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lib/streamaggr: added rate and rate_avg output (#6243)
Added `rate` and `rate_avg` output Resource usage is the same as for increase output, tested on a benchmark --------- Signed-off-by: hagen1778 <roman@victoriametrics.com> Co-authored-by: hagen1778 <roman@victoriametrics.com>
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6 changed files with 205 additions and 17 deletions
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@ -43,6 +43,7 @@ See also [LTS releases](https://docs.victoriametrics.com/lts-releases/).
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): add service discovery support for [Vultr](https://www.vultr.com/). See [these docs](https://docs.victoriametrics.com/sd_configs/#vultr_sd_configs) and [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6041).
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): allow configuring `-remoteWrite.disableOnDiskQueue` and `-remoteWrite.dropSamplesOnOverload` cmd-line flags per each `-remoteWrite.url`. See this [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6065). Thanks to @rbizos for implementaion!
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* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): add labels `path` and `url` to metrics `vmagent_remotewrite_push_failures_total` and `vmagent_remotewrite_samples_dropped_total`. Now number of failed pushes and dropped samples can be tracked per `-remoteWrite.url`.
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* FEATURE: [stream aggregation](https://docs.victoriametrics.com/stream-aggregation/): add [rate_sum](https://docs.victoriametrics.com/stream-aggregation/#rate_sum) and [rate_avg](https://docs.victoriametrics.com/stream-aggregation/#rate_avg) aggregation outputs.
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* BUGFIX: [vmui](https://docs.victoriametrics.com/#vmui): fix bug that prevents the first query trace from expanding on click event. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6186). The issue was introduced in [v1.100.0](https://docs.victoriametrics.com/changelog/#v11000) release.
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent/): prevent potential panic during [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) if more than one `--remoteWrite.streamAggr.dedupInterval` is configured. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6205).
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@ -513,6 +513,8 @@ Below are aggregation functions that can be put in the `outputs` list at [stream
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* [count_series](#count_series)
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* [increase](#increase)
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* [increase_prometheus](#increase_prometheus)
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* [rate_sum](#rate_sum)
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* [rate_avg](#rate_avg)
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* [histogram_bucket](#histogram_bucket)
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* [last](#last)
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* [max](#max)
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@ -577,7 +579,7 @@ The results of `increase` is equal to the following [MetricsQL](https://docs.vic
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sum(increase_pure(some_counter[interval]))
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```
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`increase` assumes that all the counters start from 0. For example, if the fist seen sample for new [time series](https://docs.victoriametrics.com/keyconcepts/#time-series)
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`increase` assumes that all the counters start from 0. For example, if the first seen sample for new [time series](https://docs.victoriametrics.com/keyconcepts/#time-series)
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is `10`, then `increase` assumes that the time series has been increased by `10`. If you need ignoring the first sample for new time series,
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then take a look at [increase_prometheus](#increase_prometheus).
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@ -585,21 +587,37 @@ For example, see below time series produced by config with aggregation interval
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<img alt="increase aggregation" src="stream-aggregation-check-increase.webp">
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`increase` can be used as an alternative for [rate](https://docs.victoriametrics.com/metricsql/#rate) function.
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For example, if `increase` is calculated for `some_counter` with `interval: 5m`, then `rate` can be calculated
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by dividing the resulting aggregation by `5m`:
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```metricsql
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some_counter:5m_increase / 5m
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```
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This is similar to `rate(some_counter[5m])`.
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Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/)
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or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_interval](#staleness) option.
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See also [increase_prometheus](#increase_prometheus) and [total](#total).
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### rate_sum
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`rate_sum` returns the sum of average per-second change of input [time series](https://docs.victoriametrics.com/keyconcepts/#time-series) over the given `interval`.
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`rate_sum` makes sense only for aggregating [counters](https://docs.victoriametrics.com/keyconcepts/#counter).
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The results of `rate_sum` are equal to the following [MetricsQL](https://docs.victoriametrics.com/metricsql/) query:
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```metricsql
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sum(rate(some_counter[interval]))
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```
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See also [rate_avg](#rate_avg) and [total](#total) outputs.
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### rate_avg
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`rate_avg` returns the average of average per-second of input [time series](https://docs.victoriametrics.com/keyconcepts/#time-series) over the given `interval`.
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`rate_avg` makes sense only for aggregating [counters](https://docs.victoriametrics.com/keyconcepts/#counter).
