mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-12-29 23:30:04 +01:00
c86286ec1d
Previously it could be modified in order to improve response cache hit ratio. This is unneeded, since cache hit ratio should remain good because the query time range should be already aligned to multiple of `step` values. See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/976
867 lines
24 KiB
Go
867 lines
24 KiB
Go
package promql
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import (
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"flag"
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"fmt"
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"math"
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"sync"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/netstorage"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/searchutils"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/cgroup"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/memory"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
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"github.com/VictoriaMetrics/metrics"
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"github.com/VictoriaMetrics/metricsql"
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)
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var (
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disableCache = flag.Bool("search.disableCache", false, "Whether to disable response caching. This may be useful during data backfilling")
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maxPointsPerTimeseries = flag.Int("search.maxPointsPerTimeseries", 30e3, "The maximum points per a single timeseries returned from the search")
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)
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// The minimum number of points per timeseries for enabling time rounding.
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// This improves cache hit ratio for frequently requested queries over
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// big time ranges.
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const minTimeseriesPointsForTimeRounding = 50
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// ValidateMaxPointsPerTimeseries checks the maximum number of points that
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// may be returned per each time series.
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//
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// The number mustn't exceed -search.maxPointsPerTimeseries.
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func ValidateMaxPointsPerTimeseries(start, end, step int64) error {
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points := (end-start)/step + 1
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if uint64(points) > uint64(*maxPointsPerTimeseries) {
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return fmt.Errorf(`too many points for the given step=%d, start=%d and end=%d: %d; cannot exceed -search.maxPointsPerTimeseries=%d`,
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step, start, end, uint64(points), *maxPointsPerTimeseries)
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}
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return nil
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}
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// AdjustStartEnd adjusts start and end values, so response caching may be enabled.
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//
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// See EvalConfig.mayCache for details.
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func AdjustStartEnd(start, end, step int64) (int64, int64) {
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if *disableCache {
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// Do not adjust start and end values when cache is disabled.
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// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/563
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return start, end
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}
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points := (end-start)/step + 1
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if points < minTimeseriesPointsForTimeRounding {
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// Too small number of points for rounding.
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return start, end
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}
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// Round start and end to values divisible by step in order
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// to enable response caching (see EvalConfig.mayCache).
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start, end = alignStartEnd(start, end, step)
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// Make sure that the new number of points is the same as the initial number of points.
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newPoints := (end-start)/step + 1
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for newPoints > points {
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end -= step
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newPoints--
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}
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return start, end
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}
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func alignStartEnd(start, end, step int64) (int64, int64) {
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// Round start to the nearest smaller value divisible by step.
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start -= start % step
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// Round end to the nearest bigger value divisible by step.
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adjust := end % step
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if adjust > 0 {
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end += step - adjust
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}
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return start, end
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}
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// EvalConfig is the configuration required for query evaluation via Exec
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type EvalConfig struct {
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Start int64
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End int64
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Step int64
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// QuotedRemoteAddr contains quoted remote address.
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QuotedRemoteAddr string
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Deadline searchutils.Deadline
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MayCache bool
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// LookbackDelta is analog to `-query.lookback-delta` from Prometheus.
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LookbackDelta int64
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timestamps []int64
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timestampsOnce sync.Once
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}
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// newEvalConfig returns new EvalConfig copy from src.
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func newEvalConfig(src *EvalConfig) *EvalConfig {
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var ec EvalConfig
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ec.Start = src.Start
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ec.End = src.End
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ec.Step = src.Step
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ec.Deadline = src.Deadline
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ec.MayCache = src.MayCache
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ec.LookbackDelta = src.LookbackDelta
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// do not copy src.timestamps - they must be generated again.
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return &ec
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}
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func (ec *EvalConfig) validate() {
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if ec.Start > ec.End {
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logger.Panicf("BUG: start cannot exceed end; got %d vs %d", ec.Start, ec.End)
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}
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if ec.Step <= 0 {
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logger.Panicf("BUG: step must be greater than 0; got %d", ec.Step)
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}
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}
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func (ec *EvalConfig) mayCache() bool {
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if *disableCache {
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return false
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}
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if !ec.MayCache {
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return false
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}
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if ec.Start%ec.Step != 0 {
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return false
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}
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if ec.End%ec.Step != 0 {
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return false
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}
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return true
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}
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func (ec *EvalConfig) getSharedTimestamps() []int64 {
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ec.timestampsOnce.Do(ec.timestampsInit)
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return ec.timestamps
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}
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func (ec *EvalConfig) timestampsInit() {
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ec.timestamps = getTimestamps(ec.Start, ec.End, ec.Step)
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}
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func getTimestamps(start, end, step int64) []int64 {
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// Sanity checks.
