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feat(alerting): implement transform objects

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This commit is contained in:
bergquist
2016-06-10 15:31:17 +02:00
parent c18017381b
commit 83c422e6ef
6 changed files with 128 additions and 86 deletions
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pkg/services/alerting/executor.go
+9 -75
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@@ -3,8 +3,6 @@ package alerting
import (
"fmt"
"math"
"github.com/grafana/grafana/pkg/bus"
"github.com/grafana/grafana/pkg/log"
m "github.com/grafana/grafana/pkg/models"
@@ -26,63 +24,6 @@ func NewExecutor() *ExecutorImpl {
}
}
type compareFn func(float64, float64) bool
type aggregationFn func(*tsdb.TimeSeries) float64
var operators = map[string]compareFn{
">": func(num1, num2 float64) bool { return num1 > num2 },
">=": func(num1, num2 float64) bool { return num1 >= num2 },
"<": func(num1, num2 float64) bool { return num1 < num2 },
"<=": func(num1, num2 float64) bool { return num1 <= num2 },
"": func(num1, num2 float64) bool { return false },
}
var aggregator = map[string]aggregationFn{
"avg": func(series *tsdb.TimeSeries) float64 {
sum := float64(0)
for _, v := range series.Points {
sum += v[0]
}
return sum / float64(len(series.Points))
},
"sum": func(series *tsdb.TimeSeries) float64 {
sum := float64(0)
for _, v := range series.Points {
sum += v[0]
}
return sum
},
"min": func(series *tsdb.TimeSeries) float64 {
min := series.Points[0][0]
for _, v := range series.Points {
if v[0] < min {
min = v[0]
}
}
return min
},
"max": func(series *tsdb.TimeSeries) float64 {
max := series.Points[0][0]
for _, v := range series.Points {
if v[0] > max {
max = v[0]
}
}
return max
},
"mean": func(series *tsdb.TimeSeries) float64 {
midPosition := int64(math.Floor(float64(len(series.Points)) / float64(2)))
return series.Points[midPosition][0]
},
}
func (e *ExecutorImpl) Execute(job *AlertJob, resultQueue chan *AlertResult) {
timeSeries, err := e.executeQuery(job)
if err != nil {
@@ -156,32 +97,25 @@ func (e *ExecutorImpl) evaluateRule(rule *AlertRule, series tsdb.TimeSeriesSlice
for _, serie := range series {
e.log.Debug("Evaluating series", "series", serie.Name)
transformedValue, _ := rule.Transformer.Transform(serie)
if aggregator["avg"] == nil {
continue
}
var aggValue = aggregator["avg"](serie)
var critOperartor = operators[rule.Critical.Operator]
var critResult = critOperartor(aggValue, rule.Critical.Level)
e.log.Debug("Alert execution Crit", "name", serie.Name, "aggValue", aggValue, "operator", rule.Critical.Operator, "level", rule.Critical.Level, "result", critResult)
critResult := evalCondition(rule.Critical, transformedValue)
e.log.Debug("Alert execution Crit", "name", serie.Name, "transformedValue", transformedValue, "operator", rule.Critical.Operator, "level", rule.Critical.Level, "result", critResult)
if critResult {
return &AlertResult{
State: alertstates.Critical,
ActualValue: aggValue,
Description: fmt.Sprintf(descriptionFmt, aggValue, serie.Name),
ActualValue: transformedValue,
Description: fmt.Sprintf(descriptionFmt, transformedValue, serie.Name),
}
}
var warnOperartor = operators[rule.Warning.Operator]
var warnResult = warnOperartor(aggValue, rule.Warning.Level)
e.log.Debug("Alert execution Warn", "name", serie.Name, "aggValue", aggValue, "operator", rule.Warning.Operator, "level", rule.Warning.Level, "result", warnResult)
warnResult := evalCondition(rule.Warning, transformedValue)
e.log.Debug("Alert execution Warn", "name", serie.Name, "transformedValue", transformedValue, "operator", rule.Warning.Operator, "level", rule.Warning.Level, "result", warnResult)
if warnResult {
return &AlertResult{
State: alertstates.Warn,
Description: fmt.Sprintf(descriptionFmt, aggValue, serie.Name),
ActualValue: aggValue,
Description: fmt.Sprintf(descriptionFmt, transformedValue, serie.Name),
ActualValue: transformedValue,
}
}
}