Remove extraction result type, simplify code.
This commit is contained in:
parent
376c7c732b
commit
0bb9a56250
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@ -101,7 +101,7 @@ func extractCounter(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error
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sample.Value = model.SampleValue(m.Counter.GetValue())
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}
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return out.Ingest(&Result{Samples: samples})
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return out.Ingest(samples)
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}
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func extractGauge(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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@ -132,7 +132,7 @@ func extractGauge(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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sample.Value = model.SampleValue(m.Gauge.GetValue())
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}
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return out.Ingest(&Result{Samples: samples})
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return out.Ingest(samples)
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}
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func extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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@ -194,7 +194,7 @@ func extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error
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}
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}
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return out.Ingest(&Result{Samples: samples})
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return out.Ingest(samples)
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}
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func extractUntyped(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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@ -225,5 +225,5 @@ func extractUntyped(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error
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sample.Value = model.SampleValue(m.Untyped.GetValue())
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}
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return out.Ingest(&Result{Samples: samples})
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return out.Ingest(samples)
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}
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@ -25,11 +25,11 @@ var testTime = model.Now()
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type metricFamilyProcessorScenario struct {
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in string
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expected, actual []*Result
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expected, actual []model.Samples
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}
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func (s *metricFamilyProcessorScenario) Ingest(r *Result) error {
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s.actual = append(s.actual, r)
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func (s *metricFamilyProcessorScenario) Ingest(samples model.Samples) error {
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s.actual = append(s.actual, samples)
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return nil
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}
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@ -50,10 +50,10 @@ func (s *metricFamilyProcessorScenario) test(t *testing.T, set int) {
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}
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for i, expected := range s.expected {
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sort.Sort(s.actual[i].Samples)
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sort.Sort(expected.Samples)
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sort.Sort(s.actual[i])
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sort.Sort(expected)
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if !expected.equal(s.actual[i]) {
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if !expected.Equal(s.actual[i]) {
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t.Errorf("%d.%d. expected %s, got %s", set, i, expected, s.actual[i])
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}
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}
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@ -66,43 +66,39 @@ func TestMetricFamilyProcessor(t *testing.T) {
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},
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{
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in: "\x8f\x01\n\rrequest_count\x12\x12Number of requests\x18\x00\"0\n#\n\x0fsome_label_name\x12\x10some_label_value\x1a\t\t\x00\x00\x00\x00\x00\x00E\xc0\"6\n)\n\x12another_label_name\x12\x13another_label_value\x1a\t\t\x00\x00\x00\x00\x00\x00U@",
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expected: []*Result{
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{
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Samples: model.Samples{
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value"},
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Value: -42,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "another_label_name": "another_label_value"},
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Value: 84,
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Timestamp: testTime,
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},
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expected: []model.Samples{
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model.Samples{
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value"},
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Value: -42,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "another_label_name": "another_label_value"},
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Value: 84,
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Timestamp: testTime,
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},
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},
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},
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},
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{
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in: "\xb9\x01\n\rrequest_count\x12\x12Number of requests\x18\x02\"O\n#\n\x0fsome_label_name\x12\x10some_label_value\"(\x1a\x12\t\xaeG\xe1z\x14\xae\xef?\x11\x00\x00\x00\x00\x00\x00E\xc0\x1a\x12\t+\x87\x16\xd9\xce\xf7\xef?\x11\x00\x00\x00\x00\x00\x00U\xc0\"A\n)\n\x12another_label_name\x12\x13another_label_value\"\x14\x1a\x12\t\x00\x00\x00\x00\x00\x00\xe0?\x11\x00\x00\x00\x00\x00\x00$@",
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expected: []*Result{
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{
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Samples: model.Samples{
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value", "quantile": "0.99"},
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Value: -42,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value", "quantile": "0.999"},
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Value: -84,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "another_label_name": "another_label_value", "quantile": "0.5"},
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Value: 10,
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Timestamp: testTime,
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},
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expected: []model.Samples{
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model.Samples{
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value", "quantile": "0.99"},
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Value: -42,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "some_label_name": "some_label_value", "quantile": "0.999"},
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Value: -84,
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Timestamp: testTime,
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},
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&model.Sample{
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Metric: model.Metric{model.MetricNameLabel: "request_count", "another_label_name": "another_label_value", "quantile": "0.5"},
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Value: 10,
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Timestamp: testTime,
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},
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},
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},
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@ -30,7 +30,7 @@ type ProcessOptions struct {
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// Ingester consumes result streams in whatever way is desired by the user.
