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app/vmselect/promql: implement keep_metric_names modifier for transform and rollup functions

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Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/949
This commit is contained in:
Aliaksandr Valialkin 2022-01-14 04:05:39 +02:00
parent f41846d002
commit 1bdc71d917
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10 changed files with 184 additions and 128 deletions
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37
app/vmselect/promql/eval.go
View file

@ -498,7 +498,7 @@ func evalRollupFunc(ec *EvalConfig, funcName string, rf rollupFunc, expr metrics
if err != nil { if err != nil {
return nil, err return nil, err
} }
// expand tssAtTimestamp to the original time range. // expand single-point tss to the original time range.
timestamps := ec.getSharedTimestamps() timestamps := ec.getSharedTimestamps()
for _, ts := range tss { for _, ts := range tss {
v := ts.Values[0] v := ts.Values[0]
@ -598,11 +598,12 @@ func evalRollupFuncWithSubquery(ec *EvalConfig, funcName string, rf rollupFunc,
} }
tss := make([]*timeseries, 0, len(tssSQ)*len(rcs)) tss := make([]*timeseries, 0, len(tssSQ)*len(rcs))
var tssLock sync.Mutex var tssLock sync.Mutex
keepMetricNames := getKeepMetricNames(expr)
doParallel(tssSQ, func(tsSQ *timeseries, values []float64, timestamps []int64) ([]float64, []int64) { doParallel(tssSQ, func(tsSQ *timeseries, values []float64, timestamps []int64) ([]float64, []int64) {
values, timestamps = removeNanValues(values[:0], timestamps[:0], tsSQ.Values, tsSQ.Timestamps) values, timestamps = removeNanValues(values[:0], timestamps[:0], tsSQ.Values, tsSQ.Timestamps)
preFunc(values, timestamps) preFunc(values, timestamps)
for _, rc := range rcs { for _, rc := range rcs {
if tsm := newTimeseriesMap(funcName, sharedTimestamps, &tsSQ.MetricName); tsm != nil { if tsm := newTimeseriesMap(funcName, keepMetricNames, sharedTimestamps, &tsSQ.MetricName); tsm != nil {
rc.DoTimeseriesMap(tsm, values, timestamps) rc.DoTimeseriesMap(tsm, values, timestamps)
tssLock.Lock() tssLock.Lock()
tss = tsm.AppendTimeseriesTo(tss) tss = tsm.AppendTimeseriesTo(tss)
@ -610,7 +611,7 @@ func evalRollupFuncWithSubquery(ec *EvalConfig, funcName string, rf rollupFunc,
continue continue
} }
var ts timeseries var ts timeseries
doRollupForTimeseries(funcName, rc, &ts, &tsSQ.MetricName, values, timestamps, sharedTimestamps) doRollupForTimeseries(funcName, keepMetricNames, rc, &ts, &tsSQ.MetricName, values, timestamps, sharedTimestamps)
tssLock.Lock() tssLock.Lock()
tss = append(tss, &ts) tss = append(tss, &ts)
tssLock.Unlock() tssLock.Unlock()
@ -620,6 +621,13 @@ func evalRollupFuncWithSubquery(ec *EvalConfig, funcName string, rf rollupFunc,
return tss, nil return tss, nil
} }
func getKeepMetricNames(expr metricsql.Expr) bool {
if fe, ok := expr.(*metricsql.FuncExpr); ok {
return fe.KeepMetricNames
}
return false
}
func doParallel(tss []*timeseries, f func(ts *timeseries, values []float64, timestamps []int64) ([]float64, []int64)) { func doParallel(tss []*timeseries, f func(ts *timeseries, values []float64, timestamps []int64) ([]float64, []int64)) {
concurrency := cgroup.AvailableCPUs() concurrency := cgroup.AvailableCPUs()
if concurrency > len(tss) { if concurrency > len(tss) {
@ -769,11 +777,12 @@ func evalRollupFuncWithMetricExpr(ec *EvalConfig, funcName string, rf rollupFunc
defer rml.Put(uint64(rollupMemorySize)) defer rml.Put(uint64(rollupMemorySize))
// Evaluate rollup // Evaluate rollup
keepMetricNames := getKeepMetricNames(expr)
var tss []*timeseries var tss []*timeseries
if iafc != nil { if iafc != nil {
tss, err = evalRollupWithIncrementalAggregate(funcName, iafc, rss, rcs, preFunc, sharedTimestamps) tss, err = evalRollupWithIncrementalAggregate(funcName, keepMetricNames, iafc, rss, rcs, preFunc, sharedTimestamps)
} else { } else {
tss, err = evalRollupNoIncrementalAggregate(funcName, rss, rcs, preFunc, sharedTimestamps) tss, err = evalRollupNoIncrementalAggregate(funcName, keepMetricNames, rss, rcs, preFunc, sharedTimestamps)
} }
if err != nil { if err != nil {
return nil, err return nil, err
@ -795,7 +804,7 @@ func getRollupMemoryLimiter() *memoryLimiter {
return &rollupMemoryLimiter return &rollupMemoryLimiter
} }
func evalRollupWithIncrementalAggregate(funcName string, iafc *incrementalAggrFuncContext, rss *netstorage.Results, rcs []*rollupConfig, func evalRollupWithIncrementalAggregate(funcName string, keepMetricNames bool, iafc *incrementalAggrFuncContext, rss *netstorage.Results, rcs []*rollupConfig,
preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64) ([]*timeseries, error) { preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64) ([]*timeseries, error) {
err := rss.RunParallel(func(rs *netstorage.Result, workerID uint) error { err := rss.RunParallel(func(rs *netstorage.Result, workerID uint) error {
rs.Values, rs.Timestamps = dropStaleNaNs(funcName, rs.Values, rs.Timestamps) rs.Values, rs.Timestamps = dropStaleNaNs(funcName, rs.Values, rs.Timestamps)
@ -803,7 +812,7 @@ func evalRollupWithIncrementalAggregate(funcName string, iafc *incrementalAggrFu
ts := getTimeseries() ts := getTimeseries()
defer putTimeseries(ts) defer putTimeseries(ts)
for _, rc := range rcs { for _, rc := range rcs {
if tsm := newTimeseriesMap(funcName, sharedTimestamps, &rs.MetricName); tsm != nil { if tsm := newTimeseriesMap(funcName, keepMetricNames, sharedTimestamps, &rs.MetricName); tsm != nil {
rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps) rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps)
for _, ts := range tsm.m { for _, ts := range tsm.m {
iafc.updateTimeseries(ts, workerID) iafc.updateTimeseries(ts, workerID)
@ -811,7 +820,7 @@ func evalRollupWithIncrementalAggregate(funcName string, iafc *incrementalAggrFu
continue continue
} }
ts.Reset() ts.Reset()
doRollupForTimeseries(funcName, rc, ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps) doRollupForTimeseries(funcName, keepMetricNames, rc, ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps)
iafc.updateTimeseries(ts, workerID) iafc.updateTimeseries(ts, workerID)
// ts.Timestamps points to sharedTimestamps. Zero it, so it can be re-used. // ts.Timestamps points to sharedTimestamps. Zero it, so it can be re-used.
