VictoriaMetrics/app/vmalert/rule/recording_test.go
Hui Wang 18afeff742
app/vmalert: fix flaky ut TestRecordingRule_Exec
The order of stale metrics can't be controlled in recording rule, only
use two time series then.
2024-11-14 15:30:39 +01:00

426 lines
10 KiB
Go

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/decimal"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
)
func TestRecordingRule_Exec(t *testing.T) {
ts, _ := time.Parse(time.RFC3339, "2024-10-29T00:00:00Z")
const defaultStep = 5 * time.Millisecond
f := func(rule *RecordingRule, steps [][]datasource.Metric, tssExpected [][]prompbmarshal.TimeSeries) {
t.Helper()
fq := &datasource.FakeQuerier{}
for i, step := range steps {
fq.Reset()
fq.Add(step...)
rule.q = fq
rule.state = &ruleState{
entries: make([]StateEntry, 10),
}
tss, err := rule.exec(context.TODO(), ts, 0)
if err != nil {
t.Fatalf("fail to test rule %s: unexpected error: %s", rule.Name, err)
}
if err := compareTimeSeries(t, tssExpected[i], tss); err != nil {
t.Fatalf("fail to test rule %s: time series mismatch on step %d: %s", rule.Name, i, err)
}
ts = ts.Add(defaultStep)
}
}
f(&RecordingRule{
Name: "foo",
}, [][]datasource.Metric{{
metricWithValueAndLabels(t, 10, "__name__", "bar"),
}}, [][]prompbmarshal.TimeSeries{{
newTimeSeries([]float64{10}, []int64{ts.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foo",
},
}),
}})
f(&RecordingRule{
Name: "foobarbaz",
}, [][]datasource.Metric{
{
metricWithValueAndLabels(t, 1, "__name__", "foo", "job", "foo"),
metricWithValueAndLabels(t, 2, "__name__", "bar", "job", "bar"),
},
{
metricWithValueAndLabels(t, 10, "__name__", "foo", "job", "foo"),
},
{
metricWithValueAndLabels(t, 10, "__name__", "foo", "job", "bar"),
},
}, [][]prompbmarshal.TimeSeries{
{
newTimeSeries([]float64{1}, []int64{ts.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "foo",
},
}),
newTimeSeries([]float64{2}, []int64{ts.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "bar",
},
}),
},
{
newTimeSeries([]float64{10}, []int64{ts.Add(defaultStep).UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "foo",
},
}),
// stale time series
newTimeSeries([]float64{decimal.StaleNaN}, []int64{ts.Add(defaultStep).UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "bar",
},
}),
},
{
newTimeSeries([]float64{10}, []int64{ts.Add(2 * defaultStep).UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "bar",
},
}),
newTimeSeries([]float64{decimal.StaleNaN}, []int64{ts.Add(2 * defaultStep).UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "foo",
},
}),
},
})
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{ts.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "job:foo",
},
{
Name: "job",
Value: "foo",
},
{
Name: "source",
Value: "test",
},
}),
newTimeSeries([]float64{1}, []int64{ts.UnixNano()},
[]prompbmarshal.Label{
{
Name: "__name__",
Value: "job:foo",
},
{
Name: "job",
Value: "bar",
},
{
Name: "source",
Value: "test",
},
{
Name: "exported_source",
Value: "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()},
[]prompbmarshal.Label{
{
Name: "__name__",
Value: "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()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "foo",
},
}),
newTimeSeries([]float64{2, 3}, []int64{timestamp.UnixNano(), timestamp.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "bar",
},
}),
newTimeSeries([]float64{4, 5, 6},
[]int64{timestamp.UnixNano(), timestamp.UnixNano(), timestamp.UnixNano()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "foobarbaz",
},
{
Name: "job",
Value: "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()}, []prompbmarshal.Label{
{
Name: "__name__",
Value: "job:foo",
},
{
Name: "job",
Value: "foo",
},
{
Name: "source",
Value: "test",
},
}),
newTimeSeries([]float64{1}, []int64{timestamp.UnixNano()},
[]prompbmarshal.Label{
{
Name: "__name__",
Value: "job:foo",
},
{
Name: "job",
Value: "bar",
},
{
Name: "source",
Value: "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)
}
}
func TestSetIntervalAsTimeFilter(t *testing.T) {
f := func(s, dType string, expected bool) {
t.Helper()
if setIntervalAsTimeFilter(dType, s) != expected {
t.Fatalf("unexpected result for hasTimeFilter(%q); want %v", s, expected)
}
}
f(`* | count()`, "prometheus", false)
f(`* | count()`, "vlogs", true)
f(`error OR _time:5m | count()`, "vlogs", true)
f(`(_time: 5m AND error) OR (_time: 5m AND warn) | count()`, "vlogs", true)
f(`* | error OR _time:5m | count()`, "vlogs", true)
f(`_time:5m | count()`, "vlogs", false)
f(`_time:2023-04-25T22:45:59Z | count()`, "vlogs", false)
f(`error AND _time:5m | count()`, "vlogs", false)
f(`* | error AND _time:5m | count()`, "vlogs", false)
}