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type Ingester interface {
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Ingest(*Result) error
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Ingest(model.Samples) error
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}
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// Processor is responsible for decoding the actual message responses from
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@ -56,42 +56,6 @@ func labelSet(labels map[string]string) model.LabelSet {
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return labelset
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}
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// Result encapsulates the outcome from processing samples from a source.
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type Result struct {
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Err error
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Samples model.Samples
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}
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func (r *Result) equal(o *Result) bool {
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if r == o {
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return true
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}
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if r.Err != o.Err {
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if r.Err == nil || o.Err == nil {
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return false
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}
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if r.Err.Error() != o.Err.Error() {
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return false
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}
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}
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if len(r.Samples) != len(o.Samples) {
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return false
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}
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for i, mine := range r.Samples {
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other := o.Samples[i]
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if !mine.Equal(other) {
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return false
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}
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}
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return true
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}
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// A basic interface only useful in testing contexts for dispensing the time
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// in a controlled manner.
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type instantProvider interface {
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@ -77,11 +77,7 @@ func (p *processor001) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
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case gauge001, counter001:
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sampleValue, ok := value.Value.(float64)
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if !ok {
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err = fmt.Errorf("could not convert value from %s %s to float64", entity, value)
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if err := out.Ingest(&Result{Err: err}); err != nil {
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return err
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}
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continue
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return fmt.Errorf("could not convert value from %s %s to float64", entity, value)
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}
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pendingSamples = append(pendingSamples, &model.Sample{
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@ -95,21 +91,13 @@ func (p *processor001) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
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case histogram001:
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sampleValue, ok := value.Value.(map[string]interface{})
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if !ok {
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err = fmt.Errorf("could not convert value from %q to a map[string]interface{}", value.Value)
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if err := out.Ingest(&Result{Err: err}); err != nil {
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return err
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}
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continue
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return fmt.Errorf("could not convert value from %q to a map[string]interface{}", value.Value)
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}
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for percentile, percentileValue := range sampleValue {
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individualValue, ok := percentileValue.(float64)
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if !ok {
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err = fmt.Errorf("could not convert value from %q to a float64", percentileValue)
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if err := out.Ingest(&Result{Err: err}); err != nil {
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return err
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}
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continue
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return fmt.Errorf("could not convert value from %q to a float64", percentileValue)
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}
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childMetric := make(map[model.LabelName]model.LabelValue, len(labels)+1)
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@ -132,7 +120,7 @@ func (p *processor001) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
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}
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}
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if len(pendingSamples) > 0 {
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return out.Ingest(&Result{Samples: pendingSamples})
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return out.Ingest(pendingSamples)
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}
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return nil
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@ -29,12 +29,12 @@ var test001Time = model.Now()
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type testProcessor001ProcessScenario struct {
