package promql import ( "flag" "fmt" "math" "runtime" "sync" "github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/netstorage" "github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil" "github.com/VictoriaMetrics/VictoriaMetrics/lib/logger" "github.com/VictoriaMetrics/VictoriaMetrics/lib/memory" "github.com/VictoriaMetrics/VictoriaMetrics/lib/storage" "github.com/VictoriaMetrics/metrics" "github.com/VictoriaMetrics/metricsql" ) var ( maxPointsPerTimeseries = flag.Int("search.maxPointsPerTimeseries", 30e3, "The maximum points per a single timeseries returned from the search") ) // The minimum number of points per timeseries for enabling time rounding. // This improves cache hit ratio for frequently requested queries over // big time ranges. const minTimeseriesPointsForTimeRounding = 50 // ValidateMaxPointsPerTimeseries checks the maximum number of points that // may be returned per each time series. // // The number mustn't exceed -search.maxPointsPerTimeseries. func ValidateMaxPointsPerTimeseries(start, end, step int64) error { points := (end-start)/step + 1 if uint64(points) > uint64(*maxPointsPerTimeseries) { return fmt.Errorf(`too many points for the given step=%d, start=%d and end=%d: %d; cannot exceed -search.maxPointsPerTimeseries=%d`, step, start, end, uint64(points), *maxPointsPerTimeseries) } return nil } // AdjustStartEnd adjusts start and end values, so response caching may be enabled. // // See EvalConfig.mayCache for details. func AdjustStartEnd(start, end, step int64) (int64, int64) { points := (end-start)/step + 1 if points < minTimeseriesPointsForTimeRounding { // Too small number of points for rounding. return start, end } // Round start and end to values divisible by step in order // to enable response caching (see EvalConfig.mayCache). // Round start to the nearest smaller value divisible by step. start -= start % step // Round end to the nearest bigger value divisible by step. adjust := end % step if adjust > 0 { end += step - adjust } // Make sure that the new number of points is the same as the initial number of points. newPoints := (end-start)/step + 1 for newPoints > points { end -= step newPoints-- } return start, end } // EvalConfig is the configuration required for query evaluation via Exec type EvalConfig struct { Start int64 End int64 Step int64 RemoteAddr string Deadline netstorage.Deadline MayCache bool // LookbackDelta is analog to `-query.lookback-delta` from Prometheus. LookbackDelta int64 timestamps []int64 timestampsOnce sync.Once } // newEvalConfig returns new EvalConfig copy from src. func newEvalConfig(src *EvalConfig) *EvalConfig { var ec EvalConfig ec.Start = src.Start ec.End = src.End ec.Step = src.Step ec.Deadline = src.Deadline ec.MayCache = src.MayCache ec.LookbackDelta = src.LookbackDelta // do not copy src.timestamps - they must be generated again. return &ec } func (ec *EvalConfig) validate() { if ec.Start > ec.End { logger.Panicf("BUG: start cannot exceed end; got %d vs %d", ec.Start, ec.End) } if ec.Step <= 0 { logger.Panicf("BUG: step must be greater than 0; got %d", ec.Step) } } func (ec *EvalConfig) mayCache() bool { if !ec.MayCache { return false } if ec.Start%ec.Step != 0 { return false } if ec.End%ec.Step != 0 { return false } return true } func (ec *EvalConfig) getSharedTimestamps() []int64 { ec.timestampsOnce.Do(ec.timestampsInit) return ec.timestamps } func (ec *EvalConfig) timestampsInit() { ec.timestamps = getTimestamps(ec.Start, ec.End, ec.Step) } func getTimestamps(start, end, step int64) []int64 { // Sanity checks. if step <= 0 { logger.Panicf("BUG: Step must be bigger than 0; got %d", step) } if start > end { logger.Panicf("BUG: Start cannot exceed End; got %d vs %d", start, end) } if err := ValidateMaxPointsPerTimeseries(start, end, step); err != nil { logger.Panicf("BUG: %s; this must be validated before the call to getTimestamps", err) } // Prepare timestamps. points := 1 + (end-start)/step timestamps := make([]int64, points) for i := range timestamps { timestamps[i] = start start += step } return timestamps } func evalExpr(ec *EvalConfig, e metricsql.Expr) ([]*timeseries, error) { if me, ok := e.