql"
"encoding/json"
"fmt"
"log/slog"
"math"
"slices"
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/factory"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/telemetrystore"
"github.com/SigNoz/signoz/pkg/types/ctxtypes"
"github.com/SigNoz/signoz/pkg/types/instrumentationtypes"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
"github.com/prometheus/prometheus/model/labels"
promValue "github.com/prometheus/prometheus/model/value"
)
// seriesLookup is a series-lookup result: matched fingerprints with their
// labels, and the distinct metric names seen on them.
type seriesLookup struct {
fingerprints map[uint64]labels.Labels
metricNames []string
}
// client executes the series, samples and raw queries against ClickHouse.
type client struct {
settings factory.ScopedProviderSettings
telemetryStore telemetrystore.TelemetryStore
cfg prometheus.ClickhouseV2Config
lookbackMs int64
}
func newClient(settings factory.ScopedProviderSettings, telemetryStore telemetrystore.TelemetryStore, cfg prometheus.Config) *client {
lookback := cfg.LookbackDelta
if lookback <= 0 {
// Mirror the engine: promql defaults an unset lookback to 5m.
lookback = defaultLookbackDelta
}
return &client{
settings: settings,
telemetryStore: telemetryStore,
cfg: cfg.ClickhouseV2,
lookbackMs: lookback.Milliseconds(),
}
}
func (c *client) withContext(ctx context.Context, functionName string) context.Context {
return ctxtypes.NewContextWithCommentVals(ctx, map[string]string{
instrumentationtypes.TelemetrySignal: telemetrytypes.SignalMetrics.StringValue(),
instrumentationtypes.CodeNamespace: "clickhouse-prometheus-v2",
instrumentationtypes.CodeFunctionName: functionName,
})
}
// selectSeries runs the series lookup for the given matchers and window.
func (c *client) selectSeries(ctx context.Context, query string, args []any) (*seriesLookup, error) {
ctx = c.withContext(ctx, "selectSeries")
rows, err := c.telemetryStore.ClickhouseDB().Query(ctx, query, args...)
if err != nil {
return nil, err
}
defer rows.Close()
lookup := &seriesLookup{fingerprints: make(map[uint64]labels.Labels)}
names := make(map[string]struct{})
var fingerprint uint64
var labelsJSON string
for rows.Next() {
if err := rows.Scan(&fingerprint, &labelsJSON); err != nil {
return nil, err
}
lset, err := unmarshalLabels(labelsJSON)
if err != nil {
return nil, err
}
lookup.fingerprints[fingerprint] = lset
if name := lset.Get(metricNameLabel); name != "" {
names[name] = struct{}{}
}
if c.cfg.MaxFetchedSeries > 0 && len(lookup.fingerprints) > c.cfg.MaxFetchedSeries {
return nil, errors.NewInvalidInputf(
errors.CodeInvalidInput,
"promql selector matched more than %d series; narrow the label matchers or raise prometheus::clickhousev2::max_fetched_series",
c.cfg.MaxFetchedSeries,
)
}
}
if err := rows.Err(); err != nil {
return nil, err
}
for name := range names {
lookup.metricNames = append(lookup.metricNames, name)
}
slices.Sort(lookup.metricNames)
return lookup, nil
}
// unmarshalLabels parses the labels JSON column. Unlike v1, the fingerprint
// is not injected as a synthetic label (it would take part in `without (...)`
// grouping and vector matching) and empty-valued labels are dropped: an empty
// label value means "label absent" in Prometheus, and upstream never produces
// such labels, but stored attribute JSON can carry them.
func unmarshalLabels(s string) (labels.Labels, error) {
m := make(map[string]string)
if err := json.Unmarshal([]byte(s), &m); err != nil {
return labels.EmptyLabels(), err
}
builder := labels.NewScratchBuilder(len(m))
for k, v := range m {
if v == "" {
continue
}
builder.Add(k, v)
}
builder.Sort()
return builder.Labels(), nil
}
// selectSamples executes a samples query (raw or last-sample-per-step; both
// produce the same column shape) and assembles the per-series sample slices.
// Rows arrive ordered by (fingerprint, unix_milli). Rows whose fingerprint
// is missing from the lookup are skipped (possible in the subquery filter
// mode, where the fingerprint filter re-runs after the lookup and can see
// series born in between). Stale flags map to the engine's StaleNaN.
// Duplicate timestamps pass through as stored: upstream Prometheus cannot
// produce them (its TSDB rejects them at ingest), our ingest can under
// at-least-once retries, and v1 feeds them to the engine as-is —
// deduplicating here would make this provider silently disagree with both
// v1 and the transpiled statements over the same dirty data. Uniqueness
// belongs to the ingest layer.
func (c *client) selectSamples(ctx context.Context, query string, args []any, lookup *seriesLookup) ([]*series, error) {
ctx = c.withContext(ctx, "selectSamples")
rows, err := c.telemetryStore.ClickhouseDB().Query(ctx, query, args...)
if err != nil {
return nil, err
}
defer rows.Close()
var (
result []*series
current *series
fingerprint uint64
prevFp uint64
timestampMs int64
val float64
flags uint32
first = true
haveCurrent bool
staleMarker = math.Float64frombits(promValue.StaleNaN)
maxSamples = c.cfg.MaxFetchedSamples
fetched int64
unknownCount int
)
for rows.Next() {
if err := rows.Scan(&fingerprint, &timestampMs, &val, &flags); err != nil {
return nil, err
}
fetched++
if maxSamples > 0 && fetched > maxSamples {
return nil, errors.NewInvalidInputf(
errors.CodeInvalidInput,
"promql query would fetch more than %d samples; narrow the selector or time range, or raise prometheus::clickhousev2::max_fetched_samples",
maxSamples,
)
}
if first || fingerprint != prevFp {
first = false
prevFp = fingerprint
lset, ok := lookup.fingerprints[fingerprint]
if !ok {
unknownCount++
haveCurrent = false
continue
}
current = &series{lset: lset}
result = append(result, current)
haveCurrent = true
}
if !haveCurrent {
// Remaining rows of a fingerprint missing from the lookup.
continue
}
if flags&1 == 1 {
val = staleMarker
}
current.ts = append(current.ts, timestampMs)
current.vs = append(current.vs, val)
}
if err := rows.Err(); err != nil {
return nil, err
}
if unknownCount > 0 {
c.settings.Logger().DebugContext(ctx, "skipped samples of fingerprints missing from series lookup",
slog.Int("unknown_fingerprints", unknownCount))
}
return result, nil
}
// queryRaw supports the {job="rawsql", query="..."} escape hatch: the value of
// the query matcher runs as-is, each row becoming a single-sample series
// stamped at the query end. Column "value" is the sample value; every other
// column is a label.
func (c *client) queryRaw(ctx context.Context, query string, ts int64) ([]*series, error) {
ctx = c.withContext(ctx, "queryRaw")
rows, err := c.telemetryStore.ClickhouseDB().Query(ctx, query)
if err != nil {
return nil, err
}
defer rows.Close()
columns := rows.Columns()
targets := make([]any, len(columns))
for i := range targets {
targets[i] = new(scanner)
}
var result []*series
for rows.Next() {
if err := rows.Scan(targets...); err != nil {
return nil, err
}
builder := labels.NewScratchBuilder(len(columns))
var val float64
for i, col := range columns {
v := targets[i].(*scanner)
if col == "value" {
val = v.f
continue
}
builder.Add(col, v.s)
}
builder.Sort()
result = append(result, &series{
lset: builder.Labels(),
ts: []int64{ts},
vs: []float64{val},
})
}
if err := rows.Err(); err != nil {
return nil, err
}
return result, nil
}
var _ sql.Scanner = (*scanner)(nil)
type scanner struct {
f float64
s string
}
func (s *scanner) Scan(val any) error {
s.f = 0
s.s = ""
s.s = fmt.Sprintf("%v", val)
switch val := val.(type) {
case int64:
s.f = float64(val)
case uint64:
s.f = float64(val)
case float64:
s.f = val
case []byte:
s.s = string(val)
}
return nil
}

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@@ -0,0 +1,334 @@
// Package clickhouseprometheusv2 is the second-generation ClickHouse-backed
// 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, 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);
// 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: toJSONString of the
// sorted [label, value] pairs the unit projects, extracted from the stored
// labels JSON. by keeps the listed labels, without excludes them plus
// __name__, no aggregation keeps everything minus __name__ unless the unit
// keeps its name — the engine's name-dropping rules. Correct as a grouping
// key because the pairs are sorted and empty values are filtered: key
// equality is then exactly label-set equality on the projection —
// Prometheus treats an empty label value as the label being absent, and
// stored attribute JSON can carry empties that must not split groups — and
// the same canonical 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: fan-out 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.) Instead, each sample is fanned out to every grid
// index whose window contains it:
//
// ARRAY JOIN range(toUInt64(greatest(0, intDiv(unix_milli - <start> + <step> - 1, <step>))),
// toUInt64(least(<lastIdx>, intDiv(unix_milli + <range> - 1 - <start>, <step>)) + 1)) AS k
//
// Correct because the bounds solve the window condition for k. A sample at
// ts contributes to slot k iff t_k - range < ts <= t_k. The right side
// gives t_k >= ts, so the first index is ceil((ts - start)/step) — a sample
// at exactly t_k belongs to k, the window is right-closed. The left side
// gives t_k < ts + range, and with millisecond-integer timestamps that is
// t_k <= ts + range - 1, so the last index is
// floor((ts + range - 1 - start)/step) — a sample at exactly t_k - range is
// excluded, the window is left-open. Clamped to the grid, the fan-out
// therefore lands each sample in exactly the slots whose windows contain
// it, and GROUP BY (fingerprint, k) with the plain aggregate (avg(value),
// min(value), ...) computes per slot over precisely the engine's sample
// multiset — the same numbers, since avg/min/max/sum/count are
// order-insensitive on a given multiset (sum/avg up to summation order, the
// float caveat above). A second level assembles the positional array with
// groupArray + indexOf, mapping missing indices to NULL — groupArrayInsertAt
// would coerce NULL defaults to 0, which is a value, not absence. The
// group-key join happens at the initiator here, over rows already reduced
// to per-(series, index); see the sharding section for why that costs
// nothing.
//
// # 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
//
// Both paths resolve matchers the same way, once per selector
// (selectSeries): __name__ matchers translate to the metric_name column —
// all four matcher types; the v1 client silently returned nothing for regex
// metric names — and every other matcher to a JSONExtractString condition on
// the labels column (applySeriesConditions). Regexes are anchored before
// they reach match(): PromQL matchers match the whole value, ClickHouse
// match() searches for a substring, and without anchoring =~"api" would
// also select "x-api-y". An equality matcher against "" matches series
// without the label, mirroring PromQL, because JSONExtractString returns ""
// for missing keys. The series tables 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. The resulting label sets drop what v1 leaked into results: the
// synthetic fingerprint label (it would take part in without() grouping and
// vector matching) and empty-valued labels. MaxFetchedSeries fails the
// lookup with a typed invalid-input error past the ceiling — v1's behavior
// for an oversized selector was to buffer everything and OOM, and a 4xx the
// user can narrow beats a dead process serving nobody.
//
// # The engine path
//
// 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 counts rows against
// MaxFetchedSamples while scanning, keeps the first of consecutive equal
// timestamps, maps stale flags to the engine's StaleNaN, and merges series
// with identical label sets (sortAndMerge) — the engine assumes storages
// never emit duplicates. A {job="rawsql", query="..."} selector bypasses all
// of this and runs the query matcher's value verbatim.
//
// # 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 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. Fingerprint filters follow suit:
// matched sets inline as sorted literals up to inlineFingerprintsLimit
// (literals engage the samples primary key; sorting keeps statements
// deterministic), beyond it the group-key join alone restricts — a
// semi-join on the same predicates would only rescan the series table —
// except the windowed *_over_time fan-out, which has no join and keeps a
// shard-local IN subquery rather than expand every series of the metric.
// The engine path's over-limit filter is the same shard-local subquery, 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 (selectSeries, selectSamples, transpiledUnit, LabelValues,
// LabelNames), so this provider's work is attributable in system.query_log
// without guessing from query text.
package clickhouseprometheusv2

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package clickhouseprometheusv2
import (
"fmt"
"math/rand"
"sort"
"testing"
"github.com/stretchr/testify/require"
)
// The lastSamplePerStep correctness argument, executed: for instant selectors, keeping
// only the last sample of every step bucket (bucket 0 = (start, firstEval],
// bucket i = (firstEval+(i-1)·step, firstEval+i·step]) yields exactly the
// same instant-vector selections as the raw samples, for every evaluation
// timestamp on the grid. The engine picks the latest sample in
// (t-lookback, t] per evaluation timestamp t and treats a stale marker as
// absent; both behaviors are emulated here directly.
type tsample struct {
ts int64
value float64
stale bool
}
// engineSelect emulates the engine's instant-selector resolution at
// evaluation timestamp t over samples ordered by timestamp: the latest sample
// in (t-lookback, t], absent when none or when it is a stale marker.
func engineSelect(samples []tsample, t, lookbackMs int64) (tsample, bool) {
var picked tsample
found := false
for _, s := range samples {
if s.ts > t-lookbackMs && s.ts <= t {
picked = s
found = true
}
}
if !found || picked.stale {
return tsample{}, false
}
return picked, true
}
// lastPerStep emulates the last-sample-per-step samples query: group samples into buckets and
// keep only the last sample of each (ties keep either; ClickHouse argMax over
// equal keys is unspecified, so generated timestamps are unique).
func lastPerStep(samples []tsample, firstEvalMs, stepMs int64) []tsample {
last := make(map[int64]tsample)
for _, s := range samples {
var bucket int64
if stepMs > 0 && s.ts > firstEvalMs {
bucket = (s.ts-firstEvalMs-1)/stepMs + 1
}
if cur, ok := last[bucket]; !ok || s.ts > cur.ts {
last[bucket] = s
}
}
out := make([]tsample, 0, len(last))
for _, s := range last {
out = append(out, s)
}
sort.Slice(out, func(i, j int) bool { return out[i].ts < out[j].ts })
return out
}
func TestLastSamplePerStepEquivalence(t *testing.T) {
rng := rand.New(rand.NewSource(42))
for caseIdx := 0; caseIdx < 2000; caseIdx++ {
// Random query shape. Units are milliseconds but kept small so bucket
// boundaries are hit often.
stepMs := []int64{1, 2, 5, 7, 30, 60}[rng.Intn(6)]
lookbackMs := []int64{1, 3, 5, 10, 45}[rng.Intn(5)]
queryStart := int64(1000)
numSteps := rng.Int63n(20)
queryEnd := queryStart + numSteps*stepMs + rng.Int63n(stepMs) // grid may not divide the range
// Engine-derived selector window for instant selectors:
// hints.Start = firstEval - (lookback - 1), hints.End = queryEnd.
hintsStart := queryStart - (lookbackMs - 1)
hintsEnd := queryEnd
firstEval := hintsStart + lookbackMs - 1
require.Equal(t, queryStart, firstEval)
// Random samples inside the fetch window [hints.Start, hints.End],
// with unique timestamps and occasional stale markers. The sample
// count is capped by the window size: timestamps are unique.
windowSize := hintsEnd - hintsStart + 1
numSamples := rng.Int63n(40)
if numSamples > windowSize {
numSamples = windowSize
}
seen := make(map[int64]bool)
var samples []tsample
for int64(len(samples)) < numSamples {
ts := hintsStart + rng.Int63n(windowSize)
if seen[ts] {
continue
}
seen[ts] = true
samples = append(samples, tsample{ts: ts, value: rng.Float64(), stale: rng.Intn(8) == 0})
}
sort.Slice(samples, func(i, j int) bool { return samples[i].ts < samples[j].ts })
reduced := lastPerStep(samples, firstEval, stepMs)
desc := fmt.Sprintf("case=%d step=%d lookback=%d start=%d end=%d samples=%d",
caseIdx, stepMs, lookbackMs, queryStart, queryEnd, len(samples))
for evalTs := queryStart; evalTs <= queryEnd; evalTs += stepMs {
rawPick, rawOK := engineSelect(samples, evalTs, lookbackMs)
reducedPick, reducedOK := engineSelect(reduced, evalTs, lookbackMs)
require.Equal(t, rawOK, reducedOK, "%s eval=%d presence mismatch", desc, evalTs)
if rawOK {
require.Equal(t, rawPick, reducedPick, "%s eval=%d sample mismatch", desc, evalTs)
}
}
}
}
// Instant queries (step 0) evaluate once at firstEval == hints.End; lastSamplePerStep
// collapses to a single bucket over the whole window.
func TestLastSamplePerStepEquivalenceInstantQuery(t *testing.T) {
rng := rand.New(rand.NewSource(7))
for caseIdx := 0; caseIdx < 500; caseIdx++ {
lookbackMs := []int64{1, 3, 5, 10, 45}[rng.Intn(5)]
evalTs := int64(1000)
hintsStart := evalTs - (lookbackMs - 1)
hintsEnd := evalTs
firstEval := hintsStart + lookbackMs - 1
require.Equal(t, evalTs, firstEval)
windowSize := hintsEnd - hintsStart + 1
numSamples := rng.Int63n(10)
if numSamples > windowSize {
numSamples = windowSize
}
seen := make(map[int64]bool)
var samples []tsample
for int64(len(samples)) < numSamples {
ts := hintsStart + rng.Int63n(windowSize)
if seen[ts] {
continue
}
seen[ts] = true
samples = append(samples, tsample{ts: ts, value: rng.Float64(), stale: rng.Intn(4) == 0})
}
sort.Slice(samples, func(i, j int) bool { return samples[i].ts < samples[j].ts })
reduced := lastPerStep(samples, firstEval, 0)
require.LessOrEqual(t, len(reduced), 1, "instant reduction must keep at most one sample")
rawPick, rawOK := engineSelect(samples, evalTs, lookbackMs)
reducedPick, reducedOK := engineSelect(reduced, evalTs, lookbackMs)
require.Equal(t, rawOK, reducedOK, "case=%d presence mismatch", caseIdx)
if rawOK {
require.Equal(t, rawPick, reducedPick, "case=%d sample mismatch", caseIdx)
}
}
}
// A stale marker that is the latest sample of its bucket must shadow older
// samples: the engine sees the marker and reports the series absent, exactly
// as with raw samples. Pre-filtering stale rows would instead resurrect the
// older sample.
func TestLastSamplePerStepKeepsStaleShadowing(t *testing.T) {
lookbackMs := int64(10)
stepMs := int64(5)
queryStart := int64(1000)
samples := []tsample{
{ts: 998, value: 1.0}, // bucket 0
{ts: 999, stale: true}, // bucket 0: marker shadows 998
{ts: 1003, value: 2.0}, // bucket 1
{ts: 1004, stale: true}, // bucket 1: marker shadows 1003
{ts: 1008, value: 3.0, stale: false}, // bucket 2
}
firstEval := queryStart
reduced := lastPerStep(samples, firstEval, stepMs)
for evalTs := queryStart; evalTs <= queryStart+2*stepMs; evalTs += stepMs {
rawPick, rawOK := engineSelect(samples, evalTs, lookbackMs)
reducedPick, reducedOK := engineSelect(reduced, evalTs, lookbackMs)
require.Equal(t, rawOK, reducedOK, "eval=%d", evalTs)
if rawOK {
require.Equal(t, rawPick, reducedPick, "eval=%d", evalTs)
}
}
}

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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, 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 (
_ prometheus.Prometheus = (*Provider)(nil)
_ prometheus.StatementCapturer = (*Provider)(nil)
)
func NewFactory(telemetryStore telemetrystore.TelemetryStore) factory.ProviderFactory[prometheus.Prometheus, prometheus.Config] {
return factory.NewProviderFactory(factory.MustNewName("clickhousev2"), func(ctx context.Context, providerSettings factory.ProviderSettings, config prometheus.Config) (prometheus.Prometheus, error) {
return New(ctx, providerSettings, config, telemetryStore)
})
}
func New(_ context.Context, providerSettings factory.ProviderSettings, config prometheus.Config, telemetryStore telemetrystore.TelemetryStore) (*Provider, error) {
settings := factory.NewScopedProviderSettings(providerSettings, "github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2")
engine := prometheus.NewEngine(settings.Logger(), config)
parser := prometheus.NewParser()
client := newClient(settings, telemetryStore, config)
return &Provider{
settings: settings,
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
}
func (p *Provider) Parser() prometheus.Parser {
return p.parser
}
func (p *Provider) Storage() storage.Queryable {
return p
}
func (p *Provider) Querier(mint, maxt int64) (storage.Querier, error) {
return &querier{mint: mint, maxt: maxt, client: p.client}, nil
}
// CapturingStorage implements prometheus.StatementCapturer: a storage that
// records each selector's SQL without executing it, for the preview path.
// A fresh recorder per call keeps concurrent dry-runs isolated.
func (p *Provider) CapturingStorage() (storage.Queryable, prometheus.StatementRecorder) {
recorder := &statementRecorder{}
return &captureQueryable{client: p.client, recorder: recorder}, recorder
}

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package clickhouseprometheusv2
import (
"context"
"fmt"
"slices"
"sort"
"time"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/huandu/go-sqlbuilder"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/util/annotations"
)
// defaultLookbackDelta mirrors promql's default when the config leaves the
// lookback unset; the engine and the storage must agree on it for
// last-sample-per-step bucket anchoring.
const defaultLookbackDelta = 5 * time.Minute
// querier is a native storage.Querier over ClickHouse. Unlike v1 it does not
// round-trip through the remote-read protobuf machinery: Select builds SQL
// directly from the matchers and hints, and the result set is assembled once
// into compact series.
type querier struct {
mint, maxt int64
client *client
}
var _ storage.Querier = (*querier)(nil)
func (q *querier) Select(ctx context.Context, sortSeries bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {
if rawQuery, ok := rawSQLQuery(matchers); ok {
_, end := q.window(hints)
list, err := q.client.queryRaw(ctx, rawQuery, end)
if err != nil {
return storage.ErrSeriesSet(err)
}
if sortSeries {
sort.Slice(list, func(i, j int) bool { return labels.Compare(list[i].lset, list[j].lset) < 0 })
}
return newSeriesSet(list)
}
start, end := q.window(hints)
seriesQuery, seriesArgs, err := buildSeriesQuery(start, end, matchers)
if err != nil {
return storage.ErrSeriesSet(err)
}
lookup, err := q.client.selectSeries(ctx, seriesQuery, seriesArgs)
if err != nil {
return storage.ErrSeriesSet(err)
}
if len(lookup.fingerprints) == 0 {
return storage.EmptySeriesSet()
}
list, err := q.fetchSamples(ctx, start, end, matchers, lookup, q.lastSamplePerStepFor(ctx, hints))
if err != nil {
return storage.ErrSeriesSet(err)
}
// Sorting doubles as duplicate-label-set detection, which the engine
// depends on storages never emitting; the cost is on series count, not
// samples.
list = sortAndMerge(list)
return newSeriesSet(list)
}
// LabelValues returns the values of a label across series matching the
// matchers within the querier window.
func (q *querier) LabelValues(ctx context.Context, name string, hints *storage.LabelHints, matchers ...*labels.Matcher) ([]string, annotations.Annotations, error) {
sb := sqlbuilder.NewSelectBuilder()
if name == metricNameLabel {
sb.Select("DISTINCT metric_name AS value")
} else {
sb.Select(fmt.Sprintf("DISTINCT JSONExtractString(labels, %s) AS value", sb.Var(name)))
}
adjustedStart, table := timeSeriesTableFor(q.mint, q.maxt)
sb.From(fmt.Sprintf("%s.%s", databaseName, table))
if err := applySeriesConditions(sb, adjustedStart, q.maxt, matchers); err != nil {
return nil, nil, err
}
sb.Where("value != ''")
if hints != nil && hints.Limit > 0 {
sb.Limit(hints.Limit)
}
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
values, err := q.selectStrings(ctx, "LabelValues", query, args)
if err != nil {
return nil, nil, err
}
slices.Sort(values)
return values, nil, nil
}
// LabelNames returns the label names present on series matching the matchers
// within the querier window.
func (q *querier) LabelNames(ctx context.Context, hints *storage.LabelHints, matchers ...*labels.Matcher) ([]string, annotations.Annotations, error) {
sb := sqlbuilder.NewSelectBuilder()
sb.Select("DISTINCT arrayJoin(JSONExtractKeys(labels)) AS name")
adjustedStart, table := timeSeriesTableFor(q.mint, q.maxt)
sb.From(fmt.Sprintf("%s.%s", databaseName, table))
if err := applySeriesConditions(sb, adjustedStart, q.maxt, matchers); err != nil {
return nil, nil, err
}
if hints != nil && hints.Limit > 0 {
sb.Limit(hints.Limit)
}
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
names, err := q.selectStrings(ctx, "LabelNames", query, args)
if err != nil {
return nil, nil, err
}
slices.Sort(names)
return names, nil, nil
}
func (q *querier) Close() error {
return nil
}
// window returns the per-selector fetch window. The engine sends per-selector
// bounds in the hints (already adjusted for offset, @, range and lookback);
// they are always at least as tight as the querier-level mint/maxt, which
// span the union of all selectors in the query.
func (q *querier) window(hints *storage.SelectHints) (int64, int64) {
if hints != nil && hints.Start != 0 && hints.End != 0 && hints.Start <= hints.End {
return hints.Start, hints.End
}
return q.mint, q.maxt
}
// lastSamplePerStepFor decides whether the fetch can keep only the last
// sample per step bucket, and computes the bucket parameters. Requirements:
// - the call site attached QueryTraits proving the query has no subquery
// (subquery selectors evaluate at the subquery's own step, but hints
// carry the top-level step);
// - the selector is an instant selector (hints.Range == 0); range selectors
// need every raw sample in the window;
// - per-selector hints are present.
//
// The engine derives hints.Start for instant selectors as
// firstEval - (lookback - 1ms), so the first evaluation timestamp is
// recovered as hints.Start + lookback - 1ms. Bucket boundaries then coincide
// with evaluation timestamps, which is what makes keeping only the last
// sample per bucket lossless.
func (q *querier) lastSamplePerStepFor(ctx context.Context, hints *storage.SelectHints) *lastSamplePerStep {
if hints == nil || hints.Range != 0 || hints.Start <= 0 {
return nil
}
traits, ok := prometheus.QueryTraitsFromContext(ctx)
if !ok || !traits.SubqueryFree {
return nil
}
firstEval := hints.Start + q.client.lookbackMs - 1
if firstEval > hints.End {
// Defensive: never anchor a bucket past the window.
firstEval = hints.End
}
return &lastSamplePerStep{firstEvalMs: firstEval, stepMs: hints.Step}
}
// fetchSamples runs the samples query for the matched series. Small sets
// inline the fingerprints as sorted uint64 literals — literals engage the
// samples primary key, and sorting keeps the statement deterministic for
// logging and tests. Larger sets re-run the series predicates as a
// shard-local IN subquery instead: inlining hundreds of thousands of
// literals makes the statement itself the bottleneck, while the subquery is
// a cheap primary-key scan on each shard's own series table (see
// localTimeSeriesTable for why that is complete).
func (q *querier) fetchSamples(ctx context.Context, start, end int64, matchers []*labels.Matcher, lookup *seriesLookup, lastPerStep *lastSamplePerStep) ([]*series, error) {
var fingerprints []uint64
if len(lookup.fingerprints) <= inlineFingerprintsLimit {
fingerprints = make([]uint64, 0, len(lookup.fingerprints))
for fp := range lookup.fingerprints {
fingerprints = append(fingerprints, fp)
}
slices.Sort(fingerprints)
}
query, args, err := buildSamplesQuery(start, end, lookup.metricNames, fingerprints, matchers, lastPerStep)
if err != nil {
return nil, err
}
return q.client.selectSamples(ctx, query, args, lookup)
}
func (q *querier) selectStrings(ctx context.Context, fn, query string, args []any) ([]string, error) {
ctx = q.client.withContext(ctx, fn)
rows, err := q.client.telemetryStore.ClickhouseDB().Query(ctx, query, args...)
if err != nil {
return nil, err
}
defer rows.Close()
var out []string
var v string
for rows.Next() {
if err := rows.Scan(&v); err != nil {
return nil, err
}
out = append(out, v)
}
if err := rows.Err(); err != nil {
return nil, err
}
return out, nil
}
// rawSQLQuery detects the {job="rawsql", query="..."} escape hatch.
func rawSQLQuery(matchers []*labels.Matcher) (string, bool) {
if len(matchers) != 2 {
return "", false
}
var hasJob bool
var query string
for _, m := range matchers {
if m.Type == labels.MatchEqual && m.Name == "job" && m.Value == "rawsql" {
hasJob = true
}
if m.Type == labels.MatchEqual && m.Name == "query" {
query = m.Value
}
}
if hasJob && query != "" {
return query, true
}
return "", false
}

