Esempio n. 1
0
func (c *QueryCondition) Eval(context *alerting.EvalContext) (*alerting.ConditionResult, error) {
	timeRange := tsdb.NewTimeRange(c.Query.From, c.Query.To)

	seriesList, err := c.executeQuery(context, timeRange)
	if err != nil {
		return nil, err
	}

	emptySerieCount := 0
	evalMatchCount := 0
	var matches []*alerting.EvalMatch

	for _, series := range seriesList {
		reducedValue := c.Reducer.Reduce(series)
		evalMatch := c.Evaluator.Eval(reducedValue)

		if reducedValue.Valid == false {
			emptySerieCount++
		}

		if context.IsTestRun {
			context.Logs = append(context.Logs, &alerting.ResultLogEntry{
				Message: fmt.Sprintf("Condition[%d]: Eval: %v, Metric: %s, Value: %s", c.Index, evalMatch, series.Name, reducedValue),
			})
		}

		if evalMatch {
			evalMatchCount++

			matches = append(matches, &alerting.EvalMatch{
				Metric: series.Name,
				Value:  reducedValue,
			})
		}
	}

	// handle no series special case
	if len(seriesList) == 0 {
		// eval condition for null value
		evalMatch := c.Evaluator.Eval(null.FloatFromPtr(nil))

		if context.IsTestRun {
			context.Logs = append(context.Logs, &alerting.ResultLogEntry{
				Message: fmt.Sprintf("Condition[%d]: Eval: %v, Query Returned No Series (reduced to null/no value)", evalMatch),
			})
		}

		if evalMatch {
			evalMatchCount++
			matches = append(matches, &alerting.EvalMatch{Metric: "NoData", Value: null.FloatFromPtr(nil)})
		}
	}

	return &alerting.ConditionResult{
		Firing:      evalMatchCount > 0,
		NoDataFound: emptySerieCount == len(seriesList),
		Operator:    c.Operator,
		EvalMatches: matches,
	}, nil
}
Esempio n. 2
0
func (rp *ResponseParser) parseValue(value interface{}) null.Float {
	number, ok := value.(json.Number)
	if !ok {
		return null.FloatFromPtr(nil)
	}

	fvalue, err := number.Float64()
	if err == nil {
		return null.FloatFrom(fvalue)
	}

	ivalue, err := number.Int64()
	if err == nil {
		return null.FloatFrom(float64(ivalue))
	}

	return null.FloatFromPtr(nil)
}
Esempio n. 3
0
func TestEvalutors(t *testing.T) {
	Convey("greater then", t, func() {
		So(evalutorScenario(`{"type": "gt", "params": [1] }`, 3), ShouldBeTrue)
		So(evalutorScenario(`{"type": "gt", "params": [3] }`, 1), ShouldBeFalse)
	})

	Convey("less then", t, func() {
		So(evalutorScenario(`{"type": "lt", "params": [1] }`, 3), ShouldBeFalse)
		So(evalutorScenario(`{"type": "lt", "params": [3] }`, 1), ShouldBeTrue)
	})

	Convey("within_range", t, func() {
		So(evalutorScenario(`{"type": "within_range", "params": [1, 100] }`, 3), ShouldBeTrue)
		So(evalutorScenario(`{"type": "within_range", "params": [1, 100] }`, 300), ShouldBeFalse)
		So(evalutorScenario(`{"type": "within_range", "params": [100, 1] }`, 3), ShouldBeTrue)
		So(evalutorScenario(`{"type": "within_range", "params": [100, 1] }`, 300), ShouldBeFalse)
	})

	Convey("outside_range", t, func() {
		So(evalutorScenario(`{"type": "outside_range", "params": [1, 100] }`, 1000), ShouldBeTrue)
		So(evalutorScenario(`{"type": "outside_range", "params": [1, 100] }`, 50), ShouldBeFalse)
		So(evalutorScenario(`{"type": "outside_range", "params": [100, 1] }`, 1000), ShouldBeTrue)
		So(evalutorScenario(`{"type": "outside_range", "params": [100, 1] }`, 50), ShouldBeFalse)
	})

