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app/vmselect/promql: follow-up after 177e345d8a
* Document changes_prometheus(), increase_prometheus() and delta_prometheus() functions. * Simplify their implementation * Mention these functions in docs/CHANGELOG.md
This commit is contained in:
Aliaksandr Valialkin
parent
46eee933b7
commit
974d9c0eee
9 changed files with 111 additions and 67 deletions
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@ -6270,6 +6270,22 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`increase_prometheus(time())`, func(t *testing.T) {
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t.Parallel()
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q := `increase_prometheus(time())`
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f(q, nil)
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})
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t.Run(`increase_prometheus(time()[201s])`, func(t *testing.T) {
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t.Parallel()
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q := `increase_prometheus(time()[201s])`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{200, 200, 200, 200, 200, 200},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_max(1)`, func(t *testing.T) {
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t.Parallel()
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q := `running_max(1)`
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@ -6512,6 +6528,22 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`delta_prometheus(time())`, func(t *testing.T) {
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t.Parallel()
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q := `delta_prometheus(time())`
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f(q, nil)
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})
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t.Run(`delta_prometheus(time()[201s])`, func(t *testing.T) {
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t.Parallel()
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q := `delta_prometheus(time()[201s])`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{200, 200, 200, 200, 200, 200},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`median_over_time("foo")`, func(t *testing.T) {
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t.Parallel()
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q := `median_over_time("foo")`
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@ -7503,6 +7535,12 @@ func TestExecError(t *testing.T) {
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f(`bitmap_xor()`)
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f(`quantiles()`)
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f(`limit_offset()`)
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f(`increase()`)
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f(`increase_prometheus()`)
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f(`changes()`)
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f(`changes_prometheus()`)
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f(`delta()`)
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f(`delta_prometheus()`)
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// Invalid argument type
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f(`median_over_time({}, 2)`)
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@ -164,12 +164,13 @@ var rollupFuncsCanAdjustWindow = map[string]bool{
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}
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var rollupFuncsRemoveCounterResets = map[string]bool{
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"increase": true,
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"increase_pure": true,
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"irate": true,
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"rate": true,
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"rollup_increase": true,
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"rollup_rate": true,
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"increase": true,
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"increase_prometheus": true,
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"increase_pure": true,
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"irate": true,
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"rate": true,
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"rollup_increase": true,
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"rollup_rate": true,
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}
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// These functions don't change physical meaning of input time series,
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@ -1492,51 +1493,12 @@ func rollupDeltaPrometheus(rfa *rollupFuncArg) float64 {
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// There is no need in handling NaNs here, since they must be cleaned up
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// before calling rollup funcs.
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values := rfa.values
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prevValue := rfa.prevValue
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if math.IsNaN(prevValue) {
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if len(values) == 0 {
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return nan
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}
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if !math.IsNaN(rfa.realPrevValue) {
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// Assume that the value didn't change during the current gap.
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// This should fix high delta() and increase() values at the end of gaps.
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// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/894
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return values[len(values)-1] - rfa.realPrevValue
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}
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// Assume that the previous non-existing value was 0 only in the following cases:
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//
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// - If the delta with the next value equals to 0.
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// This is the case for slow-changing counter - see https://github.com/VictoriaMetrics/VictoriaMetrics/issues/962
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// - If the first value doesn't exceed too much the delta with the next value.
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//
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// This should prevent from improper increase() results for os-level counters
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// such as cpu time or bytes sent over the network interface.
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// These counters may start long ago before the first value appears in the db.
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//
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// This also should prevent from improper increase() results when a part of label values are changed
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// without counter reset.
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var d float64
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if len(values) > 1 {
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d = values[1] - values[0]
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} else if !math.IsNaN(rfa.realNextValue) {
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d = rfa.realNextValue - values[0]
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}
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if d == 0 {
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d = 10
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}
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if math.Abs(values[0]) < 10*(math.Abs(d)+1) {
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//prevValue = 0
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prevValue = values[0]
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} else {
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prevValue = values[0]
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values = values[1:]
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}
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// Just return the difference between the last and the first sample like Prometheus does.
