app/vmselect/promql: add range_stdvar() and range_stddev() functions for calculating variance and deviation over time series on the selected time range

app/vmselect/promql/exec_test.go

@@ -6380,19 +6380,39 @@ func TestExecSuccess(t *testing.T) {
 		q := `range_quantile(0.5, time())`
 		r := netstorage.Result{
 			MetricName: metricNameExpected,
-			// time() results in [1000 1200 1400 1600 1800 2000]
 			Values:     []float64{1500, 1500, 1500, 1500, 1500, 1500},
 			Timestamps: timestampsExpected,
 		}
 		resultExpected := []netstorage.Result{r}
 		f(q, resultExpected)
 	})
+	t.Run(`range_stddev()`, func(t *testing.T) {
+		t.Parallel()
+		q := `round(range_stddev(time()),0.01)`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{341.57, 341.57, 341.57, 341.57, 341.57, 341.57},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
+	t.Run(`range_stdvar()`, func(t *testing.T) {
+		t.Parallel()
+		q := `round(range_stdvar(time()),0.01)`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{116666.67, 116666.67, 116666.67, 116666.67, 116666.67, 116666.67},
+			Timestamps: timestampsExpected,
+		}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
 	t.Run(`range_median()`, func(t *testing.T) {
 		t.Parallel()
 		q := `range_median(time())`
 		r := netstorage.Result{
 			MetricName: metricNameExpected,
-			// time() results in [1000 1200 1400 1600 1800 2000]
 			Values:     []float64{1500, 1500, 1500, 1500, 1500, 1500},
 			Timestamps: timestampsExpected,
 		}
@@ -8079,6 +8099,8 @@ func TestExecError(t *testing.T) {
 	f(`nonexisting()`)
 
 	// Invalid number of args
+	f(`range_stddev()`)
+	f(`range_stdvar()`)
 	f(`range_quantile()`)
 	f(`range_quantile(1, 2, 3)`)
 	f(`range_median()`)

app/vmselect/promql/rollup.go

@@ -1475,16 +1475,20 @@ func rollupStaleSamples(rfa *rollupFuncArg) float64 {
 }
 
 func rollupStddev(rfa *rollupFuncArg) float64 {
-	stdvar := rollupStdvar(rfa)
-	return math.Sqrt(stdvar)
+	return stddev(rfa.values)
 }
 
 func rollupStdvar(rfa *rollupFuncArg) float64 {
-	// See `Rapid calculation methods` at https://en.wikipedia.org/wiki/Standard_deviation
+	return stdvar(rfa.values)
+}
 
-	// There is no need in handling NaNs here, since they must be cleaned up
-	// before calling rollup funcs.
-	values := rfa.values
+func stddev(values []float64) float64 {
+	v := stdvar(values)
+	return math.Sqrt(v)
+}
+
+func stdvar(values []float64) float64 {
+	// See `Rapid calculation methods` at https://en.wikipedia.org/wiki/Standard_deviation
 	if len(values) == 0 {
 		return nan
 	}
@@ -1496,11 +1500,17 @@ func rollupStdvar(rfa *rollupFuncArg) float64 {
 	var count float64
 	var q float64
 	for _, v := range values {
+		if math.IsNaN(v) {
+			continue
+		}
 		count++
 		avgNew := avg + (v-avg)/count
 		q += (v - avg) * (v - avgNew)
 		avg = avgNew
 	}
+	if count == 0 {
+		return nan
+	}
 	return q / count
 }
 

app/vmselect/promql/transform.go

@@ -92,6 +92,8 @@ var transformFuncs = map[string]transformFunc{
 	"range_max":                  newTransformFuncRange(runningMax),
 	"range_min":                  newTransformFuncRange(runningMin),
 	"range_quantile":             transformRangeQuantile,
+	"range_stddev":               transformRangeStddev,
+	"range_stdvar":               transformRangeStdvar,
 	"range_sum":                  newTransformFuncRange(runningSum),
 	"remove_resets":              transformRemoveResets,
 	"round":                      transformRound,
@@ -141,6 +143,8 @@ var transformFuncsKeepMetricName = map[string]bool{
 	"range_max":               true,
 	"range_min":               true,
 	"range_quantile":          true,
+	"range_stdvar":            true,
+	"range_sddev":             true,
 	"round":                   true,
 	"running_avg":             true,
 	"running_max":             true,
@@ -1257,6 +1261,38 @@ func transformRangeLinearRegression(tfa *transformFuncArg) ([]*timeseries, error
 	return rvs, nil
 }
 
+func transformRangeStddev(tfa *transformFuncArg) ([]*timeseries, error) {
+	args := tfa.args
+	if err := expectTransformArgsNum(args, 1); err != nil {
+		return nil, err
+	}
+	rvs := args[0]
+	for _, ts := range rvs {
+		values := ts.Values
+		v := stddev(values)
+		for i := range values {
+			values[i] = v
+		}
+	}
+	return rvs, nil
+}
+
+func transformRangeStdvar(tfa *transformFuncArg) ([]*timeseries, error) {
+	args := tfa.args
+	if err := expectTransformArgsNum(args, 1); err != nil {
+		return nil, err
+	}
+	rvs := args[0]
+	for _, ts := range rvs {
+		values := ts.Values
+		v := stdvar(values)
+		for i := range values {
+			values[i] = v
+		}
+	}
+	return rvs, nil
+}
+
 func transformRangeQuantile(tfa *transformFuncArg) ([]*timeseries, error) {
 	args := tfa.args
 	if err := expectTransformArgsNum(args, 2); err != nil {

docs/CHANGELOG.md

@@ -16,6 +16,7 @@ The following tip changes can be tested by building VictoriaMetrics components f
 ## tip
 
 * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_linear_regression](https://docs.victoriametrics.com/MetricsQL.html#range_linear_regression) function for calculating [simple linear regression](https://en.wikipedia.org/wiki/Simple_linear_regression) over the input time series on the selected time range. This function is useful for predictions and capacity planning. For example, `range_linear_regression(process_resident_memory_bytes)` can predict future memory usage based on the past memory usage.
+* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_stddev](https://docs.victoriametrics.com/MetricsQL.html#range_stddev) and [range_stdvar](https://docs.victoriametrics.com/MetricsQL.html#range_stdvar) functions.
 
 ## [v1.83.1](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.83.1)
 

docs/MetricsQL.md

@@ -1225,6 +1225,16 @@ over the selected time range per each time series returned by `q`. This function
 `range_quantile(phi, q)` is a [transform function](#transform-functions), which returns `phi`-quantile across points per each time series returned by `q`.
 `phi` must be in the range `[0...1]`.
 
+#### range_stddev
+
+`range_stddev(q)` is a [transform function](#transform-functions), which calculates [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation)
+per each time series returned by `q` on the selected time range.
+
+#### range_stdvar
+
+`range_stdvar(q)` is a [transform function](#transform-functions), which calculates [standard variance](https://en.wikipedia.org/wiki/Variance)
+per each time series returned by `q` on the selected time range.
+
 #### range_sum
 
 `range_sum(q)` is a [transform function](#transform-functions), which calculates the sum of points per each time series returned by `q`.

go.mod

@@ -12,7 +12,7 @@ require (
 	// like https://github.com/valyala/fasthttp/commit/996610f021ff45fdc98c2ce7884d5fa4e7f9199b
 	github.com/VictoriaMetrics/fasthttp v1.1.0
 	github.com/VictoriaMetrics/metrics v1.23.0
-	github.com/VictoriaMetrics/metricsql v0.46.0
+	github.com/VictoriaMetrics/metricsql v0.47.0
 	github.com/aws/aws-sdk-go-v2 v1.17.1
 	github.com/aws/aws-sdk-go-v2/config v1.17.10
 	github.com/aws/aws-sdk-go-v2/feature/s3/manager v1.11.37

go.sum

@@ -100,8 +100,8 @@ github.com/VictoriaMetrics/fasthttp v1.1.0/go.mod h1:/7DMcogqd+aaD3G3Hg5kFgoFwlR
 github.com/VictoriaMetrics/metrics v1.18.1/go.mod h1:ArjwVz7WpgpegX/JpB0zpNF2h2232kErkEnzH1sxMmA=
 github.com/VictoriaMetrics/metrics v1.23.0 h1:WzfqyzCaxUZip+OBbg1+lV33WChDSu4ssYII3nxtpeA=
 github.com/VictoriaMetrics/metrics v1.23.0/go.mod h1:rAr/llLpEnAdTehiNlUxKgnjcOuROSzpw0GvjpEbvFc=
-github.com/VictoriaMetrics/metricsql v0.46.0 h1:UeY+3vykSflhShmBmMemYvDVlqISraiCc8uMtyAc+PI=
-github.com/VictoriaMetrics/metricsql v0.46.0/go.mod h1:6pP1ZeLVJHqJrHlF6Ij3gmpQIznSsgktEcZgsAWYel0=
+github.com/VictoriaMetrics/metricsql v0.47.0 h1:PQwadjoQnKKkaUiupkDq0ZbCAHX2qP8OOexJ9oJwupo=
+github.com/VictoriaMetrics/metricsql v0.47.0/go.mod h1:6pP1ZeLVJHqJrHlF6Ij3gmpQIznSsgktEcZgsAWYel0=
 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/go.mod h1:nz4BbCtbLyFDeC9SUHbtcT5644juEuWfUAUnGx7j5l4=

vendor/github.com/VictoriaMetrics/metricsql/transform.go

@@ -77,6 +77,8 @@ var transformFuncs = map[string]bool{
 	"range_max":                  true,
 	"range_min":                  true,
 	"range_quantile":             true,
+	"range_stddev":               true,
+	"range_stdvar":               true,
 	"range_sum":                  true,
 	"remove_resets":              true,
 	"round":                      true,

vendor/modules.txt

@@ -69,7 +69,7 @@ github.com/VictoriaMetrics/fasthttp/stackless
 # github.com/VictoriaMetrics/metrics v1.23.0
 ## explicit; go 1.15
 github.com/VictoriaMetrics/metrics
-# github.com/VictoriaMetrics/metricsql v0.46.0
+# github.com/VictoriaMetrics/metricsql v0.47.0
 ## explicit; go 1.13
 github.com/VictoriaMetrics/metricsql
 github.com/VictoriaMetrics/metricsql/binaryop