Merge pull request #1092 from prometheus/beorn7/histogram
histograms: Move to new exposition protobuf format
This commit is contained in:
Björn Rabenstein
GitHub
commit
ec86ef1833
2
go.mod
2
go.mod
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@ -8,7 +8,7 @@ require (
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github.com/davecgh/go-spew v1.1.1
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github.com/golang/protobuf v1.5.2
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github.com/json-iterator/go v1.1.12
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github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064
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github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e
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github.com/prometheus/common v0.35.0
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github.com/prometheus/procfs v0.7.3
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golang.org/x/sys v0.0.0-20220520151302-bc2c85ada10a
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4
go.sum
4
go.sum
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@ -135,8 +135,8 @@ github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZb
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github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
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github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
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github.com/prometheus/client_model v0.2.0/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
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github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064 h1:Kyx21CLOfWDA4e2TcOcupRl2g/Bmddu0AL0hR1BldEw=
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github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064/go.mod h1:LDGWKZIo7rky3hgvBe+caln+Dr3dPggB5dvjtD7w9+w=
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github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e h1:KjoQdMEQmNC8smQ731iHAXnbFbApg4uu60fNcWHs3Bk=
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github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e/go.mod h1:LDGWKZIo7rky3hgvBe+caln+Dr3dPggB5dvjtD7w9+w=
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github.com/prometheus/common v0.35.0 h1:Eyr+Pw2VymWejHqCugNaQXkAi6KayVNxaHeu6khmFBE=
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github.com/prometheus/common v0.35.0/go.mod h1:phzohg0JFMnBEFGxTDbfu3QyL5GI8gTQJFhYO5B3mfA=
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github.com/prometheus/procfs v0.7.3 h1:4jVXhlkAyzOScmCkXBTOLRLTz8EeU+eyjrwB/EPq0VU=
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@ -382,19 +382,20 @@ type HistogramOpts struct {
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Buckets []float64
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// If SparseBucketsFactor is greater than one, sparse buckets are used
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// (in addition to the regular buckets, if defined above). Sparse
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// buckets are exponential buckets covering the whole float64 range
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// (with the exception of the “zero” bucket, see
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// SparseBucketsZeroThreshold below). From any one bucket to the next,
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// the width of the bucket grows by a constant factor.
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// SparseBucketsFactor provides an upper bound for this factor
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// (exception see below). The smaller SparseBucketsFactor, the more
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// buckets will be used and thus the more costly the histogram will
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// become. A generally good trade-off between cost and accuracy is a
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// value of 1.1 (each bucket is at most 10% wider than the previous
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// one), which will result in each power of two divided into 8 buckets
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// (e.g. there will be 8 buckets between 1 and 2, same as between 2 and
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// 4, and 4 and 8, etc.).
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// (in addition to the regular buckets, if defined above). A histogram
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// with sparse buckets will be ingested as a native histogram by a
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// Prometheus server with that feature enable. Sparse buckets are
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// exponential buckets covering the whole float64 range (with the
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// exception of the “zero” bucket, see SparseBucketsZeroThreshold
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// below). From any one bucket to the next, the width of the bucket
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// grows by a constant factor. SparseBucketsFactor provides an upper
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// bound for this factor (exception see below). The smaller
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// SparseBucketsFactor, the more buckets will be used and thus the more
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// costly the histogram will become. A generally good trade-off between
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// cost and accuracy is a value of 1.1 (each bucket is at most 10% wider
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// than the previous one), which will result in each power of two
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// divided into 8 buckets (e.g. there will be 8 buckets between 1 and 2,
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// same as between 2 and 4, and 4 and 8, etc.).