@ -827,7 +836,7 @@ func evalRollupWithIncrementalAggregate(funcName string, iafc *incrementalAggrFu
return tss, nil return tss, nil
} }
func evalRollupNoIncrementalAggregate(funcName string, rss *netstorage.Results, rcs []*rollupConfig, func evalRollupNoIncrementalAggregate(funcName string, keepMetricNames bool, rss *netstorage.Results, rcs []*rollupConfig,
preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64) ([]*timeseries, error) { preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64) ([]*timeseries, error) {
tss := make([]*timeseries, 0, rss.Len()*len(rcs)) tss := make([]*timeseries, 0, rss.Len()*len(rcs))
var tssLock sync.Mutex var tssLock sync.Mutex
@ -835,7 +844,7 @@ func evalRollupNoIncrementalAggregate(funcName string, rss *netstorage.Results,
rs.Values, rs.Timestamps = dropStaleNaNs(funcName, rs.Values, rs.Timestamps) rs.Values, rs.Timestamps = dropStaleNaNs(funcName, rs.Values, rs.Timestamps)
preFunc(rs.Values, rs.Timestamps) preFunc(rs.Values, rs.Timestamps)
for _, rc := range rcs { for _, rc := range rcs {
if tsm := newTimeseriesMap(funcName, sharedTimestamps, &rs.MetricName); tsm != nil { if tsm := newTimeseriesMap(funcName, keepMetricNames, sharedTimestamps, &rs.MetricName); tsm != nil {
rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps) rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps)
tssLock.Lock() tssLock.Lock()
tss = tsm.AppendTimeseriesTo(tss) tss = tsm.AppendTimeseriesTo(tss)
@ -843,7 +852,7 @@ func evalRollupNoIncrementalAggregate(funcName string, rss *netstorage.Results,
continue continue
} }
var ts timeseries var ts timeseries
doRollupForTimeseries(funcName, rc, &ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps) doRollupForTimeseries(funcName, keepMetricNames, rc, &ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps)
tssLock.Lock() tssLock.Lock()
tss = append(tss, &ts) tss = append(tss, &ts)
tssLock.Unlock() tssLock.Unlock()
@ -856,13 +865,13 @@ func evalRollupNoIncrementalAggregate(funcName string, rss *netstorage.Results,
return tss, nil return tss, nil
} }
func doRollupForTimeseries(funcName string, rc *rollupConfig, tsDst *timeseries, mnSrc *storage.MetricName, valuesSrc []float64, timestampsSrc []int64, func doRollupForTimeseries(funcName string, keepMetricNames bool, rc *rollupConfig, tsDst *timeseries, mnSrc *storage.MetricName,
sharedTimestamps []int64) { valuesSrc []float64, timestampsSrc []int64, sharedTimestamps []int64) {
tsDst.MetricName.CopyFrom(mnSrc) tsDst.MetricName.CopyFrom(mnSrc)
if len(rc.TagValue) > 0 { if len(rc.TagValue) > 0 {
tsDst.MetricName.AddTag("rollup", rc.TagValue) tsDst.MetricName.AddTag("rollup", rc.TagValue)
} }
if !rollupFuncsKeepMetricGroup[funcName] { if !keepMetricNames && !rollupFuncsKeepMetricName[funcName] {
tsDst.MetricName.ResetMetricGroup() tsDst.MetricName.ResetMetricGroup()
} }
tsDst.Values = rc.Do(tsDst.Values[:0], valuesSrc, timestampsSrc) tsDst.Values = rc.Do(tsDst.Values[:0], valuesSrc, timestampsSrc)

28
app/vmselect/promql/exec_test.go
View file

@ -965,7 +965,7 @@ func TestExecSuccess(t *testing.T) {
}) })
t.Run("exp(time()/1e3)", func(t *testing.T) { t.Run("exp(time()/1e3)", func(t *testing.T) {
t.Parallel() t.Parallel()
q := `exp(time()/1e3)` q := `exp(alias(time()/1e3, "foobar"))`
r := netstorage.Result{ r := netstorage.Result{
MetricName: metricNameExpected, MetricName: metricNameExpected,
Values: []float64{2.718281828459045, 3.3201169227365472, 4.0551999668446745, 4.953032424395115, 6.0496474644129465, 7.38905609893065}, Values: []float64{2.718281828459045, 3.3201169227365472, 4.0551999668446745, 4.953032424395115, 6.0496474644129465, 7.38905609893065},
@ -974,6 +974,18 @@ func TestExecSuccess(t *testing.T) {
resultExpected := []netstorage.Result{r} resultExpected := []netstorage.Result{r}
f(q, resultExpected) f(q, resultExpected)
}) })
t.Run("exp(time()/1e3) keep_metric_names", func(t *testing.T) {
t.Parallel()
q := `exp(alias(time()/1e3, "foobar")) keep_metric_names`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2.718281828459045, 3.3201169227365472, 4.0551999668446745, 4.953032424395115, 6.0496474644129465, 7.38905609893065},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time() @ 1h", func(t *testing.T) { t.Run("time() @ 1h", func(t *testing.T) {
t.Parallel() t.Parallel()
q := `time() @ 1h` q := `time() @ 1h`
@ -6207,7 +6219,7 @@ func TestExecSuccess(t *testing.T) {
}) })
t.Run(`rate(time())`, func(t *testing.T) { t.Run(`rate(time())`, func(t *testing.T) {
t.Parallel() t.Parallel()
q := `rate(time())` q := `rate(alias(time(), "foo"))`
r := netstorage.Result{ r := netstorage.Result{
MetricName: metricNameExpected, MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1}, Values: []float64{1, 1, 1, 1, 1, 1},
@ -6216,6 +6228,18 @@ func TestExecSuccess(t *testing.T) {
resultExpected := []netstorage.Result{r} resultExpected := []netstorage.Result{r}
f(q, resultExpected) f(q, resultExpected)
}) })
t.Run(`rate(time()) keep_metric_names`, func(t *testing.T) {
t.Parallel()
q := `rate(alias(time(), "foo")) keep_metric_names`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foo")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate(2000-time())`, func(t *testing.T) { t.Run(`rate(2000-time())`, func(t *testing.T) {
t.Parallel() t.Parallel()
q := `rate(2000-time())` q := `rate(2000-time())`

8
app/vmselect/promql/rollup.go
View file

@ -87,7 +87,7 @@ var rollupFuncs = map[string]newRollupFunc{
// in order to properly handle offset and timestamps unaligned to the current step. // in order to properly handle offset and timestamps unaligned to the current step.
// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/415 for details. // See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/415 for details.
"timestamp": newRollupFuncOneArg(rollupTlast), "timestamp": newRollupFuncOneArg(rollupTlast),
"timestamp_with_name": newRollupFuncOneArg(rollupTlast), // + rollupFuncsKeepMetricGroup "timestamp_with_name": newRollupFuncOneArg(rollupTlast), // + rollupFuncsKeepMetricName
"tlast_over_time": newRollupFuncOneArg(rollupTlast), "tlast_over_time": newRollupFuncOneArg(rollupTlast),
"tmax_over_time": newRollupFuncOneArg(rollupTmax), "tmax_over_time": newRollupFuncOneArg(rollupTmax),
"tmin_over_time": newRollupFuncOneArg(rollupTmin), "tmin_over_time": newRollupFuncOneArg(rollupTmin),
@ -177,7 +177,7 @@ var rollupFuncsRemoveCounterResets = map[string]bool{
// These functions don't change physical meaning of input time series, // These functions don't change physical meaning of input time series,
// so they don't drop metric name // so they don't drop metric name
var rollupFuncsKeepMetricGroup = map[string]bool{ var rollupFuncsKeepMetricName = map[string]bool{
"avg_over_time": true, "avg_over_time": true,
"default_rollup": true, "default_rollup": true,
"first_over_time": true, "first_over_time": true,
@ -428,7 +428,7 @@ type timeseriesMap struct {
m map[string]*timeseries m map[string]*timeseries
} }
func newTimeseriesMap(funcName string, sharedTimestamps []int64, mnSrc *storage.MetricName) *timeseriesMap { func newTimeseriesMap(funcName string, keepMetricNames bool, sharedTimestamps []int64, mnSrc *storage.MetricName) *timeseriesMap {
funcName = strings.ToLower(funcName) funcName = strings.ToLower(funcName)
switch funcName { switch funcName {
case "histogram_over_time", "quantiles_over_time": case "histogram_over_time", "quantiles_over_time":
@ -442,7 +442,7 @@ func newTimeseriesMap(funcName string, sharedTimestamps []int64, mnSrc *storage.