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in string
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expected, actual []*Result
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expected, actual []model.Samples
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err error
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}
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func (s *testProcessor001ProcessScenario) Ingest(r *Result) error {
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s.actual = append(s.actual, r)
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func (s *testProcessor001ProcessScenario) Ingest(samples model.Samples) error {
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s.actual = append(s.actual, samples)
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return nil
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}
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@ -56,10 +56,10 @@ func (s *testProcessor001ProcessScenario) test(t testing.TB, set int) {
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}
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for i, expected := range s.expected {
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sort.Sort(s.actual[i].Samples)
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sort.Sort(expected.Samples)
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sort.Sort(s.actual[i])
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sort.Sort(expected)
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if !expected.equal(s.actual[i]) {
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if !expected.Equal(s.actual[i]) {
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t.Errorf("%d.%d. expected %s, got %s", set, i, expected, s.actual[i])
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}
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}
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@ -73,101 +73,97 @@ func testProcessor001Process(t testing.TB) {
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},
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{
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in: "test0_0_1-0_0_2.json",
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expected: []*Result{
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{
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Samples: model.Samples{
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&model.Sample{
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.0459814091918713,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 78.48563317257356,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 15.890724674774395,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.0459814091918713,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 78.48563317257356,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 15.890724674774395,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.6120456642749681,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 97.31798360385088,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 84.63044031436561,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 1.355915069887731,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 109.89202084295582,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 160.21100853053224,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 1.772733213161236,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 109.99626121011262,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 172.49828748957728,
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Timestamp: test001Time,
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},
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expected: []model.Samples{
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model.Samples{
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&model.Sample{
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
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Value: 25,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.0459814091918713,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 78.48563317257356,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 15.890724674774395,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.0459814091918713,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 78.48563317257356,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 15.890724674774395,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Value: 0.6120456642749681,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Value: 97.31798360385088,
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Timestamp: test001Time,
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},
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&model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Value: 84.63044031436561,
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Timestamp: test001Time,
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},
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&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.355915069887731,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.89202084295582,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 160.21100853053224,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.772733213161236,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.99626121011262,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 172.49828748957728,
|
||||
Timestamp: test001Time,
|
||||
},
|
||||
},
|
||||
},
|
||||
|
|
|
@ -60,11 +60,7 @@ func (p *processor002) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
|
|||
var values []counter002
|
||||
|
||||
if err := json.Unmarshal(entity.Metric.Values, &values); err != nil {
|
||||
err := fmt.Errorf("could not extract %s value: %s", entity.Metric.Type, err)
|
||||
if err := out.Ingest(&Result{Err: err}); err != nil {
|
||||
return err
|
||||
}
|
||||
continue
|
||||
return fmt.Errorf("could not extract %s value: %s", entity.Metric.Type, err)
|
||||
}
|
||||
|
||||
for _, counter := range values {
|
||||
|
@ -81,11 +77,7 @@ func (p *processor002) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
|
|||
var values []histogram002
|
||||
|
||||
if err := json.Unmarshal(entity.Metric.Values, &values); err != nil {
|
||||
err := fmt.Errorf("could not extract %s value: %s", entity.Metric.Type, err)
|
||||
if err := out.Ingest(&Result{Err: err}); err != nil {
|
||||
return err
|
||||
}
|
||||
continue
|
||||
return fmt.Errorf("could not extract %s value: %s", entity.Metric.Type, err)
|
||||
}
|
||||
|
||||
for _, histogram := range values {
|
||||
|
@ -102,15 +94,12 @@ func (p *processor002) ProcessSingle(in io.Reader, out Ingester, o *ProcessOptio
|
|||
}
|
||||
|
||||
default:
|
||||
err := fmt.Errorf("unknown metric type %q", entity.Metric.Type)