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// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1962
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if len(values) < 2 {
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return nan
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}
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if len(values) == 0 {
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// Assume that the value didn't change on the given interval.
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return 0
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}
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return values[len(values)-1] - prevValue
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return values[len(values)-1] - values[0]
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}
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func rollupIdelta(rfa *rollupFuncArg) float64 {
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@ -1702,17 +1664,14 @@ func rollupChangesPrometheus(rfa *rollupFuncArg) float64 {
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// There is no need in handling NaNs here, since they must be cleaned up
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// before calling rollup funcs.
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values := rfa.values
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prevValue := rfa.prevValue
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n := 0
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if math.IsNaN(prevValue) {
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if len(values) == 0 {
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return nan
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}
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prevValue = values[0]
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values = values[1:]
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//n++
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// Do not take into account rfa.prevValue like Prometheus does.
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// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1962
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if len(values) < 1 {
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return nan
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}
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for _, v := range values {
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prevValue := values[0]
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n := 0
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for _, v := range values[1:] {
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if v != prevValue {
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n++
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prevValue = v
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@ -490,11 +490,14 @@ func TestRollupNewRollupFuncSuccess(t *testing.T) {
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f("default_rollup", 34)
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f("changes", 11)
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f("changes_prometheus", 10)
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f("delta", 34)
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f("delta_prometheus", -89)
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f("deriv", -266.85860231406093)
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f("deriv_fast", -712)
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f("idelta", 0)
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f("increase", 398)
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f("increase_prometheus", 275)
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f("irate", 0)
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f("rate", 2200)
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f("resets", 5)
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@ -851,6 +854,20 @@ func TestRollupFuncsNoWindow(t *testing.T) {
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timestampsExpected := []int64{0, 40, 80, 120, 160}
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testRowsEqual(t, values, rc.Timestamps, valuesExpected, timestampsExpected)
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})
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t.Run("delta_prometheus", func(t *testing.T) {
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rc := rollupConfig{
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Func: rollupDeltaPrometheus,
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Start: 0,
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End: 160,
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Step: 40,
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Window: 0,
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}
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rc.Timestamps = getTimestamps(rc.Start, rc.End, rc.Step)
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values := rc.Do(nil, testValues, testTimestamps)
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valuesExpected := []float64{nan, -102, -42, -10, nan}
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timestampsExpected := []int64{0, 40, 80, 120, 160}
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testRowsEqual(t, values, rc.Timestamps, valuesExpected, timestampsExpected)
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})
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t.Run("idelta", func(t *testing.T) {
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rc := rollupConfig{
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Func: rollupIdelta,
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@ -949,6 +966,20 @@ func TestRollupFuncsNoWindow(t *testing.T) {
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timestampsExpected := []int64{0, 40, 80, 120, 160}
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testRowsEqual(t, values, rc.Timestamps, valuesExpected, timestampsExpected)
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})
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t.Run("changes_prometheus", func(t *testing.T) {
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rc := rollupConfig{
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Func: rollupChangesPrometheus,
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Start: 0,
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End: 160,
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Step: 40,
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Window: 0,
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}
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rc.Timestamps = getTimestamps(rc.Start, rc.End, rc.Step)
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values := rc.Do(nil, testValues, testTimestamps)
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valuesExpected := []float64{nan, 3, 3, 2, 0}
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timestampsExpected := []int64{0, 40, 80, 120, 160}
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testRowsEqual(t, values, rc.Timestamps, valuesExpected, timestampsExpected)
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})
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t.Run("changes_small_window", func(t *testing.T) {
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rc := rollupConfig{
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Func: rollupChanges,
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@ -17,6 +17,7 @@ sort: 15
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* FEATURE: preserve the order of time series passed to [limit_offset](https://docs.victoriametrics.com/MetricsQL.html#limit_offset) function. This allows implementing series paging via `limit_offset(limit, offset, sort_by_label(...))`. See [this](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1920) and [this](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/951) issues.
