/
metric.go
505 lines (455 loc) · 14.6 KB
/
metric.go
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
// Copyright The OpenTelemetry Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Package transform provides translations for opentelemetry-go concepts and
// structures to otlp structures.
package metrictransform // import "go.opentelemetry.io/otel/exporters/otlp/otlpmetric/internal/metrictransform"
import (
"context"
"errors"
"fmt"
"strings"
"sync"
"time"
"go.opentelemetry.io/otel/metric/number"
"go.opentelemetry.io/otel/sdk/instrumentation"
"go.opentelemetry.io/otel/sdk/metric/export"
"go.opentelemetry.io/otel/sdk/metric/export/aggregation"
"go.opentelemetry.io/otel/sdk/resource"
commonpb "go.opentelemetry.io/proto/otlp/common/v1"
metricpb "go.opentelemetry.io/proto/otlp/metrics/v1"
)
var (
// ErrUnimplementedAgg is returned when a transformation of an unimplemented
// aggregator is attempted.
ErrUnimplementedAgg = errors.New("unimplemented aggregator")
// ErrIncompatibleAgg is returned when
// aggregation.Kind implies an interface conversion that has
// failed
ErrIncompatibleAgg = errors.New("incompatible aggregation type")
// ErrUnknownValueType is returned when a transformation of an unknown value
// is attempted.
ErrUnknownValueType = errors.New("invalid value type")
// ErrContextCanceled is returned when a context cancellation halts a
// transformation.
ErrContextCanceled = errors.New("context canceled")
// ErrTransforming is returned when an unexected error is encountered transforming.
ErrTransforming = errors.New("transforming failed")
)
// result is the product of transforming Records into OTLP Metrics.
type result struct {
Metric *metricpb.Metric
Err error
}
// toNanos returns the number of nanoseconds since the UNIX epoch.
func toNanos(t time.Time) uint64 {
if t.IsZero() {
return 0
}
return uint64(t.UnixNano())
}
// InstrumentationLibraryReader transforms all records contained in a checkpoint into
// batched OTLP ResourceMetrics.
func InstrumentationLibraryReader(ctx context.Context, temporalitySelector aggregation.TemporalitySelector, res *resource.Resource, ilmr export.InstrumentationLibraryReader, numWorkers uint) (*metricpb.ResourceMetrics, error) {
var ilms []*metricpb.InstrumentationLibraryMetrics
err := ilmr.ForEach(func(lib instrumentation.Library, mr export.Reader) error {
records, errc := source(ctx, temporalitySelector, mr)
// Start a fixed number of goroutines to transform records.
transformed := make(chan result)
var wg sync.WaitGroup
wg.Add(int(numWorkers))
for i := uint(0); i < numWorkers; i++ {
go func() {
defer wg.Done()
transformer(ctx, temporalitySelector, records, transformed)
}()
}
go func() {
wg.Wait()
close(transformed)
}()
// Synchronously collect the transformed records and transmit.
ms, err := sink(ctx, transformed)
if err != nil {
return nil
}
// source is complete, check for any errors.
if err := <-errc; err != nil {
return err
}
if len(ms) == 0 {
return nil
}
ilms = append(ilms, &metricpb.InstrumentationLibraryMetrics{
Metrics: ms,
SchemaUrl: lib.SchemaURL,
InstrumentationLibrary: &commonpb.InstrumentationLibrary{
Name: lib.Name,
Version: lib.Version,
},
})
return nil
})
if len(ilms) == 0 {
return nil, err
}
rms := &metricpb.ResourceMetrics{
Resource: Resource(res),
SchemaUrl: res.SchemaURL(),
InstrumentationLibraryMetrics: ilms,
}
return rms, err
}
// source starts a goroutine that sends each one of the Records yielded by
// the Reader on the returned chan. Any error encountered will be sent
// on the returned error chan after seeding is complete.
func source(ctx context.Context, temporalitySelector aggregation.TemporalitySelector, mr export.Reader) (<-chan export.Record, <-chan error) {
errc := make(chan error, 1)
out := make(chan export.Record)
// Seed records into process.
go func() {
defer close(out)
// No select is needed since errc is buffered.
errc <- mr.ForEach(temporalitySelector, func(r export.Record) error {
select {
case <-ctx.Done():
return ErrContextCanceled
case out <- r:
}
return nil
})
}()
return out, errc
}
// transformer transforms records read from the passed in chan into
// OTLP Metrics which are sent on the out chan.
func transformer(ctx context.Context, temporalitySelector aggregation.TemporalitySelector, in <-chan export.Record, out chan<- result) {
for r := range in {
m, err := Record(temporalitySelector, r)
// Propagate errors, but do not send empty results.
if err == nil && m == nil {
continue
}
res := result{
Metric: m,
Err: err,
}
select {
case <-ctx.Done():
return
case out <- res:
}
}
}
// sink collects transformed Records and batches them.
