VictoriaMetrics/app/vmalert/rule/recording_test.go

269 lines
7.7 KiB
Go
Raw Normal View History

package rule
import (
"context"
"errors"
"strings"
"testing"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmalert/datasource"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmalert/utils"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
)
func TestRecordingRule_Exec(t *testing.T) {
f := func(rule *RecordingRule, metrics []datasource.Metric, tssExpected []prompbmarshal.TimeSeries) {
t.Helper()
fq := &datasource.FakeQuerier{}
fq.Add(metrics...)
rule.q = fq
rule.state = &ruleState{
entries: make([]StateEntry, 10),
}
tss, err := rule.exec(context.TODO(), time.Now(), 0)
if err != nil {
t.Fatalf("unexpected RecordingRule.exec error: %s", err)
}
if err := compareTimeSeries(t, tssExpected, tss); err != nil {
t.Fatalf("timeseries missmatch: %s", err)
}
}
timestamp := time.Now()
f(&RecordingRule{
Name: "foo",
}, []datasource.Metric{
metricWithValueAndLabels(t, 10, "__name__", "bar"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{10}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foo",
}),
})
f(&RecordingRule{
Name: "foobarbaz",
}, []datasource.Metric{
metricWithValueAndLabels(t, 1, "__name__", "foo", "job", "foo"),
metricWithValueAndLabels(t, 2, "__name__", "bar", "job", "bar"),
metricWithValueAndLabels(t, 3, "__name__", "baz", "job", "baz"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "foo",
}),
newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "bar",
}),
newTimeSeries([]float64{3}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "baz",
}),
})
f(&RecordingRule{
Name: "job:foo",
Labels: map[string]string{
"source": "test",
},
}, []datasource.Metric{
metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "foo"),
metricWithValueAndLabels(t, 1, "__name__", "bar", "job", "bar", "source", "origin"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "job:foo",
"job": "foo",
"source": "test",
}),
newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "job:foo",
"job": "bar",
"source": "test",
"exported_source": "origin",
}),
})
}
func TestRecordingRule_ExecRange(t *testing.T) {
f := func(rule *RecordingRule, metrics []datasource.Metric, tssExpected []prompbmarshal.TimeSeries) {
t.Helper()
fq := &datasource.FakeQuerier{}
fq.Add(metrics...)
rule.q = fq
tss, err := rule.execRange(context.TODO(), time.Now(), time.Now())
if err != nil {
t.Fatalf("unexpected RecordingRule.execRange error: %s", err)
}
if err := compareTimeSeries(t, tssExpected, tss); err != nil {
t.Fatalf("timeseries missmatch: %s", err)
}
}
timestamp := time.Now()
f(&RecordingRule{
Name: "foo",
}, []datasource.Metric{
metricWithValuesAndLabels(t, []float64{10, 20, 30}, "__name__", "bar"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{10, 20, 30}, []int64{timestamp.UnixNano(), timestamp.UnixNano(), timestamp.UnixNano()}, map[string]string{
"__name__": "foo",
}),
})
f(&RecordingRule{
Name: "foobarbaz",
}, []datasource.Metric{
metricWithValuesAndLabels(t, []float64{1}, "__name__", "foo", "job", "foo"),
metricWithValuesAndLabels(t, []float64{2, 3}, "__name__", "bar", "job", "bar"),
metricWithValuesAndLabels(t, []float64{4, 5, 6}, "__name__", "baz", "job", "baz"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "foo",
}),
newTimeSeries([]float64{2, 3}, []int64{timestamp.UnixNano(), timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "bar",
}),
newTimeSeries([]float64{4, 5, 6},
[]int64{timestamp.UnixNano(), timestamp.UnixNano(), timestamp.UnixNano()}, map[string]string{
"__name__": "foobarbaz",
"job": "baz",
}),
})
f(&RecordingRule{
Name: "job:foo",
Labels: map[string]string{
"source": "test",
},
}, []datasource.Metric{
metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "foo"),
metricWithValueAndLabels(t, 1, "__name__", "bar", "job", "bar"),
}, []prompbmarshal.TimeSeries{
newTimeSeries([]float64{2}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "job:foo",
"job": "foo",
"source": "test",
}),
newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "job:foo",
"job": "bar",
"source": "test",
}),
})
}
func TestRecordingRuleLimit_Failure(t *testing.T) {
f := func(limit int, errStrExpected string) {
t.Helper()
testMetrics := []datasource.Metric{
metricWithValuesAndLabels(t, []float64{1}, "__name__", "foo", "job", "foo"),
metricWithValuesAndLabels(t, []float64{2, 3}, "__name__", "bar", "job", "bar"),
metricWithValuesAndLabels(t, []float64{4, 5, 6}, "__name__", "baz", "job", "baz"),
}
fq := &datasource.FakeQuerier{}
fq.Add(testMetrics...)