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package clickhouseprometheusv2
import (
"context"
"fmt"
"testing"
"github.com/DATA-DOG/go-sqlmock"
cmock "github.com/SigNoz/clickhouse-go-mock"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"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/storage"
)
var (
seriesCols = []cmock.ColumnType{
{Name: "fingerprint", Type: "UInt64"},
{Name: "labels", Type: "String"},
}
samplesCols = []cmock.ColumnType{
{Name: "fingerprint", Type: "UInt64"},
{Name: "unix_milli", Type: "Int64"},
{Name: "value", Type: "Float64"},
{Name: "flags", Type: "UInt32"},
}
)
func newTestClient(t *testing.T, cfg prometheus.ClickhouseV2Config) (*client, *telemetrystoretest.Provider) {
t.Helper()
store := telemetrystoretest.New(telemetrystore.Config{Provider: "clickhouse"}, sqlmock.QueryMatcherRegexp)
settings := factory.NewScopedProviderSettings(instrumentationtest.New().ToProviderSettings(), "clickhouseprometheusv2_test")
promCfg := prometheus.Config{ClickhouseV2: cfg}
return newClient(settings, store, promCfg), store
}
func testMatchers(t *testing.T) []*labels.Matcher {
t.Helper()
return []*labels.Matcher{
mustMatcher(t, labels.MatchEqual, "__name__", "cpu_usage"),
mustMatcher(t, labels.MatchEqual, "job", "api"),
}
}
func TestQuerierSelectRawPath(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{})
q := &querier{mint: 1000, maxt: 2000, client: c}
store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("cpu_usage", int64(0), int64(2000), "job", "api").WillReturnRows(cmock.NewRows(seriesCols, [][]any{
{uint64(42), `{"__name__":"cpu_usage","job":"api","instance":"a"}`},
{uint64(7), `{"__name__":"cpu_usage","job":"api","instance":"b"}`},
}))
// Inline fingerprints (sorted), raw samples: no traits in ctx -> no
// last-sample-per-step reduction.
store.Mock().ExpectQuery("SELECT fingerprint, unix_milli, value, flags FROM signoz_metrics.distributed_samples_v4 WHERE metric_name = \\? AND temporality IN \\['Cumulative', 'Unspecified'\\] AND fingerprint IN \\(7, 42\\)").
WithArgs("cpu_usage", int64(1000), int64(2000)).
WillReturnRows(cmock.NewRows(samplesCols, [][]any{
{uint64(7), int64(1100), 1.5, uint32(0)},
{uint64(7), int64(1200), 2.5, uint32(0)},
{uint64(42), int64(1100), 3.5, uint32(1)}, // stale marker
}))
hints := &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000}
set := q.Select(context.Background(), false, hints, testMatchers(t)...)
var got []*series
for set.Next() {
got = append(got, set.At().(*series))
}
require.NoError(t, set.Err())
require.Len(t, got, 2)
// Sorted by labels: instance=a (fp 42) before instance=b (fp 7).
assert.Equal(t, "a", got[0].lset.Get("instance"))
require.Len(t, got[0].ts, 1)
assert.True(t, got[0].vs[0] != got[0].vs[0], "stale marker must be NaN") //nolint:testifylint
assert.Equal(t, "b", got[1].lset.Get("instance"))
assert.Equal(t, []int64{1100, 1200}, got[1].ts)
assert.Equal(t, []float64{1.5, 2.5}, got[1].vs)
// No fingerprint label injected.
assert.Empty(t, got[0].lset.Get("fingerprint"))
}
// Wrong gating silently corrupts range functions (a rate over reduced
// samples loses points), so the decision logic is pinned here even though
// the helper is unexported: the integration suite would catch it too, but
// with far worse failure locality.
func TestLastSamplePerStepFor(t *testing.T) {
c, _ := newTestClient(t, prometheus.ClickhouseV2Config{})
q := &querier{mint: 0, maxt: 2000, client: c}
traitsCtx := prometheus.NewContextWithQueryTraits(context.Background(), prometheus.QueryTraits{SubqueryFree: true})
tests := []struct {
name string
ctx context.Context
hints *storage.SelectHints
want *lastSamplePerStep
}{
{"no traits in context stays raw", context.Background(), &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000}, nil},
{"subquery in the query stays raw", prometheus.NewContextWithQueryTraits(context.Background(), prometheus.QueryTraits{SubqueryFree: false}), &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000}, nil},
{"range selector stays raw", traitsCtx, &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000, Range: 300_000}, nil},
{"instant selector reduces, anchored at first eval", traitsCtx, &storage.SelectHints{Start: 1000, End: 2_000_000, Step: 60_000}, &lastSamplePerStep{firstEvalMs: 1000 + c.lookbackMs - 1, stepMs: 60_000}},
{"anchor never passes the window end", traitsCtx, &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000}, &lastSamplePerStep{firstEvalMs: 2000, stepMs: 60_000}},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
assert.Equal(t, tt.want, q.lastSamplePerStepFor(tt.ctx, tt.hints))
})
}
}
func TestQuerierSelectSeriesBudget(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{MaxFetchedSeries: 1})
q := &querier{mint: 1000, maxt: 2000, client: c}
store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("cpu_usage", int64(0), int64(2000), "job", "api").WillReturnRows(cmock.NewRows(seriesCols, [][]any{
{uint64(1), `{"__name__":"cpu_usage","instance":"a"}`},
{uint64(2), `{"__name__":"cpu_usage","instance":"b"}`},
}))
set := q.Select(context.Background(), false, &storage.SelectHints{Start: 1000, End: 2000}, testMatchers(t)...)
assert.False(t, set.Next())
require.Error(t, set.Err())
assert.True(t, errors.Ast(set.Err(), errors.TypeInvalidInput), "budget error must be typed invalid input, got %v", set.Err())
}
func TestQuerierSelectSamplesBudget(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{MaxFetchedSamples: 2})
q := &querier{mint: 1000, maxt: 2000, client: c}
store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("cpu_usage", int64(0), int64(2000)).WillReturnRows(cmock.NewRows(seriesCols, [][]any{
{uint64(7), `{"__name__":"cpu_usage"}`},
}))
store.Mock().ExpectQuery("SELECT fingerprint, unix_milli, value, flags").
WithArgs("cpu_usage", int64(1000), int64(2000)).
WillReturnRows(cmock.NewRows(samplesCols, [][]any{
{uint64(7), int64(1100), 1.0, uint32(0)},
{uint64(7), int64(1200), 2.0, uint32(0)},
{uint64(7), int64(1300), 3.0, uint32(0)},
}))
set := q.Select(context.Background(), false, &storage.SelectHints{Start: 1000, End: 2000},
mustMatcher(t, labels.MatchEqual, "__name__", "cpu_usage"))
assert.False(t, set.Next())
require.Error(t, set.Err())
assert.True(t, errors.Ast(set.Err(), errors.TypeInvalidInput))
}
func TestQuerierSelectSubqueryFilterOverInlineLimit(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{})
q := &querier{mint: 1000, maxt: 2000, client: c}
seriesRows := make([][]any, inlineFingerprintsLimit+1)
for i := range seriesRows {
seriesRows[i] = []any{uint64(i + 1), fmt.Sprintf(`{"__name__":"cpu_usage","instance":"i%d"}`, i)}
}
store.Mock().ExpectQuery("SELECT fingerprint, any\\(labels\\)").WithArgs("cpu_usage", int64(0), int64(2000), "job", "api").WillReturnRows(cmock.NewRows(seriesCols, seriesRows))
// The over-limit samples query embeds the semi-join against the
// shard-local series table (fingerprint co-locality), not a GLOBAL
// broadcast; args follow placeholder order — samples metric name, then
// the semi-join's series predicates, then the samples window bounds.
store.Mock().ExpectQuery("fingerprint IN \\(SELECT fingerprint FROM signoz_metrics\\.time_series_v4").
WithArgs("cpu_usage", "cpu_usage", int64(0), int64(2000), "job", "api", int64(1000), int64(2000)).
WillReturnRows(cmock.NewRows(samplesCols, [][]any{}))
set := q.Select(context.Background(), false, &storage.SelectHints{Start: 1000, End: 2000}, testMatchers(t)...)
assert.False(t, set.Next())
require.NoError(t, set.Err())
}
func TestQuerierSelectRawSQLPassthrough(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{})
q := &querier{mint: 1000, maxt: 2000, client: c}
rawCols := []cmock.ColumnType{
{Name: "le", Type: "String"},
{Name: "value", Type: "Float64"},
}
store.Mock().ExpectQuery("SELECT le, avg\\(v\\) AS value FROM t").WillReturnRows(cmock.NewRows(rawCols, [][]any{
{"0.5", 12.5},
}))
set := q.Select(context.Background(), false, &storage.SelectHints{Start: 1000, End: 2000},
mustMatcher(t, labels.MatchEqual, "job", "rawsql"),
mustMatcher(t, labels.MatchEqual, "query", "SELECT le, avg(v) AS value FROM t"),
)
require.True(t, set.Next())
s := set.At()
assert.Equal(t, "0.5", s.Labels().Get("le"))
it := s.Iterator(nil)
require.NotNil(t, it)
_, v := func() (int64, float64) { it.Next(); return it.At() }()
assert.Equal(t, 12.5, v)
assert.False(t, set.Next())
}
func TestCaptureQuerierRecordsWithoutExecuting(t *testing.T) {
c, _ := newTestClient(t, prometheus.ClickhouseV2Config{})
recorder := &statementRecorder{}
cq := &captureQuerier{querier: querier{mint: 1000, maxt: 2000, client: c}, recorder: recorder}
ctx := prometheus.NewContextWithQueryTraits(context.Background(), prometheus.QueryTraits{SubqueryFree: true})
set := cq.Select(ctx, false, &storage.SelectHints{Start: 1000, End: 2000, Step: 60_000}, testMatchers(t)...)
assert.False(t, set.Next())
require.NoError(t, set.Err())
statements := recorder.Statements()
require.Len(t, statements, 1)
assert.Contains(t, statements[0].Query, "IN (SELECT fingerprint FROM signoz_metrics.time_series_v4")
assert.Contains(t, statements[0].Query, "argMax(value, unix_milli)")
}

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package clickhouseprometheusv2
import (
"sort"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/chunkenc"
"github.com/prometheus/prometheus/util/annotations"
)
// series is one time series with samples stored as parallel slices, ordered
// by timestamp. The compact layout avoids per-sample allocations and keeps
// iteration cache friendly.
type series struct {
lset labels.Labels
ts []int64
vs []float64
}
var _ storage.Series = (*series)(nil)
func (s *series) Labels() labels.Labels {
return s.lset
}
func (s *series) Iterator(it chunkenc.Iterator) chunkenc.Iterator {
if fit, ok := it.(*floatIterator); ok {
fit.reset(s)
return fit
}
fit := &floatIterator{}
fit.reset(s)
return fit
}
// floatIterator implements chunkenc.Iterator over a series' sample slices.
type floatIterator struct {
s *series
i int
}
var _ chunkenc.Iterator = (*floatIterator)(nil)
func (it *floatIterator) reset(s *series) {
it.s = s
it.i = -1
}
func (it *floatIterator) Next() chunkenc.ValueType {
it.i++
if it.i >= len(it.s.ts) {
return chunkenc.ValNone
}
return chunkenc.ValFloat
}
func (it *floatIterator) Seek(t int64) chunkenc.ValueType { //nolint:govet // stdmethods flags io.Seeker; this is chunkenc.Iterator's Seek
if it.i < 0 {
it.i = 0
}
if it.i >= len(it.s.ts) {
return chunkenc.ValNone
}
// The current position, once valid, must not move backwards.
if it.s.ts[it.i] >= t {
return chunkenc.ValFloat
}
it.i += sort.Search(len(it.s.ts)-it.i, func(j int) bool {
return it.s.ts[it.i+j] >= t
})
if it.i >= len(it.s.ts) {
return chunkenc.ValNone
}
return chunkenc.ValFloat
}
func (it *floatIterator) At() (int64, float64) {
return it.s.ts[it.i], it.s.vs[it.i]
}
func (it *floatIterator) AtHistogram(*histogram.Histogram) (int64, *histogram.Histogram) {
return 0, nil
}
func (it *floatIterator) AtFloatHistogram(*histogram.FloatHistogram) (int64, *histogram.FloatHistogram) {
return 0, nil
}
func (it *floatIterator) AtT() int64 {
return it.s.ts[it.i]
}
// AtST returns the current start timestamp; not tracked by this storage.
func (it *floatIterator) AtST() int64 {
return 0
}
func (it *floatIterator) Err() error {
return nil
}
// seriesSet iterates a fully materialized, label-sorted list of series.
type seriesSet struct {
series []*series
i int
}
var _ storage.SeriesSet = (*seriesSet)(nil)
func newSeriesSet(list []*series) *seriesSet {
return &seriesSet{series: list, i: -1}
}
func (s *seriesSet) Next() bool {
s.i++
return s.i < len(s.series)
}
func (s *seriesSet) At() storage.Series {
return s.series[s.i]
}
func (s *seriesSet) Err() error {
return nil
}
func (s *seriesSet) Warnings() annotations.Annotations {
return nil
}
// sortAndMerge orders series by label set and merges series whose label sets
// are identical. Distinct fingerprints can carry identical label sets (e.g.
// series differing only in a non-label dimension); Prometheus storages never
// expose duplicate label sets to the engine, so merge their samples by
// timestamp, keeping the first sample on ties.
func sortAndMerge(list []*series) []*series {
if len(list) < 2 {
return list
}
sort.Slice(list, func(i, j int) bool {
return labels.Compare(list[i].lset, list[j].lset) < 0
})
out := list[:1]
for _, s := range list[1:] {
last := out[len(out)-1]
if labels.Compare(last.lset, s.lset) != 0 {
out = append(out, s)
continue
}
merged := mergeSamples(last, s)
out[len(out)-1] = merged
}
return out
}
func mergeSamples(a, b *series) *series {
ts := make([]int64, 0, len(a.ts)+len(b.ts))
vs := make([]float64, 0, len(a.ts)+len(b.ts))
i, j := 0, 0
for i < len(a.ts) && j < len(b.ts) {
switch {
case a.ts[i] < b.ts[j]:
ts = append(ts, a.ts[i])
vs = append(vs, a.vs[i])
i++
case a.ts[i] > b.ts[j]:
ts = append(ts, b.ts[j])
vs = append(vs, b.vs[j])
j++
default:
ts = append(ts, a.ts[i])
vs = append(vs, a.vs[i])
i++
j++
}
}
ts = append(ts, a.ts[i:]...)
vs = append(vs, a.vs[i:]...)
ts = append(ts, b.ts[j:]...)
vs = append(vs, b.vs[j:]...)
return &series{lset: a.lset, ts: ts, vs: vs}
}

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package clickhouseprometheusv2
import (
"fmt"
"strconv"
"strings"
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/query-service/constants"
"github.com/huandu/go-sqlbuilder"
"github.com/prometheus/prometheus/model/labels"
)
// inlineFingerprintsLimit is the largest matched-series count inlined into
// the samples query as literals. Literals engage the samples primary key and
// avoid a second series-table scan; past a few thousand the statement itself
// becomes the cost, and the shard-local subquery filter wins. Not
// configurable: the crossover depends on statement parsing, not on any
// property of a deployment an operator could know better.
const inlineFingerprintsLimit = 5_000
// buildSeriesQuery renders the series lookup: one row per matched fingerprint
// with its labels.
func buildSeriesQuery(start, end int64, matchers []*labels.Matcher) (string, []any, error) {
adjustedStart, table := timeSeriesTableFor(start, end)
sb := sqlbuilder.NewSelectBuilder()
sb.Select("fingerprint", "any(labels)")
sb.From(fmt.Sprintf("%s.%s", databaseName, table))
if err := applySeriesConditions(sb, adjustedStart, end, matchers); err != nil {
return "", nil, err
}
sb.GroupBy("fingerprint")
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
return query, args, nil
}
// buildSamplesQuery renders the samples fetch for the series selected by the
// series lookup. Small matched sets pass inlineFingerprints — sorted uint64
// literals that engage the samples primary key; nil means the set exceeded
// the inline limit, and the filter becomes a semi-join re-running the series
// predicates against the shard-local series table (complete by fingerprint
// co-locality, see localTimeSeriesTable; a GLOBAL broadcast of the matched
// set would ship it to every shard instead). metricNames narrows the
// primary-key scan; when the selector had no __name__ equality, the names
// observed on the matched series are used. A non-nil lastPerStep groups to
// one (the last) sample per step bucket.
func buildSamplesQuery(start, end int64, metricNames []string, inlineFingerprints []uint64, matchers []*labels.Matcher, lastPerStep *lastSamplePerStep) (string, []any, error) {
sb := sqlbuilder.NewSelectBuilder()
if lastPerStep != nil {
// Aliases must not shadow source columns: ClickHouse resolves aliases
// in WHERE too, and "max(unix_milli) AS unix_milli" would put an
// aggregate into the WHERE clause (error 184).
sb.Select("fingerprint", "max(unix_milli) AS ts", "argMax(value, unix_milli) AS val", "argMax(flags, unix_milli) AS fl")
} else {
sb.Select("fingerprint", "unix_milli", "value", "flags")
}
sb.From(fmt.Sprintf("%s.%s", databaseName, distributedSamplesV4))
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']")
if inlineFingerprints != nil {
sb.Where("fingerprint " + inlineFingerprintFilter(inlineFingerprints))
} else {
sub := sqlbuilder.NewSelectBuilder()
sub.Select("fingerprint")
adjustedStart, table := timeSeriesTableFor(start, end)
sub.From(fmt.Sprintf("%s.%s", databaseName, localTimeSeriesTable(table)))
if err := applySeriesConditions(sub, adjustedStart, end, matchers); err != nil {
return "", nil, err
}
sb.Where(sb.In("fingerprint", sub))
}
sb.Where(sb.GTE("unix_milli", start), sb.LTE("unix_milli", end))
if lastPerStep != nil {
sb.GroupBy("fingerprint")
if expr := lastPerStep.bucketExpr(); expr != "" {
sb.GroupBy(expr)
}
sb.OrderBy("fingerprint", "ts")
} else {
sb.OrderBy("fingerprint", "unix_milli")
}
query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
return query, args, nil
}
// applySeriesConditions adds the WHERE conditions of a series table scan for
// the given matchers and window. __name__ matchers translate to the
// metric_name column (all four matcher types — the v1 client silently
// returned nothing for regex metric names); every other matcher translates
// to a JSONExtractString condition on the labels column. An equality matcher
// against "" matches series without the label, mirroring PromQL, because
// JSONExtractString returns "" for missing keys. Regexes are anchored:
// PromQL matchers match the whole value, while ClickHouse match() searches
// for a partial match — without anchoring, =~"api" would also select
// "x-api-y".
func applySeriesConditions(sb *sqlbuilder.SelectBuilder, start, end int64, matchers []*labels.Matcher) error {
for _, m := range matchers {
if m.Name != metricNameLabel {
continue
}
switch m.Type {
case labels.MatchEqual:
sb.Where(sb.EQ("metric_name", m.Value))
case labels.MatchNotEqual:
sb.Where(sb.NE("metric_name", m.Value))
case labels.MatchRegexp:
sb.Where(fmt.Sprintf("match(metric_name, %s)", sb.Var(anchorRegex(m.Value))))
case labels.MatchNotRegexp:
sb.Where(fmt.Sprintf("NOT match(metric_name, %s)", sb.Var(anchorRegex(m.Value))))
default:
return errors.NewInvalidInputf(errors.CodeInvalidInput, "unsupported matcher type %q for __name__", m.Type)
}
}
sb.Where("temporality IN ['Cumulative', 'Unspecified']")
sb.Where(fmt.Sprintf("__normalized = %v", !constants.IsDotMetricsEnabled))
sb.Where(sb.GTE("unix_milli", start), sb.LT("unix_milli", end))
for _, m := range matchers {
if m.Name == metricNameLabel {
continue
}
switch m.Type {
case labels.MatchEqual:
sb.Where(fmt.Sprintf("JSONExtractString(labels, %s) = %s", sb.Var(m.Name), sb.Var(m.Value)))
case labels.MatchNotEqual:
sb.Where(fmt.Sprintf("JSONExtractString(labels, %s) != %s", sb.Var(m.Name), sb.Var(m.Value)))
case labels.MatchRegexp:
sb.Where(fmt.Sprintf("match(JSONExtractString(labels, %s), %s)", sb.Var(m.Name), sb.Var(anchorRegex(m.Value))))
case labels.MatchNotRegexp:
sb.Where(fmt.Sprintf("NOT match(JSONExtractString(labels, %s), %s)", sb.Var(m.Name), sb.Var(anchorRegex(m.Value))))
default:
return errors.NewInvalidInputf(errors.CodeInvalidInput, "unsupported matcher type %q", m.Type)
}
}
return nil
}
// anchorRegex turns a PromQL regex into its fully-anchored form (see
// applySeriesConditions).
func anchorRegex(v string) string {
return "^(?:" + v + ")$"
}
// inlineFingerprintFilter renders "IN (fp1, fp2, ...)" with literal uint64s.
func inlineFingerprintFilter(fingerprints []uint64) string {
var b strings.Builder
b.Grow(len(fingerprints)*21 + 8)
b.WriteString("IN (")
for i, fp := range fingerprints {
if i > 0 {
b.WriteString(", ")
}
b.WriteString(strconv.FormatUint(fp, 10))
}
b.WriteString(")")
return b.String()
}
// lastSamplePerStep reduces an instant-selector fetch to the last sample of
// each step bucket. Buckets are anchored at the selector's first evaluation
// timestamp so that every bucket boundary coincides with an evaluation
// timestamp: bucket 0 is (start, firstEval] (the initial lookback window)
// and bucket i is (firstEval+(i-1)·step, firstEval+i·step]. Keeping only the
// last sample per bucket is lossless: the engine resolves each evaluation
// timestamp t to the latest sample in (t-lookback, t], and a non-final
// sample of a bucket can never be that latest sample for any t on the
// evaluation grid. Real timestamps are preserved, so the engine's own
// lookback and staleness handling remain exact.
type lastSamplePerStep struct {
firstEvalMs int64
stepMs int64
}
func (t *lastSamplePerStep) bucketExpr() string {
if t.stepMs <= 0 {
// Instant query: a single evaluation at firstEval; one bucket.
return ""
}
return fmt.Sprintf(
"if(unix_milli <= %d, 0, intDiv(unix_milli - %d - 1, %d) + 1)",
t.firstEvalMs, t.firstEvalMs, t.stepMs,
)
}

View File

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package clickhouseprometheusv2
import (
"testing"
"time"
"github.com/prometheus/prometheus/model/labels"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func mustMatcher(t *testing.T, mt labels.MatchType, name, value string) *labels.Matcher {
t.Helper()
m, err := labels.NewMatcher(mt, name, value)
require.NoError(t, err)
return m
}
func TestTimeSeriesTableFor(t *testing.T) {
base := time.Date(2026, 7, 10, 3, 27, 0, 0, time.UTC).UnixMilli()
tests := []struct {
name string
span time.Duration
wantTable string
roundTo time.Duration
}{
{"under 6h uses hourly table", 2 * time.Hour, distributedTimeSeriesV4, time.Hour},
{"under 1d uses 6h table", 12 * time.Hour, distributedTimeSeriesV46hrs, 6 * time.Hour},
{"under 1w uses 1d table", 3 * 24 * time.Hour, distributedTimeSeriesV41day, 24 * time.Hour},
{"over 1w uses 1w table", 10 * 24 * time.Hour, distributedTimeSeriesV41week, 7 * 24 * time.Hour},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
start, table := timeSeriesTableFor(base, base+tt.span.Milliseconds())
assert.Equal(t, tt.wantTable, table)
assert.Zero(t, start%tt.roundTo.Milliseconds())
assert.LessOrEqual(t, start, base)
})
}
}
func TestBuildSeriesQuery(t *testing.T) {
start := int64(1_700_000_000_000)
end := start + time.Hour.Milliseconds()
// The series table window rounds down to the table's bucket boundary.
adjustedStart := start - (start % time.Hour.Milliseconds())
t.Run("equality name and label matchers", func(t *testing.T) {
query, args, err := buildSeriesQuery(start, end, []*labels.Matcher{
mustMatcher(t, labels.MatchEqual, "__name__", "http_requests_total"),
mustMatcher(t, labels.MatchEqual, "job", "api"),
})
require.NoError(t, err)
assert.Equal(t,
"SELECT fingerprint, any(labels) FROM signoz_metrics.distributed_time_series_v4 WHERE metric_name = ? AND temporality IN ['Cumulative', 'Unspecified'] AND __normalized = false AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, ?) = ? GROUP BY fingerprint",
query,
)
assert.Equal(t, []any{"http_requests_total", adjustedStart, end, "job", "api"}, args)
})
t.Run("regex matchers are anchored", func(t *testing.T) {
_, args, err := buildSeriesQuery(start, end, []*labels.Matcher{
mustMatcher(t, labels.MatchEqual, "__name__", "up"),
mustMatcher(t, labels.MatchRegexp, "instance", "prod.*"),
mustMatcher(t, labels.MatchNotRegexp, "env", "dev|test"),
})
require.NoError(t, err)
assert.Equal(t, []any{"up", adjustedStart, end, "instance", "^(?:prod.*)$", "env", "^(?:dev|test)$"}, args)
})
t.Run("regex name matcher uses metric_name column", func(t *testing.T) {
query, args, err := buildSeriesQuery(start, end, []*labels.Matcher{
mustMatcher(t, labels.MatchRegexp, "__name__", "node_cpu.*|node_memory.*"),
})
require.NoError(t, err)
assert.Contains(t, query, "match(metric_name, ?)")
assert.NotContains(t, query, "JSONExtractString")
assert.Equal(t, []any{"^(?:node_cpu.*|node_memory.*)$", adjustedStart, end}, args)
})
t.Run("no name matcher omits metric_name condition", func(t *testing.T) {
query, _, err := buildSeriesQuery(start, end, []*labels.Matcher{
mustMatcher(t, labels.MatchEqual, "job", "api"),
})
require.NoError(t, err)
assert.NotContains(t, query, "metric_name")
})
}
func TestBuildSamplesQuery(t *testing.T) {
start := int64(1_700_000_000_000)
end := start + time.Hour.Milliseconds()
adjustedStart := start - (start % time.Hour.Milliseconds())
matchers := []*labels.Matcher{
mustMatcher(t, labels.MatchEqual, "__name__", "up"),
mustMatcher(t, labels.MatchEqual, "job", "api"),
}
t.Run("raw with inline fingerprints", func(t *testing.T) {
query, args, err := buildSamplesQuery(start, end, []string{"up"}, []uint64{7, 42}, matchers, nil)
require.NoError(t, err)
assert.Equal(t,
"SELECT fingerprint, unix_milli, value, flags FROM signoz_metrics.distributed_samples_v4 WHERE metric_name = ? AND temporality IN ['Cumulative', 'Unspecified'] AND fingerprint IN (7, 42) AND unix_milli >= ? AND unix_milli <= ? ORDER BY fingerprint, unix_milli",
query,
)
assert.Equal(t, []any{"up", start, end}, args)
})
t.Run("last-sample-per-step groups by step bucket anchored at first eval", func(t *testing.T) {
lastPerStep := &lastSamplePerStep{firstEvalMs: start + 299_999, stepMs: 60_000}
query, _, err := buildSamplesQuery(start, end, []string{"up"}, []uint64{7}, matchers, lastPerStep)
require.NoError(t, err)
assert.Contains(t, query, "argMax(value, unix_milli) AS val")
assert.Contains(t, query, "argMax(flags, unix_milli) AS fl")
assert.Contains(t, query, "GROUP BY fingerprint, if(unix_milli <= 1700000299999, 0, intDiv(unix_milli - 1700000299999 - 1, 60000) + 1)")
assert.Contains(t, query, "ORDER BY fingerprint, ts")
// Aliases must not shadow the source columns referenced in WHERE.
assert.NotContains(t, query, "AS unix_milli")
assert.NotContains(t, query, "AS value")
assert.NotContains(t, query, "AS flags")
})
t.Run("instant query keeps one bucket", func(t *testing.T) {
lastPerStep := &lastSamplePerStep{firstEvalMs: end, stepMs: 0}
query, _, err := buildSamplesQuery(start, end, []string{"up"}, []uint64{7}, matchers, lastPerStep)
require.NoError(t, err)
assert.Contains(t, query, "GROUP BY fingerprint ORDER BY fingerprint, ts")
assert.NotContains(t, query, "intDiv")
})
t.Run("over-limit set becomes a shard-local semi-join", func(t *testing.T) {
query, args, err := buildSamplesQuery(start, end, []string{"up"}, nil, matchers, nil)
require.NoError(t, err)
assert.Contains(t, query, "fingerprint IN (SELECT fingerprint FROM signoz_metrics.time_series_v4 WHERE ")
assert.NotContains(t, query, "GLOBAL IN")
// Args follow placeholder order: samples metric name, the semi-join's
// series predicates, then the samples window bounds.
assert.Equal(t, []any{"up", "up", adjustedStart, end, "job", "api", start, end}, args)
})
t.Run("multiple metric names from regex selector", func(t *testing.T) {
query, args, err := buildSamplesQuery(start, end, []string{"node_cpu", "node_memory"}, []uint64{7}, matchers, nil)
require.NoError(t, err)
assert.Contains(t, query, "metric_name IN (?, ?)")
assert.Equal(t, []any{"node_cpu", "node_memory", start, end}, args)
})
}

