[chore] prometheusreceiver: remove unnecessary string concatenations …

…and copies, use struct key (open-telemetry#13917)

This is not the final solution, but it is better than what we have right now.

Signed-off-by: Bogdan Drutu <[email protected]>

Signed-off-by: Bogdan Drutu <[email protected]>

receiver/prometheusreceiver/internal/metrics_adjuster.go

@@ -15,7 +15,6 @@
 package internal // import "github.com/open-telemetry/opentelemetry-collector-contrib/receiver/prometheusreceiver/internal"
 
 import (
- "fmt"
  "strings"
  "sync"
  "time"
@@ -85,6 +84,12 @@ type summaryInfo struct {
  previousSum float64
 }
 
+type timeserieskey struct {
+ name string
+ attributes string
+ aggTemporality pmetric.MetricAggregationTemporality
+}
+
 // timeseriesMap maps from a timeseries instance (metric * label values) to the timeseries info for
 // the instance.
 type timeseriesMap struct {
@@ -93,34 +98,37 @@ type timeseriesMap struct {
  // AdjustMetricSlice() and also acquired by gc().
 
  mark bool
- tsiMap map[string]*timeseriesinfo
+ tsiMap map[timeserieskey]*timeseriesinfo
 }
 
 // Get the timeseriesinfo for the timeseries associated with the metric and label values.
 func (tsm *timeseriesMap) get(metric pmetric.Metric, kv pcommon.Map) (*timeseriesinfo, bool) {
  // This should only be invoked be functions called (directly or indirectly) by AdjustMetricSlice().
  // The lock protecting tsm.tsiMap is acquired there.
  name := metric.Name()
- sig := getTimeseriesSignature(name, kv)
+ key := timeserieskey{
+ name: name,
+ attributes: getAttributesSignature(kv),
+ }
  if metric.DataType() == pmetric.MetricDataTypeHistogram {
  // There are 2 types of Histograms whose aggregation temporality needs distinguishing:
  // * CumulativeHistogram
  // * GaugeHistogram
- aggTemporality := metric.Histogram().AggregationTemporality()
- sig += "," + aggTemporality.String()
+ key.aggTemporality = metric.Histogram().AggregationTemporality()
  }
- tsi, ok := tsm.tsiMap[sig]
+
+ tsm.mark = true
+ tsi, ok := tsm.tsiMap[key]
  if !ok {
  tsi = &timeseriesinfo{}
- tsm.tsiMap[sig] = tsi
+ tsm.tsiMap[key] = tsi
  }
- tsm.mark = true
  tsi.mark = true
  return tsi, ok
 }
 
 // Create a unique timeseries signature consisting of the metric name and label values.
-func getTimeseriesSignature(name string, kv pcommon.Map) string {
+func getAttributesSignature(kv pcommon.Map) string {
  labelValues := make([]string, 0, kv.Len())
  kv.Sort().Range(func(_ string, attrValue pcommon.Value) bool {
  value := attrValue.StringVal()
@@ -129,7 +137,7 @@ func getTimeseriesSignature(name string, kv pcommon.Map) string {
  }
  return true
  })
- return fmt.Sprintf("%s,%s", name, strings.Join(labelValues, ","))
+ return strings.Join(labelValues, ",")
 }
 
 // Remove timeseries that have aged out.
@@ -151,7 +159,7 @@ func (tsm *timeseriesMap) gc() {
 }
 
 func newTimeseriesMap() *timeseriesMap {
- return &timeseriesMap{mark: true, tsiMap: map[string]*timeseriesinfo{}}
+ return &timeseriesMap{mark: true, tsiMap: map[timeserieskey]*timeseriesinfo{}}
 }
 
 // JobsMap maps from a job instance to a map of timeseries instances for the job.