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if step <= 0 {
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logger.Panicf("BUG: Step must be bigger than 0; got %d", step)
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}
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if start > end {
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logger.Panicf("BUG: Start cannot exceed End; got %d vs %d", start, end)
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}
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if err := ValidateMaxPointsPerTimeseries(start, end, step); err != nil {
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logger.Panicf("BUG: %s; this must be validated before the call to getTimestamps", err)
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}
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// Prepare timestamps.
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points := 1 + (end-start)/step
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timestamps := make([]int64, points)
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for i := range timestamps {
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timestamps[i] = start
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start += step
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}
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return timestamps
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}
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func evalExpr(ec *EvalConfig, e metricsql.Expr) ([]*timeseries, error) {
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if me, ok := e.(*metricsql.MetricExpr); ok {
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re := &metricsql.RollupExpr{
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Expr: me,
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}
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rv, err := evalRollupFunc(ec, "default_rollup", rollupDefault, e, re, nil)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, me.AppendString(nil), err)
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}
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return rv, nil
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}
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if re, ok := e.(*metricsql.RollupExpr); ok {
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rv, err := evalRollupFunc(ec, "default_rollup", rollupDefault, e, re, nil)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, re.AppendString(nil), err)
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}
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return rv, nil
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}
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if fe, ok := e.(*metricsql.FuncExpr); ok {
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nrf := getRollupFunc(fe.Name)
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if nrf == nil {
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args, err := evalExprs(ec, fe.Args)
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if err != nil {
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return nil, err
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}
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tf := getTransformFunc(fe.Name)
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if tf == nil {
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return nil, fmt.Errorf(`unknown func %q`, fe.Name)
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}
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tfa := &transformFuncArg{
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ec: ec,
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fe: fe,
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args: args,
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}
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rv, err := tf(tfa)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, fe.AppendString(nil), err)
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}
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return rv, nil
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}
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args, re, err := evalRollupFuncArgs(ec, fe)
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if err != nil {
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return nil, err
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}
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rf, err := nrf(args)
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if err != nil {
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return nil, err
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}
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rv, err := evalRollupFunc(ec, fe.Name, rf, e, re, nil)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, fe.AppendString(nil), err)
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}
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return rv, nil
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}
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if ae, ok := e.(*metricsql.AggrFuncExpr); ok {
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if callbacks := getIncrementalAggrFuncCallbacks(ae.Name); callbacks != nil {
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fe, nrf := tryGetArgRollupFuncWithMetricExpr(ae)
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if fe != nil {
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// There is an optimized path for calculating metricsql.AggrFuncExpr over rollupFunc over metricsql.MetricExpr.
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// The optimized path saves RAM for aggregates over big number of time series.
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args, re, err := evalRollupFuncArgs(ec, fe)
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if err != nil {
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return nil, err
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}
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rf, err := nrf(args)
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if err != nil {
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return nil, err
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}
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iafc := newIncrementalAggrFuncContext(ae, callbacks)
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return evalRollupFunc(ec, fe.Name, rf, e, re, iafc)
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}
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}
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args, err := evalExprs(ec, ae.Args)
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if err != nil {
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return nil, err
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}
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af := getAggrFunc(ae.Name)
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if af == nil {
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return nil, fmt.Errorf(`unknown func %q`, ae.Name)
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}
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afa := &aggrFuncArg{
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ae: ae,
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args: args,
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ec: ec,
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}
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rv, err := af(afa)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, ae.AppendString(nil), err)
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}
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return rv, nil
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}
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if be, ok := e.(*metricsql.BinaryOpExpr); ok {
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left, err := evalExpr(ec, be.Left)
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if err != nil {
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return nil, err
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}
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right, err := evalExpr(ec, be.Right)
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if err != nil {
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return nil, err
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}
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bf := getBinaryOpFunc(be.Op)
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if bf == nil {
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return nil, fmt.Errorf(`unknown binary op %q`, be.Op)
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}
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bfa := &binaryOpFuncArg{
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be: be,
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left: left,
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right: right,
