mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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0989649ad0
* vmalert: split alert's `Start` field into `ActiveAt` and `Start` The `ActiveAt` field identifies when alert becomes active for rules with `for > 0`. Previously, this value was stored in field `Start`. The field `Start` now identifies the moment alert became `FIRING`. The split is needed in order to distinguish these two moments in the API responses for alerts. Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: support specific moment of time for rules evaluation The Querier interface was extended to accept a new argument used as a timestamp at which evaluation should be made. It is needed to align rules execution time within the group. Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: mark disappeared series as stale Series generated by alerting rules, which were sent to remote write now will be marked as stale if they will disappear on the next evaluation. This would make ALERTS and ALERTS_FOR_TIME series more precise. Signed-off-by: hagen1778 <roman@victoriametrics.com> * wip Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: evaluate rules at fixed timestamp Before, time at which rules were evaluated was calculated right before rule execution. The change makes sure that timestamp is calculated only once per evalution round and all rules are using the same timestamp. It also updates the logic of resending of already resolved alert notification. Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: allow overridin `alertname` label value if it is present in response Previously, `alertname` was always equal to the Alerting Rule name. Now, its value can be overriden if series in response containt the different value for this label. The change is needed for improving compatibility with Prometheus. Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: align rules evaluation in time Now, evaluation timestamp for rules evaluates as if there was no delay in rules evaluation. It means, that rules will be evaluated at fixed timestamps+group_interval. This way provides more consistent evaluation results and improves compatibility with Prometheus, Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: add metric for missed iterations New metric `vmalert_iteration_missed_total` will show whether rules evaluation round was missed. Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: reduce delay before the initial rule evaluation in group Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: rollback alertname override According to the spec: ``` The alert name from the alerting rule (HighRequestLatency from the example above) MUST be added to the labels of the alert with the label name as alertname. It MUST override any existing alertname label. ``` https://github.com/prometheus/compliance/blob/main/alert_generator/specification.md#step-3 Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: throw err immediately on dedup detection ``` The execution of an alerting rule MUST error out immediately and MUST NOT send any alerts or add samples to samples receiver if there is more than one alert with the same labels ``` https://github.com/prometheus/compliance/blob/main/alert_generator/specification.md#step-4 Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: cleanup Signed-off-by: hagen1778 <roman@victoriametrics.com> * vmalert: use strings builder to reduce allocs Signed-off-by: hagen1778 <roman@victoriametrics.com>
204 lines
5.8 KiB
Go
204 lines
5.8 KiB
Go
package main
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import (
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"context"
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"errors"
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"strings"
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"testing"
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"time"
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"github.com/VictoriaMetrics/VictoriaMetrics/app/vmalert/datasource"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
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)
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func TestRecoridngRule_Exec(t *testing.T) {
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timestamp := time.Now()
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testCases := []struct {
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rule *RecordingRule
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metrics []datasource.Metric
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expTS []prompbmarshal.TimeSeries
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}{
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{
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&RecordingRule{Name: "foo"},
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[]datasource.Metric{metricWithValueAndLabels(t, 10,
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"__name__", "bar",
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)},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{10}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "foo",
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}),
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},
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},
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{
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&RecordingRule{Name: "foobarbaz"},
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[]datasource.Metric{
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metricWithValueAndLabels(t, 1, "__name__", "foo", "job", "foo"),
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metricWithValueAndLabels(t, 2, "__name__", "bar", "job", "bar"),
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metricWithValueAndLabels(t, 3, "__name__", "baz", "job", "baz"),
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},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "foobarbaz",
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"job": "foo",
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}),
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newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "foobarbaz",
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"job": "bar",
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}),
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newTimeSeries([]float64{3}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "foobarbaz",
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"job": "baz",
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}),
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},
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},
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{
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&RecordingRule{Name: "job:foo", Labels: map[string]string{
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"source": "test",
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}},
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[]datasource.Metric{
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metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "foo"),
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metricWithValueAndLabels(t, 1, "__name__", "bar", "job", "bar")},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "job:foo",
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"job": "foo",
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"source": "test",
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}),
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newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "job:foo",
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"job": "bar",
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"source": "test",
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}),
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},
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},
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}
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for _, tc := range testCases {
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t.Run(tc.rule.Name, func(t *testing.T) {
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fq := &fakeQuerier{}
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fq.add(tc.metrics...)