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* FEATURE: automaticall convert `(value1|...|valueN)` into `{value1,...,valueN}` inside `__graphite__` pseudo-label. This allows using [Grafana multi-value template variables](https://grafana.com/docs/grafana/latest/variables/formatting-multi-value-variables/) inside `__graphite__` pseudo-label. For example, `{__graphite__=~"foo.($bar)"}` is expanded to `{__graphite__=~"foo.{x,y}"}` if both `x` and `y` are selected for `$bar` template variable. See [these docs](https://docs.victoriametrics.com/#selecting-graphite-metrics) for details.
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* FEATURE: add [timestamp_with_name](https://docs.victoriametrics.com/MetricsQL.html#timestamp_with_name) function. It works the same as [timestamp](https://docs.victoriametrics.com/MetricsQL.html#timestamp), but leaves the original time series names, so it can be used in queries, which match multiple time series names: `timestamp_with_name({foo="bar"}[1h])`. See [this comment](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/949#issuecomment-995222388) for more context.
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* FEATURE: add [changes_prometheus](https://docs.victoriametrics.com/MetricsQL.html#changes_prometheus), [increase_prometheus](https://docs.victoriametrics.com/MetricsQL.html#increase_prometheus) and [delta_prometheus](https://docs.victoriametrics.com/MetricsQL.html#delta_prometheus) functions, which don't take into account the previous sample before the given lookbehind window specified in square brackets. These functions may be used when the Prometheus behaviour for `changes()`, `increase()` and `delta()` functions is needed to be preserved. VictoriaMetrics uses slightly different behaviour for `changes()`, `increase()` and `delta()` functions by default - see [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1962).
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* BUGFIX: fix `unaligned 64-bit atomic operation` panic on 32-bit architectures, which has been introduced in v1.70.0. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1944).
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* BUGFIX: [vmalert](https://docs.victoriametrics.com/vmalert.html): restore the ability to use `$labels.alertname` in labels templating. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1921).
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@ -92,7 +92,11 @@ See also [implicit query conversions](#implicit-query-conversions).
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#### changes
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`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). Metric names are stripped from the resulting rollups. This function is supported by PromQL.
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`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).
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#### changes_prometheus
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`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).
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#### count_eq_over_time
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@ -124,7 +128,11 @@ See also [implicit query conversions](#implicit-query-conversions).
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#### delta
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`delta(series_selector[d])` calculates the difference between the first and the last point 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. This function is supported by PromQL. See also [increase](#increase).
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`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).
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#### delta_prometheus
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`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).
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#### deriv
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@ -180,7 +188,11 @@ See also [implicit query conversions](#implicit-query-conversions).
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#### increase
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`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). Metric names are stripped from the resulting rollups. This function is supported by PromQL. See also [increase_pure](#increase_pure) and [delta](#delta).
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`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).
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#### increase_prometheus
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`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).
