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Merge pull request #1092 from prometheus/beorn7/histogram 

histograms: Move to new exposition protobuf format
This commit is contained in:
Björn Rabenstein 2022-07-20 13:26:40 +02:00 committed by GitHub
parent 6141a0784e 8cbcd4076a
commit ec86ef1833
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 59 additions and 55 deletions
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2
go.mod
View File

@ -8,7 +8,7 @@ require (
github.com/davecgh/go-spew v1.1.1 github.com/davecgh/go-spew v1.1.1
github.com/golang/protobuf v1.5.2 github.com/golang/protobuf v1.5.2
github.com/json-iterator/go v1.1.12 github.com/json-iterator/go v1.1.12
github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064 github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e
github.com/prometheus/common v0.35.0 github.com/prometheus/common v0.35.0
github.com/prometheus/procfs v0.7.3 github.com/prometheus/procfs v0.7.3
golang.org/x/sys v0.0.0-20220520151302-bc2c85ada10a golang.org/x/sys v0.0.0-20220520151302-bc2c85ada10a

4
go.sum
View File

@ -135,8 +135,8 @@ github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZb
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4= github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA= github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
github.com/prometheus/client_model v0.2.0/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA= github.com/prometheus/client_model v0.2.0/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064 h1:Kyx21CLOfWDA4e2TcOcupRl2g/Bmddu0AL0hR1BldEw= github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e h1:KjoQdMEQmNC8smQ731iHAXnbFbApg4uu60fNcWHs3Bk=
github.com/prometheus/client_model v0.2.1-0.20210624201024-61b6c1aac064/go.mod h1:LDGWKZIo7rky3hgvBe+caln+Dr3dPggB5dvjtD7w9+w= github.com/prometheus/client_model v0.2.1-0.20220719122737-1f8dcad1221e/go.mod h1:LDGWKZIo7rky3hgvBe+caln+Dr3dPggB5dvjtD7w9+w=
github.com/prometheus/common v0.35.0 h1:Eyr+Pw2VymWejHqCugNaQXkAi6KayVNxaHeu6khmFBE= github.com/prometheus/common v0.35.0 h1:Eyr+Pw2VymWejHqCugNaQXkAi6KayVNxaHeu6khmFBE=
github.com/prometheus/common v0.35.0/go.mod h1:phzohg0JFMnBEFGxTDbfu3QyL5GI8gTQJFhYO5B3mfA= github.com/prometheus/common v0.35.0/go.mod h1:phzohg0JFMnBEFGxTDbfu3QyL5GI8gTQJFhYO5B3mfA=
github.com/prometheus/procfs v0.7.3 h1:4jVXhlkAyzOScmCkXBTOLRLTz8EeU+eyjrwB/EPq0VU= github.com/prometheus/procfs v0.7.3 h1:4jVXhlkAyzOScmCkXBTOLRLTz8EeU+eyjrwB/EPq0VU=

