Skip to content

Commit f07bd12

Browse files
codebotencodeboten
committed
[chore] use generated test harness for groupbyattrs processor
Like open-telemetry#34940 but for the groupsbyattrs processor. Signed-off-by: Alex Boten <[email protected]>
1 parent 903eec5 commit f07bd12

File tree

2 files changed

+208
-274
lines changed

2 files changed

+208
-274
lines changed

‎processor/groupbyattrsprocessor/processor_test.go

+208-16
Original file line numberDiff line numberDiff line change
@@ -18,6 +18,8 @@ import (
1818
"go.opentelemetry.io/collector/pdata/pmetric"
1919
"go.opentelemetry.io/collector/pdata/ptrace"
2020
"go.opentelemetry.io/collector/processor/processortest"
21+
"go.opentelemetry.io/otel/attribute"
22+
"go.opentelemetry.io/otel/sdk/metric/metricdata"
2123
)
2224

2325
var (
@@ -270,8 +272,8 @@ func TestComplexAttributeGrouping(t *testing.T) {
270272
inputMetrics := someComplexMetrics(tt.withResourceAttrIndex, tt.inputResourceCount, tt.inputInstrumentationLibraryCount, 2)
271273
inputHistogramMetrics := someComplexHistogramMetrics(tt.withResourceAttrIndex, tt.inputResourceCount, tt.inputInstrumentationLibraryCount, 2, 2)
272274

273-
tel := setupTelemetry()
274-
gap, err := createGroupByAttrsProcessor(tel.NewProcessorCreateSettings(), tt.groupByKeys)
275+
tel := setupTestTelemetry()
276+
gap, err := createGroupByAttrsProcessor(tel.NewSettings(), tt.groupByKeys)
275277
require.NoError(t, err)
276278