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#### increase_pure
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2
go.mod
2
go.mod
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@ -8,7 +8,7 @@ require (
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// like https://github.com/valyala/fasthttp/commit/996610f021ff45fdc98c2ce7884d5fa4e7f9199b
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github.com/VictoriaMetrics/fasthttp v1.1.0
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github.com/VictoriaMetrics/metrics v1.18.1
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github.com/VictoriaMetrics/metricsql v0.33.0
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github.com/VictoriaMetrics/metricsql v0.34.0
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github.com/VividCortex/ewma v1.2.0 // indirect
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github.com/aws/aws-sdk-go v1.42.23
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github.com/census-instrumentation/opencensus-proto v0.3.0 // indirect
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4
go.sum
4
go.sum
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@ -109,8 +109,8 @@ github.com/VictoriaMetrics/fasthttp v1.1.0/go.mod h1:/7DMcogqd+aaD3G3Hg5kFgoFwlR
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github.com/VictoriaMetrics/metrics v1.12.2/go.mod h1:Z1tSfPfngDn12bTfZSCqArT3OPY3u88J12hSoOhuiRE=
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github.com/VictoriaMetrics/metrics v1.18.1 h1:OZ0+kTTto8oPfHnVAnTOoyl0XlRhRkoQrD2n2cOuRw0=
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github.com/VictoriaMetrics/metrics v1.18.1/go.mod h1:ArjwVz7WpgpegX/JpB0zpNF2h2232kErkEnzH1sxMmA=
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github.com/VictoriaMetrics/metricsql v0.33.0 h1:UBj7+Tf4dhD47tIxMYfAiy/4GXJN6xPYTweCZ+sRqw0=
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github.com/VictoriaMetrics/metricsql v0.33.0/go.mod h1:ylO7YITho/Iw6P71oEaGyHbO94bGoGtzWfLGqFhMIg8=
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github.com/VictoriaMetrics/metricsql v0.34.0 h1:zF9yzRyNCAxzgEBBnE4y/p0QYNpSQp2jGEBCVE2fUD0=
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github.com/VictoriaMetrics/metricsql v0.34.0/go.mod h1:ylO7YITho/Iw6P71oEaGyHbO94bGoGtzWfLGqFhMIg8=
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github.com/VividCortex/ewma v1.1.1/go.mod h1:2Tkkvm3sRDVXaiyucHiACn4cqf7DpdyLvmxzcbUokwA=
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github.com/VividCortex/ewma v1.2.0 h1:f58SaIzcDXrSy3kWaHNvuJgJ3Nmz59Zji6XoJR/q1ow=
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github.com/VividCortex/ewma v1.2.0/go.mod h1:nz4BbCtbLyFDeC9SUHbtcT5644juEuWfUAUnGx7j5l4=
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3
vendor/github.com/VictoriaMetrics/metricsql/rollup.go
generated
vendored
3
vendor/github.com/VictoriaMetrics/metricsql/rollup.go
generated
vendored
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@ -10,6 +10,7 @@ var rollupFuncs = map[string]bool{
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"ascent_over_time": true,
|
||||
"avg_over_time": true,
|
||||
"changes": true,
|
||||
"changes_prometheus": true,
|
||||
"count_eq_over_time": true,
|
||||
"count_gt_over_time": true,
|
||||
"count_le_over_time": true,
|
||||
|
|
@ -18,6 +19,7 @@ var rollupFuncs = map[string]bool{
|
|||
"decreases_over_time": true,
|
||||
"default_rollup": true,
|
||||
"delta": true,
|
||||
"delta_prometheus": true,
|
||||
"deriv": true,
|
||||
"deriv_fast": true,
|
||||
"descent_over_time": true,
|
||||
|
|
@ -32,6 +34,7 @@ var rollupFuncs = map[string]bool{
|
|||
"idelta": true,
|
||||
"ideriv": true,
|
||||
"increase": true,
|
||||
"increase_prometheus": true,
|
||||
"increase_pure": true,
|
||||
"increases_over_time": true,
|
||||
"integrate": true,
|
||||
|
|
|
|||
2
vendor/modules.txt
vendored
2
vendor/modules.txt
vendored
|
|
@ -21,7 +21,7 @@ github.com/VictoriaMetrics/fasthttp/stackless
|
|||
# github.com/VictoriaMetrics/metrics v1.18.1
|
||||
## explicit
|
||||
github.com/VictoriaMetrics/metrics
|
||||
# github.com/VictoriaMetrics/metricsql v0.33.0
|
||||
# github.com/VictoriaMetrics/metricsql v0.34.0
|
||||
## explicit
|
||||
github.com/VictoriaMetrics/metricsql
|
||||
github.com/VictoriaMetrics/metricsql/binaryop
|
||||
|
|
|
|||
Loading…
Reference in a new issue