add doc

Signed-off-by: jyz0309 <45495947@qq.com>

docs/querying/functions.md

@@ -192,7 +192,7 @@ bucket. Otherwise, the upper bound of the lowest bucket is returned
 for quantiles located in the lowest bucket.
 
 If `b` has 0 observations, `NaN` is returned. If `b` contains fewer than two buckets,
-`NaN` is returned. For φ < 0, `-Inf` is returned. For φ > 1, `+Inf` is returned.
+`NaN` is returned. For φ < 0, `-Inf` is returned. For φ > 1, `+Inf` is returned. For φ = `NaN`, `NaN` is returned.
 
 ## `holt_winters()`
 
@@ -456,4 +456,4 @@ The following are useful for converting between degrees and radians:
 
 - `deg(v instant-vector)`: converts radians to degrees for all elements in `v`.
 - `pi()`: returns pi.
-- `rad(v instant-vector)`: converts degrees to radians for all elements in `v`.
+- `rad(v instant-vector)`: converts degrees to radians for all elements in `v`.

docs/querying/operators.md

@@ -241,7 +241,7 @@ vector. `by` and `without` are only used to bucket the input vector.
 `quantile` calculates the φ-quantile, the value that ranks at number φ*N among
 the N metric values of the dimensions aggregated over. φ is provided as the
 aggregation parameter. For example, `quantile(0.5, ...)` calculates the median,
-`quantile(0.95, ...)` the 95th percentile.
+`quantile(0.95, ...)` the 95th percentile. For φ = `NaN`, `NaN` is returned. 
 
 Example:
 

promql/promql_test.go

@@ -34,18 +34,3 @@ func TestEvaluations(t *testing.T) {
 		})
 	}
 }
-
-func TestOne(t *testing.T) {
-	files, err := filepath.Glob("testdata/nan.test")
-	require.NoError(t, err)
-
-	for _, fn := range files {
-		t.Run(fn, func(t *testing.T) {
-			test, err := newTestFromFile(t, fn)
-			require.NoError(t, err)
-			require.NoError(t, test.Run())
-
-			test.Close()
-		})
-	}
-}

promql/quantile.go

@@ -67,11 +67,13 @@ type metricWithBuckets struct {
 //
 // If the highest bucket is not +Inf, NaN is returned.
 //
+// If q==NaN, NaN is returned.
+//
 // If q<0, -Inf is returned.
 //
 // If q>1, +Inf is returned.
 func bucketQuantile(q float64, buckets buckets) float64 {
-	if math.IsNaN(q){
+	if math.IsNaN(q) {
 		return math.NaN()
 	}
 	if q < 0 {
@@ -184,11 +186,12 @@ func ensureMonotonic(buckets buckets) {
 // quantile calculates the given quantile of a vector of samples.
 //
 // The Vector will be sorted.
-// If 'values' has zero elements or 'q' == NaN, NaN is returned.
+// If 'values' has zero elements
+// If q==NaN, NaN is returned.
 // If q<0, -Inf is returned.
 // If q>1, +Inf is returned.
 func quantile(q float64, values vectorByValueHeap) float64 {
-	if len(values) == 0 || q == math.NaN() {
+	if len(values) == 0 || math.IsNaN(q) {
 		return math.NaN()
 	}
 	if q < 0 {

promql/testdata/histograms.test

@@ -60,6 +60,11 @@ eval instant at 50m histogram_quantile(1.01, testhistogram_bucket)
 	{start="positive"} +Inf
 	{start="negative"} +Inf
 
+# Quantile invalid.
+eval instant at 50m histogram_quantile(NaN, testhistogram_bucket)
+	{start="positive"} NaN
+	{start="negative"} NaN
+
 # Quantile value in lowest bucket, which is positive.
 eval instant at 50m histogram_quantile(0, testhistogram_bucket{start="positive"})
 	{start="positive"} 0

promql/testdata/nan.test

@@ -1,21 +0,0 @@
-# Two histograms with 4 buckets each (x_sum and x_count not included,
-# only buckets). Lowest bucket for one histogram < 0, for the other >
-# 0. They have the same name, just separated by label. Not useful in
-# practice, but can happen (if clients change bucketing), and the
-# server has to cope with it.
-
-# Test histogram.
-load 5m
-	testhistogram_bucket{le="0.1", start="positive"}	0+5x10
-	testhistogram_bucket{le=".2", start="positive"}		0+7x10
-	testhistogram_bucket{le="1e0", start="positive"}	0+11x10
-	testhistogram_bucket{le="+Inf", start="positive"}	0+12x10
-	testhistogram_bucket{le="-.2", start="negative"}	0+1x10
-	testhistogram_bucket{le="-0.1", start="negative"}	0+2x10
-	testhistogram_bucket{le="0.3", start="negative"}	0+2x10
-	testhistogram_bucket{le="+Inf", start="negative"}	0+3x10
-
-
-# Quantile value in lowest bucket, which is positive.
-eval instant at 50m histogram_quantile(NaN, testhistogram_bucket{start="positive"})
-	{start="positive"} 0