View File

@@ -0,0 +1,65 @@
package clickhouseprometheusv2
import "time"
const (
// metricNameLabel is the reserved PromQL label holding the metric name.
metricNameLabel string = "__name__"
databaseName string = "signoz_metrics"
distributedTimeSeriesV4 string = "distributed_time_series_v4"
distributedTimeSeriesV46hrs string = "distributed_time_series_v4_6hrs"
distributedTimeSeriesV41day string = "distributed_time_series_v4_1day"
distributedTimeSeriesV41week string = "distributed_time_series_v4_1week"
distributedSamplesV4 string = "distributed_samples_v4"
localTimeSeriesV4 string = "time_series_v4"
localTimeSeriesV46hrs string = "time_series_v4_6hrs"
localTimeSeriesV41day string = "time_series_v4_1day"
localTimeSeriesV41week string = "time_series_v4_1week"
)
// localTimeSeriesTable maps a distributed time series table to its shard-local
// table. Samples and time series shard on the same key
// (cityHash64(env, temporality, metric_name, fingerprint)), so a query whose
// top-level FROM is the distributed samples table can join or semi-join the
// local time series table inside each shard: the shard rewrite runs the
// subquery against the shard's own series rows, which are exactly the series
// of the shard's samples. No broadcast, no initiator-side join.
func localTimeSeriesTable(distributed string) string {
switch distributed {
case distributedTimeSeriesV46hrs:
return localTimeSeriesV46hrs
case distributedTimeSeriesV41day:
return localTimeSeriesV41day
case distributedTimeSeriesV41week:
return localTimeSeriesV41week
default:
return localTimeSeriesV4
}
}
var (
oneHourInMilliseconds = time.Hour.Milliseconds()
sixHoursInMilliseconds = time.Hour.Milliseconds() * 6
oneDayInMilliseconds = time.Hour.Milliseconds() * 24
oneWeekInMilliseconds = time.Hour.Milliseconds() * 24 * 7
)
// timeSeriesTableFor returns the adjusted start and the time series table for
// the window. Time series tables hold one row per (fingerprint, bucket), with
// bucket granularities of 1h, 6h, 1d and 1w; the start is rounded down to the
// bucket boundary so a window beginning mid-bucket still matches the bucket's
// row.
func timeSeriesTableFor(start, end int64) (int64, string) {
switch {
case end-start < sixHoursInMilliseconds:
return start - (start % oneHourInMilliseconds), distributedTimeSeriesV4
case end-start < oneDayInMilliseconds:
return start - (start % sixHoursInMilliseconds), distributedTimeSeriesV46hrs
case end-start < oneWeekInMilliseconds:
return start - (start % oneDayInMilliseconds), distributedTimeSeriesV41day
default:
return start - (start % oneWeekInMilliseconds), distributedTimeSeriesV41week
}
}

View File

@@ -0,0 +1,485 @@
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 {
if vs.Timestamp != nil || vs.StartOrEnd != 0 || vs.Anchored || vs.Smoothed {
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
}
if vs.Timestamp != nil || vs.StartOrEnd != 0 || vs.Anchored || vs.Smoothed {
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 &&
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
}

View File

@@ -0,0 +1,150 @@
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, 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
case *parser.SubqueryExpr:
hasSubquery = true
case *parser.VectorSelector:
if n.Timestamp != nil || n.StartOrEnd != 0 {
hasAt = 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 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
}

View File

@@ -0,0 +1,463 @@
package clickhouseprometheusv2
import (
"context"
"encoding/json"
"math"
"sort"
"sync/atomic"
"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
}
// 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 therefore
// transpile only when their window covers the step; otherwise the engine
// path serves them exactly.
for _, unit := range plan.units {
lastStyle := unit.core.kind == unitInstant || (unit.core.kind == unitOverTime && unit.core.overFn == "last")
if !lastStyle {
continue
}
windowMs := unit.core.rangeMs
if unit.core.kind == unitInstant {
windowMs = e.client.lookbackMs
}
if windowMs < unit.grid.stepMs {
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. The
// units share one grid-cell budget: transpiled results never pass
// through the engine's sample limiter, so without this a large
// series-count x grid-width query would buffer unbounded arrays — the
// OOM this provider exists to prevent.
results := make([][]transpiledSeries, len(plan.units))
var gridCells atomic.Int64
eg, egCtx := errgroup.WithContext(ctx)
for i, unit := range plan.units {
eg.Go(func() error {
res, err := e.executeUnit(egCtx, &unit.core, unit.grid, &gridCells)
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, gridCells *atomic.Int64) ([]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
}
// The result buffers one grid array per series; series count times grid
// width is the transpiled equivalent of fetched samples, counted before
// the arrays exist rather than after the memory is spent.
gridLen := int64(1)
if stepMs > 0 {
gridLen = (endMs-startMs)/stepMs + 1
}
if maxSamples := e.client.cfg.MaxFetchedSamples; maxSamples > 0 && gridCells.Add(int64(len(lookup.fingerprints))*gridLen) > maxSamples {
return nil, errors.NewInvalidInputf(
errors.CodeInvalidInput,
"promql query would buffer more than %d output points; narrow the selector or time range, or raise prometheus::clickhousev2::max_fetched_samples",
maxSamples,
)
}
query, args, err := buildUnitSQL(unit, lookup.metricNames, transpiledFingerprintFilter(lookup), 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, and a
// post-strip collision is the engine's duplicate-labelset error — v1
// would have errored, so silently inventing a merged series would be a
// divergence.
stripName := !unit.hasAgg && !unit.keepsName()
seen := make(map[uint64]string)
var out []transpiledSeries
var gkey string
var gridValues []*float64
for rows.Next() {
if err := rows.Scan(&gkey, &gridValues); err != nil {
return nil, err
}
lset, err := labelsFromGroupKey(gkey)
if err != nil {
return nil, err
}
if stripName {
name := lset.Get(metricNameLabel)
lset = labels.NewBuilder(lset).Del(metricNameLabel).Labels()
if prev, ok := seen[lset.Hash()]; ok && prev != name {
return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "vector cannot contain metrics with the same labelset")
}
seen[lset.Hash()] = name
}
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
}
sort.Slice(out, func(i, j int) bool { return labels.Compare(out[i].lset, out[j].lset) < 0 })
return out, nil
}
// transpiledFingerprintFilter returns the matched fingerprints as a sorted
// slice when they fit the inline limit — literals engage the samples primary
// key, and sorting keeps the statement deterministic for logging and tests.
// Over the limit it returns nil: the unit query's INNER JOIN against the
// local series subquery restricts to exactly the matched fingerprints
// already, and a semi-join on the same predicates would only rescan the
// series table.
func transpiledFingerprintFilter(lookup *seriesLookup) []uint64 {
if len(lookup.fingerprints) > inlineFingerprintsLimit {
return nil
}
fingerprints := make([]uint64, 0, len(lookup.fingerprints))
for fp := range lookup.fingerprints {
fingerprints = append(fingerprints, fp)
}
sort.Slice(fingerprints, func(i, j int) bool { return fingerprints[i] < fingerprints[j] })
return fingerprints
}
// 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})
}
sort.Slice(out, func(i, j int) bool { return labels.Compare(out[i].Metric, out[j].Metric) < 0 })
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...)
}

View File

@@ -0,0 +1,303 @@
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, gkey) grid aggregation next to the data —
// complete by fingerprint co-locality (see localTimeSeriesTable) — and the
// initiator only merges per-series grid states and applies the spatial
// -ForEach step. Same layout as the telemetrymetrics statement builder. The
// windowed *_over_time form is the exception: its ARRAY JOIN level
// aggregates on the shards the same way, but the group-key join happens at
// the initiator over the already-reduced per-(series, index) rows — pushing
// it down would not move any data off the initiator (the reduced rows arrive
// there either way), so the combined ARRAY JOIN + JOIN form buys nothing.
//
// inlineFingerprints carries the matched set when it fits the inline limit;
// nil means over the limit, where the group-key join restricts on its own
// (the windowed form, whose fan-out query has no join, falls back to a
// shard-local semi-join so it does not expand every series of the metric).
//
// 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: (gkey String, grid Array(Nullable(Float64))). gkey is
// toJSONString of the sorted projected [key, value] pairs; 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, inlineFingerprints []uint64, 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)
// seriesSub computes fingerprint -> group key. 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()
sub.Select("fingerprint", groupKeyExpr(unit)+" AS gkey")
sub.From(fmt.Sprintf("%s.%s", databaseName, table))
if err := applySeriesConditions(sub, adjustedTsStart, dataEnd, unit.matchers); err != nil {
return "", nil, err
}
sub.GroupBy("fingerprint", "gkey")
q, args := sub.BuildWithFlavor(sqlbuilder.ClickHouse)
return q, args, nil
}
// samplesConditions adds the samples-side WHERE. The samples table is
// aliased "points" in every kind: under the group-key join both sides
// carry a fingerprint column, so the filter must qualify it. A nil
// inline set adds no fingerprint condition — the join restricts.
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']")
if inlineFingerprints != nil {
sb.Where("points.fingerprint " + inlineFingerprintFilter(inlineFingerprints))
}
// 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", selEnd))
if excludeStale {
// PromQL excludes stale markers from range vectors. Instant
// selectors need the stale rows for shadowing instead.
sb.Where("bitAnd(flags, 1) = 0")
}
}
// joinedInner builds the shard-side SELECT for the single-pass kinds:
// grid expression per (fingerprint, gkey), 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()
sb.Select("series.gkey AS gkey", 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", "series.gkey")
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, inlineFingerprints == nil, adjustedTsStart, dataEnd, 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()])
}
query := fmt.Sprintf("SELECT gkey, %s AS grid FROM (%s) GROUP BY gkey %s", spatial, inner, gridFunctionsSetting)
return query, innerArgs, nil
}
// windowedInner builds the avg/min/max/sum/count _over_time form: each
// sample fans out to every grid index k whose window (t_k - range, t_k]
// contains it (ARRAY JOIN), aggregates per (fingerprint, k) — shard-side
// partials over the distributed table — then assembles the positional grid
// and joins the group key at the initiator over the reduced rows. The
// group-key subquery reads the distributed series table here because it does
// not ride inside a shard-rewritten query.
//
// This is the one form whose samples query has no series join, so an
// over-the-limit fingerprint set (semiJoin) must fall back to the
// shard-local semi-join: without it the fan-out would expand every series of
// the metric and discard the unmatched ones only at the group-key join.
func windowedInner(unit *coreUnit, samplesConditions func(*sqlbuilder.SelectBuilder, bool), seriesSub func(string) (string, []any, error), semiJoin bool, adjustedTsStart, dataEnd int64, tsTable string, selStart, selEnd, stepMs, windowMs int64) (string, []any, error) {
aggExpr := map[string]string{
"avg": "avg(value)",
"min": "min(value)",
"max": "max(value)",
"sum": "sum(value)",
"count": "toFloat64(count(value))",
}[unit.overFn]
effStepMs := stepMs
if effStepMs == 0 {
effStepMs = 1000
}
lastIdx := (selEnd - selStart) / effStepMs
perWindow := sqlbuilder.NewSelectBuilder()
perWindow.Select("fingerprint", "k", aggExpr+" AS v")
perWindow.From(fmt.Sprintf(
"%s.%s AS points ARRAY JOIN range(toUInt64(greatest(0, intDiv(unix_milli - %d + %d - 1, %d))), toUInt64(least(%d, intDiv(unix_milli + %d - 1 - %d, %d)) + 1)) AS k",
databaseName, distributedSamplesV4,
selStart, effStepMs, effStepMs,
lastIdx, windowMs, selStart, effStepMs,
))
samplesConditions(perWindow, true)
if semiJoin {
sub := sqlbuilder.NewSelectBuilder()
sub.Select("fingerprint")
sub.From(fmt.Sprintf("%s.%s", databaseName, localTimeSeriesTable(tsTable)))
if err := applySeriesConditions(sub, adjustedTsStart, dataEnd, unit.matchers); err != nil {
return "", nil, err
}
perWindow.Where(perWindow.In("points.fingerprint", sub))
}
perWindow.GroupBy("fingerprint", "k")
perWindowSQL, perWindowArgs := perWindow.BuildWithFlavor(sqlbuilder.ClickHouse)
grids := fmt.Sprintf(
"SELECT fingerprint, arrayMap(i -> if(indexOf(ks, i) = 0, NULL, vs[indexOf(ks, i)]), range(toUInt64(%d))) AS grid FROM (SELECT fingerprint, groupArray(k) AS ks, groupArray(v) AS vs FROM (%s) GROUP BY fingerprint)",
lastIdx+1, perWindowSQL,
)
seriesSQL, seriesArgs, err := seriesSub(tsTable)
if err != nil {
return "", nil, err
}
inner := fmt.Sprintf(
"SELECT series.gkey AS gkey, points.grid AS grid FROM (%s) AS points INNER JOIN (%s) AS series ON points.fingerprint = series.fingerprint",
grids, seriesSQL,
)
return inner, append(perWindowArgs, seriesArgs...), nil
}
// groupKeyExpr renders the canonical group key for a unit: the sorted
// [key, value] pairs of the projected labels, JSON-encoded.
// - by (a, b): keep only the listed labels (absent labels stay absent,
// matching PromQL's by() over missing labels);
// - 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 {
if len(unit.grouping) == 0 {
return "'[]'"
}
return fmt.Sprintf("toJSONString(arrayFilter(p -> p.2 != '' AND p.1 IN (%s), %s))", quotedList(unit.grouping), pairs)
}
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, ", ")
}

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@@ -0,0 +1,517 @@
package clickhouseprometheusv2
import (
"context"
"sync/atomic"
"testing"
"time"
cmock "github.com/SigNoz/clickhouse-go-mock"
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql/parser"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
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},
}
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"}, []uint64{7, 42}, 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, gkey) 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")
assert.Contains(t, sql, "GROUP BY points.fingerprint, series.gkey")
assert.Contains(t, sql, "points.fingerprint IN (7, 42)")
assert.Contains(t, sql, `toJSONString(arrayFilter(p -> p.2 != '' AND p.1 IN ('pod'),`)
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.
assert.Equal(t, []any{"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, []uint64{7}, 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"}, nil, 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 TestBuildUnitSQLOverLimitWindowedSemiJoin(t *testing.T) {
// The windowed *_over_time fan-out has no series join, so the over-limit
// regime falls back to the shard-local semi-join instead of expanding
// every series of the metric.
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"}, nil, 1_699_999_400_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, "points.fingerprint IN (SELECT fingerprint FROM signoz_metrics.time_series_v4 WHERE ")
assert.Contains(t, sql, "ARRAY JOIN range(")
}
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_LastStyleWindowBelowStepFallsBack(t *testing.T) {
c, _ := newTestClient(t, prometheus.ClickhouseV2Config{})
e := &executor{client: c, parser: prometheus.NewParser()}
start := time.UnixMilli(1_700_000_000_000)
end := time.UnixMilli(1_700_003_600_000)
_, ok, err := e.TryExecuteRange(context.Background(), `sum by (pod) (up)`, start, end, time.Hour)
require.NoError(t, err)
assert.False(t, ok, "instant selection at step > lookback must not transpile")
_, ok, err = e.TryExecuteRange(context.Background(), `last_over_time(up[10m])`, start, end, time.Hour)
require.NoError(t, err)
assert.False(t, ok, "last_over_time at range < step must not transpile")
}
// Transpiled results never pass the engine's sample limiter, so the grid
// cells (series x grid width) must be budgeted before the arrays exist —
// otherwise a wide query rebuilds the OOM this provider exists to prevent.
func TestExecuteUnit_GridCellBudget(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{MaxFetchedSamples: 100})
e := &executor{client: c, parser: prometheus.NewParser()}
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{
{uint64(1), `{"__name__":"up","instance":"a"}`},
{uint64(2), `{"__name__":"up","instance":"b"}`},
}))
plan, ok := classify(parse(t, `sum(rate(up[5m]))`), gridContext{startMs: 1_700_000_000_000, endMs: 1_700_003_600_000, stepMs: 60_000})
require.True(t, ok)
var cells atomic.Int64
// 2 series x 61 grid points = 122 cells > 100.
_, err := e.executeUnit(context.Background(), &plan.units[0].core, plan.units[0].grid, &cells)
require.Error(t, err)
assert.True(t, errors.Ast(err, errors.TypeInvalidInput), "budget refusal must be typed invalid input, got %v", err)
}
// Two metrics collapsing onto one labelset after the name drop is the
// engine's duplicate-labelset error; silently merging them would invent a
// series no engine would produce.
func TestExecuteUnit_NameCollisionErrors(t *testing.T) {
c, store := newTestClient(t, prometheus.ClickhouseV2Config{})
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)
var cells atomic.Int64
_, err := e.executeUnit(context.Background(), &plan.units[0].core, plan.units[0].grid, &cells)
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 }

View File

@@ -13,6 +13,11 @@ type ActiveQueryTrackerConfig struct {
MaxConcurrent int `mapstructure:"max_concurrent"`
}
type ClickhouseV2Config struct {
MaxFetchedSeries int `mapstructure:"max_fetched_series"`
MaxFetchedSamples int64 `mapstructure:"max_fetched_samples"`
}
type Config struct {
ActiveQueryTrackerConfig ActiveQueryTrackerConfig `mapstructure:"active_query_tracker"`
@@ -24,6 +29,13 @@ type Config struct {
// Timeout is the maximum time a query is allowed to run before being aborted.
Timeout time.Duration `mapstructure:"timeout"`
// ProviderName selects the storage provider: "clickhouse" (default) or
// "clickhousev2".
ProviderName string `mapstructure:"provider"`
// ClickhouseV2 configures the clickhousev2 provider.
ClickhouseV2 ClickhouseV2Config `mapstructure:"clickhousev2"`
}
func NewConfigFactory() factory.ConfigFactory {
@@ -37,7 +49,12 @@ func newConfig() factory.Config {
Path: "",
MaxConcurrent: 20,
},
Timeout: 2 * time.Minute,
Timeout: 2 * time.Minute,
ProviderName: "clickhouse",
ClickhouseV2: ClickhouseV2Config{
MaxFetchedSeries: 500_000,
MaxFetchedSamples: 50_000_000,
},
}
}
@@ -45,9 +62,18 @@ func (c Config) Validate() error {
if c.Timeout <= 0 {
return errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "prometheus::timeout must be greater than 0")
}
if c.ProviderName != "" && c.ProviderName != "clickhouse" && c.ProviderName != "clickhousev2" {
return errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "prometheus::provider must be one of [clickhouse, clickhousev2], got %q", c.ProviderName)
}
if c.ClickhouseV2.MaxFetchedSeries < 0 || c.ClickhouseV2.MaxFetchedSamples < 0 {
return errors.Newf(errors.TypeInvalidInput, errors.CodeInvalidInput, "prometheus::clickhousev2 limits must not be negative")
}
return nil
}
func (c Config) Provider() string {
return "clickhouse"
if c.ProviderName == "" {
return "clickhouse"
}
return c.ProviderName
}

View File

@@ -35,3 +35,9 @@ type StatementRecorder interface {
type StatementCapturer interface {
CapturingStorage() (storage.Queryable, StatementRecorder)
}
// ProviderClickhouseV2 is the clickhousev2 provider name: the factory
// registration, the prometheus::provider config value and the
// X-SigNoz-PromQL-Provider request header all use it, so they cannot drift
// apart.
const ProviderClickhouseV2 = "clickhousev2"

49
pkg/prometheus/traits.go Normal file
View File

@@ -0,0 +1,49 @@
package prometheus
import (
"context"
"github.com/prometheus/prometheus/promql/parser"
)
type queryTraitsKey struct{}
// QueryTraits carries per-query facts a storage implementation cannot derive
// from SelectHints alone. Call sites that parse the PromQL expression attach
// traits to the context before handing it to the engine; storages treat a
// missing traits value as "unknown" and stay conservative.
type QueryTraits struct {
// SubqueryFree is true when the query contains no subquery expression.
// Subquery selectors are evaluated at the subquery's own step, but
// SelectHints.Step always carries the top-level step, so step-aligned
// storage optimizations (e.g. keeping only the last sample per step
// bucket) are safe only when this is true.
SubqueryFree bool
}
// DetectQueryTraits derives QueryTraits from a parsed PromQL expression.
func DetectQueryTraits(expr parser.Expr) QueryTraits {
subqueryFree := true
parser.Inspect(expr, func(node parser.Node, _ []parser.Node) error {
if _, ok := node.(*parser.SubqueryExpr); ok {
subqueryFree = false
}
return nil
})
return QueryTraits{SubqueryFree: subqueryFree}
}
// NewContextWithQueryTraits returns a context carrying the given traits.
func NewContextWithQueryTraits(ctx context.Context, traits QueryTraits) context.Context {
return context.WithValue(ctx, queryTraitsKey{}, traits)
}
// QueryTraitsFromContext returns the traits attached to ctx, if any.
//
// Context is used here, unlike for backend selection, because traits must
// cross the promql engine to reach storage.Querier.Select, and the engine's
// interfaces offer no other channel; the alternative is a Prometheus fork.
func QueryTraitsFromContext(ctx context.Context) (QueryTraits, bool) {
traits, ok := ctx.Value(queryTraitsKey{}).(QueryTraits)
return traits, ok
}

View File

@@ -50,6 +50,7 @@ func (handler *handler) QueryRange(rw http.ResponseWriter, req *http.Request) {
render.Error(rw, err)
return
}
queryRangeRequest.PromQLProvider = req.Header.Get("X-SigNoz-PromQL-Provider")
// Validate the query request
if err := queryRangeRequest.Validate(); err != nil {

View File

@@ -230,7 +230,7 @@ func (q *querier) buildPreviewProviders(
sub.CompositeQuery = qbtypes.CompositeQuery{Queries: []qbtypes.QueryEnvelope{query}}
}
built, _, bErr := q.buildQueries(&sub, deps, missingMetricQuerySet, event)
built, _, bErr := q.buildQueries(&sub, deps, missingMetricQuerySet, event, promqlOptions{})
if bErr != nil {
errs[name] = bErr
continue

View File

@@ -8,15 +8,19 @@ import (
"regexp"
"sort"
"strings"
"sync"
"text/template"
"time"
"github.com/ClickHouse/clickhouse-go/v2"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql"
"github.com/prometheus/prometheus/promql/parser"
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/SigNoz/signoz/pkg/querybuilder"
"github.com/SigNoz/signoz/pkg/types/ctxtypes"
"github.com/SigNoz/signoz/pkg/types/instrumentationtypes"
@@ -39,6 +43,13 @@ var quotedMetricOutsideBracesPattern = regexp.MustCompile(`"([^"]+)"\s*\{`)
// tryEnhancePromQLExecError attempts to convert a PromQL execution error into
// a properly typed error. Returns nil if the error is not a recognized execution error.
func tryEnhancePromQLExecError(execErr error) error {
// A storage may fail a query with an already-typed error (e.g. the
// clickhousev2 series/sample budgets); surface it as-is instead of
// flattening it into an internal error.
if typed := typedStorageError(execErr); typed != nil {
return typed
}
var eqc promql.ErrQueryCanceled
var eqt promql.ErrQueryTimeout
var es promql.ErrStorage
@@ -58,6 +69,30 @@ func tryEnhancePromQLExecError(execErr error) error {
}
}
// typedStorageError walks an engine execution error chain looking for a
// SigNoz-typed invalid-input error raised by the storage layer (the budget
// refusals). Every wrapper level is stepped through by hand: Ast is a bare
// type cast, not an unwrap — it misses a typed error behind the engine's
// "expanding series: %w" — and promql.ErrStorage has no Unwrap method at
// all, so a plain unwrap loop would stop at it.
func typedStorageError(execErr error) error {
for e := execErr; e != nil; {
if errors.Ast(e, errors.TypeInvalidInput) {
return e
}
if es, ok := e.(promql.ErrStorage); ok {
e = es.Err
continue
}
u, ok := e.(interface{ Unwrap() error })
if !ok {
return nil
}
e = u.Unwrap()
}
return nil
}
// enhancePromQLError adds helpful context to PromQL parse errors,
// particularly for UTF-8 syntax migration issues where metric and label
// names containing dots need to be quoted.
@@ -98,6 +133,24 @@ type promqlQuery struct {
tr qbv5.TimeRange
requestType qbv5.RequestType
vars map[string]qbv5.VariableItem
opts promqlOptions
}
// promqlOptions is how a PromQL query relates to the clickhousev2 provider
// (see querier.promqlOptions for where the fields come from and why they are
// flag-gated). Both providers are nil for a plain request, so a plain
// request costs nothing extra.
type promqlOptions struct {
// shadow, when set, runs the query on this provider after serving and
// logs any result difference; the response is never affected.
shadow *clickhouseprometheusv2.Provider
// shadowSlots is the querier-wide admission for shadow runs, shared by
// every query so the bound holds per process.
shadowSlots chan struct{}
// serve, when set, serves the response from this provider instead of the
// default path. Comparison callers fetch the default and the pinned
// result as two API calls and diff them.
serve *clickhouseprometheusv2.Provider
}
var _ qbv5.Query = (*promqlQuery)(nil)
@@ -110,6 +163,7 @@ func newPromqlQuery(
tr qbv5.TimeRange,
requestType qbv5.RequestType,
variables map[string]qbv5.VariableItem,
opts promqlOptions,
) *promqlQuery {
return &promqlQuery{
logger: logger,
@@ -119,10 +173,20 @@ func newPromqlQuery(
tr: tr,
requestType: requestType,
vars: variables,
opts: opts,
}
}
func (q *promqlQuery) Fingerprint() string {
// A pinned request must not share cache entries with default serving: a
// cached default result would satisfy the pin without running the pinned
// provider, and a pinned result would poison normal serving. No
// fingerprint means no caching at all — the pin exists to observe a
// provider, so a cache in front of it defeats the point.
if q.opts.serve != nil {
return ""
}
query, err := q.renderVars(q.query.Query, q.vars, q.tr.From, q.tr.To)
if err != nil {
q.logger.ErrorContext(context.TODO(), "failed render template variables", slog.String("query", q.query.Query))
@@ -248,7 +312,16 @@ func (q *promqlQuery) PreviewStatements(ctx context.Context) ([]prometheus.Captu
start := int64(querybuilder.ToNanoSecs(q.tr.From))
end := int64(querybuilder.ToNanoSecs(q.tr.To))
// Attach the same query traits as Execute so the captured statements
// match what the live path would run.
if expr, parseErr := q.parser.ParseExpr(rendered); parseErr == nil {
ctx = prometheus.NewContextWithQueryTraits(ctx, prometheus.DetectQueryTraits(expr))
}
capStorage, recorder := storer.CapturingStorage()
if capStorage == nil {
return nil, nil
}
qry, err := q.promEngine.Engine().NewRangeQuery(
ctx,
capStorage,
@@ -292,6 +365,58 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
return nil, err
}
// Attach query traits so the storage can prove step-aligned optimizations
// safe (see prometheus.QueryTraits). A parse failure surfaces below via
// the engine with the enhanced error message.
if expr, parseErr := q.parser.ParseExpr(query); parseErr == nil {
ctx = prometheus.NewContextWithQueryTraits(ctx, prometheus.DetectQueryTraits(expr))
}
// Accumulate ClickHouse-side scan stats across every storage query this
// 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) {
statsMu.Lock()
rowsScanned += p.Rows
bytesScanned += p.Bytes
statsMu.Unlock()
}))
began := time.Now()
// A pinned provider serves directly from it: comparison callers fetch
// the default result and the pinned result as two API calls and diff
// them.
if q.opts.serve != nil {
matrix, err := q.serveFromProvider(ctx, query, start, end)
if err != nil {
if enhanced := tryEnhancePromQLExecError(err); enhanced != nil {
return nil, enhanced
}
return nil, err
}
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(),
@@ -327,6 +452,34 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
return nil, errors.WrapInternalf(promErr, errors.CodeInternal, "error getting matrix from promql query %q", query)
}
if q.opts.shadow != nil {
// Shadows detach from the request, so without admission a dashboard
// burst would stack unbounded ClickHouse work for up to the shadow
// timeout — the concurrency pattern behind the original outages.
// Non-blocking: at the cap the comparison is skipped, not queued;
// a sampled shadow stream is exactly as useful for rollout evidence.
select {
case q.opts.shadowSlots <- struct{}{}:
// The engine pools the result's sample slices on Close; the
// shadow comparison needs a stable copy of what was served.
served := copyMatrix(matrix)
servedIn := time.Since(began)
go func() {
defer func() { <-q.opts.shadowSlots }()
q.runShadowCompare(context.WithoutCancel(ctx), query, start, end, served, servedIn)
}()
default:
q.logger.DebugContext(ctx, "promql shadow skipped: at concurrency cap", slog.String("query", query))
}
}
warnings, _ := res.Warnings.AsStrings(query, 10, 0)
return q.toResult(matrix, warnings, began, &statsMu, &rowsScanned, &bytesScanned), nil
}
// toResult converts an evaluated matrix into the v5 result shape, attaching
// the ClickHouse scan stats accumulated during evaluation.
func (q *promqlQuery) toResult(matrix promql.Matrix, warnings []string, began time.Time, statsMu *sync.Mutex, rowsScanned, bytesScanned *uint64) *qbv5.Result {
excludeLabel := func(labelName string) bool {
if labelName == "__name__" {
return false
@@ -359,7 +512,13 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
series = append(series, &s)
}
warnings, _ := res.Warnings.AsStrings(query, 10, 0)
statsMu.Lock()
stats := qbv5.ExecStats{
RowsScanned: *rowsScanned,
BytesScanned: *bytesScanned,
DurationMS: uint64(time.Since(began).Milliseconds()),
}
statsMu.Unlock()
return &qbv5.Result{
Type: q.requestType,
@@ -372,6 +531,6 @@ func (q *promqlQuery) Execute(ctx context.Context) (*qbv5.Result, error) {
},
},
Warnings: warnings,
// TODO: map promql stats?
}, nil
Stats: stats,
}
}

