mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-11-23 20:37:12 +01:00
app/vmselect/promql: add increases_over_time
and decreases_over_time
functions
`increases_over_time(q[d])` returns the number of `q` increases during the given duration `d`. `decreases_over_time(q[d])` returns the number of `q` decreases during the given duration `d`.
This commit is contained in:
parent
2444433d83
commit
26dc21cf64
@ -2671,6 +2671,28 @@ func TestExecSuccess(t *testing.T) {
|
||||
resultExpected := []netstorage.Result{r}
|
||||
f(q, resultExpected)
|
||||
})
|
||||
t.Run(`increases_over_time`, func(t *testing.T) {
|
||||
t.Parallel()
|
||||
q := `increases_over_time(rand(0)[200s:10s])`
|
||||
r := netstorage.Result{
|
||||
MetricName: metricNameExpected,
|
||||
Values: []float64{11, 9, 9, 12, 9, 8},
|
||||
Timestamps: timestampsExpected,
|
||||
}
|
||||
resultExpected := []netstorage.Result{r}
|
||||
f(q, resultExpected)
|
||||
})
|
||||
t.Run(`decreases_over_time`, func(t *testing.T) {
|
||||
t.Parallel()
|
||||
q := `decreases_over_time(rand(0)[200s:10s])`
|
||||
r := netstorage.Result{
|
||||
MetricName: metricNameExpected,
|
||||
Values: []float64{9, 11, 11, 8, 11, 12},
|
||||
Timestamps: timestampsExpected,
|
||||
}
|
||||
resultExpected := []netstorage.Result{r}
|
||||
f(q, resultExpected)
|
||||
})
|
||||
t.Run(`limitk(-1)`, func(t *testing.T) {
|
||||
t.Parallel()
|
||||
q := `limitk(-1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
|
||||
|
@ -38,21 +38,23 @@ var rollupFuncs = map[string]newRollupFunc{
|
||||
"stdvar_over_time": newRollupFuncOneArg(rollupStdvar),
|
||||
|
||||
// Additional rollup funcs.
|
||||
"sum2_over_time": newRollupFuncOneArg(rollupSum2),
|
||||
"geomean_over_time": newRollupFuncOneArg(rollupGeomean),
|
||||
"first_over_time": newRollupFuncOneArg(rollupFirst),
|
||||
"last_over_time": newRollupFuncOneArg(rollupLast),
|
||||
"distinct_over_time": newRollupFuncOneArg(rollupDistinct),
|
||||
"integrate": newRollupFuncOneArg(rollupIntegrate),
|
||||
"ideriv": newRollupFuncOneArg(rollupIderiv),
|
||||
"lifetime": newRollupFuncOneArg(rollupLifetime),
|
||||
"scrape_interval": newRollupFuncOneArg(rollupScrapeInterval),
|
||||
"rollup": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_rate": newRollupFuncOneArg(rollupFake), // + rollupFuncsRemoveCounterResets
|
||||
"rollup_deriv": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_delta": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_increase": newRollupFuncOneArg(rollupFake), // + rollupFuncsRemoveCounterResets
|
||||
"rollup_candlestick": newRollupFuncOneArg(rollupFake),
|
||||
"sum2_over_time": newRollupFuncOneArg(rollupSum2),
|
||||
"geomean_over_time": newRollupFuncOneArg(rollupGeomean),
|
||||
"first_over_time": newRollupFuncOneArg(rollupFirst),
|
||||
"last_over_time": newRollupFuncOneArg(rollupLast),
|
||||
"distinct_over_time": newRollupFuncOneArg(rollupDistinct),
|
||||
"increases_over_time": newRollupFuncOneArg(rollupIncreases),
|
||||
"decreases_over_time": newRollupFuncOneArg(rollupDecreases),
|
||||
"integrate": newRollupFuncOneArg(rollupIntegrate),
|
||||
"ideriv": newRollupFuncOneArg(rollupIderiv),
|
||||
"lifetime": newRollupFuncOneArg(rollupLifetime),
|
||||
"scrape_interval": newRollupFuncOneArg(rollupScrapeInterval),
|
||||
"rollup": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_rate": newRollupFuncOneArg(rollupFake), // + rollupFuncsRemoveCounterResets
|
||||
"rollup_deriv": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_delta": newRollupFuncOneArg(rollupFake),
|
||||
"rollup_increase": newRollupFuncOneArg(rollupFake), // + rollupFuncsRemoveCounterResets
|
||||
"rollup_candlestick": newRollupFuncOneArg(rollupFake),
|
||||
}
|
||||
|
||||
var rollupFuncsMayAdjustWindow = map[string]bool{
|
||||
@ -820,6 +822,37 @@ func rollupChanges(rfa *rollupFuncArg) float64 {
|
||||
return float64(n)
|
||||
}
|
||||
|
||||
func rollupIncreases(rfa *rollupFuncArg) float64 {
|
||||
// There is no need in handling NaNs here, since they must be cleaned up
|
||||
// before calling rollup funcs.
|
||||
values := rfa.values
|
||||
if len(values) == 0 {
|
||||
if math.IsNaN(rfa.prevValue) {
|
||||
return nan
|
||||
}
|
||||
return 0
|
||||
}
|
||||
prevValue := rfa.prevValue
|
||||
if math.IsNaN(prevValue) {
|
||||
prevValue = values[0]
|
||||
values = values[1:]
|
||||
}
|
||||
if len(values) == 0 {
|
||||
return 0
|
||||
}
|
||||
n := 0
|
||||
for _, v := range values {
|
||||
if v > prevValue {
|
||||
n++
|
||||
}
|
||||
prevValue = v
|
||||
}
|
||||
return float64(n)
|
||||
}
|
||||
|
||||
// `decreases_over_time` logic is the same as `resets` logic.
|
||||
var rollupDecreases = rollupResets
|
||||
|
||||
func rollupResets(rfa *rollupFuncArg) float64 {
|
||||
// There is no need in handling NaNs here, since they must be cleaned up
|
||||
// before calling rollup funcs.
|
||||
|
@ -294,6 +294,8 @@ func TestRollupNewRollupFuncSuccess(t *testing.T) {
|
||||
f("integrate", 61.0275)
|
||||
f("distinct_over_time", 8)
|
||||
f("ideriv", 0)
|
||||
f("decreases_over_time", 5)
|
||||
f("increases_over_time", 5)
|
||||
}
|
||||
|
||||
func TestRollupNewRollupFuncError(t *testing.T) {
|
||||
|
Loading…
Reference in New Issue
Block a user