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app/vmselect/promql: return NaN values if invalid bucket counts are passed to histogram_quantile
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/136
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@ -2158,6 +2158,26 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r1, r2}
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f(q, resultExpected)
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})
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t.Run(`histogram_quantile(negative-bucket-count)`, func(t *testing.T) {
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t.Parallel()
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q := `sort(histogram_quantile(0.6,
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label_set(90, "foo", "bar", "le", "10")
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or label_set(-100, "foo", "bar", "le", "30")
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or label_set(300, "foo", "bar", "le", "+Inf")
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))`
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resultExpected := []netstorage.Result{}
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f(q, resultExpected)
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})
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t.Run(`histogram_quantile(nan-bucket-count)`, func(t *testing.T) {
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t.Parallel()
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q := `sort(histogram_quantile(0.6,
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label_set(90, "foo", "bar", "le", "10")
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or label_set(NaN, "foo", "bar", "le", "30")
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or label_set(300, "foo", "bar", "le", "+Inf")
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))`
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resultExpected := []netstorage.Result{}
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f(q, resultExpected)
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})
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t.Run(`median_over_time()`, func(t *testing.T) {
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t.Parallel()
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q := `median_over_time({})`
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@ -331,13 +331,17 @@ func transformHistogramQuantile(tfa *transformFuncArg) ([]*timeseries, error) {
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return inf
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}
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vReq := xss[len(xss)-1].ts.Values[i] * phi
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if math.IsNaN(vReq) || vReq < 0 {
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// Broken bucket.
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return nan
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}
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for _, xs := range xss {
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v := xs.ts.Values[i]
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le := xs.le
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if v <= vPrev {
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v = vPrev
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le = lePrev
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if math.IsNaN(v) || v < 0 {
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// Broken bucket.
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return nan
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}
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le := xs.le
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if v < vReq {
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vPrev = v
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lePrev = le
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