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app/vmselect/promql: properly handle histogram_quantile(0, ...)
with zero buckets
This commit is contained in:
parent
f8298c7f13
commit
193d553f6d
2 changed files with 53 additions and 5 deletions
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@ -2299,6 +2299,45 @@ 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(`histogram_quantile(single-value-valid-le-max-phi)`, func(t *testing.T) {
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t.Parallel()
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q := `histogram_quantile(1, (
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label_set(100, "le", "200"),
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label_set(0, "le", "55"),
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))`
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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(`histogram_quantile(single-value-valid-le-min-phi)`, func(t *testing.T) {
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t.Parallel()
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q := `histogram_quantile(0, (
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label_set(100, "le", "200"),
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label_set(0, "le", "55"),
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))`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{55, 55, 55, 55, 55, 55},
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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(`histogram_quantile(single-value-valid-le-min-phi-no-zero-bucket)`, func(t *testing.T) {
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t.Parallel()
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q := `histogram_quantile(0, label_set(100, "le", "200"))`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{0, 0, 0, 0, 0, 0},
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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(`histogram_quantile(scalar-phi)`, func(t *testing.T) {
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t.Parallel()
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q := `histogram_quantile(time() / 2 / 1e3, label_set(100, "le", "200"))`
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@ -447,7 +447,15 @@ func transformHistogramQuantile(tfa *transformFuncArg) ([]*timeseries, error) {
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vPrev = v
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}
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}
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if len(xss) == 0 {
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vLast := nan
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for len(xss) > 0 {
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vLast = xss[len(xss)-1].ts.Values[i]
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if !math.IsNaN(vLast) {
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break
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}
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xss = xss[:len(xss)-1]
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}
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if vLast == 0 || math.IsNaN(vLast) {
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return nan
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}
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if phi < 0 {
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@ -456,10 +464,6 @@ func transformHistogramQuantile(tfa *transformFuncArg) ([]*timeseries, error) {
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if phi > 1 {
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return inf
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}
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vLast := xss[len(xss)-1].ts.Values[i]
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if vLast == 0 {
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return nan
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}
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vReq := vLast * phi
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vPrev = 0
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lePrev := float64(0)
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@ -471,6 +475,11 @@ func transformHistogramQuantile(tfa *transformFuncArg) ([]*timeseries, error) {
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continue
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}
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le := xs.le
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if v <= 0 {
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// Skip zero buckets.
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lePrev = le
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continue
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}
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if v < vReq {
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vPrev = v
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lePrev = le
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