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//
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// Details about the actually used factor: The factor is calculated as
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// 2^(2^n), where n is an integer number between (and including) -8 and
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@ -723,8 +724,8 @@ func (h *histogram) Write(out *dto.Metric) error {
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his.Bucket = append(his.Bucket, b)
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}
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if h.sparseSchema > math.MinInt32 {
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his.SbZeroThreshold = proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sparseZeroThresholdBits)))
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his.SbSchema = proto.Int32(atomic.LoadInt32(&coldCounts.sparseSchema))
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his.ZeroThreshold = proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sparseZeroThresholdBits)))
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his.Schema = proto.Int32(atomic.LoadInt32(&coldCounts.sparseSchema))
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zeroBucket := atomic.LoadUint64(&coldCounts.sparseZeroBucket)
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defer func() {
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@ -732,9 +733,9 @@ func (h *histogram) Write(out *dto.Metric) error {
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coldCounts.sparseBucketsNegative.Range(addAndReset(&hotCounts.sparseBucketsNegative, &hotCounts.sparseBucketsNumber))
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}()
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his.SbZeroCount = proto.Uint64(zeroBucket)
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his.SbNegative = makeSparseBuckets(&coldCounts.sparseBucketsNegative)
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his.SbPositive = makeSparseBuckets(&coldCounts.sparseBucketsPositive)
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his.ZeroCount = proto.Uint64(zeroBucket)
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his.NegativeSpan, his.NegativeDelta = makeSparseBuckets(&coldCounts.sparseBucketsNegative)
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his.PositiveSpan, his.PositiveDelta = makeSparseBuckets(&coldCounts.sparseBucketsPositive)
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}
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addAndResetCounts(hotCounts, coldCounts)
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return nil
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@ -1235,7 +1236,7 @@ func pickSparseSchema(bucketFactor float64) int32 {
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}
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}
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func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
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func makeSparseBuckets(buckets *sync.Map) ([]*dto.BucketSpan, []int64) {
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var ii []int
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buckets.Range(func(k, v interface{}) bool {
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ii = append(ii, k.(int))
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@ -1244,16 +1245,19 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
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sort.Ints(ii)
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if len(ii) == 0 {
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return nil
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return nil, nil
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}
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sbs := dto.SparseBuckets{}
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var prevCount int64
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var nextI int
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var (
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spans []*dto.BucketSpan
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deltas []int64
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prevCount int64
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nextI int
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)
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appendDelta := func(count int64) {
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*sbs.Span[len(sbs.Span)-1].Length++
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sbs.Delta = append(sbs.Delta, count-prevCount)
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*spans[len(spans)-1].Length++
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deltas = append(deltas, count-prevCount)
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prevCount = count
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}
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@ -1270,7 +1274,7 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
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// We have to create a new span, either because we are
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// at the very beginning, or because we have found a gap
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// of more than two buckets.
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sbs.Span = append(sbs.Span, &dto.SparseBuckets_Span{
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spans = append(spans, &dto.BucketSpan{
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Offset: proto.Int32(iDelta),
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Length: proto.Uint32(0),
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})
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@ -1284,7 +1288,7 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
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appendDelta(count)
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nextI = i + 1