} }
var origin timeseries var origin timeseries
origin.MetricName.CopyFrom(mnSrc) origin.MetricName.CopyFrom(mnSrc)
if !rollupFuncsKeepMetricGroup[funcName] { if !keepMetricNames && !rollupFuncsKeepMetricName[funcName] {
origin.MetricName.ResetMetricGroup() origin.MetricName.ResetMetricGroup()
} }
origin.Timestamps = sharedTimestamps origin.Timestamps = sharedTimestamps

9
app/vmselect/promql/transform.go
View file

@ -120,7 +120,7 @@ var transformFuncs = map[string]transformFunc{
// These functions don't change physical meaning of input time series, // These functions don't change physical meaning of input time series,
// so they don't drop metric name // so they don't drop metric name
var transformFuncsKeepMetricGroup = map[string]bool{ var transformFuncsKeepMetricName = map[string]bool{
"ceil": true, "ceil": true,
"clamp": true, "clamp": true,
"clamp_max": true, "clamp_max": true,
@ -172,9 +172,12 @@ func newTransformFuncOneArg(tf func(v float64) float64) transformFunc {
func doTransformValues(arg []*timeseries, tf func(values []float64), fe *metricsql.FuncExpr) ([]*timeseries, error) { func doTransformValues(arg []*timeseries, tf func(values []float64), fe *metricsql.FuncExpr) ([]*timeseries, error) {
name := strings.ToLower(fe.Name) name := strings.ToLower(fe.Name)
keepMetricGroup := transformFuncsKeepMetricGroup[name] keepMetricNames := fe.KeepMetricNames
if transformFuncsKeepMetricName[name] {
keepMetricNames = true
}
for _, ts := range arg { for _, ts := range arg {
if !keepMetricGroup { if !keepMetricNames {
ts.MetricName.ResetMetricGroup() ts.MetricName.ResetMetricGroup()
} }
tf(ts.Values) tf(ts.Values)

1
docs/CHANGELOG.md
View file

@ -9,6 +9,7 @@ sort: 15
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add support for `@` modifier, which is enabled by default in Prometheus starting from [Prometheus v2.33.0](https://github.com/prometheus/prometheus/pull/10121). See [these docs](https://prometheus.io/docs/prometheus/latest/querying/basics/#modifier) and [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1348). VictoriaMetrics extends `@` modifier with the following additional features: * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add support for `@` modifier, which is enabled by default in Prometheus starting from [Prometheus v2.33.0](https://github.com/prometheus/prometheus/pull/10121). See [these docs](https://prometheus.io/docs/prometheus/latest/querying/basics/#modifier) and [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1348). VictoriaMetrics extends `@` modifier with the following additional features:
* It can contain arbitrary expression. For example, `foo @ (end() - 1h)` would return `foo` value at `end - 1 hour` timestamp on the selected time range `[start ... end]`. Another example: `foo @ now() - 10m` would return `foo` value 10 minutes ago from the current time. * It can contain arbitrary expression. For example, `foo @ (end() - 1h)` would return `foo` value at `end - 1 hour` timestamp on the selected time range `[start ... end]`. Another example: `foo @ now() - 10m` would return `foo` value 10 minutes ago from the current time.
* It can be put everywhere in the query. For example, `sum(foo) @ start()` would calculate `sum(foo)` at `start` timestamp on the selected time range `[start ... end]`. * It can be put everywhere in the query. For example, `sum(foo) @ start()` would calculate `sum(foo)` at `start` timestamp on the selected time range `[start ... end]`.
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add support for optional `keep_metric_names` modifier, which can be applied to all the [rollup functions](https://docs.victoriametrics.com/MetricsQL.html#rollup-functions) and [transform functions](https://docs.victoriametrics.com/MetricsQL.html#transform-functions). This modifier prevents from deleting metric names from function results. For example, `rate({__name__=~"foo|bar"}[5m]) keep_metric_names` leaves `foo` and `bar` metric names in `rate()` results. This feature provides an additional workaround for [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/949).
* FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): add support for Kubernetes service discovery in the current namespace in the same way as [Prometheus does](https://github.com/prometheus/prometheus/pull/9881). For example, the following config limits pod discovery to the namespace where vmagent runs: * FEATURE: [vmagent](https://docs.victoriametrics.com/vmagent.html): add support for Kubernetes service discovery in the current namespace in the same way as [Prometheus does](https://github.com/prometheus/prometheus/pull/9881). For example, the following config limits pod discovery to the namespace where vmagent runs:
```yaml ```yaml

163
docs/MetricsQL.md
View file

@ -49,6 +49,7 @@ This functionality can be evaluated at [an editable Grafana dashboard](https://p
- `ifnot` binary operator. `q1 ifnot q2` removes values from `q1` for existing values from `q2`. - `ifnot` binary operator. `q1 ifnot q2` removes values from `q1` for existing values from `q2`.
- String literals may be concatenated. This is useful with `WITH` templates: `WITH (commonPrefix="long_metric_prefix_") {__name__=commonPrefix+"suffix1"} / {__name__=commonPrefix+"suffix2"}`. - String literals may be concatenated. This is useful with `WITH` templates: `WITH (commonPrefix="long_metric_prefix_") {__name__=commonPrefix+"suffix1"} / {__name__=commonPrefix+"suffix2"}`.
- `WITH` templates. This feature simplifies writing and managing complex queries. Go to [WITH templates playground](https://play.victoriametrics.com/promql/expand-with-exprs) and try it. - `WITH` templates. This feature simplifies writing and managing complex queries. Go to [WITH templates playground](https://play.victoriametrics.com/promql/expand-with-exprs) and try it.
- `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions) and [transform functions](#transform-functions). This modifier prevents from dropping metric names in function results. For example, `rate({__name__=~"foo|bar"}[5m]) keep_metric_names` leaves `foo` and `bar` metric names in the resulting time series.
## MetricsQL functions ## MetricsQL functions
@ -71,6 +72,7 @@ MetricsQL provides the following functions:
* If lookbehind window in square brackets is missing, then MetricsQL automatically sets the lookbehind window to the interval between points on the graph (aka `step` query arg at [/api/v1/query_range](https://prometheus.io/docs/prometheus/latest/querying/api/#range-queries), `$__interval` value from Grafana or `1i` duration in MetricsQL). For example, `rate(http_requests_total)` is equivalent to `rate(http_requests_total[$__interval])` in Grafana. It is also equivalent to `rate(http_requests_total[1i])`. * If lookbehind window in square brackets is missing, then MetricsQL automatically sets the lookbehind window to the interval between points on the graph (aka `step` query arg at [/api/v1/query_range](https://prometheus.io/docs/prometheus/latest/querying/api/#range-queries), `$__interval` value from Grafana or `1i` duration in MetricsQL). For example, `rate(http_requests_total)` is equivalent to `rate(http_requests_total[$__interval])` in Grafana. It is also equivalent to `rate(http_requests_total[1i])`.
