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Add tests for sparse histogram 

Signed-off-by: beorn7 <beorn@grafana.com>
This commit is contained in:
beorn7 2021-06-23 21:56:26 +02:00
parent 31318b7523
commit 6c4e0ef740
2 changed files with 93 additions and 3 deletions
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6
prometheus/histogram.go
View File

@ -238,11 +238,11 @@ var DefBuckets = []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10}
// DefSparseBucketsZeroThreshold is the default value for
// SparseBucketsZeroThreshold in the HistogramOpts.
//
// The value is 2^-128 (or 0.5*2^-127 in the actual IEEE 754 representation),
// which is a bucket boundary at all possible resolutions.
const DefSparseBucketsZeroThreshold = 2.938735877055719e-39
// This is 2^-128 (or 0.5*2^-127 in the actual IEEE 754 representation), which
// is a bucket boundary at all possible resolutions.
var errBucketLabelNotAllowed = fmt.Errorf(
"%q is not allowed as label name in histograms", bucketLabel,
)

90
prometheus/histogram_test.go
View File

@ -456,3 +456,93 @@ func TestHistogramExemplar(t *testing.T) {
}
}
}
func TestSparseHistogram(t *testing.T) {
scenarios := []struct {
name string
observations []float64
factor float64
zeroThreshold float64
want string // String representation of protobuf.
}{
{
name: "no sparse buckets",
observations: []float64{1, 2, 3},
factor: 1,
want: `sample_count:3 sample_sum:6 bucket:<cumulative_count:0 upper_bound:0.005 > bucket:<cumulative_count:0 upper_bound:0.01 > bucket:<cumulative_count:0 upper_bound:0.025 > bucket:<cumulative_count:0 upper_bound:0.05 > bucket:<cumulative_count:0 upper_bound:0.1 > bucket:<cumulative_count:0 upper_bound:0.25 > bucket:<cumulative_count:0 upper_bound:0.5 > bucket:<cumulative_count:1 upper_bound:1 > bucket:<cumulative_count:2 upper_bound:2.5 > bucket:<cumulative_count:3 upper_bound:5 > bucket:<cumulative_count:3 upper_bound:10 > sb_schema:0 sb_zero_threshold:0 `, // Has conventional buckets because there are no sparse buckets.
},
{
name: "factor 1.1 results in schema 3",
observations: []float64{0, 1, 2, 3},
factor: 1.1,
want: `sample_count:4 sample_sum:6 sb_schema:3 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:1 > span:<offset:7 length:1 > span:<offset:4 length:1 > delta:1 delta:0 delta:0 > `,
},
{
name: "factor 1.2 results in schema 2",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2,
want: `sample_count:6 sample_sum:7.4 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
},
{
name: "negative buckets",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
factor: 1.2,
want: `sample_count:6 sample_sum:-7.4 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
},
{
name: "negative and positive buckets",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2,
want: `sample_count:11 sample_sum:0 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
},
{
name: "wide zero bucket",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2,
zeroThreshold: 1.4,
want: `sample_count:11 sample_sum:0 sb_schema:2 sb_zero_threshold:1.4 sb_zero_count:7 sb_negative:<span:<offset:4 length:1 > delta:2 > sb_positive:<span:<offset:4 length:1 > delta:2 > `,
},
{
name: "NaN observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()},
factor: 1.2,
want: `sample_count:7 sample_sum:nan sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
},
{
name: "+Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
factor: 1.2,
want: `sample_count:7 sample_sum:inf sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > span:<offset:2147483642 length:1 > delta:1 delta:-1 delta:2 delta:-2 delta:2 delta:-1 > `,
},
{
name: "-Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
factor: 1.2,
want: `sample_count:7 sample_sum:-inf sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:2147483647 length:1 > delta:1 > sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
},
}
for _, s := range scenarios {
t.Run(s.name, func(t *testing.T) {
his := NewHistogram(HistogramOpts{
Name: "name",
Help: "help",
SparseBucketsFactor: s.factor,
SparseBucketsZeroThreshold: s.zeroThreshold,
})
for _, o := range s.observations {
his.Observe(o)
}
m := &dto.Metric{}
if err := his.Write(m); err != nil {
t.Fatal("unexpected error writing metric", err)
}
got := m.Histogram.String()
if s.want != got {
t.Errorf("want histogram %q, got %q", s.want, got)
}
})
}
}