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}
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return &sbs
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return spans, deltas
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}
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// addToSparseBucket increments the sparse bucket at key by the provided
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@ -490,13 +490,13 @@ func TestSparseHistogram(t *testing.T) {
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name: "factor 1.1 results in schema 3",
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observations: []float64{0, 1, 2, 3},
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factor: 1.1,
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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 > `,
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want: `sample_count:4 sample_sum:6 schema:3 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:1 > positive_span:<offset:7 length:1 > positive_span:<offset:4 length:1 > positive_delta:1 positive_delta:0 positive_delta:0 `,
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},
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{
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name: "factor 1.2 results in schema 2",
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observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
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factor: 1.2,
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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 > `,
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want: `sample_count:6 sample_sum:7.4 schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
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},
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{
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name: "factor 4 results in schema -1",
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@ -507,7 +507,7 @@ func TestSparseHistogram(t *testing.T) {
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33.33, // Bucket 3: (16, 64]
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},
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factor: 4,
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want: `sample_count:10 sample_sum:62.83 sb_schema:-1 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_positive:<span:<offset:0 length:4 > delta:2 delta:2 delta:-1 delta:-2 > `,
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want: `sample_count:10 sample_sum:62.83 schema:-1 zero_threshold:2.938735877055719e-39 zero_count:0 positive_span:<offset:0 length:4 > positive_delta:2 positive_delta:2 positive_delta:-1 positive_delta:-2 `,
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},
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{
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name: "factor 17 results in schema -2",
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@ -517,58 +517,58 @@ func TestSparseHistogram(t *testing.T) {
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33.33, // Bucket 2: (16, 256]
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},
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factor: 17,
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want: `sample_count:10 sample_sum:62.83 sb_schema:-2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_positive:<span:<offset:0 length:3 > delta:2 delta:5 delta:-6 > `,
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want: `sample_count:10 sample_sum:62.83 schema:-2 zero_threshold:2.938735877055719e-39 zero_count:0 positive_span:<offset:0 length:3 > positive_delta:2 positive_delta:5 positive_delta:-6 `,
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},
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{
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name: "negative buckets",
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observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
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factor: 1.2,
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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 > `,
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want: `sample_count:6 sample_sum:-7.4 schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:0 length:5 > negative_delta:1 negative_delta:-1 negative_delta:2 negative_delta:-2 negative_delta:2 `,
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},
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{
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name: "negative and positive buckets",
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observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
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factor: 1.2,
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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 > `,
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want: `sample_count:11 sample_sum:0 schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:0 length:5 > negative_delta:1 negative_delta:-1 negative_delta:2 negative_delta:-2 negative_delta:2 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
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},
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{
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name: "wide zero bucket",
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observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
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factor: 1.2,
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zeroThreshold: 1.4,
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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 > `,
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want: `sample_count:11 sample_sum:0 schema:2 zero_threshold:1.4 zero_count:7 negative_span:<offset:4 length:1 > negative_delta:2 positive_span:<offset:4 length:1 > positive_delta:2 `,
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},