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The results of `rate_avg` are equal to the following [MetricsQL](https://docs.victoriametrics.com/metricsql/) query:
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```metricsql
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avg(rate(some_counter[interval]))
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```
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See also [rate_sum](#rate_avg) and [total](#total) outputs.
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### increase_prometheus
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`increase_prometheus` returns the increase of input [time series](https://docs.victoriametrics.com/keyconcepts/#time-series) over the given `interval`.
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@ -741,7 +759,7 @@ The results of `total` is roughly equal to the the following [MetricsQL](https:/
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sum(running_sum(increase_pure(some_counter)))
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```
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`total` assumes that all the counters start from 0. For example, if the fist seen sample for new [time series](https://docs.victoriametrics.com/keyconcepts/#time-series)
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`total` assumes that all the counters start from 0. For example, if the first seen sample for new [time series](https://docs.victoriametrics.com/keyconcepts/#time-series)
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is `10`, then `total` assumes that the time series has been increased by `10`. If you need ignoring the first sample for new time series,
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then take a look at [total_prometheus](#total_prometheus).
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147
lib/streamaggr/rate.go
Normal file
147
lib/streamaggr/rate.go
Normal file
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@ -0,0 +1,147 @@
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package streamaggr
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import (
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"sync"
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"time"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
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)
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// rateAggrState calculates output=rate, e.g. the counter per-second change.
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type rateAggrState struct {
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m sync.Map
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suffix string
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// Time series state is dropped if no new samples are received during stalenessSecs.
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stalenessSecs uint64
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}
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type rateStateValue struct {
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mu sync.Mutex
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lastValues map[string]*rateLastValueState
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deleteDeadline uint64
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deleted bool
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}
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type rateLastValueState struct {
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value float64
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timestamp int64
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deleteDeadline uint64
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// total stores cumulative difference between registered values
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// in the aggregation interval
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total float64
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// prevTimestamp stores timestamp of the last registered value
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// in the previous aggregation interval
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prevTimestamp int64
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}
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func newRateAggrState(stalenessInterval time.Duration, suffix string) *rateAggrState {
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stalenessSecs := roundDurationToSecs(stalenessInterval)
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return &rateAggrState{
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suffix: suffix,
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stalenessSecs: stalenessSecs,
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}
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}
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func (as *rateAggrState) pushSamples(samples []pushSample) {
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currentTime := fasttime.UnixTimestamp()
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deleteDeadline := currentTime + as.stalenessSecs
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for i := range samples {
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s := &samples[i]
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inputKey, outputKey := getInputOutputKey(s.key)
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again:
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v, ok := as.m.Load(outputKey)
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if !ok {
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// The entry is missing in the map. Try creating it.
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v = &rateStateValue{
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lastValues: make(map[string]*rateLastValueState),
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}
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vNew, loaded := as.m.LoadOrStore(outputKey, v)
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if loaded {
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// Use the entry created by a concurrent goroutine.
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v = vNew
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}
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}
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sv := v.(*rateStateValue)
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sv.mu.Lock()
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deleted := sv.deleted
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if !deleted {
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lv, ok := sv.lastValues[inputKey]
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if ok {
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if s.timestamp < lv.timestamp {
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// Skip out of order sample
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sv.mu.Unlock()
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continue
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}
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if lv.prevTimestamp == 0 {
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lv.prevTimestamp = lv.timestamp
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}
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if s.value >= lv.value {
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lv.total += s.value - lv.value
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} else {
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// counter reset
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lv.total += s.value
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}
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} else {
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lv = &rateLastValueState{}
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}
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lv.value = s.value
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lv.timestamp = s.timestamp
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lv.deleteDeadline = deleteDeadline
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sv.lastValues[inputKey] = lv
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sv.deleteDeadline = deleteDeadline
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}
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sv.mu.Unlock()
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if deleted {
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// The entry has been deleted by the concurrent call to flushState
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// Try obtaining and updating the entry again.
