mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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210 lines
6.5 KiB
Go
210 lines
6.5 KiB
Go
package graphite
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import (
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"flag"
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"fmt"
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"time"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/graphiteql"
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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/cgroup"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/timerpool"
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)
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var maxGraphiteSeries = flag.Int("search.maxGraphiteSeries", 300e3, "The maximum number of time series, which can be scanned during queries to Graphite Render API. "+
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"See https://docs.victoriametrics.com/#graphite-render-api-usage")
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type evalConfig struct {
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startTime int64
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endTime int64
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storageStep int64
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deadline searchutils.Deadline
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currentTime time.Time
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// xFilesFactor is used for determining when consolidateFunc must be applied.
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//
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// 0 means that consolidateFunc should be applied if at least a single non-NaN data point exists on the given step.
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// 1 means that consolidateFunc should be applied if all the data points are non-NaN on the given step.
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xFilesFactor float64
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// Enforced tag filters
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etfs [][]storage.TagFilter
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// originalQuery contains the original query - used for debug logging.
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originalQuery string
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}
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func (ec *evalConfig) pointsLen(step int64) int {
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return int((ec.endTime - ec.startTime) / step)
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}
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func (ec *evalConfig) newTimestamps(step int64) []int64 {
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pointsLen := ec.pointsLen(step)
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timestamps := make([]int64, pointsLen)
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ts := ec.startTime
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for i := 0; i < pointsLen; i++ {
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timestamps[i] = ts
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ts += step
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}
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return timestamps
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}
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type series struct {
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Name string
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Tags map[string]string
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Timestamps []int64
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Values []float64
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// holds current path expression like graphite does.
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pathExpression string
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expr graphiteql.Expr
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// consolidateFunc is applied to raw samples in order to generate data points algined to the given step.
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// see series.consolidate() function for details.
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consolidateFunc aggrFunc
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// xFilesFactor is used for determining when consolidateFunc must be applied.
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//
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// 0 means that consolidateFunc should be applied if at least a single non-NaN data point exists on the given step.
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// 1 means that consolidateFunc should be applied if all the data points are non-NaN on the given step.
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xFilesFactor float64
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step int64
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}
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func (s *series) consolidate(ec *evalConfig, step int64) {
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aggrFunc := s.consolidateFunc
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if aggrFunc == nil {
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aggrFunc = aggrAvg
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}
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xFilesFactor := s.xFilesFactor
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if s.xFilesFactor <= 0 {
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xFilesFactor = ec.xFilesFactor
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}
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s.summarize(aggrFunc, ec.startTime, ec.endTime, step, xFilesFactor)
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}
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func (s *series) summarize(aggrFunc aggrFunc, startTime, endTime, step int64, xFilesFactor float64) {
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pointsLen := int((endTime - startTime) / step)
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timestamps := s.Timestamps
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values := s.Values
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dstTimestamps := make([]int64, 0, pointsLen)
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dstValues := make([]float64, 0, pointsLen)
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ts := startTime
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i := 0
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for len(dstTimestamps) < pointsLen {
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tsEnd := ts + step
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j := i
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for j < len(timestamps) && timestamps[j] < tsEnd {
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j++
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}
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if i == j && i > 0 && ts-timestamps[i-1] <= 2000 {
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// The current [ts ... tsEnd) interval has no samples,
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// but the last sample on the previous interval [ts - step ... ts)
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// is closer than 2 seconds to the current interval.
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// Let's consider that this sample belongs to the current interval,
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// since such discrepancy could appear because of small jitter in samples' ingestion.
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i--
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}
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v := aggrFunc.apply(xFilesFactor, values[i:j])
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dstTimestamps = append(dstTimestamps, ts)
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dstValues = append(dstValues, v)
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ts = tsEnd
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i = j
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}
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// Do not reuse s.Timestamps and s.Values, since they can be too big
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s.Timestamps = dstTimestamps
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s.Values = dstValues
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s.step = step
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}
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func execExpr(ec *evalConfig, query string) (nextSeriesFunc, error) {
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expr, err := graphiteql.Parse(query)
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if err != nil {
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return nil, fmt.Errorf("cannot parse %q: %w", query, err)
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}
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return evalExpr(ec, expr)
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}
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func evalExpr(ec *evalConfig, expr graphiteql.Expr) (nextSeriesFunc, error) {
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switch t := expr.(type) {
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case *graphiteql.MetricExpr:
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return evalMetricExpr(ec, t)
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case *graphiteql.FuncExpr:
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return evalFuncExpr(ec, t)
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default:
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return nil, fmt.Errorf("unexpected expression type %T; want graphiteql.MetricExpr or graphiteql.FuncExpr; expr: %q", t, t.AppendString(nil))
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}
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}
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func evalMetricExpr(ec *evalConfig, me *graphiteql.MetricExpr) (nextSeriesFunc, error) {
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tfs := []storage.TagFilter{{
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Key: []byte("__graphite__"),
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Value: []byte(me.Query),
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}}
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tfss := joinTagFilterss(tfs, ec.etfs)
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sq := storage.NewSearchQuery(ec.startTime, ec.endTime, tfss, *maxGraphiteSeries)
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return newNextSeriesForSearchQuery(ec, sq, me)
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}
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func newNextSeriesForSearchQuery(ec *evalConfig, sq *storage.SearchQuery, expr graphiteql.Expr) (nextSeriesFunc, error) {
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rss, err := netstorage.ProcessSearchQuery(nil, sq, ec.deadline)
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if err != nil {
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return nil, fmt.Errorf("cannot fetch data for %q: %w", sq, err)
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}
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seriesCh := make(chan *series, cgroup.AvailableCPUs())
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errCh := make(chan error, 1)
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go func() {
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err := rss.RunParallel(nil, func(rs *netstorage.Result, workerID uint) error {
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nameWithTags := getCanonicalPath(&rs.MetricName)
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tags := unmarshalTags(nameWithTags)
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s := &series{
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Name: tags["name"],
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Tags: tags,
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Timestamps: append([]int64{}, rs.Timestamps...),
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Values: append([]float64{}, rs.Values...),
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expr: expr,
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pathExpression: string(expr.AppendString(nil)),
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}
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s.summarize(aggrAvg, ec.startTime, ec.endTime, ec.storageStep, 0)
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t := timerpool.Get(30 * time.Second)
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select {
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case seriesCh <- s:
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case <-t.C:
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logger.Errorf("resource leak when processing the %s (full query: %s); please report this error to VictoriaMetrics developers",
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expr.AppendString(nil), ec.originalQuery)
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}
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timerpool.Put(t)
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return nil
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})
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close(seriesCh)
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errCh <- err
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}()
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f := func() (*series, error) {
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s := <-seriesCh
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if s != nil {
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return s, nil
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}
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err := <-errCh
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return nil, err
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}
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return f, nil
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}
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func evalFuncExpr(ec *evalConfig, fe *graphiteql.FuncExpr) (nextSeriesFunc, error) {
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// Do not lowercase the fe.FuncName, since Graphite function names are case-sensitive.
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tf := transformFuncs[fe.FuncName]
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if tf == nil {
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return nil, fmt.Errorf("unknown function %q", fe.FuncName)
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}
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nextSeries, err := tf(ec, fe)
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if err != nil {
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return nil, fmt.Errorf("cannot evaluate %s: %w", fe.AppendString(nil), err)
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}
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return nextSeries, nil
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}
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