mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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Merge branch 'public-single-node' into pmm-6401-read-prometheus-data-files
This commit is contained in:
Aliaksandr Valialkin
commit
8db1fd2f78
6 changed files with 97 additions and 45 deletions
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@ -1357,6 +1357,7 @@ By default VictoriaMetrics is tuned for an optimal resource usage under typical
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- `-search.maxSamplesPerQuery` limits the number of raw samples a single query can process. This allows limiting CPU usage for heavy queries.
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- `-search.maxPointsPerTimeseries` limits the number of calculated points, which can be returned per each matching time series from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
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- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated per each matching time series during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
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- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) in a single query.
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- `-search.maxSeries` limits the number of time series, which may be returned from [/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers). This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxSeries` to quite low value in order limit CPU and memory usage.
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- `-search.maxTagKeys` limits the number of items, which may be returned from [/api/v1/labels](https://prometheus.io/docs/prometheus/latest/querying/api/#getting-label-names). This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagKeys` to quite low value in order to limit CPU and memory usage.
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- `-search.maxTagValues` limits the number of items, which may be returned from [/api/v1/label/.../values](https://prometheus.io/docs/prometheus/latest/querying/api/#querying-label-values). This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagValues` to quite low value in order to limit CPU and memory usage.
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@ -2438,6 +2439,8 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
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The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage (default 30000000)
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-search.maxSeries int
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The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage (default 30000)
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-search.maxSeriesPerAggrFunc int
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The maximum number of time series an aggregate MetricsQL function can generate (default 1000000)
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-search.maxStalenessInterval duration
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The maximum interval for staleness calculations. By default it is automatically calculated from the median interval between samples. This flag could be useful for tuning Prometheus data model closer to Influx-style data model. See https://prometheus.io/docs/prometheus/latest/querying/basics/#staleness for details. See also '-search.setLookbackToStep' flag
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-search.maxStatusRequestDuration duration
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@ -1,6 +1,7 @@
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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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"sort"
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@ -15,6 +16,8 @@ import (
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"github.com/cespare/xxhash/v2"
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)
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var maxSeriesPerAggrFunc = flag.Int("search.maxSeriesPerAggrFunc", 1e6, "The maximum number of time series an aggregate MetricsQL function can generate")
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var aggrFuncs = map[string]aggrFunc{
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"any": aggrFuncAny,
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"avg": newAggrFunc(aggrFuncAvg),
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@ -106,6 +109,16 @@ func removeGroupTags(metricName *storage.MetricName, modifier *metricsql.Modifie
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func aggrFuncExt(afe func(tss []*timeseries, modifier *metricsql.ModifierExpr) []*timeseries, argOrig []*timeseries,
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modifier *metricsql.ModifierExpr, maxSeries int, keepOriginal bool) ([]*timeseries, error) {
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m := aggrPrepareSeries(argOrig, modifier, maxSeries, keepOriginal)
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rvs := make([]*timeseries, 0, len(m))
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for _, tss := range m {
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rv := afe(tss, modifier)
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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 aggrPrepareSeries(argOrig []*timeseries, modifier *metricsql.ModifierExpr, maxSeries int, keepOriginal bool) map[string][]*timeseries {
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// Remove empty time series, e.g. series with all NaN samples,
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// since such series are ignored by aggregate functions.
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argOrig = removeEmptySeries(argOrig)
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@ -130,21 +143,7 @@ func aggrFuncExt(afe func(tss []*timeseries, modifier *metricsql.ModifierExpr) [
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m[k] = tss
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}
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bbPool.Put(bb)
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srcTssCount := 0
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dstTssCount := 0
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rvs := make([]*timeseries, 0, len(m))
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for _, tss := range m {
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rv := afe(tss, modifier)
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rvs = append(rvs, rv...)
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srcTssCount += len(tss)
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dstTssCount += len(rv)
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if dstTssCount > 2000 && dstTssCount > 16*srcTssCount {
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// This looks like count_values explosion.
