Merge branch 'main' into nv/6703

docs/api/openapi.yml

@@ -842,6 +842,17 @@ components:
       - temporality
       - isMonotonic
       type: object
+    MetrictypesComparisonSpaceAggregationParam:
+      properties:
+        operator:
+          type: string
+        threshold:
+          format: double
+          type: number
+      required:
+      - operator
+      - threshold
+      type: object
     MetrictypesSpaceAggregation:
       enum:
       - sum
@@ -1138,6 +1149,8 @@ components:
       type: object
     Querybuildertypesv5MetricAggregation:
       properties:
+        comparisonSpaceAggregationParam:
+          $ref: '#/components/schemas/MetrictypesComparisonSpaceAggregationParam'
         metricName:
           type: string
         reduceTo:

frontend/src/api/generated/services/sigNoz.schemas.ts

@@ -1006,6 +1006,18 @@ export interface MetricsexplorertypesUpdateMetricMetadataRequestDTO {
 	unit: string;
 }
 
+export interface MetrictypesComparisonSpaceAggregationParamDTO {
+	/**
+	 * @type string
+	 */
+	operator: string;
+	/**
+	 * @type number
+	 * @format double
+	 */
+	threshold: number;
+}
+
 export enum MetrictypesSpaceAggregationDTO {
 	sum = 'sum',
 	avg = 'avg',
@@ -1367,6 +1379,7 @@ export interface Querybuildertypesv5LogAggregationDTO {
 }
 
 export interface Querybuildertypesv5MetricAggregationDTO {
+	comparisonSpaceAggregationParam?: MetrictypesComparisonSpaceAggregationParamDTO;
 	/**
 	 * @type string
 	 */

pkg/querier/builder_query.go

@@ -80,11 +80,16 @@ func (q *builderQuery[T]) Fingerprint() string {
 			case qbtypes.LogAggregation:
 				aggParts = append(aggParts, a.Expression)
 			case qbtypes.MetricAggregation:
-				aggParts = append(aggParts, fmt.Sprintf("%s:%s:%s:%s",
+				var spaceAggParamStr string
+				if a.ComparisonSpaceAggregationParam != nil {
+					spaceAggParamStr = a.ComparisonSpaceAggregationParam.StringValue()
+				}
+				aggParts = append(aggParts, fmt.Sprintf("%s:%s:%s:%s:%s",
 					a.MetricName,
 					a.Temporality.StringValue(),
 					a.TimeAggregation.StringValue(),
 					a.SpaceAggregation.StringValue(),
+					spaceAggParamStr,
 				))
 			}
 		}

pkg/querier/querier.go

@@ -276,15 +276,17 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
 
 	// Fetch temporality for all metrics at once
 	var metricTemporality map[string]metrictypes.Temporality
+	var metricTypes map[string]metrictypes.Type
 	if len(metricNames) > 0 {
 		var err error
-		metricTemporality, err = q.metadataStore.FetchTemporalityMulti(ctx, req.Start, req.End, metricNames...)
+		metricTemporality, metricTypes, err = q.metadataStore.FetchTemporalityAndTypeMulti(ctx, req.Start, req.End, metricNames...)
 		if err != nil {
 			q.logger.WarnContext(ctx, "failed to fetch metric temporality", "error", err, "metrics", metricNames)
 			// Continue without temporality - statement builder will handle unspecified
 			metricTemporality = make(map[string]metrictypes.Temporality)
+			metricTypes = make(map[string]metrictypes.Type)
 		}
-		q.logger.DebugContext(ctx, "fetched metric temporalities", "metric_temporality", metricTemporality)
+		q.logger.DebugContext(ctx, "fetched metric temporalities and types", "metric_temporality", metricTemporality, "metric_types", metricTypes)
 	}
 
