Chore: Reduce TSDB Go code complexity (#26401)

* tsdb: Make code less complex

pkg/tsdb/cloudmonitoring/cloudmonitoring.go

@@ -502,11 +502,43 @@ func (e *CloudMonitoringExecutor) unmarshalResponse(res *http.Response) (cloudMo
 	return data, nil
 }
 
+func handleDistributionSeries(series timeSeries, defaultMetricName string, seriesLabels map[string]string,
+	query *cloudMonitoringQuery, queryRes *tsdb.QueryResult) {
+	points := make([]tsdb.TimePoint, 0)
+	for i := len(series.Points) - 1; i >= 0; i-- {
+		point := series.Points[i]
+		value := point.Value.DoubleValue
+
+		if series.ValueType == "INT64" {
+			parsedValue, err := strconv.ParseFloat(point.Value.IntValue, 64)
+			if err == nil {
+				value = parsedValue
+			}
+		}
+
+		if series.ValueType == "BOOL" {
+			if point.Value.BoolValue {
+				value = 1
+			} else {
+				value = 0
+			}
+		}
+
+		points = append(points, tsdb.NewTimePoint(null.FloatFrom(value), float64((point.Interval.EndTime).Unix())*1000))
+	}
+
+	metricName := formatLegendKeys(series.Metric.Type, defaultMetricName, seriesLabels, nil, query)
+
+	queryRes.Series = append(queryRes.Series, &tsdb.TimeSeries{
+		Name:   metricName,
+		Points: points,
+	})
+}
+
 func (e *CloudMonitoringExecutor) parseResponse(queryRes *tsdb.QueryResult, data cloudMonitoringResponse, query *cloudMonitoringQuery) error {
 	labels := make(map[string]map[string]bool)
 
 	for _, series := range data.TimeSeries {
-		points := make([]tsdb.TimePoint, 0)
 		seriesLabels := make(map[string]string)
 		defaultMetricName := series.Metric.Type
 		labels["resource.type"] = map[string]bool{series.Resource.Type: true}
@@ -566,34 +598,7 @@ func (e *CloudMonitoringExecutor) parseResponse(queryRes *tsdb.QueryResult, data
 
 		// reverse the order to be ascending
 		if series.ValueType != "DISTRIBUTION" {
-			for i := len(series.Points) - 1; i >= 0; i-- {
-				point := series.Points[i]
-				value := point.Value.DoubleValue
-
-				if series.ValueType == "INT64" {
-					parsedValue, err := strconv.ParseFloat(point.Value.IntValue, 64)
-					if err == nil {
-						value = parsedValue
-					}
-				}
-
-				if series.ValueType == "BOOL" {
-					if point.Value.BoolValue {
-						value = 1
-					} else {
-						value = 0
-					}
-				}
-
-				points = append(points, tsdb.NewTimePoint(null.FloatFrom(value), float64((point.Interval.EndTime).Unix())*1000))
-			}
-
-			metricName := formatLegendKeys(series.Metric.Type, defaultMetricName, seriesLabels, nil, query)
-
-			queryRes.Series = append(queryRes.Series, &tsdb.TimeSeries{
-				Name:   metricName,
-				Points: points,
-			})
+			handleDistributionSeries(series, defaultMetricName, seriesLabels, query, queryRes)
 		} else {
 			buckets := make(map[int]*tsdb.TimeSeries)
 

pkg/tsdb/cloudmonitoring/types.go

@@ -65,7 +65,11 @@ type (
 	}
 
 	cloudMonitoringResponse struct {
-		TimeSeries []struct {
+		TimeSeries []timeSeries `json:"timeSeries"`
+	}
+)
+
+type timeSeries struct {
 	Metric struct {
 		Labels map[string]string `json:"labels"`
 		Type   string            `json:"type"`
@@ -105,6 +109,4 @@ type (
 			} `json:"distributionValue"`
 		} `json:"value"`
 	} `json:"points"`
-		} `json:"timeSeries"`
-	}
-)
+}

pkg/tsdb/elasticsearch/time_series_query.go

@@ -24,9 +24,6 @@ var newTimeSeriesQuery = func(client es.Client, tsdbQuery *tsdb.TsdbQuery, inter
 }
 
 func (e *timeSeriesQuery) execute() (*tsdb.Response, error) {
-	result := &tsdb.Response{}
-	result.Results = make(map[string]*tsdb.QueryResult)
-
 	tsQueryParser := newTimeSeriesQueryParser()
 	queries, err := tsQueryParser.parse(e.tsdbQuery)
 	if err != nil {
@@ -37,12 +34,35 @@ func (e *timeSeriesQuery) execute() (*tsdb.Response, error) {
 
 	from := fmt.Sprintf("%d", e.tsdbQuery.TimeRange.GetFromAsMsEpoch())
 	to := fmt.Sprintf("%d", e.tsdbQuery.TimeRange.GetToAsMsEpoch())
-
+	result := &tsdb.Response{
+		Results: make(map[string]*tsdb.QueryResult),
+	}
 	for _, q := range queries {
-		minInterval, err := e.client.GetMinInterval(q.Interval)
+		if err := e.processQuery(q, ms, from, to, result); err != nil {
+			return nil, err
+		}
+	}
+
+	req, err := ms.Build()
 	if err != nil {
 		return nil, err
 	}
+
+	res, err := e.client.ExecuteMultisearch(req)
+	if err != nil {
+		return nil, err
+	}
+
+	rp := newResponseParser(res.Responses, queries, res.DebugInfo)
+	return rp.getTimeSeries()
+}
+
+func (e *timeSeriesQuery) processQuery(q *Query, ms *es.MultiSearchRequestBuilder, from, to string,
+	result *tsdb.Response) error {
+	minInterval, err := e.client.GetMinInterval(q.Interval)
+	if err != nil {
+		return err
+	}
 	interval := e.intervalCalculator.Calculate(e.tsdbQuery.TimeRange, minInterval)
 
 	b := ms.Search(interval)
@@ -61,13 +81,13 @@ func (e *timeSeriesQuery) execute() (*tsdb.Response, error) {
 				Error:       fmt.Errorf("invalid query, missing metrics and aggregations"),
 				ErrorString: "invalid query, missing metrics and aggregations",
 			}
-				continue
+			return nil
 		}
 		metric := q.Metrics[0]
 		b.Size(metric.Settings.Get("size").MustInt(500))
 		b.SortDesc("@timestamp", "boolean")
 		b.AddDocValueField("@timestamp")
-			continue
+		return nil
 	}
 
 	aggBuilder := b.Agg()
@@ -152,20 +172,8 @@ func (e *timeSeriesQuery) execute() (*tsdb.Response, error) {
 			})
 		}
 	}
-	}
-
-	req, err := ms.Build()
-	if err != nil {
-		return nil, err
-	}
-
-	res, err := e.client.ExecuteMultisearch(req)
-	if err != nil {
-		return nil, err
-	}
 
-	rp := newResponseParser(res.Responses, queries, res.DebugInfo)
-	return rp.getTimeSeries()
+	return nil
 }
 
 func addDateHistogramAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg, timeFrom, timeTo string) es.AggBuilder {