(*metricsql.MetricExpr); ok { re := &metricsql.RollupExpr{ Expr: me, } rv, err := evalRollupFunc(ec, "default_rollup", rollupDefault, e, re, nil) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, me.AppendString(nil), err) } return rv, nil } if re, ok := e.(*metricsql.RollupExpr); ok { rv, err := evalRollupFunc(ec, "default_rollup", rollupDefault, e, re, nil) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, re.AppendString(nil), err) } return rv, nil } if fe, ok := e.(*metricsql.FuncExpr); ok { nrf := getRollupFunc(fe.Name) if nrf == nil { args, err := evalExprs(ec, fe.Args) if err != nil { return nil, err } tf := getTransformFunc(fe.Name) if tf == nil { return nil, fmt.Errorf(`unknown func %q`, fe.Name) } tfa := &transformFuncArg{ ec: ec, fe: fe, args: args, } rv, err := tf(tfa) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, fe.AppendString(nil), err) } return rv, nil } args, re, err := evalRollupFuncArgs(ec, fe) if err != nil { return nil, err } rf, err := nrf(args) if err != nil { return nil, err } rv, err := evalRollupFunc(ec, fe.Name, rf, e, re, nil) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, fe.AppendString(nil), err) } return rv, nil } if ae, ok := e.(*metricsql.AggrFuncExpr); ok { if callbacks := getIncrementalAggrFuncCallbacks(ae.Name); callbacks != nil { fe, nrf := tryGetArgRollupFuncWithMetricExpr(ae) if fe != nil { // There is an optimized path for calculating metricsql.AggrFuncExpr over rollupFunc over metricsql.MetricExpr. // The optimized path saves RAM for aggregates over big number of time series. args, re, err := evalRollupFuncArgs(ec, fe) if err != nil { return nil, err } rf, err := nrf(args) if err != nil { return nil, err } iafc := newIncrementalAggrFuncContext(ae, callbacks) return evalRollupFunc(ec, fe.Name, rf, e, re, iafc) } } args, err := evalExprs(ec, ae.Args) if err != nil { return nil, err } af := getAggrFunc(ae.Name) if af == nil { return nil, fmt.Errorf(`unknown func %q`, ae.Name) } afa := &aggrFuncArg{ ae: ae, args: args, ec: ec, } rv, err := af(afa) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, ae.AppendString(nil), err) } return rv, nil } if be, ok := e.(*metricsql.BinaryOpExpr); ok { left, err := evalExpr(ec, be.Left) if err != nil { return nil, err } right, err := evalExpr(ec, be.Right) if err != nil { return nil, err } bf := getBinaryOpFunc(be.Op) if bf == nil { return nil, fmt.Errorf(`unknown binary op %q`, be.Op) } bfa := &binaryOpFuncArg{ be: be, left: left, right: right, } rv, err := bf(bfa) if err != nil { return nil, fmt.Errorf(`cannot evaluate %q: %w`, be.AppendString(nil), err) } return rv, nil } if ne, ok := e.(*metricsql.NumberExpr); ok { rv := evalNumber(ec, ne.N) return rv, nil } if se, ok := e.(*metricsql.StringExpr); ok { rv := evalString(ec, se.S) return rv, nil } return nil, fmt.Errorf("unexpected expression %q", e.AppendString(nil)) } func tryGetArgRollupFuncWithMetricExpr(ae *metricsql.AggrFuncExpr) (*metricsql.FuncExpr, newRollupFunc) { if len(ae.Args) != 1 { return nil, nil } e := ae.Args[0] // Make sure e contains one of the following: // - metricExpr // - metricExpr[d] // - rollupFunc(metricExpr) // - rollupFunc(metricExpr[d]) if me, ok := e.(*metricsql.MetricExpr); ok { // e = metricExpr if me.IsEmpty() { return nil, nil } fe := &metricsql.FuncExpr{ Name: "default_rollup", Args: []metricsql.Expr{me}, } nrf := getRollupFunc(fe.Name) return fe, nrf } if re, ok := e.