	Convey("no_value", t, func() {
		Convey("should be false if serie have values", func() {
			So(evalutorScenario(`{"type": "no_value", "params": [] }`, 50), ShouldBeFalse)
		})

		Convey("should be true when the serie have no value", func() {
			jsonModel, err := simplejson.NewJson([]byte(`{"type": "no_value", "params": [] }`))
			So(err, ShouldBeNil)

			evaluator, err := NewAlertEvaluator(jsonModel)
			So(err, ShouldBeNil)

			So(evaluator.Eval(null.FloatFromPtr(nil)), ShouldBeTrue)

		})
	})
}
Esempio n. 4
0
func TestQueryCondition(t *testing.T) {

	Convey("when evaluating query condition", t, func() {

		queryConditionScenario("Given avg() and > 100", func(ctx *queryConditionTestContext) {

			ctx.reducer = `{"type": "avg"}`
			ctx.evaluator = `{"type": "gt", "params": [100]}`

			Convey("Can read query condition from json model", func() {
				ctx.exec()

				So(ctx.condition.Query.From, ShouldEqual, "5m")
				So(ctx.condition.Query.To, ShouldEqual, "now")
				So(ctx.condition.Query.DatasourceId, ShouldEqual, 1)

				Convey("Can read query reducer", func() {
					reducer, ok := ctx.condition.Reducer.(*SimpleReducer)
					So(ok, ShouldBeTrue)
					So(reducer.Type, ShouldEqual, "avg")
				})

				Convey("Can read evaluator", func() {
					evaluator, ok := ctx.condition.Evaluator.(*ThresholdEvaluator)
					So(ok, ShouldBeTrue)
					So(evaluator.Type, ShouldEqual, "gt")
				})
			})

			Convey("should fire when avg is above 100", func() {
				points := tsdb.NewTimeSeriesPointsFromArgs(120, 0)
				ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", points)}
				cr, err := ctx.exec()

				So(err, ShouldBeNil)
				So(cr.Firing, ShouldBeTrue)
			})

			Convey("Should not fire when avg is below 100", func() {
				points := tsdb.NewTimeSeriesPointsFromArgs(90, 0)
				ctx.series = tsdb.TimeSeriesSlice{tsdb.NewTimeSeries("test1", points)}
				cr, err := ctx.exec()

				So(err, ShouldBeNil)
				So(cr.Firing, ShouldBeFalse)
			})

			Convey("Should fire if only first serie matches", func() {
				ctx.series = tsdb.TimeSeriesSlice{
					tsdb.NewTimeSeries("test1", tsdb.NewTimeSeriesPointsFromArgs(120, 0)),
					tsdb.NewTimeSeries("test2", tsdb.NewTimeSeriesPointsFromArgs(0, 0)),
				}
				cr, err := ctx.exec()

				So(err, ShouldBeNil)
				So(cr.Firing, ShouldBeTrue)
			})

			Convey("No series", func() {
				Convey("Should set NoDataFound when condition is gt", func() {
					ctx.series = tsdb.TimeSeriesSlice{}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.Firing, ShouldBeFalse)
					So(cr.NoDataFound, ShouldBeTrue)
				})

				Convey("Should be firing when condition is no_value", func() {
					ctx.evaluator = `{"type": "no_value", "params": []}`
					ctx.series = tsdb.TimeSeriesSlice{}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.Firing, ShouldBeTrue)
				})
			})

			Convey("Empty series", func() {
				Convey("Should set Firing if eval match", func() {
					ctx.evaluator = `{"type": "no_value", "params": []}`
					ctx.series = tsdb.TimeSeriesSlice{
						tsdb.NewTimeSeries("test1", tsdb.NewTimeSeriesPointsFromArgs()),
					}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.Firing, ShouldBeTrue)
				})

				Convey("Should set NoDataFound both series are empty", func() {
					ctx.series = tsdb.TimeSeriesSlice{
						tsdb.NewTimeSeries("test1", tsdb.NewTimeSeriesPointsFromArgs()),
						tsdb.NewTimeSeries("test2", tsdb.NewTimeSeriesPointsFromArgs()),
					}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.NoDataFound, ShouldBeTrue)
				})