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{
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name: "NaN observation",
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observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()},
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factor: 1.2,
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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 > `,
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want: `sample_count:7 sample_sum:nan schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
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},
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{
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name: "+Inf observation",
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observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
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factor: 1.2,
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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 > `,
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want: `sample_count:7 sample_sum:inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_span:<offset:2147483642 length:1 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 positive_delta:-1 `,
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},
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{
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name: "-Inf observation",
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observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
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factor: 1.2,
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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 > `,
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want: `sample_count:7 sample_sum:-inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:2147483647 length:1 > negative_delta:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
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},
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{
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name: "limited buckets but nothing triggered",
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observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
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factor: 1.2,
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maxBuckets: 4,
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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 > `,
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want: `sample_count:6 sample_sum:7.4 schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
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},
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{
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name: "buckets limited by halving resolution",
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observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3},
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factor: 1.2,
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maxBuckets: 4,
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want: `sample_count:8 sample_sum:11.5 sb_schema:1 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > delta:1 delta:2 delta:-1 delta:-2 delta:1 > `,
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want: `sample_count:8 sample_sum:11.5 schema:1 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:2 positive_delta:-1 positive_delta:-2 positive_delta:1 `,
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},
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{
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name: "buckets limited by widening the zero bucket",
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@ -576,7 +576,7 @@ func TestSparseHistogram(t *testing.T) {
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factor: 1.2,
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maxBuckets: 4,
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maxZeroThreshold: 1.2,
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want: `sample_count:8 sample_sum:11.5 sb_schema:2 sb_zero_threshold:1 sb_zero_count:2 sb_positive:<span:<offset:1 length:7 > delta:1 delta:1 delta:-2 delta:2 delta:-2 delta:0 delta:1 > `,
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want: `sample_count:8 sample_sum:11.5 schema:2 zero_threshold:1 zero_count:2 positive_span:<offset:1 length:7 > positive_delta:1 positive_delta:1 positive_delta:-2 positive_delta:2 positive_delta:-2 positive_delta:0 positive_delta:1 `,
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},
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{
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name: "buckets limited by widening the zero bucket twice",
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@ -584,7 +584,7 @@ func TestSparseHistogram(t *testing.T) {
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factor: 1.2,
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maxBuckets: 4,
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maxZeroThreshold: 1.2,
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want: `sample_count:9 sample_sum:15.5 sb_schema:2 sb_zero_threshold:1.189207115002721 sb_zero_count:3 sb_positive:<span:<offset:2 length:7 > delta:2 delta:-2 delta:2 delta:-2 delta:0 delta:1 delta:0 > `,
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want: `sample_count:9 sample_sum:15.5 schema:2 zero_threshold:1.189207115002721 zero_count:3 positive_span:<offset:2 length:7 > positive_delta:2 positive_delta:-2 positive_delta:2 positive_delta:-2 positive_delta:0 positive_delta:1 positive_delta:0 `,
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},
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{
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name: "buckets limited by reset",
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@ -593,21 +593,21 @@ func TestSparseHistogram(t *testing.T) {
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maxBuckets: 4,