View File

@@ -7,7 +7,9 @@ import (
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
qbv5 "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
"github.com/prometheus/prometheus/promql"
"github.com/stretchr/testify/assert"
)
@@ -440,3 +442,35 @@ func TestQuotedMetricOutsideBracesPattern(t *testing.T) {
})
}
}
// wrappedErr stands in for the engine's fmt-based "expanding series: %w"
// wrapper: an ordinary error with an Unwrap chain that is not a SigNoz base
// error itself.
type wrappedErr struct{ inner error }
func (w wrappedErr) Error() string { return "expanding series: " + w.inner.Error() }
func (w wrappedErr) Unwrap() error { return w.inner }
// A typed budget refusal must survive the engine's wrapping and reach the
// API as invalid input; flattened to internal it becomes a 500 the user
// cannot act on — the exact failure this error type exists to prevent.
func TestTypedStorageError_SeesThroughEngineWrappers(t *testing.T) {
budget := errors.NewInvalidInputf(errors.CodeInvalidInput, "promql selector matched more than 500000 series")
assert.NotNil(t, typedStorageError(wrappedErr{inner: budget}), "typed error behind an Unwrap wrapper")
assert.NotNil(t, typedStorageError(promql.ErrStorage{Err: wrappedErr{inner: budget}}), "typed error behind ErrStorage then a wrapper")
assert.NotNil(t, typedStorageError(wrappedErr{inner: promql.ErrStorage{Err: budget}}), "typed error behind a wrapper then ErrStorage")
assert.Nil(t, typedStorageError(wrappedErr{inner: errors.NewInternalf(errors.CodeInternal, "boom")}), "internal errors stay internal")
}
// A pinned request must not share cache entries with default serving: a
// cached default result would satisfy the pin without running the pinned
// provider.
func TestFingerprint_PinnedProviderBypassesCache(t *testing.T) {
q := &promqlQuery{
logger: slog.Default(),
query: qbv5.PromQuery{Query: "up"},
opts: promqlOptions{serve: &clickhouseprometheusv2.Provider{}},
}
assert.Empty(t, q.Fingerprint())
}

View File

@@ -0,0 +1,195 @@
package querier
import (
"context"
"fmt"
"log/slog"
"math"
"sort"
"time"
"github.com/ClickHouse/clickhouse-go/v2"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql"
)
// shadowTimeout bounds a shadow evaluation; a shadow run must never outlive
// the request by much or pile up.
const shadowTimeout = 2 * time.Minute
// runShadowCompare executes the query on the clickhousev2 provider exactly
// 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 {
q.logger.ErrorContext(ctx, "promql shadow comparison panicked", slog.Any("panic", r), slog.String("query", query))
}
}()
ctx, cancel := context.WithTimeout(ctx, shadowTimeout)
defer cancel()
// The request context carries the served response's scan-stats progress
// callback; without replacing it the shadow's ClickHouse progress would
// race into the served stats. The response itself was already sent.
ctx = clickhouse.Context(ctx, clickhouse.WithProgress(func(*clickhouse.Progress) {}))
if expr, parseErr := q.parser.ParseExpr(query); parseErr == nil {
ctx = prometheus.NewContextWithQueryTraits(ctx, prometheus.DetectQueryTraits(expr))
}
start, end := time.Unix(0, startNs), time.Unix(0, endNs)
began := time.Now()
shadow, transpiled, err := executeOnProvider(ctx, q.opts.shadow, query, start, end, q.query.Step.Duration)
shadowIn := time.Since(began)
logAttrs := []any{
slog.String("query", query),
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),
}
if err != nil {
// A shadow failure would be a serving failure after rollout; surface
// it at the same level as a result mismatch.
q.logger.WarnContext(ctx, "promql shadow execution failed", append(logAttrs, slog.Any("error", err))...)
return
}
servedNorm := normalizeShadowMatrix(served)
shadowNorm := normalizeShadowMatrix(shadow)
if diff := diffShadowMatrices(servedNorm, shadowNorm); diff != "" {
q.logger.WarnContext(ctx, "promql shadow comparison mismatch", append(logAttrs,
slog.String("diff", diff),
slog.Int("served_series", len(servedNorm)),
slog.Int("shadow_series", len(shadowNorm)),
)...)
return
}
// Matches log the timings: served_in vs shadow_in across the fleet is
// the perf evidence for the cutover, gathered for free.
q.logger.DebugContext(ctx, "promql shadow comparison matched", logAttrs...)
}
// 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) {
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:
// 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, false, err
}
defer qry.Close()
res := qry.Exec(ctx)
if res.Err != nil {
return nil, false, res.Err
}
matrix, err = res.Matrix()
if err != nil {
return nil, false, err
}
// Close returns the result's sample slices to the engine pool.
return copyMatrix(matrix), false, nil
}
func copyMatrix(matrix promql.Matrix) promql.Matrix {
out := make(promql.Matrix, 0, len(matrix))
for _, s := range matrix {
floats := make([]promql.FPoint, len(s.Floats))
copy(floats, s.Floats)
out = append(out, promql.Series{Metric: s.Metric.Copy(), Floats: floats})
}
return out
}
// normalizeShadowMatrix strips the labels the two providers legitimately
// disagree on — v1 injects a synthetic fingerprint label and leaks
// empty-valued labels from the stored attribute JSON, both removed from API
// responses anyway — and sorts by label set.
func normalizeShadowMatrix(matrix promql.Matrix) promql.Matrix {
out := make(promql.Matrix, 0, len(matrix))
for _, s := range matrix {
builder := labels.NewBuilder(s.Metric)
builder.Del(prometheus.FingerprintAsPromLabelName)
s.Metric.Range(func(l labels.Label) {
if l.Value == "" {
builder.Del(l.Name)
}
})
out = append(out, promql.Series{Metric: builder.Labels(), Floats: s.Floats})
}
sort.Slice(out, func(i, j int) bool { return labels.Compare(out[i].Metric, out[j].Metric) < 0 })
return out
}
// diffShadowMatrices returns a description of the first difference, or "".
// Values compare with relative tolerance: spatial aggregations accumulate
// floats in storage order, which differs between the providers in the last
// ULP.
func diffShadowMatrices(served, shadow promql.Matrix) string {
const relTol = 1e-9
if len(served) != len(shadow) {
return fmt.Sprintf("series count: served=%d shadow=%d", len(served), len(shadow))
}
for i := range served {
if labels.Compare(served[i].Metric, shadow[i].Metric) != 0 {
return fmt.Sprintf("series %d labels: served=%s shadow=%s", i, served[i].Metric, shadow[i].Metric)
}
if len(served[i].Floats) != len(shadow[i].Floats) {
return fmt.Sprintf("series %s points: served=%d shadow=%d", served[i].Metric, len(served[i].Floats), len(shadow[i].Floats))
}
for j := range served[i].Floats {
a, b := served[i].Floats[j], shadow[i].Floats[j]
if a.T != b.T {
return fmt.Sprintf("series %s point %d ts: served=%d shadow=%d", served[i].Metric, j, a.T, b.T)
}
// NaN and infinities first: NaN != NaN and Inf-Inf arithmetic
// would otherwise make one-sided NaN and Inf-vs-finite compare
// as equal (NaN > x and Inf > Inf are both false).
if math.IsNaN(a.F) || math.IsNaN(b.F) {
if math.IsNaN(a.F) != math.IsNaN(b.F) {
return fmt.Sprintf("series %s @%d value: served=%v shadow=%v", served[i].Metric, a.T, a.F, b.F)
}
continue
}
if math.IsInf(a.F, 0) || math.IsInf(b.F, 0) {
if a.F != b.F {
return fmt.Sprintf("series %s @%d value: served=%v shadow=%v", served[i].Metric, a.T, a.F, b.F)
}
continue
}
diff := math.Abs(a.F - b.F)
scale := math.Max(math.Abs(a.F), math.Abs(b.F))
if diff > relTol*math.Max(scale, 1e-300) && diff > 1e-12 {
return fmt.Sprintf("series %s @%d value: served=%v shadow=%v", served[i].Metric, a.T, a.F, b.F)
}
}
}
return ""
}

View File

@@ -0,0 +1,66 @@
package querier
import (
"math"
"testing"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql"
"github.com/stretchr/testify/assert"
)
func TestNormalizeShadowMatrix(t *testing.T) {
matrix := promql.Matrix{
{
Metric: labels.FromStrings("__name__", "up", "fingerprint", "42", "empty", "", "job", "api"),
Floats: []promql.FPoint{{T: 1000, F: 1}},
},
{
Metric: labels.FromStrings("a", "1"),
Floats: []promql.FPoint{{T: 1000, F: 2}},
},
}
norm := normalizeShadowMatrix(matrix)
// sorted by labels; fingerprint and empty-valued labels stripped
assert.Equal(t, labels.FromStrings("__name__", "up", "job", "api"), norm[0].Metric)
assert.Equal(t, labels.FromStrings("a", "1"), norm[1].Metric)
}
func TestDiffShadowMatrices(t *testing.T) {
series := func(v float64) promql.Matrix {
return promql.Matrix{{Metric: labels.FromStrings("a", "1"), Floats: []promql.FPoint{{T: 1000, F: v}}}}
}
assert.Empty(t, diffShadowMatrices(series(1.5), series(1.5)))
// last-ULP differences from storage-order float accumulation are expected
assert.Empty(t, diffShadowMatrices(series(0.08888888888888889), series(0.08888888888888888)))
assert.Empty(t, diffShadowMatrices(series(math.NaN()), series(math.NaN())))
assert.Contains(t, diffShadowMatrices(series(1.5), series(1.6)), "value")
assert.Contains(t, diffShadowMatrices(series(1.5), promql.Matrix{}), "series count")
assert.Contains(t, diffShadowMatrices(
series(1.5),
promql.Matrix{{Metric: labels.FromStrings("a", "2"), Floats: []promql.FPoint{{T: 1000, F: 1.5}}}},
), "labels")
assert.Contains(t, diffShadowMatrices(
series(1.5),
promql.Matrix{{Metric: labels.FromStrings("a", "1"), Floats: []promql.FPoint{{T: 2000, F: 1.5}}}},
), "ts")
}
// One-sided NaN makes every float comparison false, and Inf-Inf arithmetic
// yields Inf > Inf == false; without explicit handling both divergences log
// as matched — a shadow comparator that cannot see them would green-light a
// broken rollout.
func TestDiffShadowMatrices_SpecialFloats(t *testing.T) {
point := func(v float64) promql.Matrix {
return promql.Matrix{{Metric: labels.FromStrings("a", "1"), Floats: []promql.FPoint{{T: 1000, F: v}}}}
}
assert.NotEmpty(t, diffShadowMatrices(point(math.NaN()), point(1.5)), "one-sided NaN must diff")
assert.NotEmpty(t, diffShadowMatrices(point(1.5), point(math.NaN())), "one-sided NaN must diff either way")
assert.NotEmpty(t, diffShadowMatrices(point(math.Inf(1)), point(1.5)), "Inf vs finite must diff")
assert.NotEmpty(t, diffShadowMatrices(point(math.Inf(1)), point(math.Inf(-1))), "opposite infinities must diff")
assert.Empty(t, diffShadowMatrices(point(math.Inf(1)), point(math.Inf(1))), "equal infinities match")
assert.Empty(t, diffShadowMatrices(point(math.NaN()), point(math.NaN())), "both NaN match")
}

View File

@@ -19,10 +19,12 @@ import (
"github.com/SigNoz/signoz/pkg/factory"
"github.com/SigNoz/signoz/pkg/flagger"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/SigNoz/signoz/pkg/query-service/utils"
"github.com/SigNoz/signoz/pkg/querybuilder"
"github.com/SigNoz/signoz/pkg/telemetrystore"
"github.com/SigNoz/signoz/pkg/types/ctxtypes"
"github.com/SigNoz/signoz/pkg/types/featuretypes"
"github.com/SigNoz/signoz/pkg/types/instrumentationtypes"
"github.com/SigNoz/signoz/pkg/types/metrictypes"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
@@ -36,11 +38,19 @@ var (
)
type querier struct {
logger *slog.Logger
fl flagger.Flagger
telemetryStore telemetrystore.TelemetryStore
metadataStore telemetrytypes.MetadataStore
promEngine prometheus.Prometheus
logger *slog.Logger
fl flagger.Flagger
telemetryStore telemetrystore.TelemetryStore
metadataStore telemetrytypes.MetadataStore
promEngine prometheus.Prometheus
// promV2 is the clickhousev2 prometheus provider, wired only when the
// serving provider is the default one (nil otherwise). It reads the same
// ClickHouse data through a different implementation; PromQL queries
// shadow-compare against it behind the use_prometheus_clickhouse_v2 flag
// and can be pinned to it for a response (see promqlOptions). It never
// serves by default — that cutover happens only after the shadow logs
// stay clean.
promV2 *clickhouseprometheusv2.Provider
traceStmtBuilder qbtypes.StatementBuilder[qbtypes.TraceAggregation]
logStmtBuilder qbtypes.StatementBuilder[qbtypes.LogAggregation]
auditStmtBuilder qbtypes.StatementBuilder[qbtypes.LogAggregation]
@@ -51,8 +61,16 @@ type querier struct {
liveDataRefresh time.Duration
builderConfig builderConfig
maxConcurrentQueries int
// shadowSlots bounds concurrent shadow comparisons per process; shadows
// detach from their requests, so nothing else limits how many pile up.
shadowSlots chan struct{}
}
// maxConcurrentShadows is deliberately small: a shadow is a full extra
// ClickHouse evaluation, and a sampled stream of comparisons is exactly as
// useful for rollout evidence as an exhaustive one under load.
const maxConcurrentShadows = 8
var _ Querier = (*querier)(nil)
func New(
@@ -60,6 +78,7 @@ func New(
telemetryStore telemetrystore.TelemetryStore,
metadataStore telemetrytypes.MetadataStore,
promEngine prometheus.Prometheus,
promV2 *clickhouseprometheusv2.Provider,
traceStmtBuilder qbtypes.StatementBuilder[qbtypes.TraceAggregation],
logStmtBuilder qbtypes.StatementBuilder[qbtypes.LogAggregation],
auditStmtBuilder qbtypes.StatementBuilder[qbtypes.LogAggregation],
@@ -81,6 +100,7 @@ func New(
telemetryStore: telemetryStore,
metadataStore: metadataStore,
promEngine: promEngine,
promV2: promV2,
traceStmtBuilder: traceStmtBuilder,
logStmtBuilder: logStmtBuilder,
auditStmtBuilder: auditStmtBuilder,
@@ -93,6 +113,7 @@ func New(
logTraceIDWindowPaddingMS: uint64(logTraceIDWindowPadding.Milliseconds()),
},
maxConcurrentQueries: maxConcurrentQueries,
shadowSlots: make(chan struct{}, maxConcurrentShadows),
}
}
@@ -132,7 +153,11 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
missingMetricQuerySet[name] = true
}
queries, steps, err := q.buildQueries(req, dependencyQueries, missingMetricQuerySet, event)
promqlOpts, err := q.promqlOptions(ctx, orgID, req)
if err != nil {
return nil, err
}
queries, steps, err := q.buildQueries(req, dependencyQueries, missingMetricQuerySet, event, promqlOpts)
if err != nil {
return nil, err
}
@@ -175,11 +200,40 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
return qbResp, qbErr
}
// promqlOptions derives the PromQL execution options for a request. With the
// org's use_prometheus_clickhouse_v2 flag on, queries are shadow-compared
// against the clickhousev2 provider (serving unaffected, diffs logged; see
// promql_shadow.go). The X-SigNoz-PromQL-Provider header may instead pin the
// response to that provider — integration tests and support fetch both
// results for comparison — so it is deliberately flag-gated too: without the
// gate the header would be an unaudited switch onto a provider still under
// validation.
func (q *querier) promqlOptions(ctx context.Context, orgID valuer.UUID, req *qbtypes.QueryRangeRequest) (promqlOptions, error) {
enabled := q.fl.BooleanOrEmpty(ctx, flagger.FeatureUsePrometheusClickhouseV2, featuretypes.NewFlaggerEvaluationContext(orgID))
if req.PromQLProvider == "" {
if enabled && q.promV2 != nil {
return promqlOptions{shadow: q.promV2, shadowSlots: q.shadowSlots}, nil
}
return promqlOptions{}, nil
}
if req.PromQLProvider != prometheus.ProviderClickhouseV2 {
return promqlOptions{}, errors.NewInvalidInputf(errors.CodeInvalidInput, "unknown promql provider %q", req.PromQLProvider)
}
if !enabled {
return promqlOptions{}, errors.NewInvalidInputf(errors.CodeInvalidInput, "promql provider %q requires the use_prometheus_clickhouse_v2 flag", req.PromQLProvider)
}
if q.promV2 == nil {
return promqlOptions{}, errors.NewInvalidInputf(errors.CodeInvalidInput, "promql provider %q is not available", req.PromQLProvider)
}
return promqlOptions{serve: q.promV2}, nil
}
func (q *querier) buildQueries(
req *qbtypes.QueryRangeRequest,
dependencyQueries map[string]bool,
missingMetricQuerySet map[string]bool,
event *qbtypes.QBEvent,
promqlOpts promqlOptions,
) (map[string]qbtypes.Query, map[string]qbtypes.Step, error) {
tmplVars := req.Variables
@@ -204,7 +258,7 @@ func (q *querier) buildQueries(
if !ok {
return nil, nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "invalid promql query spec %T", query.Spec)
}
promqlQuery := newPromqlQuery(q.logger, q.promEngine, promQuery, qbtypes.TimeRange{From: req.Start, To: req.End}, req.RequestType, tmplVars)
promqlQuery := newPromqlQuery(q.logger, q.promEngine, promQuery, qbtypes.TimeRange{From: req.Start, To: req.End}, req.RequestType, tmplVars, promqlOpts)
queries[promQuery.Name] = promqlQuery
steps[promQuery.Name] = promQuery.Step
case qbtypes.QueryTypeClickHouseSQL:
@@ -846,7 +900,7 @@ func (q *querier) createRangedQuery(originalQuery qbtypes.Query, timeRange qbtyp
switch qt := originalQuery.(type) {
case *promqlQuery:
queryCopy := qt.query.Copy()
return newPromqlQuery(q.logger, q.promEngine, queryCopy, timeRange, qt.requestType, qt.vars)
return newPromqlQuery(q.logger, qt.promEngine, queryCopy, timeRange, qt.requestType, qt.vars, qt.opts)
case *chSQLQuery:
queryCopy := qt.query.Copy()

View File

@@ -48,6 +48,7 @@ func TestQueryRange_MetricTypeMissing(t *testing.T) {
nil, // telemetryStore
metadataStore,
nil, // prometheus
nil, // promV2
nil, // traceStmtBuilder
nil, // logStmtBuilder
nil, // auditStmtBuilder
@@ -120,6 +121,7 @@ func TestQueryRange_MetricTypeFromStore(t *testing.T) {
telemetryStore,
metadataStore,
nil, // prometheus
nil, // promV2
nil, // traceStmtBuilder
nil, // logStmtBuilder
nil, // auditStmtBuilder

View File

@@ -7,6 +7,7 @@ import (
"github.com/SigNoz/signoz/pkg/factory"
"github.com/SigNoz/signoz/pkg/flagger"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/SigNoz/signoz/pkg/querier"
"github.com/SigNoz/signoz/pkg/querybuilder"
"github.com/SigNoz/signoz/pkg/telemetryaudit"
@@ -22,6 +23,7 @@ import (
func NewFactory(
telemetryStore telemetrystore.TelemetryStore,
prometheus prometheus.Prometheus,
promV2 *clickhouseprometheusv2.Provider,
cache cache.Cache,
flagger flagger.Flagger,
) factory.ProviderFactory[querier.Querier, querier.Config] {
@@ -32,7 +34,7 @@ func NewFactory(
settings factory.ProviderSettings,
cfg querier.Config,
) (querier.Querier, error) {
return newProvider(ctx, settings, cfg, telemetryStore, prometheus, cache, flagger)
return newProvider(ctx, settings, cfg, telemetryStore, prometheus, promV2, cache, flagger)
},
)
}
@@ -43,6 +45,7 @@ func newProvider(
cfg querier.Config,
telemetryStore telemetrystore.TelemetryStore,
prometheus prometheus.Prometheus,
promV2 *clickhouseprometheusv2.Provider,
cache cache.Cache,
flagger flagger.Flagger,
) (querier.Querier, error) {
@@ -184,6 +187,7 @@ func newProvider(
telemetryStore,
telemetryMetadataStore,
prometheus,
promV2,
traceStmtBuilder,
logStmtBuilder,
auditStmtBuilder,

View File

@@ -105,7 +105,7 @@ func NewTestManager(t *testing.T, testOpts *TestManagerOptions) *Manager {
}
// Create querier with test values
providerFactory := signozquerier.NewFactory(telemetryStore, prometheus, cache, flagger)
providerFactory := signozquerier.NewFactory(telemetryStore, prometheus, nil, cache, flagger)
mockQuerier, err := providerFactory.New(context.Background(), providerSettings, querier.Config{})
require.NoError(t, err)

View File

@@ -47,6 +47,7 @@ func prepareQuerierForMetrics(t *testing.T, telemetryStore telemetrystore.Teleme
telemetryStore,
metadataStore,
nil, // prometheus
nil, // promV2
nil, // traceStmtBuilder
nil, // logStmtBuilder
nil, // auditStmtBuilder
@@ -102,6 +103,7 @@ func prepareQuerierForLogs(t *testing.T, telemetryStore telemetrystore.Telemetry
telemetryStore,
metadataStore,
nil, // prometheus
nil, // promV2
nil, // traceStmtBuilder
logStmtBuilder, // logStmtBuilder
nil, // auditStmtBuilder
@@ -151,6 +153,7 @@ func prepareQuerierForTraces(t *testing.T, telemetryStore telemetrystore.Telemet
telemetryStore,
metadataStore,
nil, // prometheus
nil, // promV2
traceStmtBuilder, // traceStmtBuilder
nil, // logStmtBuilder
nil, // auditStmtBuilder

View File

@@ -44,6 +44,7 @@ import (
"github.com/SigNoz/signoz/pkg/pprof/nooppprof"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/SigNoz/signoz/pkg/querier"
"github.com/SigNoz/signoz/pkg/querier/signozquerier"
"github.com/SigNoz/signoz/pkg/sharder"
@@ -237,6 +238,7 @@ func NewTelemetryStoreProviderFactories() factory.NamedMap[factory.ProviderFacto
func NewPrometheusProviderFactories(telemetryStore telemetrystore.TelemetryStore) factory.NamedMap[factory.ProviderFactory[prometheus.Prometheus, prometheus.Config]] {
return factory.MustNewNamedMap(
clickhouseprometheus.NewFactory(telemetryStore),
clickhouseprometheusv2.NewFactory(telemetryStore),
)
}
@@ -278,9 +280,9 @@ func NewStatsReporterProviderFactories(aggregator statsreporter.Aggregator, orgG
)
}
func NewQuerierProviderFactories(telemetryStore telemetrystore.TelemetryStore, prometheus prometheus.Prometheus, cache cache.Cache, flagger flagger.Flagger) factory.NamedMap[factory.ProviderFactory[querier.Querier, querier.Config]] {
func NewQuerierProviderFactories(telemetryStore telemetrystore.TelemetryStore, prometheus prometheus.Prometheus, promV2 *clickhouseprometheusv2.Provider, cache cache.Cache, flagger flagger.Flagger) factory.NamedMap[factory.ProviderFactory[querier.Querier, querier.Config]] {
return factory.MustNewNamedMap(
signozquerier.NewFactory(telemetryStore, prometheus, cache, flagger),
signozquerier.NewFactory(telemetryStore, prometheus, promV2, cache, flagger),
)
}

View File

@@ -39,6 +39,7 @@ import (
"github.com/SigNoz/signoz/pkg/modules/tag/impltag"
"github.com/SigNoz/signoz/pkg/modules/user/impluser"
"github.com/SigNoz/signoz/pkg/prometheus"
"github.com/SigNoz/signoz/pkg/prometheus/clickhouseprometheusv2"
"github.com/SigNoz/signoz/pkg/querier"
"github.com/SigNoz/signoz/pkg/queryparser"
"github.com/SigNoz/signoz/pkg/ruler"
@@ -241,6 +242,11 @@ func New(
retentionGetter := implretention.NewGetter(implretention.NewStore(sqlstore))
// promV2 is the clickhousev2 provider handed to the querier for shadow
// comparison and pinned serving (declared before the serving provider,
// whose variable shadows the package name below).
var promV2 *clickhouseprometheusv2.Provider
// Initialize prometheus from the available prometheus provider factories
prometheus, err := factory.NewProviderFromNamedMap(
ctx,
@@ -253,12 +259,29 @@ func New(
return nil, err
}
// With the default provider, also stand up the clickhousev2 provider for
// the querier: PromQL queries shadow-compare against it behind the
// use_prometheus_clickhouse_v2 flag (see pkg/querier/promql_shadow.go).
// It never serves by default. An explicit
// prometheus::provider: clickhousev2 makes v2 the serving provider
// outright, so there is nothing to compare against.
if config.Prometheus.Provider() == "clickhouse" {
v2Config := config.Prometheus
// The v2 engine only evaluates shadow and pinned queries; disable its
// active query tracker so two trackers never share a file.
v2Config.ActiveQueryTrackerConfig.Enabled = false
promV2, err = clickhouseprometheusv2.New(ctx, providerSettings, v2Config, telemetrystore)
if err != nil {
return nil, err
}
}
// Initialize querier from the available querier provider factories
querier, err := factory.NewProviderFromNamedMap(
ctx,
providerSettings,
config.Querier,
NewQuerierProviderFactories(telemetrystore, prometheus, cache, flagger),
NewQuerierProviderFactories(telemetrystore, prometheus, promV2, cache, flagger),
config.Querier.Provider(),
)
if err != nil {

View File

@@ -10,7 +10,6 @@ import (
"strings"
"github.com/SigNoz/signoz/pkg/telemetrytraces"
"github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
)
type migrateCommon struct {
@@ -24,10 +23,119 @@ func NewMigrateCommon(logger *slog.Logger) *migrateCommon {
}
}
// WrapInV5Envelope delegates to querybuildertypesv5.WrapInV5Envelope; the
// transform is stateless and shared with the v1→v2 dashboard conversion.
func (migration *migrateCommon) WrapInV5Envelope(name string, queryMap map[string]any, queryType string) map[string]any {
return querybuildertypesv5.WrapInV5Envelope(name, queryMap, queryType)
// Create a properly structured v5 query
v5Query := map[string]any{
"name": name,
"disabled": queryMap["disabled"],
"legend": queryMap["legend"],
}
if name != queryMap["expression"] {
// formula
queryType = "builder_formula"
v5Query["expression"] = queryMap["expression"]
if functions, ok := queryMap["functions"]; ok {
v5Query["functions"] = functions
}
return map[string]any{
"type": queryType,
"spec": v5Query,
}
}
// Add signal based on data source
if dataSource, ok := queryMap["dataSource"].(string); ok {
switch dataSource {
case "traces":
v5Query["signal"] = "traces"
case "logs":
v5Query["signal"] = "logs"
case "metrics":
v5Query["signal"] = "metrics"
}
}
if stepInterval, ok := queryMap["stepInterval"]; ok {
v5Query["stepInterval"] = stepInterval
}
if aggregations, ok := queryMap["aggregations"]; ok {
v5Query["aggregations"] = aggregations
}
if filter, ok := queryMap["filter"]; ok {
v5Query["filter"] = filter
}
// Copy groupBy with proper structure
if groupBy, ok := queryMap["groupBy"].([]any); ok {
v5GroupBy := make([]any, len(groupBy))
for i, gb := range groupBy {
if gbMap, ok := gb.(map[string]any); ok {
v5GroupBy[i] = map[string]any{
"name": gbMap["key"],
"fieldDataType": gbMap["dataType"],
"fieldContext": gbMap["type"],
}
}
}
v5Query["groupBy"] = v5GroupBy
}
// Copy orderBy with proper structure
if orderBy, ok := queryMap["orderBy"].([]any); ok {
v5OrderBy := make([]any, len(orderBy))
for i, ob := range orderBy {
if obMap, ok := ob.(map[string]any); ok {
v5OrderBy[i] = map[string]any{
"key": map[string]any{
"name": obMap["columnName"],
"fieldDataType": obMap["dataType"],
"fieldContext": obMap["type"],
},
"direction": obMap["order"],
}
}
}
v5Query["order"] = v5OrderBy
}
// Copy selectColumns as selectFields
if selectColumns, ok := queryMap["selectColumns"].([]any); ok {
v5SelectFields := make([]any, len(selectColumns))
for i, col := range selectColumns {
if colMap, ok := col.(map[string]any); ok {
v5SelectFields[i] = map[string]any{
"name": colMap["key"],
"fieldDataType": colMap["dataType"],
"fieldContext": colMap["type"],
}
}
}
v5Query["selectFields"] = v5SelectFields
}
// Copy limit and offset
if limit, ok := queryMap["limit"]; ok {
v5Query["limit"] = limit
}
if offset, ok := queryMap["offset"]; ok {
v5Query["offset"] = offset
}
if having, ok := queryMap["having"]; ok {
v5Query["having"] = having
}
if functions, ok := queryMap["functions"]; ok {
v5Query["functions"] = functions
}
return map[string]any{
"type": queryType,
"spec": v5Query,
}
}
func (mc *migrateCommon) updateQueryData(ctx context.Context, queryData map[string]any, version, widgetType string) bool {

