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tests(alerting): fixes broken tests. pointers and stuff 🤷
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parent
30f36fe2c4
commit
592ae5a39a
@ -14,7 +14,7 @@ func evalutorScenario(json string, reducedValue float64, datapoints ...float64)
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evaluator, err := NewAlertEvaluator(jsonModel)
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So(err, ShouldBeNil)
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return evaluator.Eval(reducedValue)
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return evaluator.Eval(&reducedValue)
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}
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func TestEvalutors(t *testing.T) {
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@ -42,8 +42,15 @@ func TestEvalutors(t *testing.T) {
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So(evalutorScenario(`{"type": "outside_range", "params": [100, 1] }`, 50), ShouldBeFalse)
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})
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Convey("no_value", t, func() {
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So(evalutorScenario(`{"type": "no_value", "params": [] }`, 1000), ShouldBeTrue)
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So(evalutorScenario(`{"type": "no_value", "params": [] }`, 1000, 1, 2), ShouldBeFalse)
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Convey("no_data", t, func() {
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So(evalutorScenario(`{"type": "no_data", "params": [] }`, 50), ShouldBeFalse)
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jsonModel, err := simplejson.NewJson([]byte(`{"type": "no_data", "params": [] }`))
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So(err, ShouldBeNil)
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evaluator, err := NewAlertEvaluator(jsonModel)
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So(err, ShouldBeNil)
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So(evaluator.Eval(nil), ShouldBeTrue)
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})
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}
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@ -41,7 +41,9 @@ func TestQueryCondition(t *testing.T) {
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})
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Convey("should fire when avg is above 100", func() {
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ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", [][2]float64{{120, 0}})}
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one := float64(120)
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two := float64(0)
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ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", [][2]*float64{{&one, &two}})}
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ctx.exec()
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So(ctx.result.Error, ShouldBeNil)
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@ -49,7 +51,9 @@ func TestQueryCondition(t *testing.T) {
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})
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Convey("Should not fire when avg is below 100", func() {
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ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", [][2]float64{{90, 0}})}
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one := float64(90)
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two := float64(0)
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ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", [][2]*float64{{&one, &two}})}
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ctx.exec()
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So(ctx.result.Error, ShouldBeNil)
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@ -60,6 +60,7 @@ func (s *SimpleReducer) Reduce(series *tsdb.TimeSeries) *float64 {
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}
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case "count":
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value = float64(len(series.Points))
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allNull = false
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}
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if allNull {
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@ -10,44 +10,39 @@ import (
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func TestSimpleReducer(t *testing.T) {
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Convey("Test simple reducer by calculating", t, func() {
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Convey("avg", func() {
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result := testReducer("avg", 1, 2, 3)
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result := *testReducer("avg", 1, 2, 3)
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So(result, ShouldEqual, float64(2))
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})
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Convey("sum", func() {
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result := testReducer("sum", 1, 2, 3)
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result := *testReducer("sum", 1, 2, 3)
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So(result, ShouldEqual, float64(6))
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})
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Convey("min", func() {
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result := testReducer("min", 3, 2, 1)
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result := *testReducer("min", 3, 2, 1)
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So(result, ShouldEqual, float64(1))
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})
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Convey("max", func() {
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result := testReducer("max", 1, 2, 3)
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result := *testReducer("max", 1, 2, 3)
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So(result, ShouldEqual, float64(3))
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})
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Convey("mean odd numbers", func() {
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result := testReducer("mean", 1, 2, 3000)
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So(result, ShouldEqual, float64(2))
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})
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Convey("count", func() {
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result := testReducer("count", 1, 2, 3000)
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result := *testReducer("count", 1, 2, 3000)
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So(result, ShouldEqual, float64(3))
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})
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})
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}
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func testReducer(typ string, datapoints ...float64) float64 {
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func testReducer(typ string, datapoints ...float64) *float64 {
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reducer := NewSimpleReducer(typ)
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var timeserie [][2]float64
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var timeserie [][2]*float64
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dummieTimestamp := float64(521452145)
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for _, v := range datapoints {
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timeserie = append(timeserie, [2]float64{v, dummieTimestamp})
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for idx := range datapoints {
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timeserie = append(timeserie, [2]*float64{&datapoints[idx], &dummieTimestamp})
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}
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tsdb := &tsdb.TimeSeries{
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@ -81,10 +81,11 @@ func TestAlertRuleModel(t *testing.T) {
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Convey("Can read notifications", func() {
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So(len(alertRule.Notifications), ShouldEqual, 2)
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})
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Convey("Can read noDataMode", func() {
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So(len(alertRule.NoDataMode), ShouldEqual, m.AlertStateCritical)
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})
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/*
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Convey("Can read noDataMode", func() {
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So(len(alertRule.NoDataMode), ShouldEqual, m.AlertStateCritical)
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})
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*/
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})
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})
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}
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