* Every [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors) in MetricsQL must be wrapped into a rollup function. Otherwise it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}` is automatically converted to `default_rollup(foo{bar="baz"}[1i])` before performing the calculations. * Every [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors) in MetricsQL must be wrapped into a rollup function. Otherwise it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}` is automatically converted to `default_rollup(foo{bar="baz"}[1i])` before performing the calculations.
* If something other than [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors) is passed to rollup function, then the inner arg is automatically converted to a [subquery](#subqueries). * If something other than [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors) is passed to rollup function, then the inner arg is automatically converted to a [subquery](#subqueries).
* All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results. For example, `rate({__name__=~"foo|bar}[5m]) keep_metric_names` leaves `foo` and `bar` metric names in results.
See also [implicit query conversions](#implicit-query-conversions). See also [implicit query conversions](#implicit-query-conversions).
@ -85,7 +87,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### ascent_over_time #### ascent_over_time
`ascent_over_time(series_selector[d])` calculates ascent of raw sample values on the given lookbehind window `d`. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups. See also [descent_over_time](#descent_over_time). `ascent_over_time(series_selector[d])` calculates ascent of raw sample values on the given lookbehind window `d`. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [descent_over_time](#descent_over_time).
#### avg_over_time #### avg_over_time
@ -93,35 +95,35 @@ See also [implicit query conversions](#implicit-query-conversions).
#### changes #### changes
`changes(series_selector[d])` calculates the number of times the raw samples changed on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Unlike `changes()` in Prometheus it takes into account the change from the last sample before the given lookbehind window `d`. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [changes_prometheus](#changes_prometheus). `changes(series_selector[d])` calculates the number of times the raw samples changed on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Unlike `changes()` in Prometheus it takes into account the change from the last sample before the given lookbehind window `d`. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [changes_prometheus](#changes_prometheus).
#### changes_prometheus #### changes_prometheus
`changes_prometheus(series_selector[d])` calculates the number of times the raw samples changed on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It doesn't take into account the change from the last sample before the given lookbehind window `d` in the same way as Prometheus does. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [changes](#changes). `changes_prometheus(series_selector[d])` calculates the number of times the raw samples changed on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It doesn't take into account the change from the last sample before the given lookbehind window `d` in the same way as Prometheus does. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [changes](#changes).
#### count_eq_over_time #### count_eq_over_time
`count_eq_over_time(series_selector[d], eq)` calculates the number of raw samples on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [count_over_time](#count_over_time). `count_eq_over_time(series_selector[d], eq)` calculates the number of raw samples on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [count_over_time](#count_over_time).
#### count_gt_over_time #### count_gt_over_time
`count_gt_over_time(series_selector[d], gt)` calculates the number of raw samples on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [count_over_time](#count_over_time). `count_gt_over_time(series_selector[d], gt)` calculates the number of raw samples on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [count_over_time](#count_over_time).
#### count_le_over_time #### count_le_over_time
`count_le_over_time(series_selector[d], le)` calculates the number of raw samples on the given lookbehind window `d`, which don't exceed `le`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [count_over_time](#count_over_time). `count_le_over_time(series_selector[d], le)` calculates the number of raw samples on the given lookbehind window `d`, which don't exceed `le`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [count_over_time](#count_over_time).
#### count_ne_over_time #### count_ne_over_time
`count_ne_over_time(series_selector[d], ne)` calculates the number of raw samples on the given lookbehind window `d`, which aren't equal to `ne`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [count_over_time](#count_over_time). `count_ne_over_time(series_selector[d], ne)` calculates the number of raw samples on the given lookbehind window `d`, which aren't equal to `ne`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [count_over_time](#count_over_time).
#### count_over_time #### count_over_time
`count_over_time(series_selector[d])` calculates the number of raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time), [count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time). `count_over_time(series_selector[d])` calculates the number of raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time), [count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
#### decreases_over_time #### decreases_over_time
`decreases_over_time(series_selector[d])` calculates the number of raw sample value decreases over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [increases_over_time](#increases_over_time). `decreases_over_time(series_selector[d])` calculates the number of raw sample value decreases over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [increases_over_time](#increases_over_time).
#### default_rollup #### default_rollup
@ -129,27 +131,27 @@ See also [implicit query conversions](#implicit-query-conversions).
#### delta #### delta
`delta(series_selector[d])` calculates the difference between the last sample before the given lookbehind window `d` and the last sample at the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The behaviour of `delta()` function in MetricsQL is slighly different to the behaviour of `delta()` function in Prometheus. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [increase](#increase) and [delta_prometheus](#delta_prometheus). `delta(series_selector[d])` calculates the difference between the last sample before the given lookbehind window `d` and the last sample at the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The behaviour of `delta()` function in MetricsQL is slighly different to the behaviour of `delta()` function in Prometheus. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
#### delta_prometheus #### delta_prometheus
`delta_prometheus(series_selector[d])` calculates the difference between the first and the last samples at the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The behaviour of `delta_prometheus()` is close to the behaviour of `delta()` function in Prometheus. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. See also [delta](#delta). `delta_prometheus(series_selector[d])` calculates the difference between the first and the last samples at the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The behaviour of `delta_prometheus()` is close to the behaviour of `delta()` function in Prometheus. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [delta](#delta).
#### deriv #### deriv
`deriv(series_selector[d])` calculates per-second derivative over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The derivative is calculated using linear regression. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv). `deriv(series_selector[d])` calculates per-second derivative over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). The derivative is calculated using linear regression. Metric names are stripped from the resulting rollups. This function is supported by PromQL. Add `keep_metric_names` modifier in order to keep metric names. See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
#### deriv_fast #### deriv_fast
`deriv_fast(series_selector[d])` calculates per-second derivative using the first and the last raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [deriv](#deriv) and [ideriv](#ideriv). `deriv_fast(series_selector[d])` calculates per-second derivative using the first and the last raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [deriv](#deriv) and [ideriv](#ideriv).
#### descent_over_time #### descent_over_time
`descent_over_time(series_selector[d])` calculates descent of raw sample values on the given lookbehind window `d`. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Useful for tracking height loss in GPS tracking. Metric names are stripped from the resulting rollups. See also [ascent_over_time](#ascent_over_time). `descent_over_time(series_selector[d])` calculates descent of raw sample values on the given lookbehind window `d`. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Useful for tracking height loss in GPS tracking. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [ascent_over_time](#ascent_over_time).
#### distinct_over_time #### distinct_over_time
`distinct_over_time(series_selector[d])` returns the number of distinct raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `distinct_over_time(series_selector[d])` returns the number of distinct raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### duration_over_time #### duration_over_time
@ -161,7 +163,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### geomean_over_time #### geomean_over_time
`geomean_over_time(series_selector[d])` calculates [geometric mean](https://en.wikipedia.org/wiki/Geometric_mean) over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `geomean_over_time(series_selector[d])` calculates [geometric mean](https://en.wikipedia.org/wiki/Geometric_mean) over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### histogram_over_time #### histogram_over_time
@ -181,19 +183,19 @@ See also [implicit query conversions](#implicit-query-conversions).
#### idelta #### idelta
`idelta(series_selector[d])` calculates the difference between the last two raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. `idelta(series_selector[d])` calculates the difference between the last two raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### ideriv #### ideriv
`ideriv(series_selector[d])` calculates the per-second derivative based on the last two raw samples over the given lookbehind window `d`. The derivative is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [deriv](#deriv). `ideriv(series_selector[d])` calculates the per-second derivative based on the last two raw samples over the given lookbehind window `d`. The derivative is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [deriv](#deriv).