View File

@@ -1,353 +0,0 @@
// nolint
package transition
import (
"context"
"log/slog"
)
// ══════════════════════════════════════════════
// Shape-safe (idempotent) migration
// ══════════════════════════════════════════════
//
// A copy of the Migrate → updateWidget → updateQueryData chain with the
// "uniformly v4 input" assumption removed, so it is safe on a dashboard whose
// `version` tag lies (a "v5"-labelled dashboard with un-upgraded, possibly mixed,
// bodies — the v1→v2 converter's case). Versus the original: no version gate, and
// each step acts only on the pre-v5 shape (leaving a v5 field alone), so it is
// idempotent. The original Migrate is left unchanged (battle-tested, no test net).
// The *ShapeSafe methods below each note the original they copy; the reused steps
// (createFilterExpression, fixGroupBy, buildAggregationExpression, orderByExpr) are
// already v5-safe.
// MigrateQueryDataShapeSafe is the per-query entry point (the core of
// updateQueryDataShapeSafe) for callers that process queries one at a time (the
// v1→v2 converter). widgetType is the v1 panelTypes (metric reduceTo on tables);
// "" is safe.
func (m *dashboardMigrateV5) MigrateQueryDataShapeSafe(ctx context.Context, queryData map[string]any, widgetType string) bool {
return m.updateQueryDataShapeSafe(ctx, queryData, widgetType)
}
// updateQueryDataShapeSafe copies updateQueryData, with each destructive step
// guarded to act only on the pre-v5 shape (see the file header).
func (mc *migrateCommon) updateQueryDataShapeSafe(ctx context.Context, queryData map[string]any, widgetType string) bool {
updated := false
aggregateOp, _ := queryData["aggregateOperator"].(string)
hasAggregation := aggregateOp != "" && aggregateOp != "noop"
if mc.createAggregationsShapeSafe(ctx, queryData, widgetType) {
updated = true
}
// createFilterExpression only touches v4 `filters`; skip if a v5 `filter` exists.
if _, hasFilter := queryData["filter"]; !hasFilter {
if mc.createFilterExpression(ctx, queryData) {
updated = true
}
}
if mc.fixGroupBy(queryData) {
updated = true
}
if mc.createHavingExpressionShapeSafe(queryData) {
updated = true
}
if hasAggregation {
if orderBy, ok := queryData["orderBy"].([]any); ok && orderByIsPreV5(orderBy) {
newOrderBy := make([]any, 0)
for _, order := range orderBy {
if orderMap, ok := order.(map[string]any); ok {
columnName, _ := orderMap["columnName"].(string)
// skip timestamp, id (logs, traces), samples(metrics) ordering for aggregation queries
if columnName != "timestamp" && columnName != "samples" && columnName != "id" {
if columnName == "#SIGNOZ_VALUE" {
if expr, has := mc.orderByExpr(queryData); has {
orderMap["columnName"] = expr
}
} else {
// if the order by key is not part of the group by keys, remove it
present := false
groupBy, ok := queryData["groupBy"].([]any)
if !ok {
return false
}
for idx := range groupBy {
item, ok := groupBy[idx].(map[string]any)
if !ok {
continue
}
key, ok := item["key"].(string)
if !ok {
continue
}
if key == columnName {
present = true
}
}
if !present {
mc.logger.WarnContext(ctx, "found a order by without group by, skipping", slog.String("order_col_name", columnName))
continue
}
}
newOrderBy = append(newOrderBy, orderMap)
}
}
}
queryData["orderBy"] = newOrderBy
updated = true
}
} else {
dataSource, _ := queryData["dataSource"].(string)
if orderBy, ok := queryData["orderBy"].([]any); ok && orderByIsPreV5(orderBy) {
newOrderBy := make([]any, 0)
for _, order := range orderBy {
if orderMap, ok := order.(map[string]any); ok {
columnName, _ := orderMap["columnName"].(string)
// skip id and timestamp for (traces)
if (columnName == "id" || columnName == "timestamp") && dataSource == "traces" {
mc.logger.InfoContext(ctx, "skipping `id` order by for traces")
continue
}
// skip id for (logs)
if (columnName == "id" || columnName == "timestamp") && dataSource == "logs" {
mc.logger.InfoContext(ctx, "skipping `id`/`timestamp` order by for logs")
continue
}
newOrderBy = append(newOrderBy, orderMap)
}
}
queryData["orderBy"] = newOrderBy
updated = true
}
}
// Only the `&& functionsArePreV5(functions)` guard differs from updateQueryData.
if functions, ok := queryData["functions"].([]any); ok && functionsArePreV5(functions) {
v5Functions := make([]any, len(functions))
for i, fn := range functions {
if fnMap, ok := fn.(map[string]any); ok {
v5Function := map[string]any{
"name": fnMap["name"],
}
// Convert args from v4 format to v5 FunctionArg format
if args, ok := fnMap["args"].([]any); ok {
v5Args := make([]any, len(args))
for j, arg := range args {
// In v4, args were just values. In v5, they are FunctionArg objects
v5Args[j] = map[string]any{
"name": "", // v4 didn't have named args
"value": arg,
}
}
v5Function["args"] = v5Args
}
// Handle namedArgs if present (some functions might have used this)
if namedArgs, ok := fnMap["namedArgs"].(map[string]any); ok {
// Convert named args to the new format
existingArgs, _ := v5Function["args"].([]any)
if existingArgs == nil {
existingArgs = []any{}
}
for name, value := range namedArgs {
existingArgs = append(existingArgs, map[string]any{
"name": name,
"value": value,
})
}
v5Function["args"] = existingArgs
}
v5Functions[i] = v5Function
}
}
queryData["functions"] = v5Functions
updated = true
}
delete(queryData, "aggregateOperator")
delete(queryData, "aggregateAttribute")
delete(queryData, "temporality")
delete(queryData, "timeAggregation")
delete(queryData, "spaceAggregation")
delete(queryData, "reduceTo")
delete(queryData, "filters")
delete(queryData, "ShiftBy")
delete(queryData, "IsAnomaly")
delete(queryData, "QueriesUsedInFormula")
delete(queryData, "seriesAggregation")
return updated
}
// createHavingExpressionShapeSafe copies createHavingExpression but leaves an
// already-v5 having:{expression} alone instead of wiping it.
func (mc *migrateCommon) createHavingExpressionShapeSafe(queryData map[string]any) bool {
if _, ok := queryData["having"].(map[string]any); ok {
return false // already v5-shaped
}
having, ok := queryData["having"].([]any)
if !ok || len(having) == 0 {
queryData["having"] = map[string]any{"expression": ""}
return true
}
dataSource, _ := queryData["dataSource"].(string)
for idx := range having {
if havingItem, ok := having[idx].(map[string]any); ok {
havingCol, has := mc.orderByExpr(queryData)
if has {
havingItem["columnName"] = havingCol
havingItem["key"] = map[string]any{"key": havingCol}
}
having[idx] = havingItem
}
}
queryData["having"] = map[string]any{"expression": mc.buildExpression(context.Background(), having, "AND", dataSource)}
return true
}
// createAggregationsShapeSafe copies createAggregations but skips a query that
// already has a v5 aggregations[], and picks the metric time/space aggregation
// from the body's shape (has timeAggregation/spaceAggregation?) rather than the
// version tag.
func (mc *migrateCommon) createAggregationsShapeSafe(ctx context.Context, queryData map[string]any, widgetType string) bool {
if aggs, ok := queryData["aggregations"].([]any); ok && len(aggs) > 0 {
return false // already v5-shaped
}
aggregateOp, hasOp := queryData["aggregateOperator"].(string)
aggregateAttr, hasAttr := queryData["aggregateAttribute"].(map[string]any)
dataSource, _ := queryData["dataSource"].(string)
if aggregateOp == "noop" && dataSource != "metrics" {
return false
}
if !hasOp || !hasAttr {
return false
}
var aggregation map[string]any
switch dataSource {
case "metrics":
_, hasTime := queryData["timeAggregation"]
_, hasSpace := queryData["spaceAggregation"]
if hasTime || hasSpace { // acts as a check for v4 shape: the body carries its own time/space aggregation.
if _, ok := queryData["spaceAggregation"]; !ok {
queryData["spaceAggregation"] = aggregateOp
}
aggregation = map[string]any{
"metricName": aggregateAttr["key"],
"temporality": queryData["temporality"],
"timeAggregation": queryData["timeAggregation"],
"spaceAggregation": queryData["spaceAggregation"],
}
if reduceTo, ok := queryData["reduceTo"].(string); ok {
aggregation["reduceTo"] = reduceTo
}
} else {
// v3 shape: derive time/space from the compound operator.
var timeAgg, spaceAgg, reduceTo string
switch aggregateOp {
case "sum_rate", "rate_sum":
timeAgg, spaceAgg, reduceTo = "rate", "sum", "sum"
case "avg_rate", "rate_avg":
timeAgg, spaceAgg, reduceTo = "rate", "avg", "avg"
case "min_rate", "rate_min":
timeAgg, spaceAgg, reduceTo = "rate", "min", "min"
case "max_rate", "rate_max":
timeAgg, spaceAgg, reduceTo = "rate", "max", "max"
case "hist_quantile_50":
timeAgg, spaceAgg, reduceTo = "", "p50", "avg"
case "hist_quantile_75":
timeAgg, spaceAgg, reduceTo = "", "p75", "avg"
case "hist_quantile_90":
timeAgg, spaceAgg, reduceTo = "", "p90", "avg"
case "hist_quantile_95":
timeAgg, spaceAgg, reduceTo = "", "p95", "avg"
case "hist_quantile_99":
timeAgg, spaceAgg, reduceTo = "", "p99", "avg"
case "rate":
timeAgg, spaceAgg, reduceTo = "rate", "sum", "sum"
case "p99", "p90", "p75", "p50", "p25", "p20", "p10", "p05":
mc.logger.InfoContext(ctx, "found invalid config")
timeAgg, spaceAgg, reduceTo = "avg", "avg", "avg"
case "min":
timeAgg, spaceAgg, reduceTo = "min", "min", "min"
case "max":
timeAgg, spaceAgg, reduceTo = "max", "max", "max"
case "avg":
timeAgg, spaceAgg, reduceTo = "avg", "avg", "avg"
case "sum":
timeAgg, spaceAgg, reduceTo = "sum", "sum", "sum"
case "count":
timeAgg, spaceAgg, reduceTo = "count", "sum", "sum"
case "count_distinct":
timeAgg, spaceAgg, reduceTo = "count_distinct", "sum", "sum"
case "noop":
mc.logger.WarnContext(ctx, "noop found in the aggregation data")
timeAgg, spaceAgg, reduceTo = "max", "max", "max"
}
aggregation = map[string]any{
"metricName": aggregateAttr["key"],
"temporality": queryData["temporality"],
"timeAggregation": timeAgg,
"spaceAggregation": spaceAgg,
}
if widgetType == "table" {
aggregation["reduceTo"] = reduceTo
} else if reduceTo, ok := queryData["reduceTo"].(string); ok {
aggregation["reduceTo"] = reduceTo
}
}
case "logs", "traces":
aggregation = map[string]any{"expression": mc.buildAggregationExpression(aggregateOp, aggregateAttr)}
default:
return false
}
queryData["aggregations"] = []any{aggregation}
return true
}
// orderByIsPreV5 reports whether an orderBy slice is still in the v4 shape (an
// entry carries "columnName"); a v5 orderBy uses {key:{name}, direction}.
func orderByIsPreV5(orderBy []any) bool {
for _, o := range orderBy {
if m, ok := o.(map[string]any); ok {
if _, has := m["columnName"]; has {
return true
}
}
}
return false
}
// functionsArePreV5 reports whether a functions slice is still in the v4 shape
// (args are raw values); a v5 function's args are {name,value} objects.
func functionsArePreV5(functions []any) bool {
for _, f := range functions {
if m, ok := f.(map[string]any); ok {
args, ok := m["args"].([]any)
if !ok || len(args) == 0 {
continue
}
_, argIsObject := args[0].(map[string]any)
return !argIsObject
}
}
return false
}

View File

@@ -7,6 +7,7 @@ import (
"time"
"github.com/SigNoz/signoz/pkg/errors"
"github.com/SigNoz/signoz/pkg/transition"
"github.com/SigNoz/signoz/pkg/types"
"github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
"github.com/SigNoz/signoz/pkg/valuer"
@@ -21,7 +22,6 @@ var (
ErrCodeDashboardInvalidSource = errors.MustNewCode("dashboard_invalid_source")
ErrCodeDashboardImmutable = errors.MustNewCode("dashboard_immutable")
ErrCodeDashboardInvalidPatch = errors.MustNewCode("dashboard_invalid_patch")
ErrCodeDashboardMigrationFailed = errors.MustNewCode("dashboard_migration_failed")
)
type StorableDashboard struct {
@@ -413,26 +413,27 @@ func (dashboard *Dashboard) GetWidgetQuery(startTime, endTime, widgetIndex uint6
widgetData := data.Widgets[widgetIndex]
switch widgetData.Query.QueryType {
case "builder":
migrate := transition.NewMigrateCommon(logger)
for _, query := range widgetData.Query.Builder.QueryData {
queryName, ok := query["queryName"].(string)
if !ok {
return nil, errors.New(errors.TypeInvalidInput, ErrCodeDashboardInvalidWidgetQuery, "cannot type cast query name as string")
}
compositeQueries = append(compositeQueries, querybuildertypesv5.WrapInV5Envelope(queryName, query, "builder_query"))
compositeQueries = append(compositeQueries, migrate.WrapInV5Envelope(queryName, query, "builder_query"))
}
for _, query := range widgetData.Query.Builder.QueryFormulas {
queryName, ok := query["queryName"].(string)
if !ok {
return nil, errors.New(errors.TypeInvalidInput, ErrCodeDashboardInvalidWidgetQuery, "cannot type cast query name as string")
}
compositeQueries = append(compositeQueries, querybuildertypesv5.WrapInV5Envelope(queryName, query, "builder_formula"))
compositeQueries = append(compositeQueries, migrate.WrapInV5Envelope(queryName, query, "builder_formula"))
}
for _, query := range widgetData.Query.Builder.QueryTraceOperator {
queryName, ok := query["queryName"].(string)
if !ok {
return nil, errors.New(errors.TypeInvalidInput, ErrCodeDashboardInvalidWidgetQuery, "cannot type cast query name as string")
}
compositeQueries = append(compositeQueries, querybuildertypesv5.WrapInV5Envelope(queryName, query, "builder_trace_operator"))
compositeQueries = append(compositeQueries, migrate.WrapInV5Envelope(queryName, query, "builder_trace_operator"))
}
case "clickhouse_sql":
for _, query := range widgetData.Query.ClickhouseSQL {

View File

@@ -106,7 +106,7 @@ func (d *DashboardSpec) validatePanels() error {
}
panelKind := panel.Spec.Plugin.Kind
if len(panel.Spec.Queries) != 1 {
return errors.NewInvalidInputf(ErrCodeDashboardInvalidInput, "%s.spec.queries: panel must have one query, found %d", path, len(panel.Spec.Queries))
return errors.NewInvalidInputf(ErrCodeDashboardInvalidInput, "%s.spec.queries: panel must have one query", path)
}
allowed := allowedQueryKinds[panelKind]
for qi, q := range panel.Spec.Queries {
@@ -269,8 +269,8 @@ func (d *DashboardSpec) validateLayouts() error {
return errors.NewInternalf(errors.CodeInternal, "spec.layouts[%d].spec: unexpected layout spec type %T", li, layout.Spec)
}
if grid.Display != nil {
if n := utf8.RuneCountInString(grid.Display.Title); n > MaxLayoutTitleLen {
return errors.NewInvalidInputf(ErrCodeDashboardInvalidInput, "spec.layouts[%d].spec.display.title: layout name must be at most %d characters, got %d", li, MaxLayoutTitleLen, n)
if n := utf8.RuneCountInString(grid.Display.Title); n > MaxDisplayNameLen {
return errors.NewInvalidInputf(ErrCodeDashboardInvalidInput, "spec.layouts[%d].spec.display.title: layout name must be at most %d characters, got %d", li, MaxDisplayNameLen, n)
}
}
if err := validateGridLayoutGeometry(grid, li); err != nil {

View File

@@ -1059,34 +1059,6 @@ func TestValidateRequiredFields(t *testing.T) {
}
}
// TestThresholdZeroValueAcceptedMissingRejected documents the *float64 Value:
// a threshold at 0 (or 0.0) is valid, because the pointer lets validate:"required"
// tell a present zero (non-nil) from an absent value (nil) — while a genuinely
// missing value is still rejected.
func TestThresholdZeroValueAcceptedMissingRejected(t *testing.T) {
numberPanel := func(thresholdSpec string) string {
return `{
"panels": {"p1": {"kind": "Panel", "spec": {
"plugin": {"kind": "signoz/NumberPanel", "spec": {"thresholds": [` + thresholdSpec + `]}},
"queries": [{"kind": "time_series", "spec": {"plugin": {"kind": "signoz/PromQLQuery", "spec": {"name": "A", "query": "up"}}}}]
}}},
"layouts": []
}`
}
_, errZero := unmarshalDashboard([]byte(numberPanel(`{"value": 0, "operator": "above", "format": "text", "color": "Red"}`)))
require.NoError(t, errZero, `a threshold "value": 0 is valid`)
// "value": 0.0 is the same float64 zero as "value": 0 — JSON has one number
// type — and is accepted identically.
_, errZeroFloat := unmarshalDashboard([]byte(numberPanel(`{"value": 0.0, "operator": "above", "format": "text", "color": "Red"}`)))
require.NoError(t, errZeroFloat, `"value": 0.0 is the same valid zero`)
_, errMissing := unmarshalDashboard([]byte(numberPanel(`{"operator": "above", "format": "text", "color": "Red"}`)))
require.Error(t, errMissing, "a genuinely missing value is still rejected")
require.Contains(t, errMissing.Error(), "Value")
}
func TestTimeSeriesPanelDefaults(t *testing.T) {
data := []byte(`{
"panels": {
@@ -1669,61 +1641,55 @@ func TestInvalidateDuplicatePanelReference(t *testing.T) {
assert.Contains(t, err.Error(), "spec.layouts[0].spec.items[1].content")
}
// Every display name — dashboard, panel, variable — is bounded at MaxDisplayNameLen,
// while the grid layout title has its own, larger bound (MaxLayoutTitleLen). The name
// is one over the relevant limit in each case, and the message reads "<json path>:
// <field> name must be at most ...", pairing the locatable path (like the other spec
// errors) with a human field label.
// Every display name — dashboard, panel, variable — and the grid layout title is
// bounded at MaxDisplayNameLen. The name is one over the limit in each case, and
// the message reads "<json path>: <field> name must be at most ...", pairing the
// locatable path (like the other spec errors) with a human field label.
func TestInvalidateDisplayNameTooLong(t *testing.T) {
tooLong := strings.Repeat("x", MaxDisplayNameLen+1)
lengthMsg := fmt.Sprintf("must be at most %d characters, got %d", MaxDisplayNameLen, MaxDisplayNameLen+1)
testCases := []struct {
scenario string
limit int
dashboardJSONFmt string
expectedPath string
expectedLabel string
scenario string
dashboardJSON string
expectedPath string
expectedLabel string
}{
{
scenario: "dashboard display name",
limit: MaxDisplayNameLen,
dashboardJSONFmt: `{"display": {"name": "%s"}, "layouts": []}`,
expectedLabel: "dashboard",
expectedPath: "spec.display.name",
scenario: "dashboard display name",
dashboardJSON: `{"display": {"name": "` + tooLong + `"}, "layouts": []}`,
expectedLabel: "dashboard",
expectedPath: "spec.display.name",
},
{
scenario: "panel display name",
limit: MaxDisplayNameLen,
dashboardJSONFmt: `{"panels": {"p1": {"kind": "Panel", "spec": {"display": {"name": "%s"}, "plugin": {"kind": "signoz/TablePanel", "spec": {}}, "queries": []}}}, "layouts": []}`,
expectedLabel: "panel",
expectedPath: "spec.panels.p1.spec.display.name",
scenario: "panel display name",
dashboardJSON: `{"panels": {"p1": {"kind": "Panel", "spec": {"display": {"name": "` + tooLong + `"}, "plugin": {"kind": "signoz/TablePanel", "spec": {}}, "queries": []}}}, "layouts": []}`,
expectedLabel: "panel",
expectedPath: "spec.panels.p1.spec.display.name",
},
{
scenario: "list variable display name",
limit: MaxDisplayNameLen,
dashboardJSONFmt: `{"variables": [{"kind": "ListVariable", "spec": {"name": "svc", "display": {"name": "%s"}, "plugin": {"kind": "signoz/DynamicVariable", "spec": {"name": "service.name", "signal": "metrics"}}}}], "layouts": []}`,
expectedLabel: "variable",
expectedPath: "spec.variables[0].spec.display.name",
scenario: "list variable display name",
dashboardJSON: `{"variables": [{"kind": "ListVariable", "spec": {"name": "svc", "display": {"name": "` + tooLong + `"}, "plugin": {"kind": "signoz/DynamicVariable", "spec": {"name": "service.name", "signal": "metrics"}}}}], "layouts": []}`,
expectedLabel: "variable",
expectedPath: "spec.variables[0].spec.display.name",
},
{
scenario: "text variable display name",
limit: MaxDisplayNameLen,
dashboardJSONFmt: `{"variables": [{"kind": "TextVariable", "spec": {"name": "mytext", "value": "v", "display": {"name": "%s"}}}], "layouts": []}`,
expectedLabel: "variable",
expectedPath: "spec.variables[0].spec.display.name",
scenario: "text variable display name",
dashboardJSON: `{"variables": [{"kind": "TextVariable", "spec": {"name": "mytext", "value": "v", "display": {"name": "` + tooLong + `"}}}], "layouts": []}`,
expectedLabel: "variable",
expectedPath: "spec.variables[0].spec.display.name",
},
{
scenario: "layout title",
limit: MaxLayoutTitleLen,
dashboardJSONFmt: `{"layouts": [{"kind": "Grid", "spec": {"display": {"title": "%s"}, "items": []}}]}`,
expectedLabel: "layout",
expectedPath: "spec.layouts[0].spec.display.title",
scenario: "layout title",
dashboardJSON: `{"layouts": [{"kind": "Grid", "spec": {"display": {"title": "` + tooLong + `"}, "items": []}}]}`,
expectedLabel: "layout",
expectedPath: "spec.layouts[0].spec.display.title",
},
}
for _, testCase := range testCases {
t.Run(testCase.scenario, func(t *testing.T) {
tooLong := strings.Repeat("x", testCase.limit+1)
lengthMsg := fmt.Sprintf("must be at most %d characters, got %d", testCase.limit, testCase.limit+1)
_, err := unmarshalDashboard([]byte(fmt.Sprintf(testCase.dashboardJSONFmt, tooLong)))
_, err := unmarshalDashboard([]byte(testCase.dashboardJSON))
require.Error(t, err)
// Message is "<path>: <label> name must be at most N characters, got M".
want := testCase.expectedPath + ": " + testCase.expectedLabel + " name " + lengthMsg

View File

@@ -16,14 +16,10 @@ import (
"github.com/swaggest/jsonschema-go"
)
// MaxDisplayNameLen bounds the human-readable display names — dashboard, panel,
// and variable. The grid layout title has its own, larger bound (MaxLayoutTitleLen).
// MaxDisplayNameLen bounds every human-readable display name — dashboard, panel,
// and variable display names, plus the grid layout title.
const MaxDisplayNameLen = 128
// MaxLayoutTitleLen bounds a grid layout title. It is larger than MaxDisplayNameLen
// because v1 section (row) titles ran longer.
const MaxLayoutTitleLen = 256
type Display struct {
Name string `json:"name" required:"true"`
Description string `json:"description,omitempty"`

View File

@@ -252,20 +252,14 @@ type Legend struct {
}
type ThresholdWithLabel struct {
// Value is a pointer so a threshold at 0 is valid: validate:"required" treats
// the float64 zero as "missing", but a non-nil *float64 to 0 passes (and nil
// still fails, so a genuinely absent value is still rejected). nullable:"false"
// keeps it a plain required number in the schema — it is never null in valid
// data (validation rejects nil), so the pointer must not leak as `number|null`.
Value *float64 `json:"value" validate:"required" required:"true" nullable:"false"`
Unit string `json:"unit"`
Color string `json:"color" validate:"required" required:"true"`
Label string `json:"label"`
Value float64 `json:"value" validate:"required" required:"true"`
Unit string `json:"unit"`
Color string `json:"color" validate:"required" required:"true"`
Label string `json:"label"`
}
type ComparisonThreshold struct {
// Value is a pointer so a threshold at 0 is valid (see ThresholdWithLabel.Value).
Value *float64 `json:"value" validate:"required" required:"true" nullable:"false"`
Value float64 `json:"value" validate:"required" required:"true"`
Operator ComparisonOperator `json:"operator"`
Unit string `json:"unit"`
Color string `json:"color" validate:"required" required:"true"`

View File

@@ -1,95 +0,0 @@
package dashboardtypes
import (
"encoding/json"
"github.com/SigNoz/signoz/pkg/errors"
)
// V1 → V2 migration. The v1 storable shape is the frontend's `DashboardData`
// (see frontend/src/types/api/dashboard/getAll.ts); v2 is DashboardV2 /
// DashboardSpec.
//
// Assumes the v1 widget query data has already been migrated to v5 shape
// (transition.dashboardMigrateV5). Pre-v5 builder queries will produce
// invalid v2 envelopes — run the v4→v5 migration first.
//
// The conversion is split across sibling files by concern:
// - perses_v1_to_v2_tags.go tags
// - perses_v1_to_v2_panels.go widgets → panels (+ panel field mappers)
// - perses_v1_to_v2_queries.go widget queries
// - perses_v1_to_v2_layouts.go grid layouts and sections
// - perses_v1_to_v2_variables.go variables
// - perses_v1_to_v2_decoder.go v1Decoder: typed field reads + malformed-field detection
// ══════════════════════════════════════════════
// Entry point
// ══════════════════════════════════════════════
func (storable StorableDashboard) IsV2() bool {
metadata, _ := storable.Data["metadata"].(map[string]any)
if metadata == nil {
return false
}
version, _ := metadata["schemaVersion"].(string)
return version == SchemaVersion
}
func (storable StorableDashboard) ConvertV1ToV2() (result *DashboardV2, err error) {
// Legacy v1 data can be arbitrarily malformed. The accessors degrade
// gracefully, but recover from any unforeseen panic so one bad dashboard
// surfaces as an error (to be logged and skipped) rather than crashing the run.
defer func() {
if r := recover(); r != nil {
result, err = nil, errors.Newf(errors.TypeInternal, ErrCodeDashboardMigrationFailed, "panic converting dashboard %s: %v", storable.ID, r)
}
}()
if storable.IsV2() {
return nil, errors.Newf(errors.TypeInvalidInput, ErrCodeDashboardMigrationFailed, "dashboard %s is already in %s schema", storable.ID, SchemaVersion)
}
d := &v1Decoder{}
title := d.readString(storable.Data, "title")
description := d.readString(storable.Data, "description")
image := d.readString(storable.Data, "image")
sanitizeWidgetIDs(storable.Data)
panels := d.convertV1Panels(retainPlacedWidgets(storable.Data))
spec := DashboardSpec{
Display: Display{Name: clipName(title, MaxDisplayNameLen), Description: description},
Variables: d.convertV1Variables(storable.Data["variables"]),
Panels: panels,
Layouts: d.convertV1Layouts(storable.Data, panels),
}
// marshal and unmarshal cycle to confirm full validation
raw, marshalErr := json.Marshal(spec)
if marshalErr != nil {
return nil, errors.WrapInternalf(marshalErr, errors.CodeInternal, "marshal converted dashboard %s", storable.ID)
}
if err := json.Unmarshal(raw, new(DashboardSpec)); err != nil {
return nil, errors.WrapInvalidInputf(err, ErrCodeDashboardMigrationFailed, "converted dashboard %s is invalid", storable.ID)
}
tags := d.convertV1TagsForOrg(storable.OrgID, storable.Data["tags"])
if err := d.errIfHasMalformedFields(); err != nil {
return nil, err
}
return &DashboardV2{
Identifiable: storable.Identifiable,
TimeAuditable: storable.TimeAuditable,
UserAuditable: storable.UserAuditable,
OrgID: storable.OrgID,
Locked: storable.Locked,
Source: storable.Source,
DashboardV2MetadataBase: DashboardV2MetadataBase{
SchemaVersion: SchemaVersion,
Image: image,
},
Name: generateDashboardName(title),
Tags: tags,
Spec: spec,
}, nil
}