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tc.rule.q = fq
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tss, err := tc.rule.Exec(context.TODO(), time.Now())
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if err != nil {
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t.Fatalf("unexpected Exec err: %s", err)
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}
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if err := compareTimeSeries(t, tc.expTS, tss); err != nil {
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t.Fatalf("timeseries missmatch: %s", err)
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}
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})
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}
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}
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func TestRecoridngRule_ExecRange(t *testing.T) {
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timestamp := time.Now()
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testCases := []struct {
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rule *RecordingRule
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metrics []datasource.Metric
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expTS []prompbmarshal.TimeSeries
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}{
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{
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&RecordingRule{Name: "foo"},
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[]datasource.Metric{metricWithValuesAndLabels(t, []float64{10, 20, 30},
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"__name__", "bar",
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)},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{10, 20, 30},
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[]int64{timestamp.UnixNano(), timestamp.UnixNano(), timestamp.UnixNano()},
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map[string]string{
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"__name__": "foo",
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}),
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},
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},
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{
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&RecordingRule{Name: "foobarbaz"},
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[]datasource.Metric{
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metricWithValuesAndLabels(t, []float64{1}, "__name__", "foo", "job", "foo"),
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metricWithValuesAndLabels(t, []float64{2, 3}, "__name__", "bar", "job", "bar"),
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metricWithValuesAndLabels(t, []float64{4, 5, 6}, "__name__", "baz", "job", "baz"),
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},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "foobarbaz",
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"job": "foo",
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}),
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newTimeSeries([]float64{2, 3}, []int64{timestamp.UnixNano(), timestamp.UnixNano()}, map[string]string{
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"__name__": "foobarbaz",
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"job": "bar",
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}),
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newTimeSeries([]float64{4, 5, 6},
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[]int64{timestamp.UnixNano(), timestamp.UnixNano(), timestamp.UnixNano()},
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map[string]string{
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"__name__": "foobarbaz",
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"job": "baz",
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}),
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},
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},
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{
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&RecordingRule{Name: "job:foo", Labels: map[string]string{
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"source": "test",
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}},
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[]datasource.Metric{
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metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "foo"),
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metricWithValueAndLabels(t, 1, "__name__", "bar", "job", "bar")},
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[]prompbmarshal.TimeSeries{
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newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "job:foo",
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"job": "foo",
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"source": "test",
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}),
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newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
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"__name__": "job:foo",
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"job": "bar",
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"source": "test",
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}),
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},
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},
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}
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for _, tc := range testCases {
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t.Run(tc.rule.Name, func(t *testing.T) {
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fq := &fakeQuerier{}
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fq.add(tc.metrics...)
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tc.rule.q = fq
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tss, err := tc.rule.ExecRange(context.TODO(), time.Now(), time.Now())
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if err != nil {
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t.Fatalf("unexpected Exec err: %s", err)
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}
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if err := compareTimeSeries(t, tc.expTS, tss); err != nil {
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t.Fatalf("timeseries missmatch: %s", err)
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}
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})
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}
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}
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func TestRecoridngRule_ExecNegative(t *testing.T) {
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rr := &RecordingRule{Name: "job:foo", Labels: map[string]string{
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"job": "test",
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}}
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fq := &fakeQuerier{}
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expErr := "connection reset by peer"
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fq.setErr(errors.New(expErr))
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rr.q = fq
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_, err := rr.Exec(context.TODO(), time.Now())
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if err == nil {
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t.Fatalf("expected to get err; got nil")
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}
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if !strings.Contains(err.Error(), expErr) {
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t.Fatalf("expected to get err %q; got %q insterad", expErr, err)
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}
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fq.reset()
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// add metrics which differs only by `job` label
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// which will be overridden by rule
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fq.add(metricWithValueAndLabels(t, 1, "__name__", "foo", "job", "foo"))
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fq.add(metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "bar"))
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_, err = rr.Exec(context.TODO(), time.Now())
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if err == nil {
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t.Fatalf("expected to get err; got nil")
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}
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if !strings.Contains(err.Error(), errDuplicate.Error()) {
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t.Fatalf("expected to get err %q; got %q insterad", errDuplicate, err)
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}
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}
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