277279
processedLogs, err := gap.processLogs(context.Background(), inputLogs)
@@ -371,23 +373,213 @@ func TestComplexAttributeGrouping(t *testing.T) {
371373
}
372374
}
373375
}
374-
375-
expected := expectedMetrics{}
376+
var want []metricdata.Metrics
376377
if tt.shouldMoveCommonGroupedAttr {
377-
expected.mDistLogGroups = int64(tt.outputResourceCount)
378-
expected.mNumGroupedLogs = int64(tt.outputTotalRecordsCount)
379-
380-
expected.mDistMetricGroups = int64(tt.outputResourceCount)
381-
expected.mNumGroupedMetrics = 4 * int64(tt.outputTotalRecordsCount)
382-
383-
expected.mDistSpanGroups = int64(tt.outputResourceCount)
384-
expected.mNumGroupedSpans = int64(tt.outputTotalRecordsCount)
378+
want = []metricdata.Metrics{
379+
{
380+
Name: "otelcol_processor_groupbyattrs_num_grouped_logs",
381+
Description: "Number of logs that had attributes grouped",
382+
Unit: "1",
383+
Data: metricdata.Sum[int64]{
384+
Temporality: metricdata.CumulativeTemporality,
385+
IsMonotonic: true,
386+
DataPoints: []metricdata.DataPoint[int64]{
387+
{
388+
Value: int64(tt.outputTotalRecordsCount),
389+
},
390+
},
391+
},
392+
},
393+
{
394+
Name: "otelcol_processor_groupbyattrs_num_grouped_metrics",
395+
Description: "Number of metrics that had attributes grouped",
396+
Unit: "1",
397+
Data: metricdata.Sum[int64]{
398+
Temporality: metricdata.CumulativeTemporality,
399+
IsMonotonic: true,
400+
DataPoints: []metricdata.DataPoint[int64]{
401+
{
402+
Value: 4 * int64(tt.outputTotalRecordsCount),
403+
},
404+
},
405+
},
406+
},
407+
{
408+
Name: "otelcol_processor_groupbyattrs_num_grouped_spans",
409+
Description: "Number of spans that had attributes grouped",
410+
Unit: "1",
411+
Data: metricdata.Sum[int64]{
412+
Temporality: metricdata.CumulativeTemporality,
413+
IsMonotonic: true,
414+
DataPoints: []metricdata.DataPoint[int64]{
415+
{
416+
Value: int64(tt.outputTotalRecordsCount),
417+
},
418+
},
419+
},
420+
},
421+
{
422+
Name: "otelcol_processor_groupbyattrs_log_groups",
423+
Description: "Distribution of groups extracted for logs",
424+
Unit: "1",
425+
Data: metricdata.Histogram[int64]{
426+
Temporality: metricdata.CumulativeTemporality,
427+
DataPoints: []metricdata.HistogramDataPoint[int64]{
428+
{
429+
Attributes: *attribute.EmptySet(),
430+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
431+
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
432+
Count: 1,
433+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
434+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
435+
Sum: int64(tt.outputResourceCount),
436+
},
437+
},
438+
},
439+
},
440+
{
441+
Name: "otelcol_processor_groupbyattrs_metric_groups",
442+
Description: "Distribution of groups extracted for metrics",
443+
Unit: "1",
444+
Data: metricdata.Histogram[int64]{
445+
Temporality: metricdata.CumulativeTemporality,
446+
DataPoints: []metricdata.HistogramDataPoint[int64]{
447+
{
448+
Attributes: *attribute.EmptySet(),
449+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
450+
BucketCounts: []uint64{0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
451+
Count: 2,
452+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
453+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
454+
Sum: 2 * int64(tt.outputResourceCount),
455+
},
456+
},
457+
},
458+
},
459+
{
460+
Name: "otelcol_processor_groupbyattrs_span_groups",
461+
Description: "Distribution of groups extracted for spans",
462+
Unit: "1",
463+
Data: metricdata.Histogram[int64]{
464+
Temporality: metricdata.CumulativeTemporality,
465+
DataPoints: []metricdata.HistogramDataPoint[int64]{
466+
{
467+
Attributes: *attribute.EmptySet(),
468+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
469+
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
470+
Count: 1,
471+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
472+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
473+
Sum: int64(tt.outputResourceCount),
474+
},
475+
},
476+
},
477+
},
478+
}
385479
} else {
386-
expected.mNumNonGroupedLogs = int64(tt.outputTotalRecordsCount)
387-
expected.mNumNonGroupedMetrics = 4 * int64(tt.outputTotalRecordsCount)
388-
expected.mNumNonGroupedSpans = int64(tt.outputTotalRecordsCount)
480+
want = []metricdata.Metrics{
481+
{
482+
Name: "otelcol_processor_groupbyattrs_num_non_grouped_logs",
483+
Description: "Number of logs that did not have attributes grouped",
484+
Unit: "1",
485+
Data: metricdata.Sum[int64]{
486+
Temporality: metricdata.CumulativeTemporality,
487+
IsMonotonic: true,
488+
DataPoints: []metricdata.DataPoint[int64]{
489+
{
490+
Value: int64(tt.outputTotalRecordsCount),
491+
},
492+
},
493+
},
494+
},
495+
{
496+
Name: "otelcol_processor_groupbyattrs_num_non_grouped_metrics",
497+
Description: "Number of metrics that did not have attributes grouped",
498+
Unit: "1",
499+
Data: metricdata.Sum[int64]{
500+
Temporality: metricdata.CumulativeTemporality,
501+
IsMonotonic: true,
502+
DataPoints: []metricdata.DataPoint[int64]{
503+
{
504+
Value: 4 * int64(tt.outputTotalRecordsCount),
505+
},
506+
},
507+
},
508+
},
509+
{
510+
Name: "otelcol_processor_groupbyattrs_num_non_grouped_spans",
511+
Description: "Number of spans that did not have attributes grouped",
512+
Unit: "1",
513+
Data: metricdata.Sum[int64]{
514+
Temporality: metricdata.CumulativeTemporality,
515+
IsMonotonic: true,
516+
DataPoints: []metricdata.DataPoint[int64]{
517+
{
518+
Value: int64(tt.outputTotalRecordsCount),
519+
},
520+
},
521+
},
522+
},
523+
{
524+
Name: "otelcol_processor_groupbyattrs_log_groups",
525+
Description: "Distribution of groups extracted for logs",
526+
Unit: "1",
527+
Data: metricdata.Histogram[int64]{
528+
Temporality: metricdata.CumulativeTemporality,
529+
DataPoints: []metricdata.HistogramDataPoint[int64]{
530+
{
531+
Attributes: *attribute.EmptySet(),
532+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
533+
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
534+
Count: 1,
535+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
536+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
537+
Sum: int64(tt.outputResourceCount),
538+
},
539+
},
540+
},
541+
},
542+
{
543+
Name: "otelcol_processor_groupbyattrs_metric_groups",
544+
Description: "Distribution of groups extracted for metrics",
545+
Unit: "1",
546+
Data: metricdata.Histogram[int64]{
547+
Temporality: metricdata.CumulativeTemporality,
548+
DataPoints: []metricdata.HistogramDataPoint[int64]{
549+
{
550+
Attributes: *attribute.EmptySet(),
551+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
552+
BucketCounts: []uint64{0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
553+
Count: 2,
554+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
555+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
556+
Sum: 2 * int64(tt.outputResourceCount),
557+
},
558+
},
559+
},
560+
},
561+
{
562+
Name: "otelcol_processor_groupbyattrs_span_groups",
563+
Description: "Distribution of groups extracted for spans",
564+
Unit: "1",
565+
Data: metricdata.Histogram[int64]{
566+
Temporality: metricdata.CumulativeTemporality,
567+
DataPoints: []metricdata.HistogramDataPoint[int64]{
568+
{
569+
Attributes: *attribute.EmptySet(),
570+
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
571+
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
572+
Count: 1,
573+
Min: metricdata.NewExtrema(int64(tt.outputResourceCount)),
574+
Max: metricdata.NewExtrema(int64(tt.outputResourceCount)),
575+
Sum: int64(tt.outputResourceCount),
576+
},
577+
},
578+
},
579+
},
580+
}
389581
}
390-
tel.assertMetrics(t, expected)
582+
tel.assertMetrics(t, want)
391583
})
392584
}
393585
}

0 commit comments

Comments
 (0)