View File

@@ -1,214 +0,0 @@
package dashboardtypes
import (
"encoding/json"
"fmt"
"strconv"
"strings"
"github.com/SigNoz/signoz/pkg/errors"
)
// ══════════════════════════════════════════════
// v1 decoder
// ══════════════════════════════════════════════
// v1Decoder reads fields out of the untyped v1 dashboard blob. Every read*
// method follows the same contract: a field that is absent or null yields the
// zero value; a field present with the wrong type yields zero AND records a
// malformed-field error. Conversion proceeds (so one bad field doesn't abort
// the rest) and ConvertV1ToV2 returns d.malformedFieldsErr() at the end so the
// dashboard is logged and skipped.
//
// Polymorphic v1 fields (spanGaps bool|number, selectedValue string|array, …)
// are read with a type switch on the already-extracted value, never through
// these accessors, so they stay lenient by construction.
type v1Decoder struct {
bad []string
seen map[string]struct{}
}
// note records a decoding problem (malformed field, unknown value, swallowed
// sub-parse error), deduping identical messages. ConvertV1ToV2 surfaces these
// via errIfHasMalformedFields.
func (d *v1Decoder) note(format string, args ...any) {
msg := fmt.Sprintf(format, args...)
if _, dup := d.seen[msg]; dup {
return
}
if d.seen == nil {
d.seen = make(map[string]struct{})
}
d.seen[msg] = struct{}{}
d.bad = append(d.bad, msg)
}
// noteMalformedField records a v1 field present with the wrong Go type.
func (d *v1Decoder) noteMalformedField(field string, raw any) {
d.note("%q has unexpected type %T", field, raw)
}
// detailErr renders an error for a diagnostic note, unfolding the structured
// detail our JSON binding attaches via WithAdditional. A plain %v on these
// errors prints only the innermost message ("request body contains invalid
// field value") and drops the field/type context that says which field was
// wrong — the part that actually tells you what to fix.
func detailErr(err error) string {
if err == nil {
return ""
}
j := errors.AsJSON(err)
if len(j.Errors) == 0 {
return err.Error()
}
details := make([]string, 0, len(j.Errors))
for _, e := range j.Errors {
details = append(details, e.Message)
}
return j.Message + ": " + strings.Join(details, "; ")
}
func (d *v1Decoder) errIfHasMalformedFields() error {
if len(d.bad) == 0 {
return nil
}
// One field per line: these lists run long (a bad widget query is reported
// once per widget), and a single "; "-joined line is an unscannable wall.
return errors.Newf(errors.TypeInvalidInput, ErrCodeDashboardInvalidData, "malformed v1 dashboard fields:\n %s", strings.Join(d.bad, "\n "))
}
func readField[T any](d *v1Decoder, m map[string]any, key string) T {
var zero T
v, present := m[key]
if !present || v == nil {
return zero
}
t, ok := v.(T)
if !ok {
d.noteMalformedField(key, v)
return zero
}
return t
}
func (d *v1Decoder) readString(m map[string]any, key string) string {
return readField[string](d, m, key)
}
func (d *v1Decoder) readFloat(m map[string]any, key string) float64 {
v, present := m[key]
if !present || v == nil {
return 0
}
f, ok := coerceFloat(v)
if !ok {
d.noteMalformedField(key, v)
return 0
}
return f
}
// coerceFloat accepts a JSON number or a numeric string (v1 sometimes stores
// numbers like softMin as quoted strings). A blank string is "unset", not a
// number, so it fails to coerce.
func coerceFloat(v any) (float64, bool) {
switch n := v.(type) {
case float64:
return n, true
case string:
f, err := strconv.ParseFloat(strings.TrimSpace(n), 64)
if err != nil {
return 0, false
}
return f, true
}
return 0, false
}
func (d *v1Decoder) readBool(m map[string]any, key string) bool { return readField[bool](d, m, key) }
func (d *v1Decoder) readArray(m map[string]any, key string) []any { return readField[[]any](d, m, key) }
func (d *v1Decoder) readObject(m map[string]any, key string) map[string]any {
return readField[map[string]any](d, m, key)
}
// readInt narrows a numeric field to int (JSON numbers decode as float64).
func (d *v1Decoder) readInt(m map[string]any, key string) int { return int(d.readFloat(m, key)) }
func (d *v1Decoder) readFloatPtr(m map[string]any, key string) *float64 {
v, present := m[key]
if !present || v == nil {
return nil
}
// A blank string means "unset" (v1's empty softMin/softMax), not malformed.
if s, ok := v.(string); ok && strings.TrimSpace(s) == "" {
return nil
}
f, ok := coerceFloat(v)
if !ok {
d.noteMalformedField(key, v)
return nil
}
return &f
}
// clipName truncates s to at most limit runes so a v1 name over a v2 length bound
// (MaxDisplayNameLen / MaxLayoutTitleLen) is shortened rather than failing migration.
func clipName(s string, limit int) string {
r := []rune(s)
if len(r) <= limit {
return s
}
return string(r[:limit])
}
func (d *v1Decoder) readStringMap(m map[string]any, key string) map[string]string {
// An empty list is a stand-in for an empty map here; tolerate it silently
// rather than flagging the wrong-type as malformed.
if s, ok := m[key].([]any); ok && len(s) == 0 {
return nil
}
raw := d.readObject(m, key)
if len(raw) == 0 {
return nil
}
out := make(map[string]string, len(raw))
for k, v := range raw {
s, ok := v.(string)
if !ok {
d.noteMalformedField(key+"."+k, v)
continue
}
out[k] = s
}
return out
}
func (d *v1Decoder) readObjects(m map[string]any, key string) []map[string]any {
raw := d.readArray(m, key)
if len(raw) == 0 {
return nil
}
out := make([]map[string]any, 0, len(raw))
for i, item := range raw {
obj, ok := item.(map[string]any)
if !ok {
d.noteMalformedField(fmt.Sprintf("%s[%d]", key, i), item)
continue
}
out = append(out, obj)
}
return out
}
// decodeMapInto converts an untyped map[string]any into a typed T by
// round-tripping through JSON, letting encoding/json (struct tags, custom
// UnmarshalJSON) do the field mapping instead of hand-copying out of the map.
func decodeMapInto[T any](src map[string]any) (T, error) {
var dst T
bytes, err := json.Marshal(src)
if err != nil {
return dst, err
}
if err := json.Unmarshal(bytes, &dst); err != nil {
return dst, err
}
return dst, nil
}

View File

@@ -1,349 +0,0 @@
package dashboardtypes
import (
"sort"
"strings"
"github.com/perses/spec/go/common"
"github.com/perses/spec/go/dashboard"
)
// panelRefPrefix is the JSON-ref prefix a grid item uses to point at a panel:
// "#/spec/panels/<id>".
const panelRefPrefix = "#/spec/panels/"
// sanitizePanelID rewrites a widget id to something valid in a panel $ref. Perses
// accepts only [a-zA-Z0-9_-] per ref segment (common.jsonRefMatching), so every
// other rune (em dash, spaces, dots, unicode, …) is mapped to a hyphen.
func sanitizePanelID(id string) string {
return strings.Map(func(r rune) rune {
switch {
case r >= 'a' && r <= 'z', r >= 'A' && r <= 'Z', r >= '0' && r <= '9', r == '_', r == '-':
return r
default:
return '-'
}
}, id)
}
// sanitizeWidgetIDs rewrites every widget id in the raw v1 data — widgets[].id,
// layout[].i, panelMap keys and their widgets[].i — through sanitizePanelID, so a
// panel's map key and the layout $ref pointing at it stay identical (an illegal char
// in one but not the other would dangle the ref). Runs before panels/layouts build.
func sanitizeWidgetIDs(data StorableDashboardData) {
sanitizeField := func(raw any, field string) {
items, _ := raw.([]any)
for _, it := range items {
if m, ok := it.(map[string]any); ok {
if s, ok := m[field].(string); ok {
m[field] = sanitizePanelID(s)
}
}
}
}
sanitizeField(data["widgets"], "id")
sanitizeField(data["layout"], "i")
if panelMap, ok := data["panelMap"].(map[string]any); ok {
for key, v := range panelMap {
if s := sanitizePanelID(key); s != key {
panelMap[s] = v
delete(panelMap, key)
}
if m, ok := v.(map[string]any); ok {
sanitizeField(m["widgets"], "i")
}
}
}
}
// ══════════════════════════════════════════════
// Layouts (data.layout + data.panelMap)
// ══════════════════════════════════════════════
// convertV1Layouts groups v1 react-grid-layout entries into v2 grid layouts.
// Membership is positional (as the frontend renders): each row widget owns the
// panels below it until the next row; panels above the first row form an unnamed
// grid with no section header. Collapsed rows are the exception — their children
// live in panelMap[rowID].widgets, not `layout`.
func (d *v1Decoder) convertV1Layouts(data StorableDashboardData, panels map[string]*Panel) []Layout {
layout := d.readObjects(data, "layout")
if len(layout) == 0 {
return nil
}
// react-grid-layout can persist the same widget id more than once. Keep the first
// occurrence in stored order (mirroring getUpdatedLayout — the losing entry's
// geometry is discarded, not merged) and drop the rest. Dedupe before sortByPosition
// so "first" means first-in-stored-order, not topmost. Entries with no id are left
// for the main loop to drop.
seenWidgetIds := make(map[string]bool, len(layout))
dedupedLayouts := layout[:0]
for _, item := range layout {
if id := d.readString(item, "i"); id != "" {
if seenWidgetIds[id] {
continue
}
seenWidgetIds[id] = true
}
dedupedLayouts = append(dedupedLayouts, item)
}
layout = dedupedLayouts
rows := d.extractRowsAndCollapsedWidgets(data)
// ids placed directly in `layout`. A collapsed child also listed here is rendered from
// layout (the open section), so it's dropped from its collapsed section below.
placedInLayout := make(map[string]bool, len(layout))
for _, item := range layout {
if id := d.readString(item, "i"); id != "" {
placedInLayout[id] = true
}
}
d.sortByPosition(layout)
type section struct {
row *rowInfo // nil for the unnamed grid of ungrouped panels
items []map[string]any
}
topSectionWithoutHeader := &section{}
sectionsWithHeader := make([]*section, 0, len(rows))
currentRowHeader := topSectionWithoutHeader
for _, item := range layout {
id := d.readString(item, "i")
if id == "" {
continue
}
if row, ok := rows[id]; ok {
newRowHeader := &section{row: row, items: d.extractValidLayoutItemsForCollapsedSection(row.collapsedWidgets, panels, placedInLayout)}
sectionsWithHeader = append(sectionsWithHeader, newRowHeader)
// A collapsed row owns only its stashed children; later panels → ungrouped.
if row.collapsed {
currentRowHeader = topSectionWithoutHeader
} else {
currentRowHeader = newRowHeader
}
continue
}
// Keep a layout entry only if its widget became a panel; otherwise (skipped
// widget, deleted id, or the "__dropping-elem__" drag placeholder) it would
// reference a panel that does not exist. Rows are handled above.
if _, ok := panels[id]; !ok {
continue
}
currentRowHeader.items = append(currentRowHeader.items, item)
}
out := make([]Layout, 0, len(sectionsWithHeader)+1)
if len(topSectionWithoutHeader.items) > 0 {
out = append(out, d.buildV2GridLayout(nil, topSectionWithoutHeader.items))
}
for _, sec := range sectionsWithHeader {
out = append(out, d.buildV2GridLayout(sec.row, sec.items))
}
return out
}
// retainPlacedWidgets drops widgets the v1 layout never places, returning the
// filtered widgets. v1 doesn't render an unplaced widget, so converting it — and
// noting any problems it has — is pure noise; filter before conversion so only
// rendered widgets reach convertV1Panels. A non-array widgets value is returned
// untouched for convertV1Panels to flag; non-map entries are kept so it still
// flags them as malformed.
func retainPlacedWidgets(data StorableDashboardData) any {
widgets, ok := data["widgets"].([]any)
if !ok {
return data["widgets"]
}
placed := placedWidgetIDs(data)
kept := make([]any, 0, len(widgets))
for _, w := range widgets {
wm, ok := w.(map[string]any)
if !ok {
kept = append(kept, w) // malformed entry — leave it for convertV1Panels to note
continue
}
if id, _ := wm["id"].(string); placed[id] {
kept = append(kept, w)
}
}
return kept
}
// placedWidgetIDs returns the set of widget ids the v1 layout actually renders:
// every id in `layout`, plus the collapsed-row children stashed in panelMap.
// Read leniently (no malformed notes) — convertV1Layouts re-reads these and
// reports any genuine problems.
func placedWidgetIDs(data StorableDashboardData) map[string]bool {
ids := make(map[string]bool)
if layout, ok := data["layout"].([]any); ok {
for _, e := range layout {
if m, ok := e.(map[string]any); ok {
if i, ok := m["i"].(string); ok && i != "" {
ids[i] = true
}
}
}
}
if panelMap, ok := data["panelMap"].(map[string]any); ok {
for _, v := range panelMap {
m, ok := v.(map[string]any)
if !ok {
continue
}
widgets, ok := m["widgets"].([]any)
if !ok {
continue
}
for _, w := range widgets {
if wm, ok := w.(map[string]any); ok {
if i, ok := wm["i"].(string); ok && i != "" {
ids[i] = true
}
}
}
}
}
return ids
}
// extractValidLayoutItemsForCollapsedSection keeps only the collapsed-row children
// backed by a real panel and not already placed in `layout`, dropping ghosts and any
// child the open layout renders instead. These come from panelMap and skip the main
// loop's per-item panel check, so a grid never references a missing or twice-placed panel.
func (d *v1Decoder) extractValidLayoutItemsForCollapsedSection(items []map[string]any, panels map[string]*Panel, placedInLayout map[string]bool) []map[string]any {
out := make([]map[string]any, 0, len(items))
seen := make(map[string]bool, len(items))
for _, item := range items {
id := d.readString(item, "i")
if id == "" {
continue
}
if _, ok := panels[id]; !ok {
continue
}
if placedInLayout[id] || seen[id] {
continue
}
seen[id] = true
out = append(out, item)
}
return out
}
type rowInfo struct {
title string
collapsed bool
collapsedWidgets []map[string]any
}
// extractRowsAndCollapsedWidgets returns the row widgets keyed by id; collapsed
// rows also carry their children stashed under panelMap[id].widgets.
func (d *v1Decoder) extractRowsAndCollapsedWidgets(data StorableDashboardData) map[string]*rowInfo {
panelMap := d.readObject(data, "panelMap")
rows := make(map[string]*rowInfo)
for _, w := range d.readObjects(data, "widgets") {
// Read id directly (not via readString): a non-string id is skipped silently by
// convertV1Panels, so flagging it malformed here would fail the migration for a
// widget that's already been dropped.
id, _ := w["id"].(string)
if d.readString(w, "panelTypes") != "row" || id == "" {
continue
}
row := &rowInfo{title: d.readString(w, "title")}
// Some templates store panelMap[id] as a bare []widgetID instead of the
// canonical {widgets, collapsed}. The frontend treats such a non-object
// entry as "not collapsed" (see GridCardLayout), so read it leniently: a
// non-map yields nil, which reads as not collapsed.
pm, _ := panelMap[id].(map[string]any)
if d.readBool(pm, "collapsed") {
row.collapsed = true
row.collapsedWidgets = d.readObjects(pm, "widgets")
}
rows[id] = row
}
return rows
}
// buildV2GridLayout builds one v2 grid. row is nil for the unnamed grid (no
// display); otherwise the grid takes the row's title and collapse state. Items are
// sorted by (y, x) then vertically compacted (see compactGridItemsVertically).
func (d *v1Decoder) buildV2GridLayout(row *rowInfo, items []map[string]any) Layout {
d.sortByPosition(items)
spec := dashboard.GridLayoutSpec{Items: make([]dashboard.GridItem, 0, len(items))}
if row != nil {
spec.Display = &dashboard.GridLayoutDisplay{
Title: clipName(row.title, MaxLayoutTitleLen),
Collapse: &dashboard.GridLayoutCollapse{Open: !row.collapsed},
}
}
for _, item := range items {
spec.Items = append(spec.Items, dashboard.GridItem{
X: d.readInt(item, "x"),
Y: d.readInt(item, "y"),
Width: d.readInt(item, "w"),
Height: d.readInt(item, "h"),
Content: &common.JSONRef{Ref: panelRefPrefix + d.readString(item, "i")},
})
}
compactGridItemsVertically(spec.Items)
return Layout{Kind: dashboard.KindGridLayout, Spec: &spec}
}
// compactGridItemsVertically mirrors react-grid-layout's correctBounds+compact
// (compactType "vertical", allowOverlap false): clamp each item into the grid (x,y>=0;
// x+width<=cols by shifting left), then move sorted-first items up to fill space and
// down past collisions. Fixes overlaps, gaps, and out-of-bounds coords so the migrated
// grid matches the v1 UI and passes v2 validation.
func compactGridItemsVertically(items []dashboard.GridItem) {
collides := func(a, b dashboard.GridItem) bool {
return a.X < b.X+b.Width && b.X < a.X+a.Width && a.Y < b.Y+b.Height && b.Y < a.Y+a.Height
}
firstCollision := func(l dashboard.GridItem, placed []dashboard.GridItem) (dashboard.GridItem, bool) {
for _, p := range placed {
if collides(l, p) {
return p, true
}
}
return dashboard.GridItem{}, false
}
for i := range items {
l := items[i]
if l.X+l.Width > gridColumnCount { // overflows right → shift left to fit
l.X = gridColumnCount - l.Width
}
if l.X < 0 {
l.X = 0
}
if l.Y < 0 {
l.Y = 0
}
for l.Y > 0 { // move up to fill space above
up := l
up.Y--
if _, hit := firstCollision(up, items[:i]); hit {
break
}
l.Y--
}
for { // then down past any collision with an already-placed item
c, hit := firstCollision(l, items[:i])
if !hit {
break
}
l.Y = c.Y + c.Height
}
items[i] = l
}
}
func (d *v1Decoder) sortByPosition(items []map[string]any) {
sort.SliceStable(items, func(i, j int) bool {
if yi, yj := d.readInt(items[i], "y"), d.readInt(items[j], "y"); yi != yj {
return yi < yj
}
return d.readInt(items[i], "x") < d.readInt(items[j], "x")
})
}

View File

@@ -1,484 +0,0 @@
package dashboardtypes
import (
"encoding/json"
"fmt"
"strconv"
"strings"
"time"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
"github.com/SigNoz/signoz/pkg/valuer"
)
// ══════════════════════════════════════════════
// Widgets → Panels
// ══════════════════════════════════════════════
// convertV1Panels walks the v1 `widgets` array and produces v2 panels keyed by
// the v1 widget id. WidgetRow entries (panelTypes == "row") are dropped here
// and consumed by convertV1Layouts as section headers.
func (d *v1Decoder) convertV1Panels(raw any) map[string]*Panel {
if raw == nil {
return nil
}
widgetsRaw, ok := raw.([]any)
if !ok {
d.noteMalformedField("widgets", raw)
return nil
}
panels := make(map[string]*Panel, len(widgetsRaw))
for i, widgetRaw := range widgetsRaw {
widget, ok := widgetRaw.(map[string]any)
if !ok {
d.noteMalformedField(fmt.Sprintf("widgets[%d]", i), widgetRaw)
continue
}
// A non-string (or missing) id can't be referenced by any layout entry, and
// v1 doesn't render such widgets either — skip silently, don't flag it as
// malformed. Read directly (not via readString) to avoid a malformed note.
id, ok := widget["id"].(string)
if !ok || id == "" {
continue
}
var panel *Panel
panelType := d.readString(widget, "panelTypes")
switch panelType {
case "graph":
panel = d.convertGraphWidget(widget)
case "time_series", "TIME_SERIES":
// Malformed panelTypes: the canonical v1 value is "graph". Some dashboards
// stored the v2/enum-style name instead; accept it as a time-series graph.
panel = d.convertGraphWidget(widget)
case "bar":
panel = d.convertBarWidget(widget)
case "value":
panel = d.convertValueWidget(widget)
case "pie":
panel = d.convertPieWidget(widget)
case "table":
panel = d.convertTableWidget(widget)
case "histogram":
panel = d.convertHistogramWidget(widget)
case "list":
panel = d.convertListWidget(widget)
case "row":
// "row" (section header) is handled by the layout pass;
continue
default:
// Unknown/unsupported panel type — v1 can't render it either, so skip the
// widget silently rather than failing the whole migration.
continue
}
if panel == nil {
continue
}
if len(panel.Spec.Queries) == 0 {
// No renderable queries — every query was dropped as unrenderable, or none
// were defined. v1 renders nothing, so skip the widget silently.
continue
}
panels[id] = panel
}
return panels
}
func (d *v1Decoder) convertGraphWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindTimeSeries,
Spec: &TimeSeriesPanelSpec{
Visualization: TimeSeriesVisualization{
BasicVisualization: d.basicVisualization(w),
FillSpans: d.readBool(w, "fillSpans"),
},
Formatting: d.panelFormatting(w),
ChartAppearance: TimeSeriesChartAppearance{
LineInterpolation: mapV1Enum(d.readString(w, "lineInterpolation"), LineInterpolationSpline,
LineInterpolationLinear, LineInterpolationSpline, LineInterpolationStepAfter, LineInterpolationStepBefore),
ShowPoints: d.readBool(w, "showPoints"),
LineStyle: mapV1Enum(d.readString(w, "lineStyle"), LineStyleSolid, LineStyleSolid, LineStyleDashed),
FillMode: mapV1Enum(d.readString(w, "fillMode"), FillModeNone, FillModeSolid, FillModeGradient, FillModeNone),
SpanGaps: mapV1SpanGaps(w["spanGaps"]),
},
Axes: d.axesFromWidget(w),
Legend: d.legendFromWidget(w),
Thresholds: d.mapV1ThresholdsWithLabel(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindTimeSeries),
},
}
}
func (d *v1Decoder) convertBarWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindBarChart,
Spec: &BarChartPanelSpec{
Visualization: BarChartVisualization{
BasicVisualization: d.basicVisualization(w),
FillSpans: d.readBool(w, "fillSpans"),
StackedBarChart: d.readBool(w, "stackedBarChart"),
},
Formatting: d.panelFormatting(w),
Axes: d.axesFromWidget(w),
Legend: d.legendFromWidget(w),
Thresholds: d.mapV1ThresholdsWithLabel(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindBarChart),
},
}
}
func (d *v1Decoder) convertValueWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindNumber,
Spec: &NumberPanelSpec{
Visualization: d.basicVisualization(w),
Formatting: d.panelFormatting(w),
Thresholds: d.mapV1ComparisonThresholds(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindNumber),
},
}
}
func (d *v1Decoder) convertPieWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindPieChart,
Spec: &PieChartPanelSpec{
Visualization: d.basicVisualization(w),
Formatting: d.panelFormatting(w),
Legend: d.legendFromWidget(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindPieChart),
},
}
}
func (d *v1Decoder) convertTableWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindTable,
Spec: &TablePanelSpec{
Visualization: d.basicVisualization(w),
Formatting: TableFormatting{
ColumnUnits: d.readStringMap(w, "columnUnits"),
DecimalPrecision: mapV1Precision(w["decimalPrecision"]),
},
Thresholds: d.mapV1TableThresholds(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindTable),
},
}
}
func (d *v1Decoder) convertHistogramWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindHistogram,
Spec: &HistogramPanelSpec{
HistogramBuckets: HistogramBuckets{
BucketCount: d.readFloatPtr(w, "bucketCount"),
BucketWidth: d.readFloatPtr(w, "bucketWidth"),
MergeAllActiveQueries: d.readBool(w, "mergeAllActiveQueries"),
},
Legend: d.legendFromWidget(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindHistogram),
},
}
}
func (d *v1Decoder) convertListWidget(w map[string]any) *Panel {
return &Panel{
Kind: "Panel",
Spec: PanelSpec{
Display: d.widgetDisplay(w),
Plugin: PanelPlugin{
Kind: PanelKindList,
Spec: &ListPanelSpec{
SelectFields: d.mapV1SelectFields(w),
},
},
Queries: d.convertV1WidgetQuery(w, PanelKindList),
},
}
}
// ══════════════════════════════════════════════
// Panel-spec shared helpers
// ══════════════════════════════════════════════
func (d *v1Decoder) widgetDisplay(w map[string]any) Display {
return Display{Name: clipName(d.readString(w, "title"), MaxDisplayNameLen), Description: d.readString(w, "description")}
}
func (d *v1Decoder) basicVisualization(w map[string]any) BasicVisualization {
return BasicVisualization{TimePreference: mapV1TimePreference(d.readString(w, "timePreferance"))}
}
func (d *v1Decoder) panelFormatting(w map[string]any) PanelFormatting {
return PanelFormatting{Unit: d.readString(w, "yAxisUnit"), DecimalPrecision: mapV1Precision(w["decimalPrecision"])}
}
func (d *v1Decoder) axesFromWidget(w map[string]any) Axes {
return Axes{
SoftMin: d.readFloatPtr(w, "softMin"),
SoftMax: d.readFloatPtr(w, "softMax"),
IsLogScale: d.readBool(w, "isLogScale"),
}
}
func (d *v1Decoder) legendFromWidget(w map[string]any) Legend {
return Legend{
Position: mapV1Enum(d.readString(w, "legendPosition"), LegendPositionBottom, LegendPositionBottom, LegendPositionRight),
CustomColors: d.readStringMap(w, "customLegendColors"),
}
}
func (d *v1Decoder) mapV1SelectFields(w map[string]any) []telemetrytypes.TelemetryFieldKey {
field := "selectedLogFields"
raw := d.readArray(w, field)
if len(raw) == 0 {
field = "selectedTracesFields"
raw = d.readArray(w, field)
}
if len(raw) == 0 {
return nil
}
normalizePreV5FieldKeys(raw)
fields, err := decodeTelemetryFields(raw)
if err != nil {
d.note("widget %q has malformed %s: %v", d.readString(w, "id"), field, err)
return nil
}
// Drop nameless entries (blank column rows) — v2 requires a name, and the v1
// UI renders nothing for them anyway.
out := fields[:0]
for _, f := range fields {
if f.Name != "" {
out = append(out, f)
}
}
return out
}
func decodeTelemetryFields(raw []any) ([]telemetrytypes.TelemetryFieldKey, error) {
bytes, err := json.Marshal(raw)
if err != nil {
return nil, err
}
var fields []telemetrytypes.TelemetryFieldKey
if err := json.Unmarshal(bytes, &fields); err != nil {
return nil, err
}
return fields, nil
}
// ══════════════════════════════════════════════
// Panel field mappers
// ══════════════════════════════════════════════
// v1 stores timePreferance as `GLOBAL_TIME`, `LAST_5_MIN`, … (see
// frontend/src/container/NewWidget/RightContainer/timeItems.ts). v2 uses the
// lowercase form, so the translation is just downcase.
func mapV1TimePreference(s string) TimePreference {
if s == "" {
return TimePreferenceGlobalTime
}
candidate := TimePreference{valuer.NewString(strings.ToLower(s))}
for _, allowed := range candidate.Enum() {
if allowed == candidate {
return candidate
}
}
return TimePreferenceGlobalTime
}
// mapV1Precision is polymorphic (string|number), so it type-switches the raw
// value rather than reading through a typed accessor.
func mapV1Precision(raw any) PrecisionOption {
switch v := raw.(type) {
case string:
candidate := PrecisionOption{valuer.NewString(v)}
for _, allowed := range candidate.Enum() {
if allowed == candidate {
return candidate
}
}
case float64:
n := int(v)
if n >= 0 && n <= 4 {
return PrecisionOption{valuer.NewString(strconv.Itoa(n))}
}
}
return PrecisionOption2
}
// mapV1Enum picks the v1 string value if it matches one of the allowed v2
// values, otherwise returns the fallback. v1 frontend enums (lineInterpolation,
// lineStyle, fillMode, legendPosition) already use the v2 lowercase form.
func mapV1Enum[T interface{ StringValue() string }](s string, fallback T, allowed ...T) T {
if s == "" {
return fallback
}
for _, a := range allowed {
if a.StringValue() == s {
return a
}
}
return fallback
}
// v1 spanGaps is `boolean | number`. true → span every gap; false → never span;
// a number is interpreted (per frontend SeriesProps.spanGaps docs) as an
// X-axis threshold in seconds. Polymorphic, so it type-switches the raw value.
func mapV1SpanGaps(raw any) SpanGaps {
switch v := raw.(type) {
case bool:
return SpanGaps{FillOnlyBelow: false}
case float64:
return SpanGaps{FillOnlyBelow: true, FillLessThan: time.Duration(v * float64(time.Second)).String()}
}
return SpanGaps{FillOnlyBelow: false}
}
func (d *v1Decoder) mapV1ThresholdsWithLabel(w map[string]any) []ThresholdWithLabel {
rawSlice := d.readObjects(w, "thresholds")
if len(rawSlice) == 0 {
return nil
}
out := make([]ThresholdWithLabel, 0, len(rawSlice))
for _, t := range rawSlice {
color := d.readString(t, "thresholdColor")
label := d.readString(t, "thresholdLabel")
if color == "" || label == "" {
// v2 ThresholdWithLabel requires both; drop entries that wouldn't validate.
continue
}
value := d.readFloat(t, "thresholdValue")
out = append(out, ThresholdWithLabel{Value: &value, Unit: d.readString(t, "thresholdUnit"), Color: color, Label: label})
}
if len(out) == 0 {
return nil
}
return out
}
func (d *v1Decoder) mapV1ComparisonThresholds(w map[string]any) []ComparisonThreshold {
rawSlice := d.readObjects(w, "thresholds")
if len(rawSlice) == 0 {
return nil
}
out := make([]ComparisonThreshold, 0, len(rawSlice))
for _, t := range rawSlice {
color := d.readString(t, "thresholdColor")
if color == "" {
continue
}
value := d.readFloat(t, "thresholdValue")
out = append(out, ComparisonThreshold{
Value: &value,
Operator: d.mapV1ComparisonOperator(d.readString(t, "thresholdOperator")),
Unit: d.readString(t, "thresholdUnit"),
Color: color,
Format: mapV1ThresholdFormat(t["thresholdFormat"]),
})
}
if len(out) == 0 {
return nil
}
return out
}
func (d *v1Decoder) mapV1TableThresholds(w map[string]any) []TableThreshold {
rawSlice := d.readObjects(w, "thresholds")
if len(rawSlice) == 0 {
return nil
}
out := make([]TableThreshold, 0, len(rawSlice))
for _, t := range rawSlice {
color := d.readString(t, "thresholdColor")
columnName := d.readString(t, "thresholdTableOptions")
if color == "" || columnName == "" {
continue
}
value := d.readFloat(t, "thresholdValue")
out = append(out, TableThreshold{
ComparisonThreshold: ComparisonThreshold{
Value: &value,
Operator: d.mapV1ComparisonOperator(d.readString(t, "thresholdOperator")),
Unit: d.readString(t, "thresholdUnit"),
Color: color,
Format: mapV1ThresholdFormat(t["thresholdFormat"]),
},
ColumnName: columnName,
})
}
if len(out) == 0 {
return nil
}
return out
}
func (d *v1Decoder) mapV1ComparisonOperator(s string) ComparisonOperator {
switch s {
case ">", "gt":
return ComparisonOperatorAbove
case ">=", "gte":
return ComparisonOperatorAboveOrEqual
case "<", "lt":
return ComparisonOperatorBelow
case "<=", "lte":
return ComparisonOperatorBelowOrEqual
case "=", "==", "eq":
return ComparisonOperatorEqual
case "!=", "neq":
return ComparisonOperatorNotEqual
default:
// v1 often leaves the operator empty or carries an unknown value; default to
// "above" without flagging.
return ComparisonOperatorAbove
}
}
// mapV1ThresholdFormat reads the raw value (not via readString) so a non-string
// thresholdFormat — some v1 dashboards store it as a number — defaults to text
// silently instead of being flagged malformed.
func mapV1ThresholdFormat(raw any) ThresholdFormat {
s, _ := raw.(string)
switch strings.ToLower(s) {
case "background":
return ThresholdFormatBackground
case "text":
return ThresholdFormatText
}
return ThresholdFormatText
}