				Convey("Should set NoDataFound both series contains null", func() {
					ctx.series = tsdb.TimeSeriesSlice{
						tsdb.NewTimeSeries("test1", tsdb.TimeSeriesPoints{tsdb.TimePoint{null.FloatFromPtr(nil), null.FloatFrom(0)}}),
						tsdb.NewTimeSeries("test2", tsdb.TimeSeriesPoints{tsdb.TimePoint{null.FloatFromPtr(nil), null.FloatFrom(0)}}),
					}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.NoDataFound, ShouldBeTrue)
				})

				Convey("Should not set NoDataFound if one serie is empty", func() {
					ctx.series = tsdb.TimeSeriesSlice{
						tsdb.NewTimeSeries("test1", tsdb.NewTimeSeriesPointsFromArgs()),
						tsdb.NewTimeSeries("test2", tsdb.NewTimeSeriesPointsFromArgs(120, 0)),
					}
					cr, err := ctx.exec()

					So(err, ShouldBeNil)
					So(cr.NoDataFound, ShouldBeFalse)
				})
			})
		})
	})
}
Esempio n. 5
0
func TestSimpleReducer(t *testing.T) {
	Convey("Test simple reducer by calculating", t, func() {

		Convey("sum", func() {
			result := testReducer("sum", 1, 2, 3)
			So(result, ShouldEqual, float64(6))
		})

		Convey("min", func() {
			result := testReducer("min", 3, 2, 1)
			So(result, ShouldEqual, float64(1))
		})

		Convey("max", func() {
			result := testReducer("max", 1, 2, 3)
			So(result, ShouldEqual, float64(3))
		})

		Convey("count", func() {
			result := testReducer("count", 1, 2, 3000)
			So(result, ShouldEqual, float64(3))
		})

		Convey("last", func() {
			result := testReducer("last", 1, 2, 3000)
			So(result, ShouldEqual, float64(3000))
		})

		Convey("median odd amount of numbers", func() {
			result := testReducer("median", 1, 2, 3000)
			So(result, ShouldEqual, float64(2))
		})

		Convey("median even amount of numbers", func() {
			result := testReducer("median", 1, 2, 4, 3000)
			So(result, ShouldEqual, float64(3))
		})

		Convey("median with one values", func() {
			result := testReducer("median", 1)
			So(result, ShouldEqual, float64(1))
		})

		Convey("avg", func() {
			result := testReducer("avg", 1, 2, 3)
			So(result, ShouldEqual, float64(2))
		})

		Convey("avg with only nulls", func() {
			reducer := NewSimpleReducer("avg")
			series := &tsdb.TimeSeries{
				Name: "test time serie",
			}

			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFromPtr(nil), 1))
			So(reducer.Reduce(series).Valid, ShouldEqual, false)
		})

		Convey("avg of number values and null values should ignore nulls", func() {
			reducer := NewSimpleReducer("avg")
			series := &tsdb.TimeSeries{
				Name: "test time serie",
			}

			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFrom(3), 1))
			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFromPtr(nil), 2))
			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFromPtr(nil), 3))
			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFrom(3), 4))

			So(reducer.Reduce(series).Float64, ShouldEqual, float64(3))
		})
	})
}
Esempio n. 6
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func (s *SimpleReducer) Reduce(series *tsdb.TimeSeries) null.Float {
	if len(series.Points) == 0 {
		return null.FloatFromPtr(nil)
	}