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goto again
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}
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}
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}
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func (as *rateAggrState) flushState(ctx *flushCtx, resetState bool) {
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currentTime := fasttime.UnixTimestamp()
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currentTimeMsec := int64(currentTime) * 1000
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m := &as.m
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m.Range(func(k, v interface{}) bool {
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sv := v.(*rateStateValue)
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sv.mu.Lock()
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// check for stale entries
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deleted := currentTime > sv.deleteDeadline
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if deleted {
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// Mark the current entry as deleted
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sv.deleted = deleted
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sv.mu.Unlock()
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m.Delete(k)
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return true
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}
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// Delete outdated entries in sv.lastValues
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var rate float64
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m := sv.lastValues
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for k1, v1 := range m {
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if currentTime > v1.deleteDeadline {
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delete(m, k1)
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} else if v1.prevTimestamp > 0 {
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rate += v1.total * 1000 / float64(v1.timestamp-v1.prevTimestamp)
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v1.prevTimestamp = v1.timestamp
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v1.total = 0
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}
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}
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if as.suffix == "rate_avg" {
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// note: capture m length after deleted items were removed
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rate /= float64(len(m))
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}
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sv.mu.Unlock()
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key := k.(string)
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ctx.appendSeries(key, as.suffix, currentTimeMsec, rate)
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return true
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})
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}
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@ -164,6 +164,8 @@ type Config struct {
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//
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// The following names are allowed:
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//
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// - rate_sum - calculates sum of rate for input counters
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// - rate_avg - calculates average of rate for input counters
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// - total - aggregates input counters
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// - total_prometheus - aggregates input counters, ignoring the first sample in new time series
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// - increase - calculates the increase over input series
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aggrStates[i] = newTotalAggrState(stalenessInterval, true, true)
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case "increase_prometheus":
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aggrStates[i] = newTotalAggrState(stalenessInterval, true, false)
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case "rate_sum":
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aggrStates[i] = newRateAggrState(stalenessInterval, "rate_sum")
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case "rate_avg":
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aggrStates[i] = newRateAggrState(stalenessInterval, "rate_avg")
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case "count_series":
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aggrStates[i] = newCountSeriesAggrState()
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case "count_samples":
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@ -828,7 +828,7 @@ cpu_usage:1m_without_cpu_quantiles{quantile="1"} 90
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`, `
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foo{abc="123"} 4
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bar 5
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foo{abc="123"} 8.5
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foo{abc="123"} 8.5 10
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foo{abc="456",de="fg"} 8
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`, `bar-1m-without-abc-count-samples{new_label="must_keep_metric_name"} 1
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bar-1m-without-abc-count-series{new_label="must_keep_metric_name"} 1
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foo-1m-without-abc-count-samples{new_label="must_keep_metric_name"} 2
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foo-1m-without-abc-count-series{new_label="must_keep_metric_name"} 1
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foo-1m-without-abc-sum-samples{new_label="must_keep_metric_name"} 12.5
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`, "1111")
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// test rate_sum and rate_avg
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f(`
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- interval: 1m
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by: [cde]
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outputs: [rate_sum, rate_avg]
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`, `
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foo{abc="123", cde="1"} 4
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foo{abc="123", cde="1"} 8.5 10
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foo{abc="456", cde="1"} 8
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foo{abc="456", cde="1"} 10 10
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`, `foo:1m_by_cde_rate_avg{cde="1"} 0.325
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foo:1m_by_cde_rate_sum{cde="1"} 0.65
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`, "1111")
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// keep_metric_names
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}
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rows.UnmarshalWithErrLogger(s, errLogger)
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var tss []prompbmarshal.TimeSeries
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now := time.Now().UnixMilli()
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samples := make([]prompbmarshal.Sample, 0, len(rows.Rows))
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for _, row := range rows.Rows {
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labels := make([]prompbmarshal.Label, 0, len(row.Tags)+1)
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}
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samples = append(samples, prompbmarshal.Sample{
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Value: row.Value,
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Timestamp: row.Timestamp,
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Timestamp: now + row.Timestamp,
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})
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ts := prompbmarshal.TimeSeries{
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Labels: labels,
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@ -34,13 +34,13 @@ type totalAggrState struct {
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type totalStateValue struct {
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mu sync.Mutex
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lastValues map[string]lastValueState
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lastValues map[string]totalLastValueState
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total float64
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deleteDeadline uint64
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deleted bool
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}
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type lastValueState struct {
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type totalLastValueState struct {
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value float64
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timestamp int64
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deleteDeadline uint64
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if !ok {
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// The entry is missing in the map. Try creating it.
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v = &totalStateValue{
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lastValues: make(map[string]lastValueState),
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lastValues: make(map[string]totalLastValueState),
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}
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vNew, loaded := as.m.LoadOrStore(outputKey, v)
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if loaded {
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sv.mu.Unlock()
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continue
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}
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if s.value >= lv.value {
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sv.total += s.value - lv.value
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} else {
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