(*metricsql.RollupExpr); ok { if me, ok := re.Expr.(*metricsql.MetricExpr); !ok || me.IsEmpty() || re.ForSubquery() { return nil, nil } // e = metricExpr[d] fe := &metricsql.FuncExpr{ Name: "default_rollup", Args: []metricsql.Expr{re}, } nrf := getRollupFunc(fe.Name) return fe, nrf } fe, ok := e.(*metricsql.FuncExpr) if !ok { return nil, nil } nrf := getRollupFunc(fe.Name) if nrf == nil { return nil, nil } rollupArgIdx := getRollupArgIdx(fe.Name) if rollupArgIdx >= len(fe.Args) { // Incorrect number of args for rollup func. return nil, nil } arg := fe.Args[rollupArgIdx] if me, ok := arg.(*metricsql.MetricExpr); ok { if me.IsEmpty() { return nil, nil } // e = rollupFunc(metricExpr) return &metricsql.FuncExpr{ Name: fe.Name, Args: []metricsql.Expr{me}, }, nrf } if re, ok := arg.(*metricsql.RollupExpr); ok { if me, ok := re.Expr.(*metricsql.MetricExpr); !ok || me.IsEmpty() || re.ForSubquery() { return nil, nil } // e = rollupFunc(metricExpr[d]) return fe, nrf } return nil, nil } func evalExprs(ec *EvalConfig, es []metricsql.Expr) ([][]*timeseries, error) { var rvs [][]*timeseries for _, e := range es { rv, err := evalExpr(ec, e) if err != nil { return nil, err } rvs = append(rvs, rv) } return rvs, nil } func evalRollupFuncArgs(ec *EvalConfig, fe *metricsql.FuncExpr) ([]interface{}, *metricsql.RollupExpr, error) { var re *metricsql.RollupExpr rollupArgIdx := getRollupArgIdx(fe.Name) if len(fe.Args) <= rollupArgIdx { return nil, nil, fmt.Errorf("expecting at least %d args to %q; got %d args; expr: %q", rollupArgIdx+1, fe.Name, len(fe.Args), fe.AppendString(nil)) } args := make([]interface{}, len(fe.Args)) for i, arg := range fe.Args { if i == rollupArgIdx { re = getRollupExprArg(arg) args[i] = re continue } ts, err := evalExpr(ec, arg) if err != nil { return nil, nil, fmt.Errorf("cannot evaluate arg #%d for %q: %w", i+1, fe.AppendString(nil), err) } args[i] = ts } return args, re, nil } func getRollupExprArg(arg metricsql.Expr) *metricsql.RollupExpr { re, ok := arg.(*metricsql.RollupExpr) if !ok { // Wrap non-rollup arg into metricsql.RollupExpr. return &metricsql.RollupExpr{ Expr: arg, } } if !re.ForSubquery() { // Return standard rollup if it doesn't contain subquery. return re } me, ok := re.Expr.(*metricsql.MetricExpr) if !ok { // arg contains subquery. return re } // Convert me[w:step] -> default_rollup(me)[w:step] reNew := *re reNew.Expr = &metricsql.FuncExpr{ Name: "default_rollup", Args: []metricsql.Expr{ &metricsql.RollupExpr{Expr: me}, }, } return &reNew } func evalRollupFunc(ec *EvalConfig, name string, rf rollupFunc, expr metricsql.Expr, re *metricsql.RollupExpr, iafc *incrementalAggrFuncContext) ([]*timeseries, error) { ecNew := ec var offset int64 if len(re.Offset) > 0 { var err error offset, err = metricsql.DurationValue(re.Offset, ec.Step) if err != nil { return nil, err } ecNew = newEvalConfig(ecNew) ecNew.Start -= offset ecNew.End -= offset if ecNew.MayCache { start, end := AdjustStartEnd(ecNew.Start, ecNew.End, ecNew.Step) offset += ecNew.Start - start ecNew.Start = start ecNew.End = end } } if name == "rollup_candlestick" { // Automatically apply `offset -step` to `rollup_candlestick` function // in order to obtain expected OHLC results. // See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/309#issuecomment-582113462 step := ecNew.Step ecNew = newEvalConfig(ecNew) ecNew.Start += step ecNew.End += step offset -= step } var rvs []*timeseries var err error if me, ok := re.Expr.