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return nil, fmt.Errorf(`too many timeseries after aggragation; got %d; want less than %d`, dstTssCount, 16*srcTssCount)
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}
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}
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return rvs, nil
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return m
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}
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func aggrFuncAny(afa *aggrFuncArg) ([]*timeseries, error) {
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@ -588,46 +587,56 @@ func aggrFuncCountValues(afa *aggrFuncArg) ([]*timeseries, error) {
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// Do nothing
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}
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afe := func(tss []*timeseries, modififer *metricsql.ModifierExpr) []*timeseries {
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m := make(map[float64]bool)
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afe := func(tss []*timeseries, modififer *metricsql.ModifierExpr) ([]*timeseries, error) {
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m := make(map[float64]*timeseries)
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for _, ts := range tss {
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for _, v := range ts.Values {
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for i, v := range ts.Values {
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if math.IsNaN(v) {
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continue
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}
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m[v] = true
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}
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}
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values := make([]float64, 0, len(m))
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for v := range m {
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values = append(values, v)
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}
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sort.Float64s(values)
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var rvs []*timeseries
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for _, v := range values {
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var dst timeseries
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dst.CopyFromShallowTimestamps(tss[0])
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dst.MetricName.RemoveTag(dstLabel)
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dst.MetricName.AddTag(dstLabel, strconv.FormatFloat(v, 'f', -1, 64))
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for i := range dst.Values {
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count := 0
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for _, ts := range tss {
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if ts.Values[i] == v {
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count++
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dst := m[v]
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if dst == nil {
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if len(m) >= *maxSeriesPerAggrFunc {
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return nil, fmt.Errorf("more than -search.maxSeriesPerAggrFunc=%d are generated by count_values()", *maxSeriesPerAggrFunc)
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}
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dst = ×eries{}
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dst.CopyFromShallowTimestamps(tss[0])
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dst.MetricName.RemoveTag(dstLabel)
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dst.MetricName.AddTag(dstLabel, strconv.FormatFloat(v, 'f', -1, 64))
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values := dst.Values
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for j := range values {
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values[j] = nan
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}
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m[v] = dst
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}
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n := float64(count)
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if n == 0 {
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n = nan
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values := dst.Values
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if math.IsNaN(values[i]) {
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values[i] = 1
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} else {
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values[i]++
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}
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dst.Values[i] = n
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}
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rvs = append(rvs, &dst)
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}
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return rvs
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rvs := make([]*timeseries, 0, len(m))
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for _, ts := range m {
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rvs = append(rvs, ts)
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}
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return rvs, nil
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}
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return aggrFuncExt(afe, args[1], &afa.ae.Modifier, afa.ae.Limit, false)
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m := aggrPrepareSeries(args[1], &afa.ae.Modifier, afa.ae.Limit, false)
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rvs := make([]*timeseries, 0, len(m))
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for _, tss := range m {
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rv, err := afe(tss, modifier)
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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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if len(rvs) > *maxSeriesPerAggrFunc {
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return nil, fmt.Errorf("more than -search.maxSeriesPerAggrFunc=%d are generated by count_values()", *maxSeriesPerAggrFunc)
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}
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}
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return rvs, nil
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}
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func newAggrFuncTopK(isReverse bool) aggrFunc {
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@ -35,6 +35,7 @@ The following tip changes can be tested by building VictoriaMetrics components f
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* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add `range_trim_outliers(k, q)` function for dropping outliers located farther than `k*range_mad(q)` from the `range_median(q)`. This should help removing outliers during query time at [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3759).
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* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add `range_trim_zscore(z, q)` function for dropping outliers located farther than `z*range_stddev(q)` from `range_avg(q)`. This should help removing outliers during query time at [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3759).
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* FEATURE: [vmui](https://docs.victoriametrics.com/#vmui): show `median` instead of `avg` in graph tooltip and line legend, since `median` is more tolerant against spikes. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3706).
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* FEATURE: add `-search.maxSeriesPerAggrFunc` command-line flag, which can be used for limiting the number of time series [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) can return in a single query. This flag can be useful for preventing OOMs when [count_values](https://docs.victoriametrics.com/MetricsQL.html#count_values) function is improperly used.
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* FEATURE: [vmui](https://docs.victoriametrics.com/#vmui): small UX improvements for mobile view. See [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3707) and [this pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3848).
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* FEATURE: add `-search.logQueryMemoryUsage` command-line flag for logging queries, which need more memory than specified by this command-line flag. See [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3553). Thanks to @michal-kralik for the idea and the intial implementation.
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@ -48,6 +49,24 @@ The following tip changes can be tested by building VictoriaMetrics components f
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* BUGFIX: properly parse timestamps in milliseconds when [ingesting data via OpenTSDB telnet put protocol](https://docs.victoriametrics.com/#sending-data-via-telnet-put-protocol). Previously timestamps in milliseconds were mistakenly multiplied by 1000. Thanks to @Droxenator for the [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3810).
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): do not add extrapolated points outside the real points when using [interpolate()](https://docs.victoriametrics.com/MetricsQL.html#interpolate) function. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3816).