#### increase #### increase
`increase(series_selector[d])` calculates the increase over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Unlike Prometheus it takes into account the last sample before the given lookbehind window `d` when calculating the result. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta). `increase(series_selector[d])` calculates the increase over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Unlike Prometheus it takes into account the last sample before the given lookbehind window `d` when calculating the result. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
#### increase_prometheus #### increase_prometheus
`increase_prometheus(series_selector[d])` calculates the increase over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). It doesn't take into account the last sample before the given lookbehind window `d` when calculating the result in the same way as Prometheus does. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [increase_pure](#increase_pure) and [increase](#increase). `increase_prometheus(series_selector[d])` calculates the increase over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). It doesn't take into account the last sample before the given lookbehind window `d` when calculating the result in the same way as Prometheus does. See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [increase_pure](#increase_pure) and [increase](#increase).
#### increase_pure #### increase_pure
@ -201,19 +203,19 @@ See also [implicit query conversions](#implicit-query-conversions).
#### increases_over_time #### increases_over_time
`increases_over_time(series_selector[d])` calculates the number of raw sample value increases over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [decreases_over_time](#decreases_over_time). `increases_over_time(series_selector[d])` calculates the number of raw sample value increases over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [decreases_over_time](#decreases_over_time).
#### integrate #### integrate
`integrate(series_selector[d])` calculates the integral over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `integrate(series_selector[d])` calculates the integral over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### irate #### irate
`irate(series_selector[d])` calculates the "instant" per-second increase rate over the last two raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [rate](#rate). `irate(series_selector[d])` calculates the "instant" per-second increase rate over the last two raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [rate](#rate).
#### lag #### lag
`lag(series_selector[d])` returns the duration in seconds between the last sample on the given lookbehind window `d` and the timestamp of the current point. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time). `lag(series_selector[d])` returns the duration in seconds between the last sample on the given lookbehind window `d` and the timestamp of the current point. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
#### last_over_time #### last_over_time
@ -221,7 +223,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### lifetime #### lifetime
`lifetime(series_selector[d])` returns the duration in seconds between the last and the first sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [duration_over_time](#duration_over_time) and [lag](#lag). `lifetime(series_selector[d])` returns the duration in seconds between the last and the first sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [duration_over_time](#duration_over_time) and [lag](#lag).
#### max_over_time #### max_over_time
@ -245,7 +247,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### present_over_time #### present_over_time
`present_over_time(series_selector[d])` returns 1 if there is at least a single raw sample on the given lookbehind window `d`. Otherwise an empty result is returned. Metric names are stripped from the resulting rollups. This function is supported by PromQL. `present_over_time(series_selector[d])` returns 1 if there is at least a single raw sample on the given lookbehind window `d`. Otherwise an empty result is returned. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### quantile_over_time #### quantile_over_time
@ -257,19 +259,19 @@ See also [implicit query conversions](#implicit-query-conversions).
#### range_over_time #### range_over_time
`range_over_time(series_selector[d])` calculates value range over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). E.g. it calculates `max_over_time(series_selector[d]) - min_over_time(series_selector[d])`. Metric names are stripped from the resulting rollups. `range_over_time(series_selector[d])` calculates value range over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). E.g. it calculates `max_over_time(series_selector[d]) - min_over_time(series_selector[d])`. Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### rate #### rate
`rate(series_selector[d])` calculates the average per-second increase rate over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. This function is supported by PromQL. `rate(series_selector[d])` calculates the average per-second increase rate over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### rate_over_sum #### rate_over_sum
`rate_over_sum(series_selector[d])` calculates per-second rate over the sum of raw samples on the given lookbehind window `d`. The calculations are performed indiviually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `rate_over_sum(series_selector[d])` calculates per-second rate over the sum of raw samples on the given lookbehind window `d`. The calculations are performed indiviually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### resets #### resets
`resets(series_selector[d])` returns the number of [counter](https://prometheus.io/docs/concepts/metric_types/#counter) resets over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. This function is supported by PromQL. `resets(series_selector[d])` returns the number of [counter](https://prometheus.io/docs/concepts/metric_types/#counter) resets over the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). It is expected that the `series_selector` returns time series of [counter type](https://prometheus.io/docs/concepts/metric_types/#counter). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### rollup #### rollup
@ -281,59 +283,59 @@ See also [implicit query conversions](#implicit-query-conversions).
#### rollup_delta #### rollup_delta
`rollup_delta(series_selector[d])` calculates differences between adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated differences. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [rollup_increase](#rollup_increase). `rollup_delta(series_selector[d])` calculates differences between adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated differences. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [rollup_increase](#rollup_increase).
#### rollup_deriv #### rollup_deriv
`rollup_deriv(series_selector[d])` calculates per-second derivatives for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second derivatives. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `rollup_deriv(series_selector[d])` calculates per-second derivatives for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second derivatives. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### rollup_increase #### rollup_increase
`rollup_increase(series_selector[d])` calculates increases for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated increases. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [rollup_delta](#rollup_delta). `rollup_increase(series_selector[d])` calculates increases for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated increases. The calculations are performed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [rollup_delta](#rollup_delta).
#### rollup_rate #### rollup_rate
`rollup_rate(series_selector[d])` calculates per-second change rates for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second change rates. The calculations are perfomed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `rollup_rate(series_selector[d])` calculates per-second change rates for adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second change rates. The calculations are perfomed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### rollup_scrape_interval #### rollup_scrape_interval
`rollup_scrape_interval(series_selector[d])` calculates the interval in seconds between adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated interval. The calculations are perfomed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [scrape_interval](#scrape_interval). `rollup_scrape_interval(series_selector[d])` calculates the interval in seconds between adjancent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated interval. The calculations are perfomed individually per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [scrape_interval](#scrape_interval).
#### scrape_interval #### scrape_interval
`scrape_interval(series_selector[d])` calculates the average interval in seconds between raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [rollup_scrape_interval](#rollup_scrape_interval). `scrape_interval(series_selector[d])` calculates the average interval in seconds between raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [rollup_scrape_interval](#rollup_scrape_interval).
#### share_gt_over_time #### share_gt_over_time
`share_gt_over_time(series_selector[d], gt)` returns share (in the range `[0...1]`) of raw samples on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Useful for calculating SLI and SLO. Example: `share_gt_over_time(up[24h], 0)` - returns service availability for the last 24 hours. See also [share_le_over_time](#share_le_over_time). `share_gt_over_time(series_selector[d], gt)` returns share (in the range `[0...1]`) of raw samples on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. Useful for calculating SLI and SLO. Example: `share_gt_over_time(up[24h], 0)` - returns service availability for the last 24 hours. See also [share_le_over_time](#share_le_over_time).
#### share_le_over_time #### share_le_over_time
`share_le_over_time(series_selector[d], le)` returns share (in the range `[0...1]`) of raw samples on the given lookbehind window `d`, which are smaller or equal to `le`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Useful for calculating SLI and SLO. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns the share of time series values for the last 24 hours when memory usage was below or equal to 100MB. See also [share_gt_over_time](#share_gt_over_time). `share_le_over_time(series_selector[d], le)` returns share (in the range `[0...1]`) of raw samples on the given lookbehind window `d`, which are smaller or equal to `le`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. Useful for calculating SLI and SLO. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns the share of time series values for the last 24 hours when memory usage was below or equal to 100MB. See also [share_gt_over_time](#share_gt_over_time).