 	queries := make(map[string]qbtypes.Query)
@@ -380,6 +382,12 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
 					if spec.Aggregations[i].Temporality == metrictypes.Unknown {
 						spec.Aggregations[i].Temporality = metrictypes.Unspecified
 					}
+
+					if spec.Aggregations[i].MetricName != "" && spec.Aggregations[i].Type == metrictypes.UnspecifiedType {
+						if foundMetricType, ok := metricTypes[spec.Aggregations[i].MetricName]; ok && foundMetricType != metrictypes.UnspecifiedType {
+							spec.Aggregations[i].Type = foundMetricType
+						}
+					}
 				}
 				spec.ShiftBy = extractShiftFromBuilderQuery(spec)
 				timeRange := adjustTimeRangeForShift(spec, qbtypes.TimeRange{From: req.Start, To: req.End}, req.RequestType)

pkg/telemetrymetadata/metadata.go

@@ -1616,40 +1616,52 @@ func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, queryTimeRang
 }
 
 func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
+	temporalities, _, err := t.FetchTemporalityAndTypeMulti(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
+	return temporalities, err
+}
+
+func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {
 	if len(metricNames) == 0 {
-		return make(map[string]metrictypes.Temporality), nil
+		return make(map[string]metrictypes.Temporality), make(map[string]metrictypes.Type), nil
 	}
 
-	result := make(map[string]metrictypes.Temporality)
-	metricsTemporality, err := t.fetchMetricsTemporality(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
+	temporalities := make(map[string]metrictypes.Temporality)
+	types := make(map[string]metrictypes.Type)
+	metricsTemporality, metricTypes, err := t.fetchMetricsTemporalityAndType(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
 	if err != nil {
-		return nil, err
+		return nil, nil, err
 	}
 	// TODO: return error after table migration are run
-	meterMetricsTemporality, _ := t.fetchMeterSourceMetricsTemporality(ctx, metricNames...)
+	meterMetricsTemporality, meterMetricsTypes, _ := t.fetchMeterSourceMetricsTemporalityAndType(ctx, metricNames...)
 
 	// For metrics not found in the database, set to Unknown
 	for _, metricName := range metricNames {
 		if temporality, exists := metricsTemporality[metricName]; exists && len(temporality) > 0 {
 			if len(temporality) > 1 {
-				result[metricName] = metrictypes.Multiple
+				temporalities[metricName] = metrictypes.Multiple
 			} else {
-				result[metricName] = temporality[0]
+				temporalities[metricName] = temporality[0]
 			}
-			continue
+		} else if temporality, exists := meterMetricsTemporality[metricName]; exists {
+			temporalities[metricName] = temporality
+		} else {
+			temporalities[metricName] = metrictypes.Unknown
 		}
-		if temporality, exists := meterMetricsTemporality[metricName]; exists {
-			result[metricName] = temporality
-			continue
+		if metricType, exists := metricTypes[metricName]; exists {
+			types[metricName] = metricType
+		} else if meterMetricType, exists := meterMetricsTypes[metricName]; exists {
+			types[metricName] = meterMetricType
+		} else {
+			types[metricName] = metrictypes.UnspecifiedType
 		}
-		result[metricName] = metrictypes.Unknown
 	}
 
-	return result, nil
+	return temporalities, types, nil
 }
 
-func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, error) {
-	result := make(map[string][]metrictypes.Temporality)
+func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, map[string]metrictypes.Type, error) {
+	temporalities := make(map[string][]metrictypes.Temporality)
+	types := make(map[string]metrictypes.Type)
 
 	adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, nil)
 
@@ -1660,6 +1672,8 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryT
 	sb := sqlbuilder.Select(
 		"metric_name",
 		"temporality",
+		"any(type) AS type",
+		"any(is_monotonic) as is_monotonic",
 	).
 		From(t.metricsDBName + "." + tsTableName)
 
@@ -1678,47 +1692,42 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryT
 
 	rows, err := t.telemetrystore.ClickhouseDB().Query(ctx, query, args...)
 	if err != nil {
-		return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
+		return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
 	}
 	defer rows.Close()
 
