mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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5aa7846900
* vmalert: support rules backfilling (aka `replay`) vmalert can `replay` configured rules in the past and backfill results via remote write protocol. It supports MetricsQL/PromQL storage as data source, and can backfill data to remote write compatible storage. Supports recording and alerting rules `replay`. See more details in README. https://github.com/VictoriaMetrics/VictoriaMetrics/issues/836 * vmalert: review fixes * vmalert: readme fixes
204 lines
5.7 KiB
Go
204 lines
5.7 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())
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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())
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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())
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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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