VictoriaMetrics/app/vmalert/recording_test.go
Howie 4afd7aa695
feat: rule limit (#2676)
vmalert: support `limit` param in groups definition

`limit` param limits number of time series samples produced by a single rule
during execution.
On reaching the limit rule will return an err.

Signed-off-by: lihaowei <haoweili35@gmail.com>
2022-06-09 13:15:33 +03:00

248 lines
6.9 KiB
Go

package main
import (
"context"
"errors"
"strings"
"testing"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmalert/datasource"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
)
func TestRecordingRule_Exec(t *testing.T) {
timestamp := time.Now()
testCases := []struct {
rule *RecordingRule
metrics []datasource.Metric
expTS []prompbmarshal.TimeSeries
}{
{
&RecordingRule{Name: "foo"},
[]datasource.Metric{metricWithValueAndLabels(t, 10,
"__name__", "bar",
)},
[]prompbmarshal.TimeSeries{
newTimeSeries([]float64{10}, []int64{timestamp.UnixNano()}, map[string]string{
"__name__": "foo",
}),
},
},
{
&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",
}),
},
},
{
&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",
}),
},
},
}
for _, tc := range testCases {
t.Run(tc.rule.Name, func(t *testing.T) {
fq := &fakeQuerier{}
fq.add(tc.metrics...)
tc.rule.q = fq
tss, err := tc.rule.Exec(context.TODO(), time.Now(), 0)
if err != nil {
t.Fatalf("unexpected Exec err: %s", err)
}
if err := compareTimeSeries(t, tc.expTS, tss); err != nil {
t.Fatalf("timeseries missmatch: %s", err)
}
})
}
}
func TestRecordingRule_ExecRange(t *testing.T) {
timestamp := time.Now()
testCases := []struct {
rule *RecordingRule
metrics []datasource.Metric
expTS []prompbmarshal.TimeSeries
}{
{
&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",
}),
},
},
{
&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",
}),
},
},
{
&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",
}),
},
},
}
for _, tc := range testCases {
t.Run(tc.rule.Name, func(t *testing.T) {
fq := &fakeQuerier{}
fq.add(tc.metrics...)
tc.rule.q = fq
tss, err := tc.rule.ExecRange(context.TODO(), time.Now(), time.Now(), 0)
if err != nil {
t.Fatalf("unexpected Exec err: %s", err)
}
if err := compareTimeSeries(t, tc.expTS, tss); err != nil {
t.Fatalf("timeseries missmatch: %s", err)
}
})
}
}
func TestRecordingRuleLimit(t *testing.T) {
timestamp := time.Now()
testCases := []struct {
limit int
err string
}{
{
limit: 0,
},
{
limit: -1,
},
{
limit: 1,
err: "exec exceeded limit of 1 with 3 series",
},
{
limit: 2,
err: "exec exceeded limit of 2 with 3 series",
},
}
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"),
}
rule := &RecordingRule{Name: "job:foo", Labels: map[string]string{
"source": "test_limit",
}}
var err error
for _, testCase := range testCases {
fq := &fakeQuerier{}
fq.add(testMetrics...)
rule.q = fq
_, err = rule.Exec(context.TODO(), timestamp, testCase.limit)
if err != nil && !strings.EqualFold(err.Error(), testCase.err) {
t.Fatal(err)
}
_, err = rule.ExecRange(context.TODO(), timestamp.Add(-2*time.Second), timestamp, testCase.limit)
if err != nil && !strings.EqualFold(err.Error(), testCase.err) {
t.Fatal(err)
}
}
}
func TestRecordingRule_ExecNegative(t *testing.T) {
rr := &RecordingRule{Name: "job:foo", Labels: map[string]string{
"job": "test",
}}
fq := &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("expected to get err; got nil")
}
if !strings.Contains(err.Error(), errDuplicate.Error()) {
t.Fatalf("expected to get err %q; got %q insterad", errDuplicate, err)
}
}