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## [v1.87.2](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.87.2)
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Released at 2023-02-24
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||||
**v1.87.x is a line of LTS releases (e.g. long-time support). It contains important up-to-date bugfixes.
|
||||
The v1.87.x line will be supported for at least 12 months since [v1.87.0](https://docs.victoriametrics.com/CHANGELOG.html#v1870) release**
|
||||
|
||||
* SECURITY: upgrade base docker image (alpine) from 3.17.1 to 3.17.2. See [alpine 3.17.2 release notes](https://alpinelinux.org/posts/Alpine-3.17.2-released.html).
|
||||
* SECURITY: upgrade Go builder from Go1.20.0 to Go1.20.1. See [the list of issues addressed in Go1.20.1](https://github.com/golang/go/issues?q=milestone%3AGo1.20.1+label%3ACherryPickApproved).
|
||||
|
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent.html): immediately cancel in-flight scrape requests during configuration reload when [stream parsing mode](https://docs.victoriametrics.com/vmagent.html#stream-parsing-mode) is disabled. Previously `vmagent` could wait for long time until all the in-flight requests are completed before reloading the configuration. This could significantly slow down configuration reload. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3747).
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent.html): do not wait for 2 seconds after the first unsuccessful attempt to scrape the target before performing the next attempt. This should improve scrape speed when the target closes [http keep-alive connection](https://en.wikipedia.org/wiki/HTTP_persistent_connection) between scrapes. See [this](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3293) and [this](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3747) issues.
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent.html): fix [Azure service discovery](https://docs.victoriametrics.com/sd_configs.html#azure_sd_configs) inside [Azure Container App](https://learn.microsoft.com/en-us/azure/container-apps/overview). See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3830). Thanks to @MattiasAng for the fix!
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* BUGFIX: do not put auxiliary directories scheduled for removal into snapshots. This should prevent from `cannot create hard links from ...must-remove...` errors when making snapshots / backups. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3858).
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* BUGFIX: prevent from possible data ingestion slowdown and query performance slowdown during [background merges of big parts](https://docs.victoriametrics.com/#storage) on systems with small number of CPU cores (1 or 2 CPU cores). The issue has been introduced in [v1.85.0](https://docs.victoriametrics.com/CHANGELOG.html#v1850) when implementing [this feature](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3337). See also [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3790).
|
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* BUGFIX: properly parse timestamps in milliseconds when [ingesting data via OpenTSDB telnet put protocol](https://docs.victoriametrics.com/#sending-data-via-telnet-put-protocol). Previously timestamps in milliseconds were mistakenly multiplied by 1000. Thanks to @Droxenator for the [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3810).
|
||||
* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): do not add extrapolated points outside the real points when using [interpolate()](https://docs.victoriametrics.com/MetricsQL.html#interpolate) function. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3816).
|
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|
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## [v1.87.1](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.87.1)
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Released at 2023-02-09
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@ -553,6 +572,18 @@ Released at 2022-08-08
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* BUGFIX: [vmui](https://docs.victoriametrics.com/#vmui): properly show date picker at `Table` tab. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2874).
|
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* BUGFIX: properly generate http redirects if `-http.pathPrefix` command-line flag is set. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2918).
|
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## [v1.79.9](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.79.9)
|
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|
||||
Released at 2023-02-24
|
||||
|
||||
**v1.79.x is a line of LTS releases (e.g. long-time support). It contains important up-to-date bugfixes.
|
||||
The v1.79.x line will be supported for at least 12 months since [v1.79.0](https://docs.victoriametrics.com/CHANGELOG.html#v1790) release**
|
||||
|
||||
* SECURITY: upgrade base docker image (alpine) from 3.17.1 to 3.17.2. See [alpine 3.17.2 release notes](https://alpinelinux.org/posts/Alpine-3.17.2-released.html).
|
||||
* SECURITY: upgrade Go builder from Go1.20.0 to Go1.20.1. See [the list of issues addressed in Go1.20.1](https://github.com/golang/go/issues?q=milestone%3AGo1.20.1+label%3ACherryPickApproved).
|
||||
|
||||
* BUGFIX: properly parse timestamps in milliseconds when [ingesting data via OpenTSDB telnet put protocol](https://docs.victoriametrics.com/#sending-data-via-telnet-put-protocol). Previously timestamps in milliseconds were mistakenly multiplied by 1000. Thanks to @Droxenator for the [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3810).
|
||||
|
||||
## [v1.79.8](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.79.8)
|
||||
|
||||
Released at 2023-02-03
|
||||
|
|
|
|||
|
|
@ -584,6 +584,7 @@ Some workloads may need fine-grained resource usage limits. In these cases the f
|
|||
matching time series from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated
|
||||
per each matching time series during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
|
||||
- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) in a single query.
|
||||
- `-search.maxSeries` at `vmselect` limits the number of time series, which may be returned from
|
||||
[/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers).
|
||||
This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values.