(*metricsql.MetricExpr); ok { rvs, err = evalRollupFuncWithMetricExpr(ecNew, name, rf, expr, me, iafc, re.Window) } else { if iafc != nil { logger.Panicf("BUG: iafc must be nil for rollup %q over subquery %q", name, re.AppendString(nil)) } rvs, err = evalRollupFuncWithSubquery(ecNew, name, rf, expr, re) } if err != nil { return nil, err } if offset != 0 && len(rvs) > 0 { // Make a copy of timestamps, since they may be used in other values. srcTimestamps := rvs[0].Timestamps dstTimestamps := append([]int64{}, srcTimestamps...) for i := range dstTimestamps { dstTimestamps[i] += offset } for _, ts := range rvs { ts.Timestamps = dstTimestamps } } return rvs, nil } func evalRollupFuncWithSubquery(ec *EvalConfig, name string, rf rollupFunc, expr metricsql.Expr, re *metricsql.RollupExpr) ([]*timeseries, error) { // TODO: determine whether to use rollupResultCacheV here. var step int64 if len(re.Step) > 0 { var err error step, err = metricsql.PositiveDurationValue(re.Step, ec.Step) if err != nil { return nil, err } } else { step = ec.Step } var window int64 if len(re.Window) > 0 { var err error window, err = metricsql.PositiveDurationValue(re.Window, ec.Step) if err != nil { return nil, err } } ecSQ := newEvalConfig(ec) ecSQ.Start -= window + maxSilenceInterval + step ecSQ.Step = step if err := ValidateMaxPointsPerTimeseries(ecSQ.Start, ecSQ.End, ecSQ.Step); err != nil { return nil, err } ecSQ.Start, ecSQ.End = AdjustStartEnd(ecSQ.Start, ecSQ.End, ecSQ.Step) tssSQ, err := evalExpr(ecSQ, re.Expr) if err != nil { return nil, err } if len(tssSQ) == 0 { if name == "absent_over_time" { tss := evalNumber(ec, 1) return tss, nil } return nil, nil } sharedTimestamps := getTimestamps(ec.Start, ec.End, ec.Step) preFunc, rcs, err := getRollupConfigs(name, rf, expr, ec.Start, ec.End, ec.Step, window, ec.LookbackDelta, sharedTimestamps) if err != nil { return nil, err } tss := make([]*timeseries, 0, len(tssSQ)*len(rcs)) var tssLock sync.Mutex removeMetricGroup := !rollupFuncsKeepMetricGroup[name] doParallel(tssSQ, func(tsSQ *timeseries, values []float64, timestamps []int64) ([]float64, []int64) { values, timestamps = removeNanValues(values[:0], timestamps[:0], tsSQ.Values, tsSQ.Timestamps) preFunc(values, timestamps) for _, rc := range rcs { if tsm := newTimeseriesMap(name, sharedTimestamps, &tsSQ.MetricName); tsm != nil { rc.DoTimeseriesMap(tsm, values, timestamps) tssLock.Lock() tss = tsm.AppendTimeseriesTo(tss) tssLock.Unlock() continue } var ts timeseries doRollupForTimeseries(rc, &ts, &tsSQ.MetricName, values, timestamps, sharedTimestamps, removeMetricGroup) tssLock.Lock() tss = append(tss, &ts) tssLock.Unlock() } return values, timestamps }) return tss, nil } func doParallel(tss []*timeseries, f func(ts *timeseries, values []float64, timestamps []int64) ([]float64, []int64)) { concurrency := runtime.GOMAXPROCS(-1) if concurrency > len(tss) { concurrency = len(tss) } workCh := make(chan *timeseries, concurrency) var wg sync.WaitGroup wg.Add(concurrency) for i := 0; i < concurrency; i++ { go func() { defer wg.Done() var tmpValues []float64 var tmpTimestamps []int64 for ts := range workCh { tmpValues, tmpTimestamps = f(ts, tmpValues, tmpTimestamps) } }() } for _, ts := range tss { workCh <- ts } close(workCh) wg.Wait() } func removeNanValues(dstValues []float64, dstTimestamps []int64, values []float64, timestamps []int64) ([]float64, []int64) { hasNan := false for _, v := range values { if math.IsNaN(v) { hasNan = true } } if !hasNan { // Fast path - no NaNs. dstValues = append(dstValues, values...) dstTimestamps = append(dstTimestamps, timestamps...) return dstValues, dstTimestamps } // Slow path - remove NaNs. for i, v := range values { if math.IsNaN(v) { continue } dstValues = append(dstValues, v) dstTimestamps = append(dstTimestamps, timestamps[i]) } return dstValues, dstTimestamps } var ( rollupResultCacheFullHits = metrics.NewCounter(`vm_rollup_result_cache_full_hits_total`) rollupResultCachePartialHits = metrics.NewCounter(`vm_rollup_result_cache_partial_hits_total`) rollupResultCacheMiss = metrics.NewCounter(`vm_rollup_result_cache_miss_total`) ) func evalRollupFuncWithMetricExpr(ec *EvalConfig, name string, rf rollupFunc, expr metricsql.Expr, me *metricsql.MetricExpr, iafc *incrementalAggrFuncContext, windowStr string) ([]*timeseries, error) { if me.IsEmpty() { return evalNumber(ec, nan), nil } var window int64 if len(windowStr) > 0 { var err error window, err = metricsql.PositiveDurationValue(windowStr, ec.Step) if err != nil { return nil, err } } // Search for partial results in cache. tssCached, start := rollupResultCacheV.Get(ec, expr, window) if start > ec.End { // The result is fully cached. rollupResultCacheFullHits.Inc() return tssCached, nil } if start > ec.Start { rollupResultCachePartialHits.Inc() } else { rollupResultCacheMiss.Inc() } // Obtain rollup configs before fetching data from db, // so type errors can be caught earlier. sharedTimestamps := getTimestamps(start, ec.End, ec.Step) preFunc, rcs, err := getRollupConfigs(name, rf, expr, start, ec.End, ec.Step, window, ec.LookbackDelta, sharedTimestamps) if err != nil { return nil, err } // Fetch the remaining part of the result. tfs := toTagFilters(me.LabelFilters) minTimestamp := start - maxSilenceInterval if window > ec.Step { minTimestamp -= window } else { minTimestamp -= ec.Step } sq := &storage.SearchQuery{ MinTimestamp: minTimestamp, MaxTimestamp: ec.End, TagFilterss: [][]storage.TagFilter{tfs}, } rss, err := netstorage.ProcessSearchQuery(sq, true, ec.Deadline) if err != nil { return nil, err } rssLen := rss.Len() if rssLen == 0 { rss.Cancel() var tss []*timeseries if name == "absent_over_time" { tss = getAbsentTimeseries(ec, me) } // Add missing points until ec.End. // Do not cache the result, since missing points // may be backfilled in the future. tss = mergeTimeseries(tssCached, tss, start, ec) return tss, nil } // Verify timeseries fit available memory after the rollup. // Take into account points from tssCached. pointsPerTimeseries := 1 + (ec.End-ec.Start)/ec.Step timeseriesLen := rssLen if iafc != nil { // Incremental aggregates require holding only GOMAXPROCS timeseries in memory. timeseriesLen = runtime.GOMAXPROCS(-1) if iafc.ae.Modifier.Op != "" { if iafc.ae.Limit > 0 { // There is an explicit limit on the number of output time series. timeseriesLen *= iafc.ae.Limit } else { // Increase the number of timeseries for non-empty group list: `aggr() by (something)`, // since each group can have own set of time series in memory. timeseriesLen *= 1000 } } // The maximum number of output time series is limited by rssLen. if timeseriesLen > rssLen { timeseriesLen = rssLen } } rollupPoints := mulNoOverflow(pointsPerTimeseries, int64(timeseriesLen*len(rcs))) rollupMemorySize := mulNoOverflow(rollupPoints, 16) rml := getRollupMemoryLimiter() if !rml.Get(uint64(rollupMemorySize)) { rss.Cancel() return nil, fmt.Errorf("not enough memory for processing %d data points across %d time series with %d points in each time series; "+ "total available memory for concurrent requests: %d bytes; "+ "possible solutions are: reducing the number of matching time series; switching to node with more RAM; "+ "increasing -memory.allowedPercent; increasing `step` query arg (%gs)", rollupPoints, timeseriesLen*len(rcs), pointsPerTimeseries, rml.MaxSize, float64(ec.Step)/1e3) } defer rml.Put(uint64(rollupMemorySize)) // Evaluate rollup removeMetricGroup := !rollupFuncsKeepMetricGroup[name] var tss []*timeseries if iafc != nil { tss, err = evalRollupWithIncrementalAggregate(name, iafc, rss, rcs, preFunc, sharedTimestamps, removeMetricGroup) } else { tss, err = evalRollupNoIncrementalAggregate(name, rss, rcs, preFunc, sharedTimestamps, removeMetricGroup) } if err != nil { return nil, err } tss = mergeTimeseries(tssCached, tss, start, ec) rollupResultCacheV.Put(ec, expr, window, tss) return tss, nil } var ( rollupMemoryLimiter memoryLimiter rollupMemoryLimiterOnce