(am annotatedMetric, labels []string)
| 237 | } |
| 238 | |
| 239 | func (a *labelAggregator) aggregate(am annotatedMetric, labels []string) error { |
| 240 | // Use a LabelSet because it can give deterministic fingerprints of label combinations regardless of map ordering. |
| 241 | labelSet := make(model.LabelSet, len(labels)) |
| 242 | |
| 243 | for _, label := range labels { |
| 244 | val, err := am.getFieldByLabel(label) |
| 245 | if err != nil { |
| 246 | return err |
| 247 | } |
| 248 | |
| 249 | labelSet[model.LabelName(label)] = model.LabelValue(val) |
| 250 | } |
| 251 | |
| 252 | // Memoize based on the metric name & the unique combination of labels. |
| 253 | key := fmt.Sprintf("%s:%v", am.Stats_Metric.Name, labelSet.FastFingerprint()) |
| 254 | |
| 255 | // Aggregate the value based on the key. |
| 256 | a.aggregations[key] += am.Value |
| 257 | |
| 258 | metric, found := a.metrics[key] |
| 259 | if !found { |
| 260 | // Take a copy of the given annotatedMetric because it may be manipulated later and contains pointers. |
| 261 | metric = am.shallowCopy() |
| 262 | } |
| 263 | |
| 264 | // Store the metric. |
| 265 | metric.aggregateByLabels = labels |
| 266 | metric.Value = a.aggregations[key] |
| 267 | |
| 268 | a.metrics[key] = metric |
| 269 | |
| 270 | return nil |
| 271 | } |
| 272 | |
| 273 | func (a *labelAggregator) listMetrics() []annotatedMetric { |
| 274 | var out []annotatedMetric |
no test coverage detected