View File

@@ -1,441 +0,0 @@
package dashboardtypes
import (
"encoding/json"
"strconv"
"strings"
"github.com/SigNoz/signoz/pkg/errors"
qb "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
)
// ══════════════════════════════════════════════
// Queries
// ══════════════════════════════════════════════
// convertV1WidgetQuery returns exactly one Query (per Spec.Validate). The kind
// chosen depends on the v1 widget query shape:
// - a single query (promql / clickhouse_sql / builder) → its native kind
// - multiple queries → signoz/CompositeQuery
//
// A single query is never wrapped in a CompositeQuery; in particular List
// panels accept only a bare signoz/BuilderQuery. Builder queries are routed
// through qb.WrapInV5Envelope (in collectV1QueryEnvelopes), which translates v4
// builder-field names (orderBy/selectColumns/dataSource) into their v5
// equivalents and adds the `signal` field required by BuilderQuerySpec's
// per-signal dispatch.
func (d *v1Decoder) convertV1WidgetQuery(widget map[string]any, panelKind PanelPluginKind) []Query {
envelopes, signal := d.collectV1QueryEnvelopes(widget, panelKind)
if len(envelopes) == 0 {
return nil
}
// List panels accept only a bare BuilderQuery — never a CompositeQuery. Keep the
// first query and drop the rest so a multi-query v1 list widget still migrates.
if panelKind == PanelKindList && len(envelopes) > 1 {
envelopes = envelopes[:1]
}
requestType := requestTypeForPanel(panelKind)
// A single query keeps its native kind — never wrapped in a CompositeQuery.
if len(envelopes) == 1 {
if q := singleQueryFromEnvelope(envelopes[0], requestType, signal); q != nil {
return []Query{*q}
}
}
// Default: wrap in CompositeQuery.
composite, err := parseCompositeFromEnvelopes(envelopes)
if err != nil || composite == nil {
d.note("widget %q: could not build query from %d envelope(s): %s", d.readString(widget, "id"), len(envelopes), detailErr(err))
return nil
}
return []Query{{
Kind: requestType,
Spec: QuerySpec{
Plugin: QueryPlugin{Kind: QueryKindComposite, Spec: composite},
},
}}
}
// dropUnrenderableQueries removes queries whose aggregation can't render (see
// queryIsUnrenderable). If every query is unrenderable the result is empty, so the
// widget produces no panel and is skipped silently (convertV1Panels) — matching v1,
// which renders nothing.
func dropUnrenderableQueries(queries []map[string]any) []map[string]any {
renderable := make([]map[string]any, 0, len(queries))
for _, q := range queries {
if !queryIsUnrenderable(q) {
renderable = append(renderable, q)
}
}
return renderable
}
// queryIsUnrenderable reports whether a builder query can't render because of its
// aggregations: a metrics query with none or an empty metric name, or a logs/traces
// query with an empty aggregation expression. No aggregations is valid for a raw
// logs/traces query, so that isn't flagged.
func queryIsUnrenderable(q map[string]any) bool {
aggs, _ := q["aggregations"].([]any)
switch signalFromDataSource(q["dataSource"]) {
case telemetrytypes.SignalMetrics:
if len(aggs) == 0 {
return true
}
for _, a := range aggs {
if agg, ok := a.(map[string]any); ok {
if mn, _ := agg["metricName"].(string); mn == "" {
return true
}
}
}
case telemetrytypes.SignalLogs, telemetrytypes.SignalTraces:
for _, a := range aggs {
if agg, ok := a.(map[string]any); ok {
if expr, _ := agg["expression"].(string); expr == "" {
return true
}
}
}
}
return false
}
// requestTypeForPanel maps a v2 panel plugin kind to the request type (result
// shape) its queries produce. Mirrors the frontend's panelTypeToRequestType
// (buildQueryRangeRequest.ts): time series for line/bar/histogram (histogram
// bins client-side from raw time series, V1 parity), scalar for
// number/pie/table, raw rows for list.
func requestTypeForPanel(panelKind PanelPluginKind) qb.RequestType {
switch panelKind {
case PanelKindTimeSeries, PanelKindBarChart, PanelKindHistogram:
return qb.RequestTypeTimeSeries
case PanelKindNumber, PanelKindPieChart, PanelKindTable:
return qb.RequestTypeScalar
case PanelKindList:
return qb.RequestTypeRaw
}
return qb.RequestTypeTimeSeries
}
// collectV1QueryEnvelopes inspects widget.query.queryType and produces a
// flattened list of v5-shaped envelopes. The returned signal is the dominant
// builder signal (if any), used for typed builder-query dispatch.
func (d *v1Decoder) collectV1QueryEnvelopes(widget map[string]any, panelKind PanelPluginKind) ([]map[string]any, telemetrytypes.Signal) {
queryMap := d.readObject(widget, "query")
if queryMap == nil {
d.note("widget %q has no query map", d.readString(widget, "id"))
return nil, telemetrytypes.Signal{}
}
rowLimitPanel := panelKind == PanelKindList || panelKind == PanelKindTable
// Raw (list) panels legitimately have no aggregation; every other panel needs one.
needsAggregation := requestTypeForPanel(panelKind) != qb.RequestTypeRaw
queryType := d.readString(queryMap, "queryType")
switch queryType {
case "promql":
promQueries := d.readObjects(queryMap, "promql")
var out []map[string]any
for _, q := range promQueries {
// With multiple promql queries, drop the empty ones; a lone query is
// kept even if empty (nothing else would remain).
if len(promQueries) > 1 && d.readString(q, "query") == "" {
continue
}
out = append(out, promQLEnvelope(q))
}
return out, telemetrytypes.Signal{}
case "clickhouse_sql":
chQueries := d.readObjects(queryMap, "clickhouse_sql")
var out []map[string]any
for _, q := range chQueries {
// With multiple clickhouse queries, drop the empty ones; a lone query is
// kept even if empty (nothing else would remain).
if len(chQueries) > 1 && d.readString(q, "query") == "" {
continue
}
out = append(out, clickhouseEnvelope(q))
}
return out, telemetrytypes.Signal{}
case "builder":
builder := d.readObject(queryMap, "builder")
if builder == nil {
d.note("widget %q has no builder data in the query map", d.readString(widget, "id"))
return nil, telemetrytypes.Signal{}
}
var out []map[string]any
var signal telemetrytypes.Signal
widgetType := d.readString(widget, "panelTypes")
queries := d.readObjects(builder, "queryData")
assignQueryDataNames(queries)
for _, q := range queries {
normalizePreV5QueryData(q, widgetType)
normalizePreV5SelectColumns(q)
normalizePreV5GroupBy(q)
normalizePreV5PageSize(q, rowLimitPanel)
normalizeQueryLimit(q)
if needsAggregation {
ensureDefaultAggregation(q)
}
}
queries = dropUnrenderableQueries(queries)
for _, q := range queries {
name := d.readString(q, "queryName")
out = append(out, qb.WrapInV5Envelope(name, q, string(qb.QueryTypeBuilder.StringValue())))
if signal.IsZero() {
signal = signalFromDataSource(q["dataSource"])
}
}
formulas := d.readObjects(builder, "queryFormulas")
assignMissingFormulaNames(formulas)
for _, f := range formulas {
normalizePreV5QueryData(f, widgetType)
name := d.readString(f, "queryName")
env := qb.WrapInV5Envelope(name, f, string(qb.QueryTypeFormula.StringValue()))
// Drop a formula whose expression the validator rejects (blank/unparseable);
// v1 tolerated it but v2 fails the whole query. Reuse the real validator
// rather than reimplement it, as we do for functions.
if !formulaEnvelopeIsValid(env) {
continue
}
out = append(out, env)
}
for _, op := range d.readObjects(builder, "queryTraceOperator") {
// A trace operator's expression is the operation itself ("A=>B->C") and is
// required (ParseExpression rejects a blank one); drop it if empty.
expression := d.readString(op, "expression")
if expression == "" {
continue
}
normalizePreV5QueryData(op, widgetType)
normalizePreV5GroupBy(op)
name := d.readString(op, "queryName")
out = append(out, traceOperatorEnvelope(name, expression, op))
}
return out, signal
default:
d.note("widget %q has unknown queryType %q", d.readString(widget, "id"), queryType)
}
return nil, telemetrytypes.Signal{}
}
// traceOperatorEnvelope builds a v5 builder_trace_operator envelope. WrapInV5Envelope
// would misclassify a trace operator as a formula (its name differs from its
// expression, e.g. "A=>B->C"), so route the map through the builder-query path —
// temporarily aligning expression with name to dodge that heuristic — then restore the
// real expression, drop the builder-only signal (a trace operator's spec has no signal
// field), and set the trace-operator type.
func traceOperatorEnvelope(name, expression string, op map[string]any) map[string]any {
op["expression"] = name
env := qb.WrapInV5Envelope(name, op, string(qb.QueryTypeBuilder.StringValue()))
if spec, ok := env["spec"].(map[string]any); ok {
delete(spec, "signal")
spec["expression"] = expression
}
env["type"] = string(qb.QueryTypeTraceOperator.StringValue())
return env
}
// maxQueries mirrors the frontend MAX_QUERIES; builder query names run A..Z.
const maxQueries = 26
// assignQueryDataNames names builder data queries the way the frontend does: each
// unnamed query takes the first unused A..Z, deduped against existing names. It also
// forces expression == queryName, since a data query's expression is always its own
// name and WrapInV5Envelope's name != expression heuristic would otherwise
// misclassify the query as a formula.
func assignQueryDataNames(queries []map[string]any) {
taken := make(map[string]bool, len(queries))
for _, q := range queries {
if name, _ := q["queryName"].(string); name != "" {
taken[name] = true
}
}
for _, q := range queries {
name, _ := q["queryName"].(string)
if name == "" {
for i := 0; i < maxQueries; i++ {
candidate := string(rune('A' + i))
if !taken[candidate] {
name = candidate
taken[candidate] = true
break
}
}
q["queryName"] = name
}
q["expression"] = name
}
}
// formulaEnvelopeIsValid reports whether a builder_formula envelope's spec passes
// QueryBuilderFormula.Validate (blank/unparseable expression, blank name, invalid
// functions). Reuses the real validator rather than reimplementing it.
func formulaEnvelopeIsValid(env map[string]any) bool {
spec, ok := env["spec"].(map[string]any)
if !ok {
return false
}
raw, err := json.Marshal(spec)
if err != nil {
return false
}
var f qb.QueryBuilderFormula
if err := json.Unmarshal(raw, &f); err != nil {
return false
}
return f.Validate() == nil
}
// maxFormulas mirrors the frontend MAX_FORMULAS; formula names run F1..F20.
const maxFormulas = 20
// assignMissingFormulaNames fills queryName for unnamed formulas, mirroring the
// frontend: pick the first F{n} (n in 1..20) not already used by another formula.
// Formulas that already have a name keep it.
func assignMissingFormulaNames(formulas []map[string]any) {
taken := make(map[string]bool, len(formulas))
for _, f := range formulas {
if name, _ := f["queryName"].(string); name != "" {
taken[name] = true
}
}
for _, f := range formulas {
if name, _ := f["queryName"].(string); name != "" {
continue
}
for i := 1; i <= maxFormulas; i++ {
candidate := "F" + strconv.Itoa(i)
if !taken[candidate] {
f["queryName"] = candidate
taken[candidate] = true
break
}
}
}
}
func promQLEnvelope(q map[string]any) map[string]any {
return map[string]any{
"type": qb.QueryTypePromQL.StringValue(),
"spec": map[string]any{
"name": q["name"],
"query": q["query"],
"disabled": q["disabled"],
"legend": q["legend"],
},
}
}
func clickhouseEnvelope(q map[string]any) map[string]any {
return map[string]any{
"type": qb.QueryTypeClickHouseSQL.StringValue(),
"spec": map[string]any{
"name": q["name"],
"query": q["query"],
"disabled": q["disabled"],
"legend": q["legend"],
},
}
}
// singleQueryFromEnvelope returns a typed Query for one envelope, using its
// native query kind (promql/clickhouse_sql/builder) rather than wrapping it in
// a CompositeQuery. A bare signoz/BuilderQuery is valid for every panel kind
// and is the only kind List panels accept.
func singleQueryFromEnvelope(envelope map[string]any, requestType qb.RequestType, signal telemetrytypes.Signal) *Query {
t, _ := envelope["type"].(string)
spec, _ := envelope["spec"].(map[string]any)
switch t {
case qb.QueryTypePromQL.StringValue():
prom, err := decodeMapInto[qb.PromQuery](spec)
if err != nil {
return nil
}
return &Query{
Kind: requestType,
Spec: QuerySpec{
Name: prom.Name,
Plugin: QueryPlugin{Kind: QueryKindPromQL, Spec: &prom},
},
}
case qb.QueryTypeClickHouseSQL.StringValue():
ch, err := decodeMapInto[qb.ClickHouseQuery](spec)
if err != nil {
return nil
}
return &Query{
Kind: requestType,
Spec: QuerySpec{
Name: ch.Name,
Plugin: QueryPlugin{Kind: QueryKindClickHouseSQL, Spec: &ch},
},
}
case qb.QueryTypeBuilder.StringValue():
builderSpec := parseBuilderQuerySpec(spec, signal)
if builderSpec == nil {
return nil
}
name, _ := spec["name"].(string)
return &Query{
Kind: requestType,
Spec: QuerySpec{
Name: name,
Plugin: QueryPlugin{Kind: QueryKindBuilder, Spec: &BuilderQuerySpec{Spec: builderSpec}},
},
}
}
return nil
}
func parseCompositeFromEnvelopes(envelopes []map[string]any) (*CompositeQuerySpec, error) {
bytes, err := json.Marshal(envelopes)
if err != nil {
return nil, errors.WrapInternalf(err, errors.CodeInternal, "marshal v1 query envelopes")
}
var parsed []qb.QueryEnvelope
if err := json.Unmarshal(bytes, &parsed); err != nil {
return nil, errors.WrapInvalidInputf(err, ErrCodeDashboardInvalidWidgetQuery, "decode v5 query envelopes")
}
return &CompositeQuerySpec{Queries: parsed}, nil
}
func parseBuilderQuerySpec(rawSpec any, signal telemetrytypes.Signal) any {
spec, ok := rawSpec.(map[string]any)
if !ok {
return nil
}
if !signal.IsZero() {
spec["signal"] = signal.StringValue()
}
bytes, err := json.Marshal(spec)
if err != nil {
return nil
}
parsed, err := qb.UnmarshalBuilderQueryBySignal(bytes)
if err != nil {
return nil
}
return parsed
}
// signalFromDataSource maps a v1 data-source string to a v5 signal. Casing
// varies by source: builder queries store lowercase ("traces"), while variable
// `dynamicVariablesSource` stores capitalized ("Traces"), so match
// case-insensitively. Unknown values (e.g. "All telemetry") map to the zero
// Signal.
func signalFromDataSource(raw any) telemetrytypes.Signal {
s, _ := raw.(string)
switch strings.ToLower(s) {
case "traces":
return telemetrytypes.SignalTraces
case "logs":
return telemetrytypes.SignalLogs
case "metrics":
return telemetrytypes.SignalMetrics
}
return telemetrytypes.Signal{}
}

View File

@@ -1,406 +0,0 @@
package dashboardtypes
import (
"context"
"encoding/json"
"log/slog"
"regexp"
"strings"
"github.com/SigNoz/signoz/pkg/transition"
"github.com/SigNoz/signoz/pkg/types/metrictypes"
qb "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
"github.com/SigNoz/signoz/pkg/valuer"
)
// ══════════════════════════════════════════════
// Malformed-field normalization
// ══════════════════════════════════════════════
//
// Pre-v5 query-body reshapes for dashboards whose bodies aren't actually v5-shaped
// (e.g. stamped version:"v5" but never upgraded). The bulk of the upgrade is
// delegated to transition.MigrateQueryDataShapeSafe (see normalizePreV5QueryData);
// this file keeps only the reshapes it doesn't cover.
// preV5Migrator runs transition's shape-safe (idempotent) v4→v5 upgrade. Stateless
// after construction, so a shared instance with a discard logger / no ambiguity
// keys is fine.
var preV5Migrator = transition.NewDashboardMigrateV5(slog.New(slog.DiscardHandler), nil, nil)
// normalizePreV5QueryData upgrades one builder queryData/formula in place: the
// shared migrator, then a reshape of any existing aggregations[] it leaves alone.
func normalizePreV5QueryData(query map[string]any, widgetType string) {
dropLegacyFilter(query)
preV5Migrator.MigrateQueryDataShapeSafe(context.Background(), query, widgetType)
normalizePreV5LogTraceAggregations(query)
normalizeMetricAggregations(query)
normalizeOrderByKeys(query)
normalizeFunctionArgs(query)
dropInvalidFunctions(query)
}
// dropInvalidFunctions removes any function the v5 validator would reject — an unknown
// name, or a missing/uncastable required arg (see Function.Validate). v1 tolerated these
// but v2 fails the whole query, so we drop just the offending function. Runs after
// normalizeFunctionArgs so a merely double-wrapped (but otherwise valid) function isn't
// lost.
func dropInvalidFunctions(query map[string]any) {
fns, ok := query["functions"].([]any)
if !ok {
return
}
kept := make([]any, 0, len(fns))
for _, f := range fns {
raw, err := json.Marshal(f)
if err != nil {
continue
}
var fn qb.Function
if err := json.Unmarshal(raw, &fn); err != nil {
continue
}
if fn.Validate() != nil {
continue
}
kept = append(kept, f)
}
query["functions"] = kept
}
// normalizeFunctionArgs collapses a doubly-wrapped function arg to a scalar. The
// v4→v5 migration that runs before ConvertV1ToV2 (transition.updateQueryData) wraps every arg as
// {name, value} without checking whether it's already a v5 arg, so a body that was
// already v5 comes back as {value:{value:60}} and fails validation ("must be a floating
// value"). We can't guard it at the source — transition's Migrate is shared and left
// untouched — so unwrap one level of {value:...} nesting here.
func normalizeFunctionArgs(query map[string]any) {
fns, ok := query["functions"].([]any)
if !ok {
return
}
for _, f := range fns {
fn, ok := f.(map[string]any)
if !ok {
continue
}
args, ok := fn["args"].([]any)
if !ok {
continue
}
for _, a := range args {
arg, ok := a.(map[string]any)
if !ok {
continue
}
if inner, ok := arg["value"].(map[string]any); ok {
if v, ok := inner["value"]; ok {
arg["value"] = v
}
}
}
}
}
// malformedOrderByValueKeys are v4 order-by columnNames meaning "order by the aggregation value"
// that the v5 aggregation validator rejects (validateOrderByForAggregation). All resolve
// to the same aggregation key. Add more as they surface. The frontend passes these
// through (the query-service resolves them), but the v2 dashboard validator only accepts
// a real aggregation key.
var malformedOrderByValueKeys = map[string]bool{
"#SIGNOZ_VALUE": true,
"A": true,
"A.count()": true,
"__result": true,
"value": true,
}
// normalizeOrderByKeys rewrites any orderBy columnName in orderByValueKeys to the
// v5-valid aggregation key. Left untouched if the key can't resolve (no aggregation to
// name).
func normalizeOrderByKeys(query map[string]any) {
orders, ok := query["orderBy"].([]any)
if !ok {
return
}
key, ok := aggregationOrderKey(query)
if !ok {
return
}
for _, o := range orders {
order, ok := o.(map[string]any)
if !ok {
continue
}
if cn, _ := order["columnName"].(string); malformedOrderByValueKeys[cn] {
order["columnName"] = key
}
}
}
// aggregationOrderKey names the first aggregation the way validateOrderByForAggregation
// expects: "space(metricName)" for metrics, the expression for logs/traces.
func aggregationOrderKey(query map[string]any) (string, bool) {
aggs, ok := query["aggregations"].([]any)
if !ok || len(aggs) == 0 {
return "", false
}
agg, ok := aggs[0].(map[string]any)
if !ok {
return "", false
}
if signalFromDataSource(query["dataSource"]) == telemetrytypes.SignalMetrics {
metricName, _ := agg["metricName"].(string)
space, _ := agg["spaceAggregation"].(string)
if metricName == "" || space == "" {
return "", false
}
return space + "(" + metricName + ")", true
}
expr, _ := agg["expression"].(string)
if expr == "" {
return "", false
}
return expr, true
}
// dropLegacyFilter removes a v4-shaped filter ({items, op}) stored under the v5
// `filter` key. The v5 filter is {expression}; the migrator only rewrites the v4
// `filters` key and skips when `filter` is present, so this stale shape would reach
// WrapInV5Envelope and fail v5 validation. The v1 UI ignores it — it types
// IBuilderQuery.filter as {expression} (frontend queryBuilderData.ts, filter?: Filter)
// and only ever reads filter.expression, so items/op go unread. We drop it before the
// migrator, which can then rebuild `filter` from `filters` if present.
func dropLegacyFilter(query map[string]any) {
filter, ok := query["filter"].(map[string]any)
if !ok {
return
}
_, hasItems := filter["items"]
_, hasOp := filter["op"]
if hasItems || hasOp {
delete(query, "filter")
}
}
// metricAggregationFields are the JSON keys a metric aggregation accepts (see
// MetricAggregation). The decoder is strict, so any other key (e.g. a logs/traces
// style `expression`) is rejected as an unknown field.
var metricAggregationFields = map[string]bool{
"metricName": true,
"temporality": true,
"timeAggregation": true,
"spaceAggregation": true,
"comparisonSpaceAggregationParam": true,
"reduceTo": true,
}
// normalizeMetricAggregations reshapes a metric query's aggregations to the shape v5
// expects. v1 bodies sometimes carry a logs/traces-style aggregation ({expression});
// the frontend ignores expression for metrics and builds from the metric fields
// (createAggregation, prepareQueryRangePayloadV5.ts), so we drop every non-metric
// key. A dropped expression leaves metricName empty and the widget is skipped later
// (isUnrenderableMetricQuery), matching what v1 renders.
//
// It also defaults an invalid spaceAggregation to "sum": v1 bodies often leave it
// empty or carry a stale value, which fails validation (SpaceAggregation.IsValid). A
// valid value (including a histogram percentile) is left alone; the metric type isn't
// in the body, so we can't prefer a percentile default for histograms.
func normalizeMetricAggregations(query map[string]any) {
if signalFromDataSource(query["dataSource"]) != telemetrytypes.SignalMetrics {
return
}
aggs, ok := query["aggregations"].([]any)
if !ok {
return
}
for _, a := range aggs {
agg, ok := a.(map[string]any)
if !ok {
continue
}
for k := range agg {
if !metricAggregationFields[k] {
delete(agg, k)
}
}
sa, _ := agg["spaceAggregation"].(string)
if !(metrictypes.SpaceAggregation{String: valuer.NewString(sa)}).IsValid() {
agg["spaceAggregation"] = metrictypes.SpaceAggregationSum.StringValue()
}
}
}
// aggExprRe matches one "func(args)" with an optional "as alias". Mirrors the
// frontend's parseAggregations regex; matching only well-formed func(args)
// discards trailing junk ("sum(x) ) )" → "sum(x)").
var aggExprRe = regexp.MustCompile(`([a-zA-Z0-9_]+\([^)]*\))(?:\s*as\s+('[^']*'|"[^"]*"|[a-zA-Z0-9_-]+))?`)
// normalizePreV5LogTraceAggregations reshapes an existing logs/traces aggregations[]
// via parseAggregations (extract func(args), lift inline "as alias", split
// multi-part, drop metric-only fields; empty → count()). Covers the case the
// migrator skips: it builds from flat fields but leaves a present-but-malformed
// aggregations[] alone. A query with none is left as-is.
func normalizePreV5LogTraceAggregations(query map[string]any) {
switch signalFromDataSource(query["dataSource"]) {
case telemetrytypes.SignalLogs, telemetrytypes.SignalTraces:
default:
return
}
aggs, ok := query["aggregations"].([]any)
if !ok || len(aggs) == 0 {
return
}
out := make([]any, 0, len(aggs))
for _, a := range aggs {
agg, ok := a.(map[string]any)
if !ok {
continue
}
expr, _ := agg["expression"].(string)
alias, _ := agg["alias"].(string)
parsed := parseAggregations(expr, alias)
if len(parsed) == 0 {
parsed = []any{map[string]any{"expression": "count()"}}
}
out = append(out, parsed...)
}
query["aggregations"] = out
}
// ensureDefaultAggregation defaults an empty logs/traces aggregations[] to count(),
// mirroring the frontend. Callers gate this to aggregation panels. Metrics are skipped:
// count() can't stand in for a missing metricName.
func ensureDefaultAggregation(query map[string]any) {
switch signalFromDataSource(query["dataSource"]) {
case telemetrytypes.SignalLogs, telemetrytypes.SignalTraces:
default:
return
}
if aggs, ok := query["aggregations"].([]any); ok && len(aggs) > 0 {
return
}
query["aggregations"] = []any{map[string]any{"expression": "count()"}}
}
// parseAggregations pulls every func(args) (with inline or passed-through alias,
// quotes stripped) out of a v1 expression. Mirrors the frontend's
// parseAggregations; empty result if none.
func parseAggregations(expression, availableAlias string) []any {
matches := aggExprRe.FindAllStringSubmatch(expression, -1)
out := make([]any, 0, len(matches))
for _, m := range matches {
alias := m[2]
if alias == "" {
alias = availableAlias
}
agg := map[string]any{"expression": m[1]}
if alias != "" {
agg["alias"] = strings.Trim(alias, `'"`)
}
out = append(out, agg)
}
return out
}
// normalizePreV5SelectColumns / normalizePreV5GroupBy let WrapInV5Envelope (which
// reads the old {key,dataType,type}) handle selectColumns/groupBy stored the v5 way
// ({name,…}) — see backfillPreV5FieldKeys. Inverse of normalizePreV5FieldKeys (the
// two consumers want opposite shapes).
func normalizePreV5SelectColumns(query map[string]any) {
if cols, ok := query["selectColumns"].([]any); ok {
query["selectColumns"] = backfillPreV5FieldKeys(cols)
}
}
func normalizePreV5GroupBy(query map[string]any) {
if gb, ok := query["groupBy"].([]any); ok {
query["groupBy"] = backfillPreV5FieldKeys(gb)
}
}
// backfillPreV5FieldKeys copies v5 field names (name/fieldDataType/fieldContext)
// down to their v4 equivalents (key/dataType/type) so WrapInV5Envelope, which reads
// the v4 names, sees a field stored the v5 way. Fields with no resolvable key are
// dropped.
func backfillPreV5FieldKeys(fields []any) []any {
out := make([]any, 0, len(fields))
for _, f := range fields {
field, ok := f.(map[string]any)
if !ok {
continue
}
if _, ok := field["key"]; !ok {
if name, ok := field["name"]; ok {
field["key"] = name
}
}
if _, ok := field["dataType"]; !ok {
if fdt, ok := field["fieldDataType"]; ok {
field["dataType"] = fdt
}
}
if _, ok := field["type"]; !ok {
if fc, ok := field["fieldContext"]; ok {
field["type"] = fc
}
}
if key, _ := field["key"].(string); key == "" {
continue
}
out = append(out, field)
}
return out
}
// normalizePreV5FieldKeys renames list-panel field keys {key,dataType,type} →
// {name,fieldDataType,fieldContext} in place (as WrapInV5Envelope does for
// groupBy/orderBy). Entries already carrying "name" are left as-is.
func normalizePreV5FieldKeys(fields []any) {
for _, f := range fields {
field, ok := f.(map[string]any)
if !ok {
continue
}
if _, hasName := field["name"]; hasName {
continue
}
if key, ok := field["key"]; ok {
field["name"] = key
}
if dataType, ok := field["dataType"]; ok {
field["fieldDataType"] = dataType
}
if typ, ok := field["type"]; ok {
field["fieldContext"] = typ
}
}
}
// normalizePreV5PageSize backfills limit from the legacy pageSize (frontend's
// `limit || pageSize`), for row-limited panels (list/table) only. Leaves a query
// that already has limit, or a non-row-limited panel, untouched.
func normalizePreV5PageSize(query map[string]any, rowLimitPanel bool) {
if !rowLimitPanel {
return
}
if limit, ok := query["limit"]; ok && limit != nil {
return
}
if ps, ok := query["pageSize"]; ok {
query["limit"] = ps
}
}
// normalizeQueryLimit drops a limit above the v5 maximum (MaxQueryLimit); v1 allowed
// larger/unbounded limits, and an over-max value fails validation. Removing it leaves
// the query unlimited (the field is optional).
func normalizeQueryLimit(query map[string]any) {
limit, ok := coerceFloat(query["limit"])
if !ok {
return
}
if limit > qb.MaxQueryLimit {
delete(query, "limit")
}
}