|
||||
if err := out.Ingest(&Result{Err: err}); err != nil {
|
||||
return err
|
||||
}
|
||||
return fmt.Errorf("unknown metric type %q", entity.Metric.Type)
|
||||
}
|
||||
}
|
||||
|
||||
if len(pendingSamples) > 0 {
|
||||
return out.Ingest(&Result{Samples: pendingSamples})
|
||||
return out.Ingest(pendingSamples)
|
||||
}
|
||||
|
||||
return nil
|
||||
|
|
|
@ -30,12 +30,12 @@ var test002Time = model.Now()
|
|||
|
||||
type testProcessor002ProcessScenario struct {
|
||||
in string
|
||||
expected, actual []*Result
|
||||
expected, actual []model.Samples
|
||||
err error
|
||||
}
|
||||
|
||||
func (s *testProcessor002ProcessScenario) Ingest(r *Result) error {
|
||||
s.actual = append(s.actual, r)
|
||||
func (s *testProcessor002ProcessScenario) Ingest(samples model.Samples) error {
|
||||
s.actual = append(s.actual, samples)
|
||||
return nil
|
||||
}
|
||||
|
||||
|
@ -57,10 +57,10 @@ func (s *testProcessor002ProcessScenario) test(t testing.TB, set int) {
|
|||
}
|
||||
|
||||
for i, expected := range s.expected {
|
||||
sort.Sort(s.actual[i].Samples)
|
||||
sort.Sort(expected.Samples)
|
||||
sort.Sort(s.actual[i])
|
||||
sort.Sort(expected)
|
||||
|
||||
if !expected.equal(s.actual[i]) {
|
||||
if !expected.Equal(s.actual[i]) {
|
||||
t.Fatalf("%d.%d. expected %s, got %s", set, i, expected, s.actual[i])
|
||||
}
|
||||
}
|
||||
|
@ -74,101 +74,98 @@ func testProcessor002Process(t testing.TB) {
|
|||
},
|
||||
{
|
||||
in: "test0_0_1-0_0_2.json",
|
||||
expected: []*Result{
|
||||
{
|
||||
Samples: model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.0459814091918713,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 78.48563317257356,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 15.890724674774395,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
expected: []model.Samples{
|
||||
model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job"},
|
||||
Value: 25,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.0459814091918713,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 78.48563317257356,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 15.890724674774395,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.0459814091918713,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 78.48563317257356,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 15.890724674774395,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.6120456642749681,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 97.31798360385088,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 84.63044031436561,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.355915069887731,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.89202084295582,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 160.21100853053224,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.772733213161236,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.99626121011262,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 172.49828748957728,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.0459814091918713,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 78.48563317257356,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 15.890724674774395,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 0.6120456642749681,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 97.31798360385088,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 84.63044031436561,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.355915069887731,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.89202084295582,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 160.21100853053224,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Value: 1.772733213161236,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Value: 109.99626121011262,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Value: 172.49828748957728,
|
||||
Timestamp: test002Time,
|
||||
},
|
||||
},
|
||||
},
|
||||
|
|
|
@ -32,44 +32,40 @@ mf1{label="value1"} -3.14 123456
|
|||
mf1{label="value2"} 42
|
||||
mf2 4
|
||||
`
|
||||
out = map[model.LabelValue]*Result{
|
||||
"mf1": {
|
||||
Samples: model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf1", "label": "value1"},
|
||||
Value: -3.14,
|
||||
Timestamp: 123456,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf1", "label": "value2"},
|
||||
Value: 42,
|
||||
Timestamp: ts,
|
||||
},
|
||||
out = map[model.LabelValue]model.Samples{
|
||||
"mf1": model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf1", "label": "value1"},
|
||||
Value: -3.14,
|
||||
Timestamp: 123456,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf1", "label": "value2"},
|
||||
Value: 42,
|
||||
Timestamp: ts,
|
||||
},
|
||||
},
|
||||
"mf2": {
|
||||
Samples: model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf2"},
|
||||
Value: 3,
|
||||
Timestamp: ts,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf2"},
|
||||
Value: 4,
|
||||
Timestamp: ts,
|
||||
},
|
||||
"mf2": model.Samples{
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf2"},
|
||||
Value: 3,
|
||||
Timestamp: ts,
|
||||
},
|
||||
&model.Sample{
|
||||
Metric: model.Metric{model.MetricNameLabel: "mf2"},
|
||||
Value: 4,
|
||||
Timestamp: ts,
|
||||
},
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
type testIngester struct {
|
||||
results []*Result
|
||||
results []model.Samples
|
||||
}
|
||||
|
||||
func (i *testIngester) Ingest(r *Result) error {
|
||||
i.results = append(i.results, r)
|
||||
func (i *testIngester) Ingest(s model.Samples) error {
|
||||
i.results = append(i.results, s)
|
||||
return nil
|
||||
}
|
||||
|
||||
|
@ -88,16 +84,16 @@ func TestTextProcessor(t *testing.T) {
|
|||
t.Fatalf("Expected length %d, got %d", expected, got)
|
||||
}
|
||||
for _, r := range ingester.results {
|
||||
expected, ok := out[r.Samples[0].Metric[model.MetricNameLabel]]
|
||||
expected, ok := out[r[0].Metric[model.MetricNameLabel]]
|
||||
if !ok {
|
||||
t.Fatalf(
|
||||
"Unexpected metric name %q",
|
||||
r.Samples[0].Metric[model.MetricNameLabel],
|
||||
r[0].Metric[model.MetricNameLabel],
|
||||
)
|
||||
}
|
||||
sort.Sort(expected.Samples)
|
||||
sort.Sort(r.Samples)
|
||||
if !expected.equal(r) {
|
||||
sort.Sort(expected)
|
||||
sort.Sort(r)
|
||||
if !expected.Equal(r) {
|
||||
t.Errorf("expected %s, got %s", expected, r)
|
||||
}
|
||||
}
|
||||
|
|
|
@ -63,3 +63,17 @@ func (s Samples) Less(i, j int) bool {
|
|||
func (s Samples) Swap(i, j int) {
|
||||
s[i], s[j] = s[j], s[i]
|
||||
}
|
||||
|
||||
// Equal compares two sets of samples and returns true if they are equal.
|
||||
func (s Samples) Equal(o Samples) bool {
|
||||
if len(s) != len(o) {
|
||||
return false
|
||||
}
|
||||
|
||||
for i, sample := range s {
|
||||
if !sample.Equal(o[i]) {
|
||||
return false
|
||||
}
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
|
Loading…
Reference in New Issue