public/grafana
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

CloudWatch: Expand alias variables when query yields no result (#22695)

Browse Source 
* Return empty time series with expanded aliases in case query yielded no results

* PR feedback
This commit is contained in:
Erik Sundell
2020-03-10 21:14:58 +01:00
committed by GitHub
parent 73c4bef70f
commit 763fb3bc32
4 changed files with 172 additions and 29 deletions
Download Patch File Download Diff File Expand all files Collapse all files
pkg/tsdb/cloudwatch/response_parser.go
+57 -29
View File
@@ -83,44 +83,72 @@ func parseGetMetricDataTimeSeries(metricDataResults map[string]*cloudwatch.Metri
}
}
series := tsdb.TimeSeries{
Tags: make(map[string]string),
Points: make([]tsdb.TimePoint, 0),
}
// In case a multi-valued dimension is used and the cloudwatch query yields no values, create one empty time series for each dimension value.
// Use that dimension value to expand the alias field
if len(metricDataResult.Values) == 0 && query.isMultiValuedDimensionExpression() {
series := 0
multiValuedDimension := ""
for key, values := range query.Dimensions {
if len(values) > series {
series = len(values)
multiValuedDimension = key
}
}
keys := make([]string, 0)
for k := range query.Dimensions {
keys = append(keys, k)
}
sort.Strings(keys)
for _, value := range query.Dimensions[multiValuedDimension] {
emptySeries := tsdb.TimeSeries{
Tags: map[string]string{multiValuedDimension: value},
Points: make([]tsdb.TimePoint, 0),
}
for key, values := range query.Dimensions {
if key != multiValuedDimension && len(values) > 0 {
emptySeries.Tags[key] = values[0]
}
}
for _, key := range keys {
values := query.Dimensions[key]
if len(values) == 1 && values[0] != "*" {
series.Tags[key] = values[0]
} else {
for _, value := range values {
if value == label || value == "*" {
series.Tags[key] = label
} else if strings.Contains(label, value) {
series.Tags[key] = value
emptySeries.Name = formatAlias(query, query.Stats, emptySeries.Tags, label)
result = append(result, &emptySeries)
}
} else {
keys := make([]string, 0)
for k := range query.Dimensions {
keys = append(keys, k)
}
sort.Strings(keys)
series := tsdb.TimeSeries{
Tags: make(map[string]string),
Points: make([]tsdb.TimePoint, 0),
}
for _, key := range keys {
values := query.Dimensions[key]
if len(values) == 1 && values[0] != "*" {
series.Tags[key] = values[0]
} else {
for _, value := range values {
if value == label || value == "*" {
series.Tags[key] = label
} else if strings.Contains(label, value) {
series.Tags[key] = value
}
}
}
}
}
series.Name = formatAlias(query, query.Stats, series.Tags, label)
series.Name = formatAlias(query, query.Stats, series.Tags, label)
for j, t := range metricDataResult.Timestamps {
if j > 0 {
expectedTimestamp := metricDataResult.Timestamps[j-1].Add(time.Duration(query.Period) * time.Second)
if expectedTimestamp.Before(*t) {
series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFromPtr(nil), float64(expectedTimestamp.Unix()*1000)))
for j, t := range metricDataResult.Timestamps {
if j > 0 {
expectedTimestamp := metricDataResult.Timestamps[j-1].Add(time.Duration(query.Period) * time.Second)
if expectedTimestamp.Before(*t) {
series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFromPtr(nil), float64(expectedTimestamp.Unix()*1000)))
}
}
series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFrom(*metricDataResult.Values[j]), float64((*t).Unix())*1000))
}
series.Points = append(series.Points, tsdb.NewTimePoint(null.FloatFrom(*metricDataResult.Values[j]), float64((*t).Unix())*1000))
result = append(result, &series)
}
result = append(result, &series)
}
return &result, partialData, nil
}
@@ -142,7 +170,7 @@ func formatAlias(query *cloudWatchQuery, stat string, dimensions map[string]stri
return query.Id
}
if len(query.Alias) == 0 && query.isInferredSearchExpression() {
if len(query.Alias) == 0 && query.isInferredSearchExpression() && !query.isMultiValuedDimensionExpression() {
return label
}