sync.Once ) func getRollupMemoryLimiter() *memoryLimiter { rollupMemoryLimiterOnce.Do(func() { rollupMemoryLimiter.MaxSize = uint64(memory.Allowed()) / 4 }) return &rollupMemoryLimiter } func evalRollupWithIncrementalAggregate(name string, iafc *incrementalAggrFuncContext, rss *netstorage.Results, rcs []*rollupConfig, preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64, removeMetricGroup bool) ([]*timeseries, error) { err := rss.RunParallel(func(rs *netstorage.Result, workerID uint) { preFunc(rs.Values, rs.Timestamps) ts := getTimeseries() defer putTimeseries(ts) for _, rc := range rcs { if tsm := newTimeseriesMap(name, sharedTimestamps, &rs.MetricName); tsm != nil { rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps) for _, ts := range tsm.m { iafc.updateTimeseries(ts, workerID) } continue } ts.Reset() doRollupForTimeseries(rc, ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps, removeMetricGroup) iafc.updateTimeseries(ts, workerID) // ts.Timestamps points to sharedTimestamps. Zero it, so it can be re-used. ts.Timestamps = nil ts.denyReuse = false } }) if err != nil { return nil, err } tss := iafc.finalizeTimeseries() return tss, nil } func evalRollupNoIncrementalAggregate(name string, rss *netstorage.Results, rcs []*rollupConfig, preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64, removeMetricGroup bool) ([]*timeseries, error) { tss := make([]*timeseries, 0, rss.Len()*len(rcs)) var tssLock sync.Mutex err := rss.RunParallel(func(rs *netstorage.Result, workerID uint) { preFunc(rs.Values, rs.Timestamps) for _, rc := range rcs { if tsm := newTimeseriesMap(name, sharedTimestamps, &rs.MetricName); tsm != nil { rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps) tssLock.Lock() tss = tsm.AppendTimeseriesTo(tss) tssLock.Unlock() continue } var ts timeseries doRollupForTimeseries(rc, &ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps, removeMetricGroup) tssLock.Lock() tss = append(tss, &ts) tssLock.Unlock() } }) if err != nil { return nil, err } return tss, nil } func doRollupForTimeseries(rc *rollupConfig, tsDst *timeseries, mnSrc *storage.MetricName, valuesSrc []float64, timestampsSrc []int64, sharedTimestamps []int64, removeMetricGroup bool) { tsDst.MetricName.CopyFrom(mnSrc) if len(rc.TagValue) > 0 { tsDst.MetricName.AddTag("rollup", rc.TagValue) } if removeMetricGroup { tsDst.MetricName.ResetMetricGroup() } tsDst.Values = rc.Do(tsDst.Values[:0], valuesSrc, timestampsSrc) tsDst.Timestamps = sharedTimestamps tsDst.denyReuse = true } var bbPool bytesutil.ByteBufferPool func evalNumber(ec *EvalConfig, n float64) []*timeseries { var ts timeseries ts.denyReuse = true timestamps := ec.getSharedTimestamps() values := make([]float64, len(timestamps)) for i := range timestamps { values[i] = n } ts.Values = values ts.Timestamps = timestamps return []*timeseries{&ts} } func evalString(ec *EvalConfig, s string) []*timeseries { rv := evalNumber(ec, nan) rv[0].MetricName.MetricGroup = append(rv[0].MetricName.MetricGroup[:0], s...) return rv } func evalTime(ec *EvalConfig) []*timeseries { rv := evalNumber(ec, nan) timestamps := rv[0].Timestamps values := rv[0].Values for i, ts := range timestamps { values[i] = float64(ts) * 1e-3 } return rv } func mulNoOverflow(a, b int64) int64 { if math.MaxInt64/b < a { // Overflow return math.MaxInt64 } return a * b } func toTagFilters(lfs []metricsql.LabelFilter) []storage.TagFilter { tfs := make([]storage.TagFilter, len(lfs)) for i := range lfs { toTagFilter(&tfs[i], &lfs[i]) } return tfs } func toTagFilter(dst *storage.TagFilter, src *metricsql.LabelFilter) { if src.Label != "__name__" { dst.Key = []byte(src.Label) } else { // This is required for storage.Search. dst.Key = nil } dst.Value = []byte(src.Value) dst.IsRegexp = src.IsRegexp dst.IsNegative = src.IsNegative }