//
// Any errors encountered transforming input will be reported with an
// ErrTransforming as well as the completed ResourceMetrics. It is up to the
// caller to handle any incorrect data in these ResourceMetric.
func sink(ctx context.Context, in <-chan result) ([]*metricpb.Metric, error) {
var errStrings []string
// Group by the MetricDescriptor.
grouped := map[string]*metricpb.Metric{}
for res := range in {
if res.Err != nil {
errStrings = append(errStrings, res.Err.Error())
continue
}
mID := res.Metric.GetName()
m, ok := grouped[mID]
if !ok {
grouped[mID] = res.Metric
continue
}
// Note: There is extra work happening in this code
// that can be improved when the work described in
// #2119 is completed. The SDK has a guarantee that
// no more than one point per period per label set is
// produced, so this fallthrough should never happen.
// The final step of #2119 is to remove all the
// grouping logic here.
switch res.Metric.Data.(type) {
case *metricpb.Metric_Gauge:
m.GetGauge().DataPoints = append(m.GetGauge().DataPoints, res.Metric.GetGauge().DataPoints...)
case *metricpb.Metric_Sum:
m.GetSum().DataPoints = append(m.GetSum().DataPoints, res.Metric.GetSum().DataPoints...)
case *metricpb.Metric_Histogram:
m.GetHistogram().DataPoints = append(m.GetHistogram().DataPoints, res.Metric.GetHistogram().DataPoints...)
case *metricpb.Metric_Summary:
m.GetSummary().DataPoints = append(m.GetSummary().DataPoints, res.Metric.GetSummary().DataPoints...)
default:
err := fmt.Sprintf("unsupported metric type: %T", res.Metric.Data)
errStrings = append(errStrings, err)
}
}
if len(grouped) == 0 {
return nil, nil
}
ms := make([]*metricpb.Metric, 0, len(grouped))
for _, m := range grouped {
ms = append(ms, m)
}
// Report any transform errors.
if len(errStrings) > 0 {
return ms, fmt.Errorf("%w:\n -%s", ErrTransforming, strings.Join(errStrings, "\n -"))
}
return ms, nil
}
// Record transforms a Record into an OTLP Metric. An ErrIncompatibleAgg
// error is returned if the Record Aggregator is not supported.
func Record(temporalitySelector aggregation.TemporalitySelector, r export.Record) (*metricpb.Metric, error) {
agg := r.Aggregation()
switch agg.Kind() {
case aggregation.MinMaxSumCountKind:
mmsc, ok := agg.(aggregation.MinMaxSumCount)
if !ok {
return nil, fmt.Errorf("%w: %T", ErrIncompatibleAgg, agg)
}
return minMaxSumCount(r, mmsc)
case aggregation.HistogramKind:
h, ok := agg.(aggregation.Histogram)
if !ok {
return nil, fmt.Errorf("%w: %T", ErrIncompatibleAgg, agg)
}
return histogramPoint(r, temporalitySelector.TemporalityFor(r.Descriptor(), aggregation.HistogramKind), h)
case aggregation.SumKind:
s, ok := agg.(aggregation.Sum)
if !ok {
return nil, fmt.Errorf("%w: %T", ErrIncompatibleAgg, agg)
}
sum, err := s.Sum()
if err != nil {
return nil, err
}
return sumPoint(r, sum, r.StartTime(), r.EndTime(), temporalitySelector.TemporalityFor(r.Descriptor(), aggregation.SumKind), r.Descriptor().InstrumentKind().Monotonic())
case aggregation.LastValueKind:
lv, ok := agg.(aggregation.LastValue)
if !ok {
return nil, fmt.Errorf("%w: %T", ErrIncompatibleAgg, agg)
}
value, tm, err := lv.LastValue()
if err != nil {
return nil, err
}
return gaugePoint(r, value, time.Time{}, tm)
default:
return nil, fmt.Errorf("%w: %T", ErrUnimplementedAgg, agg)
}
}
func gaugePoint(record export.Record, num number.Number, start, end time.Time) (*metricpb.Metric, error) {
desc := record.Descriptor()
labels := record.Labels()
m := &metricpb.Metric{
Name: desc.Name(),
Description: desc.Description(),
Unit: string(desc.Unit()),
}
switch n := desc.NumberKind(); n {
case number.Int64Kind:
m.Data = &metricpb.Metric_Gauge{
Gauge: &metricpb.Gauge{
DataPoints: []*metricpb.NumberDataPoint{
{
Value: &metricpb.NumberDataPoint_AsInt{
AsInt: num.CoerceToInt64(n),
},
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(start),
TimeUnixNano: toNanos(end),
},
},
},
}
case number.Float64Kind:
m.Data = &metricpb.Metric_Gauge{
Gauge: &metricpb.Gauge{
DataPoints: []*metricpb.NumberDataPoint{
{
Value: &metricpb.NumberDataPoint_AsDouble{
AsDouble: num.CoerceToFloat64(n),
},
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(start),
TimeUnixNano: toNanos(end),
},
},
},
}
default:
return nil, fmt.Errorf("%w: %v", ErrUnknownValueType, n)
}
return m, nil
}