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maxZeroThreshold: 1.2,
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minResetDuration: 5 * time.Minute,
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want: `sample_count:2 sample_sum:7 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_positive:<span:<offset:7 length:2 > delta:1 delta:0 > `,
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want: `sample_count:2 sample_sum:7 schema:2 zero_threshold:2.938735877055719e-39 zero_count:0 positive_span:<offset:7 length:2 > positive_delta:1 positive_delta:0 `,
|
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},
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{
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name: "limited buckets but nothing triggered, negative observations",
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observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
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factor: 1.2,
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maxBuckets: 4,
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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 > `,
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want: `sample_count:6 sample_sum:-7.4 schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:0 length:5 > negative_delta:1 negative_delta:-1 negative_delta:2 negative_delta:-2 negative_delta:2 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by halving resolution, negative observations",
|
||||
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3},
|
||||
factor: 1.2,
|
||||
maxBuckets: 4,
|
||||
want: `sample_count:8 sample_sum:-11.5 sb_schema:1 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:0 length:5 > delta:1 delta:2 delta:-1 delta:-2 delta:1 > `,
|
||||
want: `sample_count:8 sample_sum:-11.5 schema:1 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:0 length:5 > negative_delta:1 negative_delta:2 negative_delta:-1 negative_delta:-2 negative_delta:1 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by widening the zero bucket, negative observations",
|
||||
|
|
@ -615,7 +615,7 @@ func TestSparseHistogram(t *testing.T) {
|
|||
factor: 1.2,
|
||||
maxBuckets: 4,
|
||||
maxZeroThreshold: 1.2,
|
||||
want: `sample_count:8 sample_sum:-11.5 sb_schema:2 sb_zero_threshold:1 sb_zero_count:2 sb_negative:<span:<offset:1 length:7 > delta:1 delta:1 delta:-2 delta:2 delta:-2 delta:0 delta:1 > `,
|
||||
want: `sample_count:8 sample_sum:-11.5 schema:2 zero_threshold:1 zero_count:2 negative_span:<offset:1 length:7 > negative_delta:1 negative_delta:1 negative_delta:-2 negative_delta:2 negative_delta:-2 negative_delta:0 negative_delta:1 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by widening the zero bucket twice, negative observations",
|
||||
|
|
@ -623,7 +623,7 @@ func TestSparseHistogram(t *testing.T) {
|
|||
factor: 1.2,
|
||||
maxBuckets: 4,
|
||||
maxZeroThreshold: 1.2,
|
||||
want: `sample_count:9 sample_sum:-15.5 sb_schema:2 sb_zero_threshold:1.189207115002721 sb_zero_count:3 sb_negative:<span:<offset:2 length:7 > delta:2 delta:-2 delta:2 delta:-2 delta:0 delta:1 delta:0 > `,
|
||||
want: `sample_count:9 sample_sum:-15.5 schema:2 zero_threshold:1.189207115002721 zero_count:3 negative_span:<offset:2 length:7 > negative_delta:2 negative_delta:-2 negative_delta:2 negative_delta:-2 negative_delta:0 negative_delta:1 negative_delta:0 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by reset, negative observations",
|
||||
|
|
@ -632,7 +632,7 @@ func TestSparseHistogram(t *testing.T) {
|
|||
maxBuckets: 4,
|
||||
maxZeroThreshold: 1.2,
|
||||
minResetDuration: 5 * time.Minute,
|
||||
want: `sample_count:2 sample_sum:-7 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_negative:<span:<offset:7 length:2 > delta:1 delta:0 > `,
|
||||
want: `sample_count:2 sample_sum:-7 schema:2 zero_threshold:2.938735877055719e-39 zero_count:0 negative_span:<offset:7 length:2 > negative_delta:1 negative_delta:0 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by halving resolution, then reset",
|
||||
|
|
@ -640,7 +640,7 @@ func TestSparseHistogram(t *testing.T) {
|
|||
factor: 1.2,
|
||||
maxBuckets: 4,
|
||||
minResetDuration: 9 * time.Minute,
|
||||
want: `sample_count:2 sample_sum:7 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_positive:<span:<offset:7 length:2 > delta:1 delta:0 > `,
|
||||
want: `sample_count:2 sample_sum:7 schema:2 zero_threshold:2.938735877055719e-39 zero_count:0 positive_span:<offset:7 length:2 > positive_delta:1 positive_delta:0 `,
|
||||
},
|
||||
{
|
||||
name: "buckets limited by widening the zero bucket, then reset",
|
||||
|
|
@ -649,7 +649,7 @@ func TestSparseHistogram(t *testing.T) {
|
|||
maxBuckets: 4,
|
||||
maxZeroThreshold: 1.2,
|
||||
minResetDuration: 9 * time.Minute,
|
||||
want: `sample_count:2 sample_sum:7 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:0 sb_positive:<span:<offset:7 length:2 > delta:1 delta:0 > `,
|
||||
want: `sample_count:2 sample_sum:7 schema:2 zero_threshold:2.938735877055719e-39 zero_count:0 positive_span:<offset:7 length:2 > positive_delta:1 positive_delta:0 `,
|
||||
},
|
||||
}
|
||||
|
||||
|
|
@ -754,9 +754,9 @@ func TestSparseHistogramConcurrency(t *testing.T) {
|
|||
// t.Errorf("got sample sum %f, want %f", got, want)
|
||||
// }
|
||||
|
||||
sumBuckets := int(m.Histogram.GetSbZeroCount())
|
||||
sumBuckets := int(m.Histogram.GetZeroCount())
|
||||
current := 0
|
||||
for _, delta := range m.Histogram.GetSbNegative().GetDelta() {
|
||||
for _, delta := range m.Histogram.GetNegativeDelta() {
|
||||
current += int(delta)
|
||||
if current < 0 {
|
||||
t.Fatalf("negative bucket population negative: %d", current)
|
||||
|
|
@ -764,7 +764,7 @@ func TestSparseHistogramConcurrency(t *testing.T) {
|
|||
sumBuckets += current
|
||||
}
|
||||
current = 0
|
||||
for _, delta := range m.Histogram.GetSbPositive().GetDelta() {
|
||||
for _, delta := range m.Histogram.GetPositiveDelta() {
|
||||
current += int(delta)
|
||||
if current < 0 {
|
||||
t.Fatalf("positive bucket population negative: %d", current)
|
||||
|
|
|
|||
Loading…
Reference in New Issue