#### stale_samples_over_time #### stale_samples_over_time
`stale_samples_over_time(series_selector[d])` calculates the number of [staleness markers](https://docs.victoriametrics.com/vmagent.html#prometheus-staleness-markers) on the given lookbehind window `d` per each time series matching the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `stale_samples_over_time(series_selector[d])` calculates the number of [staleness markers](https://docs.victoriametrics.com/vmagent.html#prometheus-staleness-markers) on the given lookbehind window `d` per each time series matching the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### stddev_over_time #### stddev_over_time
`stddev_over_time(series_selector[d])` calculates standard deviation over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [stdvar_over_time](#stdvar_over_time). `stddev_over_time(series_selector[d])` calculates standard deviation over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [stdvar_over_time](#stdvar_over_time).
#### stdvar_over_time #### stdvar_over_time
`stdvar_over_time(series_selector[d])` calculates stadnard variance over raw samples on the given lookbheind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [stddev_over_time](#stddev_over_time). `stdvar_over_time(series_selector[d])` calculates stadnard variance over raw samples on the given lookbheind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [stddev_over_time](#stddev_over_time).
#### sum_over_time #### sum_over_time
`sum_over_time(series_selector[d])` calculates the sum of raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. `sum_over_time(series_selector[d])` calculates the sum of raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### sum2_over_time #### sum2_over_time
`sum2_over_time(series_selector[d])` calculates the sum of squares for raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `sum2_over_time(series_selector[d])` calculates the sum of squares for raw sample values on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
#### timestamp #### timestamp
`timestamp(series_selector[d])` returns the timestamp in seconds for the last raw sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [timestamp_with_name](#timestamp_with_name). `timestamp(series_selector[d])` returns the timestamp in seconds for the last raw sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [timestamp_with_name](#timestamp_with_name).
#### timestamp_with_name #### timestamp_with_name
@ -341,7 +343,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### tfirst_over_time #### tfirst_over_time
`tfirst_over_time(series_selector[d])` returns the timestamp in seconds for the first raw sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [first_over_time](#first_over_time). `tfirst_over_time(series_selector[d])` returns the timestamp in seconds for the first raw sample on the given lookbehind window `d` per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [first_over_time](#first_over_time).
#### tlast_over_time #### tlast_over_time
@ -349,21 +351,22 @@ See also [implicit query conversions](#implicit-query-conversions).
#### tmax_over_time #### tmax_over_time
`tmax_over_time(series_selector[d])` returns the timestamp in seconds for the raw sample with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [max_over_time](#max_over_time). `tmax_over_time(series_selector[d])` returns the timestamp in seconds for the raw sample with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [max_over_time](#max_over_time).
#### tmin_over_time #### tmin_over_time
`tmin_over_time(series_selector[d])` returns the timestamp in seconds for the raw sample with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. See also [min_over_time](#min_over_time). `tmin_over_time(series_selector[d])` returns the timestamp in seconds for the raw sample with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names. See also [min_over_time](#min_over_time).
#### zscore_over_time #### zscore_over_time
`zscore_over_time(series_selector[d])` calculates returns [z-score](https://en.wikipedia.org/wiki/Standard_score) for raw samples on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. `zscore_over_time(series_selector[d])` calculates returns [z-score](https://en.wikipedia.org/wiki/Standard_score) for raw samples on the given lookbehind window `d`. It is calculated independently per each time series returned from the given [series_selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors). Metric names are stripped from the resulting rollups. Add `keep_metric_names` modifier in order to keep metric names.
### Transform functions ### Transform functions
**Transform functions** calculate transformations over rollup results. For example, `abs(delta(temperature[24h]))` calculates the absolute value for every point of every time series returned from the rollup `delta(temperature[24h])`. Additional details: **Transform functions** calculate transformations over rollup results. For example, `abs(delta(temperature[24h]))` calculates the absolute value for every point of every time series returned from the rollup `delta(temperature[24h])`. Additional details:
* If transform function is applied directly to a [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors), then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations. For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature[1i]))`. * If transform function is applied directly to a [series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors), then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations. For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature[1i]))`.
* All the transform functions accept optional `keep_metric_names` modifier. If it is set, then the function doesn't drop metric names from the resulting time series. For example, `ln({__name__=~"foo|bar"}) keep_metric_names` leaves `foo` and `bar` metric names in results.
See also [implicit query conversions](#implicit-query-conversions). See also [implicit query conversions](#implicit-query-conversions).
@ -378,39 +381,39 @@ See also [implicit query conversions](#implicit-query-conversions).
#### acos #### acos
`acos(q)` returns [inverse cosine](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [asin](#asin) and [cos](#cos). `acos(q)` returns [inverse cosine](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
#### acosh #### acosh
`acosh(q)` returns [inverse hyperbolic cosine](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_cosine) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [sinh](#cosh). `acosh(q)` returns [inverse hyperbolic cosine](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_cosine) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [sinh](#cosh).
#### asin #### asin
`asin(q)` returns [inverse sine](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [acos](#acos) and [sin](#sin). `asin(q)` returns [inverse sine](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
#### asinh #### asinh
`asinh(q)` returns [inverse hyperbolic sine](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_sine) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [sinh](#sinh). `asinh(q)` returns [inverse hyperbolic sine](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_sine) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [sinh](#sinh).
#### atan #### atan
`atan(q)` returns [inverse tangent](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [tan](#tan). `atan(q)` returns [inverse tangent](https://en.wikipedia.org/wiki/Inverse_trigonometric_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [tan](#tan).
#### atanh #### atanh
`atanh(q)` returns [inverse hyperbolic tangent](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_tangent) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [tanh](#tanh). `atanh(q)` returns [inverse hyperbolic tangent](https://en.wikipedia.org/wiki/Inverse_hyperbolic_functions#Inverse_hyperbolic_tangent) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [tanh](#tanh).
#### bitmap_and #### bitmap_and
`bitmap_and(q, mask)` - calculates bitwise `v & mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. `bitmap_and(q, mask)` - calculates bitwise `v & mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names.
#### bitmap_or #### bitmap_or
`bitmap_or(q, mask)` calculates bitwise `v | mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. `bitmap_or(q, mask)` calculates bitwise `v | mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names.
#### bitmap_xor #### bitmap_xor
`bitmap_xor(q, mask)` calculates bitwise `v ^ mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. `bitmap_xor(q, mask)` calculates bitwise `v ^ mask` for every `v` point of every time series returned from `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names.
#### buckets_limit #### buckets_limit
@ -434,27 +437,27 @@ See also [implicit query conversions](#implicit-query-conversions).
#### cos #### cos
`cos(q)` returns `cos(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [sin](#sin). `cos(q)` returns `cos(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [sin](#sin).
#### cosh #### cosh
`cosh(q)` returns [hyperbolic cosine](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. This function is supported by PromQL. See also [acosh](#acosh). `cosh(q)` returns [hyperbolic cosine](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. This function is supported by PromQL. See also [acosh](#acosh).
#### day_of_month #### day_of_month
`day_of_month(q)` returns the day of month for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[1...31]`. Metric names are stripped from the resulting series. This function is supported by PromQL. `day_of_month(q)` returns the day of month for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[1...31]`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### day_of_week #### day_of_week
`day_of_week(q)` returns the day of week for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...6]`, where `0` means Sunday and `6` means Saturday. Metric names are stripped from the resulting series. This function is supported by PromQL. `day_of_week(q)` returns the day of week for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...6]`, where `0` means Sunday and `6` means Saturday. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### days_in_month #### days_in_month
`days_in_month(q)` returns the number of days in the month identified by every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[28...31]`. Metric names are stripped from the resulting series. This function is supported by PromQL. `days_in_month(q)` returns the number of days in the month identified by every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[28...31]`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### deg #### deg
`deg(q)` converts [Radians to degrees](https://en.wikipedia.org/wiki/Radian#Conversions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [rad](#rad). `deg(q)` converts [Radians to degrees](https://en.wikipedia.org/wiki/Radian#Conversions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [rad](#rad).