58
prometheus/histogram.go
View File

@ -382,19 +382,20 @@ type HistogramOpts struct {
Buckets []float64 Buckets []float64
// If SparseBucketsFactor is greater than one, sparse buckets are used // If SparseBucketsFactor is greater than one, sparse buckets are used
// (in addition to the regular buckets, if defined above). Sparse // (in addition to the regular buckets, if defined above). A histogram
// buckets are exponential buckets covering the whole float64 range // with sparse buckets will be ingested as a native histogram by a
// (with the exception of the “zero” bucket, see // Prometheus server with that feature enable. Sparse buckets are
// SparseBucketsZeroThreshold below). From any one bucket to the next, // exponential buckets covering the whole float64 range (with the
// the width of the bucket grows by a constant factor. // exception of the “zero” bucket, see SparseBucketsZeroThreshold
// SparseBucketsFactor provides an upper bound for this factor // below). From any one bucket to the next, the width of the bucket
// (exception see below). The smaller SparseBucketsFactor, the more // grows by a constant factor. SparseBucketsFactor provides an upper
// buckets will be used and thus the more costly the histogram will // bound for this factor (exception see below). The smaller
// become. A generally good trade-off between cost and accuracy is a // SparseBucketsFactor, the more buckets will be used and thus the more
// value of 1.1 (each bucket is at most 10% wider than the previous // costly the histogram will become. A generally good trade-off between
// one), which will result in each power of two divided into 8 buckets // cost and accuracy is a value of 1.1 (each bucket is at most 10% wider
// (e.g. there will be 8 buckets between 1 and 2, same as between 2 and // than the previous one), which will result in each power of two
// 4, and 4 and 8, etc.). // divided into 8 buckets (e.g. there will be 8 buckets between 1 and 2,
// same as between 2 and 4, and 4 and 8, etc.).
// //
// Details about the actually used factor: The factor is calculated as // Details about the actually used factor: The factor is calculated as
// 2^(2^n), where n is an integer number between (and including) -8 and // 2^(2^n), where n is an integer number between (and including) -8 and
@ -723,8 +724,8 @@ func (h *histogram) Write(out *dto.Metric) error {
his.Bucket = append(his.Bucket, b) his.Bucket = append(his.Bucket, b)
} }
if h.sparseSchema > math.MinInt32 { if h.sparseSchema > math.MinInt32 {
his.SbZeroThreshold = proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sparseZeroThresholdBits))) his.ZeroThreshold = proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sparseZeroThresholdBits)))
his.SbSchema = proto.Int32(atomic.LoadInt32(&coldCounts.sparseSchema)) his.Schema = proto.Int32(atomic.LoadInt32(&coldCounts.sparseSchema))
zeroBucket := atomic.LoadUint64(&coldCounts.sparseZeroBucket) zeroBucket := atomic.LoadUint64(&coldCounts.sparseZeroBucket)
defer func() { defer func() {
@ -732,9 +733,9 @@ func (h *histogram) Write(out *dto.Metric) error {
coldCounts.sparseBucketsNegative.Range(addAndReset(&hotCounts.sparseBucketsNegative, &hotCounts.sparseBucketsNumber)) coldCounts.sparseBucketsNegative.Range(addAndReset(&hotCounts.sparseBucketsNegative, &hotCounts.sparseBucketsNumber))
}() }()
his.SbZeroCount = proto.Uint64(zeroBucket) his.ZeroCount = proto.Uint64(zeroBucket)
his.SbNegative = makeSparseBuckets(&coldCounts.sparseBucketsNegative) his.NegativeSpan, his.NegativeDelta = makeSparseBuckets(&coldCounts.sparseBucketsNegative)
his.SbPositive = makeSparseBuckets(&coldCounts.sparseBucketsPositive) his.PositiveSpan, his.PositiveDelta = makeSparseBuckets(&coldCounts.sparseBucketsPositive)
} }
addAndResetCounts(hotCounts, coldCounts) addAndResetCounts(hotCounts, coldCounts)
return nil return nil
@ -1235,7 +1236,7 @@ func pickSparseSchema(bucketFactor float64) int32 {
} }
} }
func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets { func makeSparseBuckets(buckets *sync.Map) ([]*dto.BucketSpan, []int64) {
var ii []int var ii []int
buckets.Range(func(k, v interface{}) bool { buckets.Range(func(k, v interface{}) bool {
ii = append(ii, k.(int)) ii = append(ii, k.(int))
@ -1244,16 +1245,19 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
sort.Ints(ii) sort.Ints(ii)
if len(ii) == 0 { if len(ii) == 0 {
return nil return nil, nil
} }
sbs := dto.SparseBuckets{} var (
var prevCount int64 spans []*dto.BucketSpan
var nextI int deltas []int64
prevCount int64
nextI int
)
appendDelta := func(count int64) { appendDelta := func(count int64) {
*sbs.Span[len(sbs.Span)-1].Length++ *spans[len(spans)-1].Length++
sbs.Delta = append(sbs.Delta, count-prevCount) deltas = append(deltas, count-prevCount)
prevCount = count prevCount = count
} }
@ -1270,7 +1274,7 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
// We have to create a new span, either because we are // We have to create a new span, either because we are
// at the very beginning, or because we have found a gap // at the very beginning, or because we have found a gap
// of more than two buckets. // of more than two buckets.
sbs.Span = append(sbs.Span, &dto.SparseBuckets_Span{ spans = append(spans, &dto.BucketSpan{
Offset: proto.Int32(iDelta), Offset: proto.Int32(iDelta),
Length: proto.Uint32(0), Length: proto.Uint32(0),
}) })
@ -1284,7 +1288,7 @@ func makeSparseBuckets(buckets *sync.Map) *dto.SparseBuckets {
appendDelta(count) appendDelta(count)
nextI = i + 1 nextI = i + 1
} }
return &sbs return spans, deltas
} }
// addToSparseBucket increments the sparse bucket at key by the provided // addToSparseBucket increments the sparse bucket at key by the provided