 	// Process results
 	for rows.Next() {
-		var metricName, temporalityStr string
-		if err := rows.Scan(&metricName, &temporalityStr); err != nil {
-			return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
-		}
-
-		// Convert string to Temporality type
+		var metricName string
 		var temporality metrictypes.Temporality
-		switch temporalityStr {
-		case "Delta":
-			temporality = metrictypes.Delta
-		case "Cumulative":
-			temporality = metrictypes.Cumulative
-		case "Unspecified":
-			temporality = metrictypes.Unspecified
-		default:
-			// Unknown or empty temporality
-			temporality = metrictypes.Unknown
+		var metricType metrictypes.Type
+		var isMonotonic bool
+		if err := rows.Scan(&metricName, &temporality, &metricType, &isMonotonic); err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
 		}
 		if temporality != metrictypes.Unknown {
-			result[metricName] = append(result[metricName], temporality)
+			temporalities[metricName] = append(temporalities[metricName], temporality)
 		}
+		if metricType == metrictypes.SumType && !isMonotonic {
+			metricType = metrictypes.GaugeType
+		}
+		types[metricName] = metricType
 	}
 	if err := rows.Err(); err != nil {
-		return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
+		return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
 	}
 
-	return result, nil
+	return temporalities, types, nil
 }
 
-func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error) {
-	result := make(map[string]metrictypes.Temporality)
+func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporalityAndType(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {
+	temporalities := make(map[string]metrictypes.Temporality)
+	types := make(map[string]metrictypes.Type)
 
 	sb := sqlbuilder.Select(
 		"metric_name",
 		"argMax(temporality, unix_milli) as temporality",
+		"any(type) AS type",
 	).From(t.meterDBName + "." + t.meterFieldsTblName)
 
 	// Filter by metric names (in the temporality column due to data mix-up)
@@ -1733,35 +1742,27 @@ func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Cont
 
 	rows, err := t.telemetrystore.ClickhouseDB().Query(ctx, query, args...)
 	if err != nil {
-		return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch meter metric temporality")
+		return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch meter metric temporality")
 	}
 	defer rows.Close()
 
 	// Process results
 	for rows.Next() {
-		var metricName, temporalityStr string
-		if err := rows.Scan(&metricName, &temporalityStr); err != nil {
-			return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
-		}
-
-		// Convert string to Temporality type
+		var metricName string
 		var temporality metrictypes.Temporality
-		switch temporalityStr {
-		case "Delta":
-			temporality = metrictypes.Delta
-		case "Cumulative":
-			temporality = metrictypes.Cumulative
-		case "Unspecified":
-			temporality = metrictypes.Unspecified
-		default:
-			// Unknown or empty temporality
-			temporality = metrictypes.Unknown
+		var metricType metrictypes.Type
+		var isMonotonic bool
+		if err := rows.Scan(&metricName, &temporality, &metricType, &isMonotonic); err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
 		}
-
-		result[metricName] = temporality
+		if metricType == metrictypes.SumType && !isMonotonic {
+			metricType = metrictypes.GaugeType
+		}
+		temporalities[metricName] = temporality
+		types[metricName] = metricType
 	}
 
-	return result, nil
+	return temporalities, types, nil
 }
 
 // chunkSizeFirstSeenMetricMetadata limits the number of tuples per SQL query to avoid hitting the max_query_size limit.

pkg/telemetrymetrics/statement_builder.go

@@ -123,8 +123,7 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 	origTimeAgg := query.Aggregations[0].TimeAggregation
 	origGroupBy := slices.Clone(query.GroupBy)
 
-	if query.Aggregations[0].SpaceAggregation.IsPercentile() &&
-		query.Aggregations[0].Type != metrictypes.ExpHistogramType {
+	if query.Aggregations[0].Type == metrictypes.HistogramType {
 		// add le in the group by if doesn't exist
 		leExists := false
 		for _, g := range query.GroupBy {
@@ -154,7 +153,11 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 		}
 