	value := float64(0)
	allNull := true

	switch s.Type {
	case "avg":
		validPointsCount := 0
		for _, point := range series.Points {
			if point[0].Valid {
				value += point[0].Float64
				validPointsCount += 1
				allNull = false
			}
		}
		if validPointsCount > 0 {
			value = value / float64(validPointsCount)
		}
	case "sum":
		for _, point := range series.Points {
			if point[0].Valid {
				value += point[0].Float64
				allNull = false
			}
		}
	case "min":
		value = math.MaxFloat64
		for _, point := range series.Points {
			if point[0].Valid {
				allNull = false
				if value > point[0].Float64 {
					value = point[0].Float64
				}
			}
		}
	case "max":
		value = -math.MaxFloat64
		for _, point := range series.Points {
			if point[0].Valid {
				allNull = false
				if value < point[0].Float64 {
					value = point[0].Float64
				}
			}
		}
	case "count":
		value = float64(len(series.Points))
		allNull = false
	case "last":
		points := series.Points
		for i := len(points) - 1; i >= 0; i-- {
			if points[i][0].Valid {
				value = points[i][0].Float64
				allNull = false
				break
			}
		}
	case "median":
		var values []float64
		for _, v := range series.Points {
			if v[0].Valid {
				allNull = false
				values = append(values, v[0].Float64)
			}
		}
		if len(values) >= 1 {
			sort.Float64s(values)
			length := len(values)
			if length%2 == 1 {
				value = values[(length-1)/2]
			} else {
				value = (values[(length/2)-1] + values[length/2]) / 2
			}
		}
	}

	if allNull {
		return null.FloatFromPtr(nil)
	}

	return null.FloatFrom(value)
}
Esempio n. 7
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func init() {
	ScenarioRegistry = make(map[string]*Scenario)
	logger := log.New("tsdb.testdata")

	logger.Debug("Initializing TestData Scenario")

	registerScenario(&Scenario{
		Id:   "random_walk",
		Name: "Random Walk",

		Handler: func(query *tsdb.Query, context *tsdb.QueryContext) *tsdb.QueryResult {
			timeWalkerMs := context.TimeRange.GetFromAsMsEpoch()
			to := context.TimeRange.GetToAsMsEpoch()

			series := newSeriesForQuery(query)

			points := make(tsdb.TimeSeriesPoints, 0)
			walker := rand.Float64() * 100

			for i := int64(0); i < 10000 && timeWalkerMs < to; i++ {
				points = append(points, tsdb.NewTimePoint(null.FloatFrom(walker), float64(timeWalkerMs)))

				walker += rand.Float64() - 0.5
				timeWalkerMs += query.IntervalMs
			}

			series.Points = points

			queryRes := tsdb.NewQueryResult()
			queryRes.Series = append(queryRes.Series, series)
			return queryRes
		},
	})

	registerScenario(&Scenario{
		Id:   "no_data_points",
		Name: "No Data Points",
		Handler: func(query *tsdb.Query, context *tsdb.QueryContext) *tsdb.QueryResult {
			return tsdb.NewQueryResult()
		},
	})

	registerScenario(&Scenario{
		Id:   "datapoints_outside_range",
		Name: "Datapoints Outside Range",
		Handler: func(query *tsdb.Query, context *tsdb.QueryContext) *tsdb.QueryResult {
			queryRes := tsdb.NewQueryResult()

			series := newSeriesForQuery(query)
			outsideTime := context.TimeRange.MustGetFrom().Add(-1*time.Hour).Unix() * 1000

			series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFrom(10), float64(outsideTime)))
			queryRes.Series = append(queryRes.Series, series)

			return queryRes
		},
	})

	registerScenario(&Scenario{
		Id:          "csv_metric_values",
		Name:        "CSV Metric Values",
		StringInput: "1,20,90,30,5,0",
		Handler: func(query *tsdb.Query, context *tsdb.QueryContext) *tsdb.QueryResult {
			queryRes := tsdb.NewQueryResult()

			stringInput := query.Model.Get("stringInput").MustString()
			stringInput = strings.Replace(stringInput, " ", "", -1)

			values := []null.Float{}
			for _, strVal := range strings.Split(stringInput, ",") {
				if strVal == "null" {
					values = append(values, null.FloatFromPtr(nil))
				}
				if val, err := strconv.ParseFloat(strVal, 64); err == nil {
					values = append(values, null.FloatFrom(val))
				}
			}

			if len(values) == 0 {
				return queryRes
			}

			series := newSeriesForQuery(query)
			startTime := context.TimeRange.GetFromAsMsEpoch()
			endTime := context.TimeRange.GetToAsMsEpoch()
			step := (endTime - startTime) / int64(len(values)-1)

			for _, val := range values {
				series.Points = append(series.Points, tsdb.TimePoint{val, null.FloatFrom(float64(startTime))})
				startTime += step
			}

			queryRes.Series = append(queryRes.Series, series)

			return queryRes
		},
	})
}