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}
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rv, err := bf(bfa)
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if err != nil {
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return nil, fmt.Errorf(`cannot evaluate %q: %w`, be.AppendString(nil), err)
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}
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return rv, nil
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}
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if ne, ok := e.(*metricsql.NumberExpr); ok {
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rv := evalNumber(ec, ne.N)
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return rv, nil
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}
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if se, ok := e.(*metricsql.StringExpr); ok {
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rv := evalString(ec, se.S)
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return rv, nil
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}
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return nil, fmt.Errorf("unexpected expression %q", e.AppendString(nil))
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}
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func tryGetArgRollupFuncWithMetricExpr(ae *metricsql.AggrFuncExpr) (*metricsql.FuncExpr, newRollupFunc) {
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if len(ae.Args) != 1 {
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return nil, nil
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}
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e := ae.Args[0]
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// Make sure e contains one of the following:
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// - metricExpr
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// - metricExpr[d]
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// - rollupFunc(metricExpr)
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// - rollupFunc(metricExpr[d])
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if me, ok := e.(*metricsql.MetricExpr); ok {
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// e = metricExpr
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if me.IsEmpty() {
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return nil, nil
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}
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fe := &metricsql.FuncExpr{
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Name: "default_rollup",
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Args: []metricsql.Expr{me},
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}
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nrf := getRollupFunc(fe.Name)
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return fe, nrf
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}
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if re, ok := e.(*metricsql.RollupExpr); ok {
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if me, ok := re.Expr.(*metricsql.MetricExpr); !ok || me.IsEmpty() || re.ForSubquery() {
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return nil, nil
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}
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// e = metricExpr[d]
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fe := &metricsql.FuncExpr{
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Name: "default_rollup",
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Args: []metricsql.Expr{re},
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}
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nrf := getRollupFunc(fe.Name)
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return fe, nrf
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}
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fe, ok := e.(*metricsql.FuncExpr)
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if !ok {
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return nil, nil
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}
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nrf := getRollupFunc(fe.Name)
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if nrf == nil {
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return nil, nil
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}
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rollupArgIdx := getRollupArgIdx(fe.Name)
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if rollupArgIdx >= len(fe.Args) {
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// Incorrect number of args for rollup func.
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return nil, nil
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}
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arg := fe.Args[rollupArgIdx]
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if me, ok := arg.(*metricsql.MetricExpr); ok {
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if me.IsEmpty() {
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return nil, nil
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}
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// e = rollupFunc(metricExpr)
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return &metricsql.FuncExpr{
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Name: fe.Name,
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Args: []metricsql.Expr{me},
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}, nrf
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}
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if re, ok := arg.(*metricsql.RollupExpr); ok {
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if me, ok := re.Expr.(*metricsql.MetricExpr); !ok || me.IsEmpty() || re.ForSubquery() {
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return nil, nil
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}
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// e = rollupFunc(metricExpr[d])
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return fe, nrf
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}
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return nil, nil
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}
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func evalExprs(ec *EvalConfig, es []metricsql.Expr) ([][]*timeseries, error) {
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var rvs [][]*timeseries
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for _, e := range es {
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rv, err := evalExpr(ec, e)
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if err != nil {
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return nil, err
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}
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rvs = append(rvs, rv)
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}
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return rvs, nil
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}
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func evalRollupFuncArgs(ec *EvalConfig, fe *metricsql.FuncExpr) ([]interface{}, *metricsql.RollupExpr, error) {
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var re *metricsql.RollupExpr
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rollupArgIdx := getRollupArgIdx(fe.Name)
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if len(fe.Args) <= rollupArgIdx {
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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))
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}
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args := make([]interface{}, len(fe.Args))
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for i, arg := range fe.Args {
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if i == rollupArgIdx {
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re = getRollupExprArg(arg)
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args[i] = re
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continue
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}
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ts, err := evalExpr(ec, arg)
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if err != nil {
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return nil, nil, fmt.Errorf("cannot evaluate arg #%d for %q: %w", i+1, fe.AppendString(nil), err)
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}
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args[i] = ts
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}
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return args, re, nil
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}
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func getRollupExprArg(arg metricsql.Expr) *metricsql.RollupExpr {
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re, ok := arg.(*metricsql.RollupExpr)
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if !ok {
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// Wrap non-rollup arg into metricsql.RollupExpr.