 		// make the time aggregation rate and space aggregation sum
-		query.Aggregations[0].TimeAggregation = metrictypes.TimeAggregationRate
+		if query.Aggregations[0].SpaceAggregation.IsPercentile() {
+			query.Aggregations[0].TimeAggregation = metrictypes.TimeAggregationRate
+		} else {
+			query.Aggregations[0].TimeAggregation = metrictypes.TimeAggregationIncrease
+		}
 		query.Aggregations[0].SpaceAggregation = metrictypes.SpaceAggregationSum
 	}
 
@@ -551,6 +554,9 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 	cteArgs [][]any,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 ) (*qbtypes.Statement, error) {
+	metricType := query.Aggregations[0].Type
+	spaceAgg := query.Aggregations[0].SpaceAggregation
+
 	combined := querybuilder.CombineCTEs(cteFragments)
 
 	var args []any
@@ -560,12 +566,8 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 
 	sb := sqlbuilder.NewSelectBuilder()
 
-	var quantile float64
-	if query.Aggregations[0].SpaceAggregation.IsPercentile() {
-		quantile = query.Aggregations[0].SpaceAggregation.Percentile()
-	}
-
-	if quantile != 0 && query.Aggregations[0].Type != metrictypes.ExpHistogramType {
+	if metricType == metrictypes.HistogramType && spaceAgg.IsPercentile() {
+		quantile := query.Aggregations[0].SpaceAggregation.Percentile()
 		sb.Select("ts")
 		for _, g := range query.GroupBy {
 			sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
@@ -577,12 +579,36 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 		sb.From("__spatial_aggregation_cte")
 		sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
 		sb.GroupBy("ts")
+		if query.Having != nil && query.Having.Expression != "" {
+			rewriter := querybuilder.NewHavingExpressionRewriter()
+			rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
+			sb.Having(rewrittenExpr)
+		}
+	} else if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam != nil {
+		sb.Select("ts")
+
+		for _, g := range query.GroupBy {
+			sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+		}
+
+		aggQuery, err := AggregationQueryForHistogramCountWithParams(query.Aggregations[0].ComparisonSpaceAggregationParam)
+		if err != nil {
+			return nil, err
+		}
+		sb.SelectMore(aggQuery)
+
+		sb.From("__spatial_aggregation_cte")
+
+		sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+		sb.GroupBy("ts")
+
 		if query.Having != nil && query.Having.Expression != "" {
 			rewriter := querybuilder.NewHavingExpressionRewriter()
 			rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
 			sb.Having(rewrittenExpr)
 		}
 	} else {
+		// for count aggregation on histograms with no params, the exact result of spatial aggregation can be sent forward
 		sb.Select("*")
 		sb.From("__spatial_aggregation_cte")
 		if query.Having != nil && query.Having.Expression != "" {
@@ -593,6 +619,9 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 	}
 	sb.OrderBy(querybuilder.GroupByKeys(query.GroupBy)...)
 	sb.OrderBy("ts")
+	if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam == nil {
+		sb.OrderBy("toFloat64(le)")
+	}
 
 	q, a := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
 	return &qbtypes.Statement{Query: combined + q, Args: append(args, a...)}, nil

pkg/telemetrymetrics/tables.go

@@ -1,6 +1,7 @@
 package telemetrymetrics
 
 import (
+	"fmt"
 	"time"
 
