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Ignore +/- Inf and NaN for exponential histogram measurement (#4446)

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* Add acceptance test

* Ignore +/- Inf and NaN for expo hist record
This commit is contained in:
Tyler Yahn 2023-08-16 07:11:13 -07:00 committed by GitHub
parent d78820e905
commit a5ff7af3f3
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 55 additions and 9 deletions
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5
sdk/metric/internal/aggregate/exponential_histogram.go
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@ -113,6 +113,11 @@ func newExpoHistogramDataPoint[N int64 | float64](maxSize, maxScale int, noMinMa
// record adds a new measurement to the histogram. It will rescale the buckets if needed.
func (p *expoHistogramDataPoint[N]) record(v N) {
// Ignore NaN and infinity.
if math.IsInf(float64(v), 0) || math.IsNaN(float64(v)) {
return
}
p.count++
if !p.noMinMax {

59
sdk/metric/internal/aggregate/exponential_histogram_test.go
View File

@ -45,10 +45,10 @@ func withHandler(t *testing.T) func() {
func TestExpoHistogramDataPointRecord(t *testing.T) {
t.Run("float64", testExpoHistogramDataPointRecord[float64])
t.Run("float64 MinMaxSum", testExpoHistogramDataPointRecordMinMaxSum[float64])
t.Run("float64 MinMaxSum", testExpoHistogramDataPointRecordMinMaxSumFloat64)
t.Run("float64-2", testExpoHistogramDataPointRecordFloat64)
t.Run("int64", testExpoHistogramDataPointRecord[int64])
t.Run("int64 MinMaxSum", testExpoHistogramDataPointRecordMinMaxSum[int64])
t.Run("int64 MinMaxSum", testExpoHistogramDataPointRecordMinMaxSumInt64)
}
// TODO: This can be defined in the test after we drop support for go1.19.
@ -171,15 +171,15 @@ type expoHistogramDataPointRecordMinMaxSumTestCase[N int64 | float64] struct {
expected expectedMinMaxSum[N]
}
func testExpoHistogramDataPointRecordMinMaxSum[N int64 | float64](t *testing.T) {
testCases := []expoHistogramDataPointRecordMinMaxSumTestCase[N]{
func testExpoHistogramDataPointRecordMinMaxSumInt64(t *testing.T) {
testCases := []expoHistogramDataPointRecordMinMaxSumTestCase[int64]{
{
values: []N{2, 4, 1},
expected: expectedMinMaxSum[N]{1, 4, 7, 3},
values: []int64{2, 4, 1},
expected: expectedMinMaxSum[int64]{1, 4, 7, 3},
},
{
values: []N{4, 4, 4, 2, 16, 1},
expected: expectedMinMaxSum[N]{1, 16, 31, 6},
values: []int64{4, 4, 4, 2, 16, 1},
expected: expectedMinMaxSum[int64]{1, 16, 31, 6},
},
}
@ -188,7 +188,48 @@ func testExpoHistogramDataPointRecordMinMaxSum[N int64 | float64](t *testing.T)
restore := withHandler(t)
defer restore()
dp := newExpoHistogramDataPoint[N](4, 20, false, false)
dp := newExpoHistogramDataPoint[int64](4, 20, false, false)
for _, v := range tt.values {
dp.record(v)
}
assert.Equal(t, tt.expected.max, dp.max)
assert.Equal(t, tt.expected.min, dp.min)
assert.Equal(t, tt.expected.sum, dp.sum)
})
}
}
func testExpoHistogramDataPointRecordMinMaxSumFloat64(t *testing.T) {
testCases := []expoHistogramDataPointRecordMinMaxSumTestCase[float64]{
{
values: []float64{2, 4, 1},
expected: expectedMinMaxSum[float64]{1, 4, 7, 3},
},
{
values: []float64{2, 4, 1, math.Inf(1)},
expected: expectedMinMaxSum[float64]{1, 4, 7, 4},
},
{
values: []float64{2, 4, 1, math.Inf(-1)},
expected: expectedMinMaxSum[float64]{1, 4, 7, 4},
},
{
values: []float64{2, 4, 1, math.NaN()},
expected: expectedMinMaxSum[float64]{1, 4, 7, 4},
},
{
values: []float64{4, 4, 4, 2, 16, 1},
expected: expectedMinMaxSum[float64]{1, 16, 31, 6},
},
}
for _, tt := range testCases {
t.Run(fmt.Sprint(tt.values), func(t *testing.T) {
restore := withHandler(t)
defer restore()
dp := newExpoHistogramDataPoint[float64](4, 20, false, false)
for _, v := range tt.values {
dp.record(v)
}