func sdkTemporalityToTemporality(temporality aggregation.Temporality) metricpb.AggregationTemporality {
switch temporality {
case aggregation.DeltaTemporality:
return metricpb.AggregationTemporality_AGGREGATION_TEMPORALITY_DELTA
case aggregation.CumulativeTemporality:
return metricpb.AggregationTemporality_AGGREGATION_TEMPORALITY_CUMULATIVE
}
return metricpb.AggregationTemporality_AGGREGATION_TEMPORALITY_UNSPECIFIED
}
func sumPoint(record export.Record, num number.Number, start, end time.Time, temporality aggregation.Temporality, monotonic bool) (*metricpb.Metric, error) {
desc := record.Descriptor()
labels := record.Labels()
m := &metricpb.Metric{
Name: desc.Name(),
Description: desc.Description(),
Unit: string(desc.Unit()),
}
switch n := desc.NumberKind(); n {
case number.Int64Kind:
m.Data = &metricpb.Metric_Sum{
Sum: &metricpb.Sum{
IsMonotonic: monotonic,
AggregationTemporality: sdkTemporalityToTemporality(temporality),
DataPoints: []*metricpb.NumberDataPoint{
{
Value: &metricpb.NumberDataPoint_AsInt{
AsInt: num.CoerceToInt64(n),
},
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(start),
TimeUnixNano: toNanos(end),
},
},
},
}
case number.Float64Kind:
m.Data = &metricpb.Metric_Sum{
Sum: &metricpb.Sum{
IsMonotonic: monotonic,
AggregationTemporality: sdkTemporalityToTemporality(temporality),
DataPoints: []*metricpb.NumberDataPoint{
{
Value: &metricpb.NumberDataPoint_AsDouble{
AsDouble: num.CoerceToFloat64(n),
},
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(start),
TimeUnixNano: toNanos(end),
},
},
},
}
default:
return nil, fmt.Errorf("%w: %v", ErrUnknownValueType, n)
}
return m, nil
}
// minMaxSumCountValue returns the values of the MinMaxSumCount Aggregator
// as discrete values.
func minMaxSumCountValues(a aggregation.MinMaxSumCount) (min, max, sum number.Number, count uint64, err error) {
if min, err = a.Min(); err != nil {
return
}
if max, err = a.Max(); err != nil {
return
}
if sum, err = a.Sum(); err != nil {
return
}
if count, err = a.Count(); err != nil {
return
}
return
}
// minMaxSumCount transforms a MinMaxSumCount Aggregator into an OTLP Metric.
func minMaxSumCount(record export.Record, a aggregation.MinMaxSumCount) (*metricpb.Metric, error) {
desc := record.Descriptor()
labels := record.Labels()
min, max, sum, count, err := minMaxSumCountValues(a)
if err != nil {
return nil, err
}
m := &metricpb.Metric{
Name: desc.Name(),
Description: desc.Description(),
Unit: string(desc.Unit()),
Data: &metricpb.Metric_Summary{
Summary: &metricpb.Summary{
DataPoints: []*metricpb.SummaryDataPoint{
{
Sum: sum.CoerceToFloat64(desc.NumberKind()),
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(record.StartTime()),
TimeUnixNano: toNanos(record.EndTime()),
Count: uint64(count),
QuantileValues: []*metricpb.SummaryDataPoint_ValueAtQuantile{
{
Quantile: 0.0,
Value: min.CoerceToFloat64(desc.NumberKind()),
},
{
Quantile: 1.0,
Value: max.CoerceToFloat64(desc.NumberKind()),
},
},
},
},
},
},
}
return m, nil
}
func histogramValues(a aggregation.Histogram) (boundaries []float64, counts []uint64, err error) {
var buckets aggregation.Buckets
if buckets, err = a.Histogram(); err != nil {
return
}
boundaries, counts = buckets.Boundaries, buckets.Counts
if len(counts) != len(boundaries)+1 {
err = ErrTransforming
return
}
return
}
// histogram transforms a Histogram Aggregator into an OTLP Metric.
func histogramPoint(record export.Record, temporality aggregation.Temporality, a aggregation.Histogram) (*metricpb.Metric, error) {
desc := record.Descriptor()
labels := record.Labels()
boundaries, counts, err := histogramValues(a)
if err != nil {
return nil, err
}
count, err := a.Count()
if err != nil {
return nil, err
}
sum, err := a.Sum()
if err != nil {
return nil, err
}
m := &metricpb.Metric{
Name: desc.Name(),
Description: desc.Description(),
Unit: string(desc.Unit()),
Data: &metricpb.Metric_Histogram{
Histogram: &metricpb.Histogram{
AggregationTemporality: sdkTemporalityToTemporality(temporality),
DataPoints: []*metricpb.HistogramDataPoint{
{
Sum: sum.CoerceToFloat64(desc.NumberKind()),
Attributes: Iterator(labels.Iter()),
StartTimeUnixNano: toNanos(record.StartTime()),
TimeUnixNano: toNanos(record.EndTime()),
Count: uint64(count),
BucketCounts: counts,
ExplicitBounds: boundaries,
},
},
},
},
}
return m, nil
}