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return &metricsql.RollupExpr{
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Expr: arg,
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}
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}
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if !re.ForSubquery() {
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// Return standard rollup if it doesn't contain subquery.
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return re
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}
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me, ok := re.Expr.(*metricsql.MetricExpr)
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if !ok {
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// arg contains subquery.
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return re
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}
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// Convert me[w:step] -> default_rollup(me)[w:step]
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reNew := *re
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reNew.Expr = &metricsql.FuncExpr{
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Name: "default_rollup",
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Args: []metricsql.Expr{
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&metricsql.RollupExpr{Expr: me},
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},
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}
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return &reNew
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}
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func evalRollupFunc(ec *EvalConfig, name string, rf rollupFunc, expr metricsql.Expr, re *metricsql.RollupExpr, iafc *incrementalAggrFuncContext) ([]*timeseries, error) {
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ecNew := ec
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var offset int64
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if len(re.Offset) > 0 {
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var err error
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offset, err = metricsql.DurationValue(re.Offset, ec.Step)
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if err != nil {
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return nil, err
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}
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ecNew = newEvalConfig(ecNew)
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ecNew.Start -= offset
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ecNew.End -= offset
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// There is no need in calling AdjustStartEnd() on ecNew if ecNew.MayCache is set to true,
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// since the time range alignment has been already performed by the caller,
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// so cache hit rate should be quite good.
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// See also https://github.com/VictoriaMetrics/VictoriaMetrics/issues/976
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}
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if name == "rollup_candlestick" {
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// Automatically apply `offset -step` to `rollup_candlestick` function
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// in order to obtain expected OHLC results.
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// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/309#issuecomment-582113462
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step := ecNew.Step
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ecNew = newEvalConfig(ecNew)
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ecNew.Start += step
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ecNew.End += step
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offset -= step
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}
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var rvs []*timeseries
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var err error
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if me, ok := re.Expr.(*metricsql.MetricExpr); ok {
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rvs, err = evalRollupFuncWithMetricExpr(ecNew, name, rf, expr, me, iafc, re.Window)
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} else {
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if iafc != nil {
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logger.Panicf("BUG: iafc must be nil for rollup %q over subquery %q", name, re.AppendString(nil))
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}
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rvs, err = evalRollupFuncWithSubquery(ecNew, name, rf, expr, re)
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}
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if err != nil {
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return nil, err
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}
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if offset != 0 && len(rvs) > 0 {
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// Make a copy of timestamps, since they may be used in other values.
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srcTimestamps := rvs[0].Timestamps
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dstTimestamps := append([]int64{}, srcTimestamps...)
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for i := range dstTimestamps {
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dstTimestamps[i] += offset
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}
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for _, ts := range rvs {
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ts.Timestamps = dstTimestamps
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}
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}
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return rvs, nil
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}
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|
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func evalRollupFuncWithSubquery(ec *EvalConfig, name string, rf rollupFunc, expr metricsql.Expr, re *metricsql.RollupExpr) ([]*timeseries, error) {
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// TODO: determine whether to use rollupResultCacheV here.
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var step int64
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if len(re.Step) > 0 {
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var err error
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step, err = metricsql.PositiveDurationValue(re.Step, ec.Step)
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if err != nil {
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return nil, err
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}
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} else {
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step = ec.Step
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}
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var window int64
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if len(re.Window) > 0 {
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var err error
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window, err = metricsql.PositiveDurationValue(re.Window, ec.Step)
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if err != nil {
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return nil, err
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}
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}
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|
|
ecSQ := newEvalConfig(ec)
|
|
ecSQ.Start -= window + maxSilenceInterval + step
|
|
ecSQ.End += step
|
|
ecSQ.Step = step
|
|
if err := ValidateMaxPointsPerTimeseries(ecSQ.Start, ecSQ.End, ecSQ.Step); err != nil {
|
|
return nil, err
|
|
}
|
|
// unconditionally align start and end args to step for subquery as Prometheus does.
|
|
ecSQ.Start, ecSQ.End = alignStartEnd(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 := cgroup.AvailableCPUs()
|
|
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.NewSearchQuery(minTimestamp, ec.End, [][]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 = cgroup.AvailableCPUs()
|
|
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) error {
|
|
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
|
|
}
|
|
return nil
|
|
})
|
|
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) error {
|
|
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()
|
|
}
|
|
return nil
|
|
})
|
|
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) / 1e3
|
|
}
|
|
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
|
|
}
|