50
prometheus/histogram_test.go
View File

@ -490,13 +490,13 @@ func TestSparseHistogram(t *testing.T) {
name: "factor 1.1 results in schema 3", name: "factor 1.1 results in schema 3",
observations: []float64{0, 1, 2, 3}, observations: []float64{0, 1, 2, 3},
factor: 1.1, 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 > `, 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 `,
}, },
{ {
name: "factor 1.2 results in schema 2", name: "factor 1.2 results in schema 2",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2}, observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2, 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 > `, 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 `,
}, },
{ {
name: "factor 4 results in schema -1", name: "factor 4 results in schema -1",
@ -507,7 +507,7 @@ func TestSparseHistogram(t *testing.T) {
33.33, // Bucket 3: (16, 64] 33.33, // Bucket 3: (16, 64]
}, },
factor: 4, factor: 4,
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 > `, 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 `,
}, },
{ {
name: "factor 17 results in schema -2", name: "factor 17 results in schema -2",
@ -517,58 +517,58 @@ func TestSparseHistogram(t *testing.T) {
33.33, // Bucket 2: (16, 256] 33.33, // Bucket 2: (16, 256]
}, },
factor: 17, factor: 17,
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 > `, 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 `,
}, },
{ {
name: "negative buckets", name: "negative buckets",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2}, observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
factor: 1.2, 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 > `, 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: "negative and positive buckets", name: "negative and positive buckets",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2}, observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2, 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 > `, 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 `,
}, },
{ {
name: "wide zero bucket", name: "wide zero bucket",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2}, observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2, factor: 1.2,
zeroThreshold: 1.4, 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 > `, 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 `,
}, },
{ {
name: "NaN observation", name: "NaN observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()}, observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()},
factor: 1.2, 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 > `, 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 `,
}, },
{ {
name: "+Inf observation", name: "+Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)}, observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
factor: 1.2, 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 > `, 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 `,
}, },
{ {
name: "-Inf observation", name: "-Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)}, observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
factor: 1.2, 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 > `, 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 `,
}, },
{ {
name: "limited buckets but nothing triggered", name: "limited buckets but nothing triggered",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2}, observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
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 > `, 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 `,
}, },
{ {
name: "buckets limited by halving resolution", name: "buckets limited by halving resolution",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3}, observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3},
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
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 > `, 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 `,
}, },
{ {
name: "buckets limited by widening the zero bucket", name: "buckets limited by widening the zero bucket",
@ -576,7 +576,7 @@ func TestSparseHistogram(t *testing.T) {
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, maxZeroThreshold: 1.2,
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 > `, 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 `,
}, },
{ {
name: "buckets limited by widening the zero bucket twice", name: "buckets limited by widening the zero bucket twice",
@ -584,7 +584,7 @@ func TestSparseHistogram(t *testing.T) {
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, maxZeroThreshold: 1.2,
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 > `, 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 `,
}, },
{ {
name: "buckets limited by reset", name: "buckets limited by reset",
@ -593,21 +593,21 @@ func TestSparseHistogram(t *testing.T) {
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, maxZeroThreshold: 1.2,
minResetDuration: 5 * time.Minute, 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_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: "limited buckets but nothing triggered, negative observations", name: "limited buckets but nothing triggered, negative observations",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2}, observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
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 > `, 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", name: "buckets limited by halving resolution, negative observations",
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3}, observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3},
factor: 1.2, factor: 1.2,
maxBuckets: 4, 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", name: "buckets limited by widening the zero bucket, negative observations",
@ -615,7 +615,7 @@ func TestSparseHistogram(t *testing.T) {
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, 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", name: "buckets limited by widening the zero bucket twice, negative observations",
@ -623,7 +623,7 @@ func TestSparseHistogram(t *testing.T) {
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, 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", name: "buckets limited by reset, negative observations",
@ -632,7 +632,7 @@ func TestSparseHistogram(t *testing.T) {
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, maxZeroThreshold: 1.2,
minResetDuration: 5 * time.Minute, 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", name: "buckets limited by halving resolution, then reset",
@ -640,7 +640,7 @@ func TestSparseHistogram(t *testing.T) {
factor: 1.2, factor: 1.2,
maxBuckets: 4, maxBuckets: 4,
minResetDuration: 9 * time.Minute, 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", name: "buckets limited by widening the zero bucket, then reset",
@ -649,7 +649,7 @@ func TestSparseHistogram(t *testing.T) {
maxBuckets: 4, maxBuckets: 4,
maxZeroThreshold: 1.2, maxZeroThreshold: 1.2,
minResetDuration: 9 * time.Minute, 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) // t.Errorf("got sample sum %f, want %f", got, want)
// } // }
sumBuckets := int(m.Histogram.GetSbZeroCount()) sumBuckets := int(m.Histogram.GetZeroCount())
current := 0 current := 0
for _, delta := range m.Histogram.GetSbNegative().GetDelta() { for _, delta := range m.Histogram.GetNegativeDelta() {
current += int(delta) current += int(delta)
if current < 0 { if current < 0 {
t.Fatalf("negative bucket population negative: %d", current) t.Fatalf("negative bucket population negative: %d", current)
@ -764,7 +764,7 @@ func TestSparseHistogramConcurrency(t *testing.T) {
sumBuckets += current sumBuckets += current
} }
current = 0 current = 0
for _, delta := range m.Histogram.GetSbPositive().GetDelta() { for _, delta := range m.Histogram.GetPositiveDelta() {
current += int(delta) current += int(delta)
if current < 0 { if current < 0 {
t.Fatalf("positive bucket population negative: %d", current) t.Fatalf("positive bucket population negative: %d", current)