|
||||
|
|
@ -1161,6 +1162,8 @@ Below is the output for `/path/to/vmselect -help`:
|
|||
The maximum number of raw samples a single query can scan per each time series. See also -search.maxSamplesPerQuery (default 30000000)
|
||||
-search.maxSeries int
|
||||
The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage (default 30000)
|
||||
-search.maxSeriesPerAggrFunc int
|
||||
The maximum number of time series an aggregate MetricsQL function can generate (default 1000000)
|
||||
-search.maxStalenessInterval duration
|
||||
The maximum interval for staleness calculations. By default it is automatically calculated from the median interval between samples. This flag could be useful for tuning Prometheus data model closer to Influx-style data model. See https://prometheus.io/docs/prometheus/latest/querying/basics/#staleness for details. See also '-search.setLookbackToStep' flag
|
||||
-search.maxStatusRequestDuration duration
|
||||
|
|
|
|||
|
|
@ -1358,6 +1358,7 @@ By default VictoriaMetrics is tuned for an optimal resource usage under typical
|
|||
- `-search.maxSamplesPerQuery` limits the number of raw samples a single query can process. This allows limiting CPU usage for heavy queries.
|
||||
- `-search.maxPointsPerTimeseries` limits the number of calculated points, which can be returned per each matching time series from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated per each matching time series during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
|
||||
- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) in a single query.
|
||||
- `-search.maxSeries` limits the number of time series, which may be returned from [/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers). This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxSeries` to quite low value in order limit CPU and memory usage.
|
||||
- `-search.maxTagKeys` limits the number of items, which may be returned from [/api/v1/labels](https://prometheus.io/docs/prometheus/latest/querying/api/#getting-label-names). This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagKeys` to quite low value in order to limit CPU and memory usage.
|
||||
- `-search.maxTagValues` limits the number of items, which may be returned from [/api/v1/label/.../values](https://prometheus.io/docs/prometheus/latest/querying/api/#querying-label-values). This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagValues` to quite low value in order to limit CPU and memory usage.
|
||||
|
|
@ -2439,6 +2440,8 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
|
|||
The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage (default 30000000)
|
||||
-search.maxSeries int
|
||||
The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage (default 30000)
|
||||
-search.maxSeriesPerAggrFunc int
|
||||
The maximum number of time series an aggregate MetricsQL function can generate (default 1000000)
|
||||
-search.maxStalenessInterval duration
|
||||
The maximum interval for staleness calculations. By default it is automatically calculated from the median interval between samples. This flag could be useful for tuning Prometheus data model closer to Influx-style data model. See https://prometheus.io/docs/prometheus/latest/querying/basics/#staleness for details. See also '-search.setLookbackToStep' flag
|
||||
-search.maxStatusRequestDuration duration
|
||||
|
|
|
|||
|
|
@ -1361,6 +1361,7 @@ By default VictoriaMetrics is tuned for an optimal resource usage under typical
|
|||
- `-search.maxSamplesPerQuery` limits the number of raw samples a single query can process. This allows limiting CPU usage for heavy queries.
|
||||
- `-search.maxPointsPerTimeseries` limits the number of calculated points, which can be returned per each matching time series from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated per each matching time series during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
|
||||
- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) in a single query.
|
||||
- `-search.maxSeries` limits the number of time series, which may be returned from [/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers). This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxSeries` to quite low value in order limit CPU and memory usage.
|
||||
- `-search.maxTagKeys` limits the number of items, which may be returned from [/api/v1/labels](https://prometheus.io/docs/prometheus/latest/querying/api/#getting-label-names). This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagKeys` to quite low value in order to limit CPU and memory usage.
|
||||
- `-search.maxTagValues` limits the number of items, which may be returned from [/api/v1/label/.../values](https://prometheus.io/docs/prometheus/latest/querying/api/#querying-label-values). This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagValues` to quite low value in order to limit CPU and memory usage.
|
||||
|
|
@ -2442,6 +2443,8 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
|
|||
The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage (default 30000000)
|
||||
-search.maxSeries int
|
||||
The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage (default 30000)
|
||||
-search.maxSeriesPerAggrFunc int
|
||||
The maximum number of time series an aggregate MetricsQL function can generate (default 1000000)
|
||||
-search.maxStalenessInterval duration
|
||||
The maximum interval for staleness calculations. By default it is automatically calculated from the median interval between samples. This flag could be useful for tuning Prometheus data model closer to Influx-style data model. See https://prometheus.io/docs/prometheus/latest/querying/basics/#staleness for details. See also '-search.setLookbackToStep' flag
|
||||
-search.maxStatusRequestDuration duration
|
||||
|
|
|
|||
Loading…
Reference in a new issue