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@@ -1,122 +0,0 @@
package dashboardtypes
import (
"fmt"
"regexp"
"strings"
"github.com/SigNoz/signoz/pkg/types/coretypes"
"github.com/SigNoz/signoz/pkg/types/tagtypes"
"github.com/SigNoz/signoz/pkg/valuer"
)
// ══════════════════════════════════════════════
// Tags
// ══════════════════════════════════════════════
// v1 carries tags as a flat []string; v2 tags are (key, value) pairs. Each v1
// string is normalized into a pair (separator split, empty-side fallback,
// reserved-key prefix, `/` scrub). Tags that normalize to the same
// (lower(key), lower(value)) within a dashboard are collapsed, first occurrence
// winning the display casing.
//
// Characters still illegal after normalization (spaces, punctuation) are molded
// to fit the tag validators: disallowed runs collapse to "_" (see moldTagField).
// defaultV1TagKey is the key assigned when a v1 tag string has no usable
// separator (or one side of the split is empty).
const defaultV1TagKey = "tag"
func (d *v1Decoder) convertV1TagsForOrg(orgID valuer.UUID, raw any) []*tagtypes.Tag {
if raw == nil {
return nil
}
rawTagsList, ok := raw.([]any)
if !ok {
d.noteMalformedField("tags", raw)
return nil
}
seen := make(map[string]struct{}, len(rawTagsList))
tagsV2 := make([]*tagtypes.Tag, 0, len(rawTagsList))
for i, rawTag := range rawTagsList {
s, ok := rawTag.(string)
if !ok {
d.noteMalformedField(fmt.Sprintf("tags[%d]", i), rawTag)
continue
}
key, value, ok := normalizeV1Tag(s)
if !ok {
continue
}
dedupKey := strings.ToLower(key) + "\x00" + strings.ToLower(value)
if _, dup := seen[dedupKey]; dup {
continue
}
seen[dedupKey] = struct{}{}
tagsV2 = append(tagsV2, tagtypes.NewTag(orgID, coretypes.KindDashboard, key, value))
}
return tagsV2
}
// normalizeV1Tag derives a (key, value) pair from one v1 tag string. After
// splitting and molding both sides, a lone survivor becomes a value under the
// default key; ok is false if neither survives.
func normalizeV1Tag(s string) (string, string, bool) {
s = strings.TrimSpace(s)
if s == "" {
return "", "", false
}
var rawKey, rawValue string
switch {
case strings.Contains(s, ":"):
rawKey, rawValue, _ = strings.Cut(s, ":")
// Only the first ":" separates key from value; collapse the rest.
rawValue = strings.ReplaceAll(rawValue, ":", "_")
case strings.Contains(s, "/"):
rawKey, rawValue, _ = strings.Cut(s, "/")
default:
rawValue = s
}
rawKey = strings.TrimSpace(rawKey)
rawValue = strings.TrimSpace(rawValue)
// Reserved-key collision: prefix "_" so the list-query DSL stays unambiguous.
if _, reserved := reservedDSLKeys[DSLKey(strings.ToLower(rawKey))]; rawKey != "" && reserved {
rawKey = "_" + rawKey
}
key := moldTagField(rawKey, tagKeyDisallowed, tagKeyNotLead, tagtypes.MAX_LEN_TAG_KEY)
value := moldTagField(rawValue, tagValueDisallowed, nil, tagtypes.MAX_LEN_TAG_VALUE)
switch {
case key == "" && value == "":
return "", "", false
case key == "":
return defaultV1TagKey, value, true
case value == "":
return defaultV1TagKey, key, true
default:
return key, value, true
}
}
// Inverse of tagKeyRegex/tagValueRegex ("/" always rejected); tagKeyNotLead
// matches a bad first char for a key. TestMoldedV1TagsPassValidation guards drift.
var (
tagKeyDisallowed = regexp.MustCompile(`[^a-zA-Z0-9$_@#{}:-]+`)
tagValueDisallowed = regexp.MustCompile(`[^a-zA-Z0-9$_@#{}:.+=-]+`)
tagKeyNotLead = regexp.MustCompile(`^[^a-zA-Z$_@{#]`)
)
// moldTagField collapses disallowed runs to "_", prefixes "_" if notLead hits
// the first char, and caps at max. Keeps a leading "_", trims a trailing one.
func moldTagField(s string, disallowed, notLead *regexp.Regexp, max int) string {
s = strings.TrimRight(disallowed.ReplaceAllString(s, "_"), "_")
if s != "" && notLead != nil && notLead.MatchString(s) {
s = "_" + s
}
if len(s) > max {
s = strings.TrimRight(s[:max], "_")
}
return s
}

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@@ -1,219 +0,0 @@
package dashboardtypes
import (
"sort"
"strconv"
"strings"
"github.com/perses/spec/go/dashboard/variable"
)
// ══════════════════════════════════════════════
// Variables
// ══════════════════════════════════════════════
// convertV1Variables walks the v1 `variables` map (UUID-keyed) and produces an
// ordered []Variable. Variables sort by `order` first, then by id for stable
// output. v1 variable types map as follows:
//
// QUERY → ListVariable + signoz/QueryVariable
// CUSTOM → ListVariable + signoz/CustomVariable
// DYNAMIC → ListVariable + signoz/DynamicVariable
// TEXTBOX → TextVariable
func (d *v1Decoder) convertV1Variables(raw any) []Variable {
if raw == nil {
return nil
}
rawVariablesMap, ok := raw.(map[string]any)
if !ok {
// v1 sometimes stores variables as a list. The frontend consumes it via
// Object.entries/keys, which for an array yields the stringified index as the
// key, so mirror that: [{...}] is treated as {"0":{...}}. An empty list is
// simply "no variables".
rawSlice, isSlice := raw.([]any)
if !isSlice {
d.noteMalformedField("variables", raw)
return nil
}
rawVariablesMap = make(map[string]any, len(rawSlice))
for i, v := range rawSlice {
rawVariablesMap[strconv.Itoa(i)] = v
}
}
type ordered struct {
variableID string
variableContent map[string]any
order float64
}
entries := make([]ordered, 0, len(rawVariablesMap))
for variableID, variableContentRaw := range rawVariablesMap {
variableContent, ok := variableContentRaw.(map[string]any)
if !ok {
// A variable whose content isn't an object (e.g. a stray "list" array) can't
// render in the current UI, so it's useless — skip it instead of failing the
// migration.
continue
}
entries = append(entries, ordered{variableID: variableID, variableContent: variableContent, order: d.readFloat(variableContent, "order")})
}
sort.SliceStable(entries, func(i, j int) bool {
if entries[i].order != entries[j].order {
return entries[i].order < entries[j].order
}
return entries[i].variableID < entries[j].variableID
})
variablesV2 := make([]Variable, 0, len(entries))
for _, e := range entries {
v, ok := d.convertV1Variable(e.variableContent)
if !ok {
continue
}
variablesV2 = append(variablesV2, v)
}
return variablesV2
}
func (d *v1Decoder) convertV1Variable(v map[string]any) (Variable, bool) {
name := d.readString(v, "name")
if name == "" {
return Variable{}, false
}
description := d.readString(v, "description")
// v1 stores the type upper-cased (QUERY/CUSTOM/…); tolerate any casing.
kind := strings.ToUpper(d.readString(v, "type"))
switch kind {
case "TEXTBOX":
spec := &TextVariableSpec{
Display: Display{Name: clipName(name, MaxDisplayNameLen), Description: description},
Value: d.readString(v, "textboxValue"),
Name: name,
}
return Variable{Kind: variable.KindText, Spec: spec}, true
case "QUERY", "CUSTOM", "DYNAMIC":
// Drop (don't fail on) a dynamic variable with no attribute — it can't resolve.
if kind == "DYNAMIC" && d.readString(v, "dynamicVariablesAttribute") == "" {
return Variable{}, false
}
// Drop a custom variable with no recoverable option list — v2 requires one.
if kind == "CUSTOM" && d.readString(v, "customValue") == "" && d.readString(v, "selectedValue") == "" && d.readString(v, "defaultValue") == "" {
return Variable{}, false
}
// Drop a query variable with no query — it can't resolve.
if kind == "QUERY" && d.readString(v, "queryValue") == "" {
return Variable{}, false
}
listSpec := &ListVariableSpec{
Display: Display{Name: clipName(name, MaxDisplayNameLen), Description: description},
AllowAllValue: d.readBool(v, "showALLOption"),
AllowMultiple: d.readBool(v, "multiSelect"),
CustomAllValue: d.readString(v, "customAllValue"),
CapturingRegexp: d.readString(v, "capturingRegexp"),
Sort: mapV1Sort(v["sort"]),
Plugin: d.variablePluginFor(kind, v),
Name: name,
}
if dv := mapV1VariableDefault(v, listSpec.AllowMultiple); dv != nil {
listSpec.DefaultValue = dv
}
return Variable{Kind: variable.KindList, Spec: listSpec}, true
case "":
// v1 sometimes stores a variable with no type; it can't render, so drop it
// silently rather than flagging it malformed.
return Variable{}, false
default:
d.note("variable %q has unknown type %q", name, kind)
return Variable{}, false
}
}
func (d *v1Decoder) variablePluginFor(kind string, v map[string]any) VariablePlugin {
switch kind {
case "QUERY":
return VariablePlugin{
Kind: VariableKindQuery,
Spec: &QueryVariableSpec{QueryValue: d.readString(v, "queryValue")},
}
case "CUSTOM":
// Some v1 dashboards stored the option list in selectedValue/defaultValue
// instead of customValue; fall back so the variable survives migration.
customValue := d.readString(v, "customValue")
if customValue == "" {
customValue = d.readString(v, "selectedValue")
}
if customValue == "" {
customValue = d.readString(v, "defaultValue")
}
return VariablePlugin{
Kind: VariableKindCustom,
Spec: &CustomVariableSpec{CustomValue: customValue},
}
case "DYNAMIC":
spec := &DynamicVariableSpec{Name: d.readString(v, "dynamicVariablesAttribute")}
if signal := signalFromDataSource(v["dynamicVariablesSource"]); !signal.IsZero() {
spec.Signal = signal
}
return VariablePlugin{Kind: VariableKindDynamic, Spec: spec}
}
return VariablePlugin{}
}
// mapV1VariableDefault reads selectedValue/defaultValue, both polymorphic
// (string|array), so it indexes the raw value and lets defaultValueFromAny
// type-switch — no typed accessor, intentionally lenient.
func mapV1VariableDefault(v map[string]any, allowMultiple bool) *VariableDefaultValue {
if raw, ok := v["selectedValue"]; ok {
return defaultValueFromAny(raw, allowMultiple)
}
if raw, ok := v["defaultValue"]; ok {
return defaultValueFromAny(raw, allowMultiple)
}
return nil
}
func defaultValueFromAny(raw any, allowMultiple bool) *VariableDefaultValue {
switch v := raw.(type) {
case string:
if v == "" {
return nil
}
return &VariableDefaultValue{variable.DefaultValue{SingleValue: v}}
case []any:
if len(v) == 0 {
return nil
}
values := make([]string, 0, len(v))
for _, item := range v {
if s, ok := item.(string); ok && s != "" {
values = append(values, s)
}
}
if len(values) == 0 {
return nil
}
// A single-select variable can't carry a list default; collapse a lone value.
if !allowMultiple && len(values) == 1 {
return &VariableDefaultValue{variable.DefaultValue{SingleValue: values[0]}}
}
return &VariableDefaultValue{variable.DefaultValue{SliceValues: values}}
}
return nil
}
// mapV1Sort reads the raw value (not via readString) so a non-string sort — some v1
// dashboards store it as a number (e.g. 0) — defaults to none silently instead of
// being flagged malformed.
func mapV1Sort(raw any) ListVariableSpecSort {
s, _ := raw.(string)
switch s {
case "ASC":
return SortAlphabeticalAsc
case "DESC":
return SortAlphabeticalDesc
}
return ListVariableSpecSort{} // zero (omitzero) — SortNone is the implicit default
}

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@@ -1,127 +0,0 @@
package querybuildertypesv5
// WrapInV5Envelope translates a single v4 builder query/formula map into a
// v5 query envelope ({"type": ..., "spec": ...}). It is a pure shape transform
// over untyped maps: v4 builder field names (groupBy/orderBy/selectColumns/
// dataSource) are rewritten to their v5 equivalents and a `signal` is derived
// from the data source. queryType selects the envelope type, except a formula
// (detected when name != queryMap["expression"]) is always emitted as
// "builder_formula".
//
// Migration code (pkg/transition) and the v1→v2 dashboard conversion both
// produce v5 envelopes, so this lives here with the v5 query types rather than
// in an infra-level package.
func WrapInV5Envelope(name string, queryMap map[string]any, queryType string) map[string]any {
// Create a properly structured v5 query
v5Query := map[string]any{
"name": name,
"disabled": queryMap["disabled"],
"legend": queryMap["legend"],
}
if name != queryMap["expression"] {
// formula
queryType = "builder_formula"
v5Query["expression"] = queryMap["expression"]
if functions, ok := queryMap["functions"]; ok {
v5Query["functions"] = functions
}
return map[string]any{
"type": queryType,
"spec": v5Query,
}
}
// Add signal based on data source
if dataSource, ok := queryMap["dataSource"].(string); ok {
switch dataSource {
case "traces":
v5Query["signal"] = "traces"
case "logs":
v5Query["signal"] = "logs"
case "metrics":
v5Query["signal"] = "metrics"
}
}
if stepInterval, ok := queryMap["stepInterval"]; ok {
v5Query["stepInterval"] = stepInterval
}
if aggregations, ok := queryMap["aggregations"]; ok {
v5Query["aggregations"] = aggregations
}
if filter, ok := queryMap["filter"]; ok {
v5Query["filter"] = filter
}
// Copy groupBy with proper structure
if groupBy, ok := queryMap["groupBy"].([]any); ok {
v5GroupBy := make([]any, len(groupBy))
for i, gb := range groupBy {
if gbMap, ok := gb.(map[string]any); ok {
v5GroupBy[i] = map[string]any{
"name": gbMap["key"],
"fieldDataType": gbMap["dataType"],
"fieldContext": gbMap["type"],
}
}
}
v5Query["groupBy"] = v5GroupBy
}
// Copy orderBy with proper structure
if orderBy, ok := queryMap["orderBy"].([]any); ok {
v5OrderBy := make([]any, len(orderBy))
for i, ob := range orderBy {
if obMap, ok := ob.(map[string]any); ok {
v5OrderBy[i] = map[string]any{
"key": map[string]any{
"name": obMap["columnName"],
"fieldDataType": obMap["dataType"],
"fieldContext": obMap["type"],
},
"direction": obMap["order"],
}
}
}
v5Query["order"] = v5OrderBy
}
// Copy selectColumns as selectFields
if selectColumns, ok := queryMap["selectColumns"].([]any); ok {
v5SelectFields := make([]any, len(selectColumns))
for i, col := range selectColumns {
if colMap, ok := col.(map[string]any); ok {
v5SelectFields[i] = map[string]any{
"name": colMap["key"],
"fieldDataType": colMap["dataType"],
"fieldContext": colMap["type"],
}
}
}
v5Query["selectFields"] = v5SelectFields
}
// Copy limit and offset
if limit, ok := queryMap["limit"]; ok {
v5Query["limit"] = limit
}
if offset, ok := queryMap["offset"]; ok {
v5Query["offset"] = offset
}
if having, ok := queryMap["having"]; ok {
v5Query["having"] = having
}
if functions, ok := queryMap["functions"]; ok {
v5Query["functions"] = functions
}
return map[string]any{
"type": queryType,
"spec": v5Query,
}
}

View File

@@ -370,6 +370,14 @@ type QueryRangeRequest struct {
// NoCache is a flag to disable caching for the request.
NoCache bool `json:"noCache,omitempty"`
// PromQLProvider serves this request's PromQL queries via the named
// prometheus provider ("clickhousev2") instead of the default — the same
// data read through a different implementation. It is set from the
// X-SigNoz-PromQL-Provider header by the API handler, never from the
// body: a rollout-scoped comparison hook for integration tests and
// support should not become part of the public request schema.
PromQLProvider string `json:"-"`
FormatOptions *FormatOptions `json:"formatOptions,omitempty"`
}

View File

@@ -0,0 +1,257 @@
"""PromQL provider parity: the CI guard for the clickhousev2 rollout.
Every battery query is fetched through /api/v5/query_range twice — once
served from the default provider, once pinned to the clickhousev2 provider
via the flag-gated X-SigNoz-PromQL-Provider header — over several evaluation
grids, and the two responses are compared series-by-series, point-by-point,
in the test. The providers read the same data through different
implementations, so timestamps and label sets must match exactly; values
within 1e-9 relative (they accumulate floats in different orders in the last
bit).
The fixtures are deterministic and target the semantics that historically
diverge between implementations:
- parity.counter: job=a resets mid-window; job=b is clean; job=c resets
twice AND has a gap longer than the 5m lookback, so its series vanishes
from instant selections and re-enters extrapolation windows.
- parity.gauge: pod=p1 lives forever; pod=p2 emits one stale marker and
resumes (a scrape blip); pod=p3 dies with a stale marker and stays dead;
pod=p4 is born mid-window; pod=p5 dies and resurrects 10 minutes later.
Per-pod magnitudes are distinct so topk never sees ties (tied topk picks
winners by evaluation order — legitimately different between two correct
implementations).
- parity.hist.bucket: a classic cumulative histogram.
All values are powers of two so float aggregation is order-independent.
The evaluation grids vary the query window and step: aligned and unaligned
starts (grid anchoring), a step that is no multiple of the scrape cadence,
a coarse step, and a window that begins before any data exists.
"""
import math
from datetime import UTC, datetime, timedelta
from http import HTTPStatus
import requests
from fixtures import types
from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
from fixtures.metrics import Metrics
REL_TOL = 1e-9
QUERIES = [
# instant selectors: lookback, stale-marker shadowing, name keeping
'{"parity.gauge"}',
'{"parity.gauge"} > 4',
'sum by (pod) ({"parity.gauge"})',
'sum({"parity.gauge"} offset 10m)',
# instant selection over a counter with a lookback-sized gap
'{"parity.counter", job="c"}',
# range functions: counter resets, double resets, gaps, extrapolation
'sum by (job) (rate({"parity.counter"}[5m]))',
'rate({"parity.counter", job="c"}[5m])',
'increase({"parity.counter", job="c"}[15m])',
'sum(increase({"parity.counter"}[10m] offset 15m))',
'sum by (pod) (delta({"parity.gauge"}[15m]))',
'irate({"parity.counter"}[5m])',
'idelta({"parity.gauge"}[5m])',
# *_over_time
'max by (pod) (avg_over_time({"parity.gauge"}[10m]))',
'count_over_time({"parity.gauge"}[10m])',
'last_over_time({"parity.gauge"}[10m])',
'min_over_time({"parity.gauge"}[7m])',
'sum_over_time({"parity.counter", job="c"}[10m])',
# hybrid shapes: quantiles, ratios, topk, or-fill
'histogram_quantile(0.9, sum by (le) (rate({"parity.hist.bucket"}[5m])))',
'sum(rate({"parity.counter"}[5m])) / sum(rate({"parity.counter"}[10m]))',
'topk(2, sum by (pod) ({"parity.gauge"}))',
'sum(rate({"parity.counter", job="missing"}[5m])) or vector(0)',
# subquery smoothing evaluates inner units on the subquery grid
'min_over_time((sum by (job) (increase({"parity.counter"}[5m])))[10m:5m])',
'avg_over_time((sum by (pod) ({"parity.gauge"}))[10m:2m])',
]
def grids(now_ms: int) -> list[tuple[str, int, int, int]]:
"""(description, start_ms, end_ms, step_seconds) variations. Different
starts anchor the evaluation grid differently; PromQL evaluates at
start + k*step, so an unaligned start shifts which samples each lookback
window sees. The long windows select the coarser series tables
(time_series_v4_6hrs at > 6h, _1week at > 1w) so the table choice and
its bucket rounding are exercised end to end, not just in unit tests."""
minute = 60_000
return [
("90m window, 60s step, minute-aligned", now_ms - 90 * minute, now_ms, 60),
("90m window, 60s step, start unaligned by 17s", now_ms - 90 * minute + 17_000, now_ms, 60),
("90m window, 90s step (no cadence multiple)", now_ms - 90 * minute, now_ms, 90),
("3h window starting before any data, 300s step", now_ms - 180 * minute, now_ms, 300),
("7h window (6h series table), 300s step", now_ms - 420 * minute, now_ms, 300),
("8d window (1w series table), 3600s step", now_ms - 8 * 24 * 60 * minute, now_ms, 3600),
]
def seed(insert_metrics, now: datetime) -> None:
"""95 minutes of 30s-cadence series ending at now (see module docstring
for the shapes). Values are powers of two so float aggregation is
order-independent."""
metrics: list[Metrics] = []
start = now - timedelta(minutes=95)
counters = {"a": 0.0, "b": 0.0, "c": 0.0}
step = 0
ts = start
while ts <= now:
for i, job in enumerate(("a", "b", "c")):
counters[job] += 2 << i
if job == "a" and ts == start + timedelta(minutes=45):
counters[job] = 8 # counter reset
if job == "c":
# Two resets and a >5m gap: the gap exceeds the lookback, so
# the series vanishes from instant selections mid-window.
if ts == start + timedelta(minutes=30) or ts == start + timedelta(minutes=70):
counters[job] = 4
if start + timedelta(minutes=50) < ts <= start + timedelta(minutes=56):
continue
metrics.append(
Metrics(
metric_name="parity.counter",
labels={"job": job},
timestamp=ts,
value=counters[job],
temporality="Cumulative",
type_="Sum",
)
)
# Distinct per-pod magnitudes keep topk free of ties: tied series
# would make the winner storage-order-dependent and the comparison
# nondeterministic.
for pod, scale in (("p1", 1), ("p2", 8), ("p3", 64), ("p4", 128), ("p5", 256)):
flags = 0
value = float((1 << (step % 6)) * scale)
if pod == "p2" and ts == start + timedelta(minutes=40):
flags, value = 1, 0.0 # stale marker, series resumes after
if pod == "p3":
if ts > start + timedelta(minutes=50, seconds=30):
continue
if ts == start + timedelta(minutes=50, seconds=30):
flags, value = 1, 0.0 # series dies and stays dead
if pod == "p4" and ts < start + timedelta(minutes=60):
continue # born mid-window
if pod == "p5":
# Dies with a stale marker, resurrects 10 minutes later.
if ts == start + timedelta(minutes=20):
flags, value = 1, 0.0
elif start + timedelta(minutes=20) < ts < start + timedelta(minutes=30):
continue
metrics.append(
Metrics(
metric_name="parity.gauge",
labels={"pod": pod},
timestamp=ts,
value=value,
temporality="Unspecified",
type_="Gauge",
is_monotonic=False,
flags=flags,
)
)
for i, le in enumerate(("0.5", "2", "+Inf")):
metrics.append(
Metrics(
metric_name="parity.hist.bucket",
labels={"le": le},
timestamp=ts,
value=float((step + 1) * (2 << i)),
temporality="Cumulative",
type_="Histogram",
)
)
step += 1
ts += timedelta(seconds=30)
insert_metrics(metrics)
def normalize(response_json: dict) -> dict[tuple, list[tuple]]:
"""Response results as {sorted-label-pairs: [(ts, value), ...]}."""
out: dict[tuple, list[tuple]] = {}
for result in response_json["data"]["data"]["results"]:
for aggregation in result.get("aggregations") or []:
for series in aggregation.get("series") or []:
key = tuple(
sorted((label["key"]["name"], label["value"]) for label in (series.get("labels") or []))
)
out[key] = [(v["timestamp"], v["value"]) for v in (series.get("values") or [])]
return out
def values_equal(a: float, b: float) -> bool:
if isinstance(a, str) or isinstance(b, str): # "NaN" and friends
return str(a) == str(b)
if math.isnan(a) and math.isnan(b):
return True
return math.isclose(a, b, rel_tol=REL_TOL, abs_tol=1e-12)
def fetch(signoz: types.SigNoz, token: str, query: str, start_ms: int, end_ms: int, step: int, provider: str | None):
payload = {
"schemaVersion": "v1",
"start": start_ms,
"end": end_ms,
"requestType": "time_series",
"compositeQuery": {"queries": [{"type": "promql", "spec": {"name": "A", "query": query, "step": step}}]},
"formatOptions": {"formatTableResultForUI": False, "fillGaps": False},
"noCache": True,
}
headers = {"authorization": f"Bearer {token}"}
if provider:
headers["X-SigNoz-PromQL-Provider"] = provider
response = requests.post(
signoz.self.host_configs["8080"].get("/api/v5/query_range"),
timeout=60,
headers=headers,
json=payload,
)
assert response.status_code == HTTPStatus.OK, f"{query} (provider={provider}): {response.text}"
return normalize(response.json())
def test_provider_parity(
signoz: types.SigNoz,
create_user_admin: None, # pylint: disable=unused-argument
get_token,
insert_metrics,
) -> None:
now = datetime.now(tz=UTC).replace(second=0, microsecond=0)
seed(insert_metrics, now)
token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
now_ms = int(now.timestamp() * 1000)
served_any_data = False
for grid_desc, start_ms, end_ms, step in grids(now_ms):
for query in QUERIES:
where = f"{query} [{grid_desc}]"
served = fetch(signoz, token, query, start_ms, end_ms, step, provider=None)
pinned = fetch(signoz, token, query, start_ms, end_ms, step, provider="clickhousev2")
assert served.keys() == pinned.keys(), (
f"{where}: series sets differ\nonly default: {sorted(set(served) - set(pinned))}"
f"\nonly clickhousev2: {sorted(set(pinned) - set(served))}"
)
for key, served_points in served.items():
pinned_points = pinned[key]
assert len(served_points) == len(pinned_points), f"{where} {key}: point counts differ ({len(served_points)} vs {len(pinned_points)})"
for (ts_a, val_a), (ts_b, val_b) in zip(served_points, pinned_points):
assert ts_a == ts_b, f"{where} {key}: timestamps differ ({ts_a} vs {ts_b})"
assert values_equal(val_a, val_b), f"{where} {key} @{ts_a}: values differ ({val_a} vs {val_b})"
if served:
served_any_data = True
assert served_any_data, "fixtures produced no data; the comparison would be over empties"

View File

@@ -0,0 +1,44 @@
import pytest
from testcontainers.core.container import Network
from fixtures import types
from fixtures.signoz import create_signoz
@pytest.fixture(name="signoz", scope="package")
def signoz_promql_shadow(
network: Network,
migrator: types.Operation, # pylint: disable=unused-argument
zeus: types.TestContainerDocker,
gateway: types.TestContainerDocker,
sqlstore: types.TestContainerSQL,
clickhouse: types.TestContainerClickhouse,
request: pytest.FixtureRequest,
pytestconfig: pytest.Config,
) -> types.SigNoz:
"""
Package-scoped SigNoz with the PromQL shadow-comparison flag on: every
PromQL query is served from the default engine path and re-run on the
clickhousev2 provider, with differences logged.
"""
# The clickhousev2 provider assumes the timeSeries*ToGrid aggregate
# functions exist (ClickHouse >= 25.6); older versions cannot serve the
# pinned side of the comparison at all.
version = pytestconfig.getoption("--clickhouse-version")
major, minor = (int(part) for part in str(version).split(".")[:2])
if (major, minor) < (25, 6):
pytest.skip(f"clickhousev2 requires ClickHouse >= 25.6, matrix leg runs {version}")
return create_signoz(
network=network,
zeus=zeus,
gateway=gateway,
sqlstore=sqlstore,
clickhouse=clickhouse,
request=request,
pytestconfig=pytestconfig,
cache_key="signoz-promql-shadow",
env_overrides={
"SIGNOZ_FLAGGER_CONFIG_BOOLEAN_USE__PROMETHEUS__CLICKHOUSE__V2": True,
},
)