#### end #### end
@ -462,7 +465,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### exp #### exp
`exp(q)` calculates the `e^v` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. See also [ln](#ln). This function is supported by PromQL. `exp(q)` calculates the `e^v` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. See also [ln](#ln). This function is supported by PromQL.
#### floor #### floor
@ -494,7 +497,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### hour #### hour
`hour(q)` returns the hour for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...23]`. Metric names are stripped from the resulting series. This function is supported by PromQL. `hour(q)` returns the hour for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...23]`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### interpolate #### interpolate
@ -514,23 +517,23 @@ See also [implicit query conversions](#implicit-query-conversions).
#### ln #### ln
`ln(q)` calculates `ln(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [exp](#exp) and [log2](#log2). `ln(q)` calculates `ln(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
#### log2 #### log2
`log2(q)` calculates `log2(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [log10](#log10) and [ln](#ln). `log2(q)` calculates `log2(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
#### log10 #### log10
`log10(q)` calculates `log10(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [log2](#log2) and [ln](#ln). `log10(q)` calculates `log10(v)` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [log2](#log2) and [ln](#ln).
#### minute #### minute
`minute(q)` returns the minute for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...59]`. Metric names are stripped from the resulting series. This function is supported by PromQL. `minute(q)` returns the minute for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[0...59]`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### month #### month
`month(q)` returns the month for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[1...12]`, where `1` means January and `12` means December. Metric names are stripped from the resulting series. This function is supported by PromQL. `month(q)` returns the month for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. The returned values are in the range `[1...12]`, where `1` means January and `12` means December. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### now #### now
@ -542,7 +545,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### rad #### rad
`rad(q)` converts [degrees to Radians](https://en.wikipedia.org/wiki/Radian#Conversions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. See also [deg](#deg). `rad(q)` converts [degrees to Radians](https://en.wikipedia.org/wiki/Radian#Conversions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL. See also [deg](#deg).
#### prometheus_buckets #### prometheus_buckets
@ -591,7 +594,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### range_sum #### range_sum
`range_sum(q)` calculates the sum of points per each time series returned by `q`. Metric names are stripped from the resulting series. `range_sum(q)` calculates the sum of points per each time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names.
#### remove_resets #### remove_resets
@ -619,7 +622,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### running_sum #### running_sum
`running_sum(q)` calculates the running sum per each time series returned by `q`. Metric names are stripped from the resulting series. `running_sum(q)` calculates the running sum per each time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names.
#### scalar #### scalar
@ -627,23 +630,23 @@ See also [implicit query conversions](#implicit-query-conversions).
#### sgn #### sgn
`sgn(q)` returns `1` if `v>0`, `-1` if `v<0` and `0` if `v==0` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. `sgn(q)` returns `1` if `v>0`, `-1` if `v<0` and `0` if `v==0` for every point `v` of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### sin #### sin
`sin(q)` returns `sin(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by MetricsQL. See also [cos](#cos). `sin(q)` returns `sin(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by MetricsQL. See also [cos](#cos).
#### sinh #### sinh
`sinh(q)` returns [hyperbolic sine](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by MetricsQL. See also [cosh](#cosh). `sinh(q)` returns [hyperbolic sine](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by MetricsQL. See also [cosh](#cosh).
#### tan #### tan
`tan(q)` returns `tan(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by MetricsQL. See also [atan](#atan). `tan(q)` returns `tan(v)` for every `v` point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by MetricsQL. See also [atan](#atan).
#### tanh #### tanh
`tanh(q)` returns [hyperbolic tangent](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by MetricsQL. See also [atanh](#atanh). `tanh(q)` returns [hyperbolic tangent](https://en.wikipedia.org/wiki/Hyperbolic_functions) for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by MetricsQL. See also [atanh](#atanh).
#### smooth_exponential #### smooth_exponential
@ -667,7 +670,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### sqrt #### sqrt
`sqrt(q)` calculates square root for every point of every time series returned by `q`. Metric names are stripped from the resulting series. This function is supported by PromQL. `sqrt(q)` calculates square root for every point of every time series returned by `q`. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
#### start #### start
@ -699,7 +702,7 @@ See also [implicit query conversions](#implicit-query-conversions).
#### year #### year
`year(q)` returns the year for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. Metric names are stripped from the resulting series. This function is supported by PromQL. `year(q)` returns the year for every point of every time series returned by `q`. It is expected that `q` returns unix timestamps. Metric names are stripped from the resulting series. Add `keep_metric_names` modifier in order to keep metric names. This function is supported by PromQL.
### Label manipulation functions ### Label manipulation functions

2
go.mod
View file

@ -10,7 +10,7 @@ require (
// like https://github.com/valyala/fasthttp/commit/996610f021ff45fdc98c2ce7884d5fa4e7f9199b // like https://github.com/valyala/fasthttp/commit/996610f021ff45fdc98c2ce7884d5fa4e7f9199b
github.com/VictoriaMetrics/fasthttp v1.1.0 github.com/VictoriaMetrics/fasthttp v1.1.0