rule := &RecordingRule{Name: "job:foo",
state: &ruleState{entries: make([]StateEntry, 10)},
Labels: map[string]string{
"source": "test_limit",
},
metrics: &recordingRuleMetrics{
errors: utils.GetOrCreateCounter(`vmalert_recording_rules_errors_total{alertname="job:foo"}`),
},
}
rule.q = fq
_, err := rule.exec(context.TODO(), time.Now(), limit)
if err == nil {
t.Fatalf("expecting non-nil error")
}
errStr := err.Error()
if !strings.Contains(errStr, errStrExpected) {
t.Fatalf("missing %q in the error %q", errStrExpected, errStr)
}
}
f(1, "exec exceeded limit of 1 with 3 series")
f(2, "exec exceeded limit of 2 with 3 series")
}
func TestRecordingRuleLimit_Success(t *testing.T) {
f := func(limit int) {
t.Helper()
testMetrics := []datasource.Metric{
metricWithValuesAndLabels(t, []float64{1}, "__name__", "foo", "job", "foo"),
metricWithValuesAndLabels(t, []float64{2, 3}, "__name__", "bar", "job", "bar"),
metricWithValuesAndLabels(t, []float64{4, 5, 6}, "__name__", "baz", "job", "baz"),
}
fq := &datasource.FakeQuerier{}
fq.Add(testMetrics...)
rule := &RecordingRule{Name: "job:foo",
state: &ruleState{entries: make([]StateEntry, 10)},
Labels: map[string]string{
"source": "test_limit",
},
metrics: &recordingRuleMetrics{
errors: utils.GetOrCreateCounter(`vmalert_recording_rules_errors_total{alertname="job:foo"}`),
},
}
rule.q = fq
_, err := rule.exec(context.TODO(), time.Now(), limit)
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
}
f(0)
f(-1)
}
func TestRecordingRuleExec_Negative(t *testing.T) {
rr := &RecordingRule{
Name: "job:foo",
Labels: map[string]string{
"job": "test",
},
state: &ruleState{entries: make([]StateEntry, 10)},
metrics: &recordingRuleMetrics{
errors: utils.GetOrCreateCounter(`vmalert_recording_rules_errors_total{alertname="job:foo"}`),
},
}
fq := &datasource.FakeQuerier{}
expErr := "connection reset by peer"
fq.SetErr(errors.New(expErr))
rr.q = fq
_, err := rr.exec(context.TODO(), time.Now(), 0)
if err == nil {
t.Fatalf("expected to get err; got nil")
}
if !strings.Contains(err.Error(), expErr) {
t.Fatalf("expected to get err %q; got %q insterad", expErr, err)
}
fq.Reset()
// add metrics which differs only by `job` label
// which will be overridden by rule
fq.Add(metricWithValueAndLabels(t, 1, "__name__", "foo", "job", "foo"))
fq.Add(metricWithValueAndLabels(t, 2, "__name__", "foo", "job", "bar"))
_, err = rr.exec(context.TODO(), time.Now(), 0)
if err != nil {
t.Fatalf("cannot execute recroding rule: %s", err)
}
}