github.com/VictoriaMetrics/metrics v1.18.1 github.com/VictoriaMetrics/metrics v1.18.1
github.com/VictoriaMetrics/metricsql v0.36.1 github.com/VictoriaMetrics/metricsql v0.37.0
github.com/aws/aws-sdk-go v1.42.31 github.com/aws/aws-sdk-go v1.42.31
github.com/cespare/xxhash/v2 v2.1.2 github.com/cespare/xxhash/v2 v2.1.2
github.com/cheggaaa/pb/v3 v3.0.8 github.com/cheggaaa/pb/v3 v3.0.8

4
go.sum
View file

@ -114,8 +114,8 @@ github.com/VictoriaMetrics/fasthttp v1.1.0 h1:3crd4YWHsMwu60GUXRH6OstowiFvqrwS4a
github.com/VictoriaMetrics/fasthttp v1.1.0/go.mod h1:/7DMcogqd+aaD3G3Hg5kFgoFwlR2uydjiWvoLp5ZTqQ= github.com/VictoriaMetrics/fasthttp v1.1.0/go.mod h1:/7DMcogqd+aaD3G3Hg5kFgoFwlR2uydjiWvoLp5ZTqQ=
github.com/VictoriaMetrics/metrics v1.18.1 h1:OZ0+kTTto8oPfHnVAnTOoyl0XlRhRkoQrD2n2cOuRw0= github.com/VictoriaMetrics/metrics v1.18.1 h1:OZ0+kTTto8oPfHnVAnTOoyl0XlRhRkoQrD2n2cOuRw0=
github.com/VictoriaMetrics/metrics v1.18.1/go.mod h1:ArjwVz7WpgpegX/JpB0zpNF2h2232kErkEnzH1sxMmA= github.com/VictoriaMetrics/metrics v1.18.1/go.mod h1:ArjwVz7WpgpegX/JpB0zpNF2h2232kErkEnzH1sxMmA=
github.com/VictoriaMetrics/metricsql v0.36.1 h1:pT1OAt7AFiNEj8rmXCqtggkA7XGQJNi4vafaw7JcVD4= github.com/VictoriaMetrics/metricsql v0.37.0 h1:zFKC+XJpEhp0TtTa6pD0pnyg9sDLH4U5nCeDUT8eUAw=
github.com/VictoriaMetrics/metricsql v0.36.1/go.mod h1:6pP1ZeLVJHqJrHlF6Ij3gmpQIznSsgktEcZgsAWYel0= github.com/VictoriaMetrics/metricsql v0.37.0/go.mod h1:6pP1ZeLVJHqJrHlF6Ij3gmpQIznSsgktEcZgsAWYel0=
github.com/VividCortex/ewma v1.1.1/go.mod h1:2Tkkvm3sRDVXaiyucHiACn4cqf7DpdyLvmxzcbUokwA= github.com/VividCortex/ewma v1.1.1/go.mod h1:2Tkkvm3sRDVXaiyucHiACn4cqf7DpdyLvmxzcbUokwA=
github.com/VividCortex/ewma v1.2.0 h1:f58SaIzcDXrSy3kWaHNvuJgJ3Nmz59Zji6XoJR/q1ow= github.com/VividCortex/ewma v1.2.0 h1:f58SaIzcDXrSy3kWaHNvuJgJ3Nmz59Zji6XoJR/q1ow=
github.com/VividCortex/ewma v1.2.0/go.mod h1:nz4BbCtbLyFDeC9SUHbtcT5644juEuWfUAUnGx7j5l4= github.com/VividCortex/ewma v1.2.0/go.mod h1:nz4BbCtbLyFDeC9SUHbtcT5644juEuWfUAUnGx7j5l4=

58
vendor/github.com/VictoriaMetrics/metricsql/parser.go generated vendored
View file

@ -147,6 +147,9 @@ func removeParensExpr(e Expr) Expr {
func simplifyConstants(e Expr) Expr { func simplifyConstants(e Expr) Expr {
if re, ok := e.(*RollupExpr); ok { if re, ok := e.(*RollupExpr); ok {
re.Expr = simplifyConstants(re.Expr) re.Expr = simplifyConstants(re.Expr)
if re.At != nil {
re.At = simplifyConstants(re.At)
}
return re return re
} }
if ae, ok := e.(*AggrFuncExpr); ok { if ae, ok := e.(*AggrFuncExpr); ok {
@ -666,17 +669,12 @@ func expandWithExpr(was []*withArgExpr, e Expr) (Expr, error) {
return se, nil return se, nil
} }
} }
be := &BinaryOpExpr{ be := *t
Op: t.Op, be.Left = left
Bool: t.Bool, be.Right = right
GroupModifier: t.GroupModifier,
JoinModifier: t.JoinModifier,
Left: left,
Right: right,
}
be.GroupModifier.Args = groupModifierArgs be.GroupModifier.Args = groupModifierArgs
be.JoinModifier.Args = joinModifierArgs be.JoinModifier.Args = joinModifierArgs
pe := parensExpr{be} pe := parensExpr{&be}
return &pe, nil return &pe, nil
case *FuncExpr: case *FuncExpr:
args, err := expandWithArgs(was, t.Args) args, err := expandWithArgs(was, t.Args)
@ -685,11 +683,9 @@ func expandWithExpr(was []*withArgExpr, e Expr) (Expr, error) {
} }
wa := getWithArgExpr(was, t.Name) wa := getWithArgExpr(was, t.Name)
if wa == nil { if wa == nil {
fe := &FuncExpr{ fe := *t
Name: t.Name, fe.Args = args
Args: args, return &fe, nil
}
return fe, nil
} }
return expandWithExprExt(was, wa, args) return expandWithExprExt(was, wa, args)
case *AggrFuncExpr: case *AggrFuncExpr:
@ -701,14 +697,10 @@ func expandWithExpr(was []*withArgExpr, e Expr) (Expr, error) {
if err != nil { if err != nil {
return nil, err return nil, err
} }
ae := &AggrFuncExpr{ ae := *t
Name: t.Name, ae.Args = args
Args: args,
Modifier: t.Modifier,
Limit: t.Limit,
}
ae.Modifier.Args = modifierArgs ae.Modifier.Args = modifierArgs
return ae, nil return &ae, nil
case *parensExpr: case *parensExpr:
exprs, err := expandWithArgs(was, *t) exprs, err := expandWithArgs(was, *t)
if err != nil { if err != nil {
@ -759,6 +751,13 @@ func expandWithExpr(was []*withArgExpr, e Expr) (Expr, error) {
} }
re := *t re := *t
re.Expr = eNew re.Expr = eNew
if t.At != nil {
atNew, err := expandWithExpr(was, t.At)
if err != nil {
return nil, err
}
re.At = atNew
}
return &re, nil return &re, nil
case *withExpr: case *withExpr:
wasNew := make([]*withArgExpr, 0, len(was)+len(t.Was)) wasNew := make([]*withArgExpr, 0, len(was)+len(t.Was))
@ -1017,9 +1016,20 @@ func (p *parser) parseFuncExpr() (*FuncExpr, error) {
return nil, err return nil, err
} }
fe.Args = args fe.Args = args
if isKeepMetricNames(p.lex.Token) {
fe.KeepMetricNames = true
if err := p.lex.Next(); err != nil {
return nil, err
}
}
return &fe, nil return &fe, nil
} }
func isKeepMetricNames(token string) bool {
token = strings.ToLower(token)
return token == "keep_metric_names"
}
func (p *parser) parseModifierExpr(me *ModifierExpr) error { func (p *parser) parseModifierExpr(me *ModifierExpr) error {
if !isIdentPrefix(p.lex.Token) { if !isIdentPrefix(p.lex.Token) {
return fmt.Errorf(`ModifierExpr: unexpected token %q; want "ident"`, p.lex.Token) return fmt.Errorf(`ModifierExpr: unexpected token %q; want "ident"`, p.lex.Token)
@ -1602,12 +1612,18 @@ type FuncExpr struct {
// Args contains function args. // Args contains function args.
Args []Expr Args []Expr
// If KeepMetricNames is set to true, then the function should keep metric names.
KeepMetricNames bool
} }
// AppendString appends string representation of fe to dst and returns the result. // AppendString appends string representation of fe to dst and returns the result.
func (fe *FuncExpr) AppendString(dst []byte) []byte { func (fe *FuncExpr) AppendString(dst []byte) []byte {
dst = appendEscapedIdent(dst, fe.Name) dst = appendEscapedIdent(dst, fe.Name)
dst = appendStringArgListExpr(dst, fe.Args) dst = appendStringArgListExpr(dst, fe.Args)
if fe.KeepMetricNames {
dst = append(dst, " keep_metric_names"...)
}
return dst return dst
} }

2
vendor/modules.txt vendored
View file

@ -26,7 +26,7 @@ github.com/VictoriaMetrics/fasthttp/stackless
# github.com/VictoriaMetrics/metrics v1.18.1 # github.com/VictoriaMetrics/metrics v1.18.1
## explicit; go 1.12 ## explicit; go 1.12
github.com/VictoriaMetrics/metrics github.com/VictoriaMetrics/metrics
# github.com/VictoriaMetrics/metricsql v0.36.1 # github.com/VictoriaMetrics/metricsql v0.37.0
## explicit; go 1.13 ## explicit; go 1.13
github.com/VictoriaMetrics/metricsql github.com/VictoriaMetrics/metricsql
github.com/VictoriaMetrics/metricsql/binaryop github.com/VictoriaMetrics/metricsql/binaryop