 	"github.com/SigNoz/signoz/pkg/errors"
@@ -308,3 +309,20 @@ func AggregationColumnForSamplesTable(
 	}
 	return aggregationColumn, nil
 }
+
+func AggregationQueryForHistogramCountWithParams(param *metrictypes.ComparisonSpaceAggregationParam) (string, error) {
+	if param == nil {
+		return "", errors.New(errors.TypeInvalidInput, errors.CodeInvalidInput, "no aggregation param provided for histogram count")
+	}
+	histogramCountThreshold := param.Threshold
+
+	switch param.Operater {
+	case "<=":
+		return fmt.Sprintf("argMaxIf(value, toFloat64(le), toFloat64(le) <= %f) + (argMinIf(value, toFloat64(le), toFloat64(le) > %f) - argMaxIf(value, toFloat64(le), toFloat64(le) <= %f)) * (%f - maxIf(toFloat64(le), toFloat64(le) <= %f)) / (minIf(toFloat64(le), toFloat64(le) > %f) - maxIf(toFloat64(le), toFloat64(le) <= %f)) AS value", histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold), nil
+	case ">":
+		return fmt.Sprintf("argMax(value, toFloat64(le)) - (argMaxIf(value, toFloat64(le), toFloat64(le) <= %f) + (argMinIf(value, toFloat64(le), toFloat64(le) > %f) - argMaxIf(value, toFloat64(le), toFloat64(le) <= %f)) * (%f - maxIf(toFloat64(le), toFloat64(le) <= %f)) / (minIf(toFloat64(le), toFloat64(le) > %f) - maxIf(toFloat64(le), toFloat64(le) <= %f))) AS value", histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold, histogramCountThreshold), nil
+	default:
+		return "", errors.New(errors.TypeInvalidInput, errors.CodeInvalidInput, "invalid space aggregation operator, should be one of the following: [`<=`, `>`]")
+	}
+
+}

pkg/types/metrictypes/metrictypes.go

@@ -2,6 +2,7 @@ package metrictypes
 
 import (
 	"database/sql/driver"
+	"fmt"
 	"strings"
 
 	"github.com/SigNoz/signoz/pkg/errors"
@@ -256,3 +257,12 @@ type MetricTableHints struct {
 type MetricValueFilter struct {
 	Value float64
 }
+
+type ComparisonSpaceAggregationParam struct {
+	Operater  string  `json:"operator" required:"true"`
+	Threshold float64 `json:"threshold" required:"true"`
+}
+
+func (param ComparisonSpaceAggregationParam) StringValue() string {
+	return fmt.Sprintf("operator=%s:threshold=%f", param.Operater, param.Threshold)
+}

pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go

@@ -446,6 +446,8 @@ type MetricAggregation struct {
 	TimeAggregation metrictypes.TimeAggregation `json:"timeAggregation"`
 	// space aggregation to apply to the query
 	SpaceAggregation metrictypes.SpaceAggregation `json:"spaceAggregation"`
+	// param for space aggregation if needed
+	ComparisonSpaceAggregationParam *metrictypes.ComparisonSpaceAggregationParam `json:"comparisonSpaceAggregationParam"`
 	// table hints to use for the query
 	TableHints *metrictypes.MetricTableHints `json:"-"`
 	// value filter to apply to the query

pkg/types/telemetrytypes/store.go

@@ -32,6 +32,8 @@ type MetadataStore interface {
 	// FetchTemporalityMulti fetches the temporality for multiple metrics
 	FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error)
 
+	FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error)
+
 	// ListLogsJSONIndexes lists the JSON indexes for the logs table.
 	ListLogsJSONIndexes(ctx context.Context, filters ...string) (map[string][]schemamigrator.Index, error)
 

pkg/types/telemetrytypes/telemetrytypestest/metadata_store.go

@@ -16,6 +16,7 @@ type MockMetadataStore struct {
 	RelatedValuesMap   map[string][]string
 	AllValuesMap       map[string]*telemetrytypes.TelemetryFieldValues
 	TemporalityMap     map[string]metrictypes.Temporality
+	TypeMap            map[string]metrictypes.Type
 	PromotedPathsMap   map[string]struct{}
 	LogsJSONIndexesMap map[string][]schemamigrator.Index
 	LookupKeysMap      map[telemetrytypes.MetricMetadataLookupKey]int64
@@ -28,6 +29,7 @@ func NewMockMetadataStore() *MockMetadataStore {
 		RelatedValuesMap:   make(map[string][]string),
 		AllValuesMap:       make(map[string]*telemetrytypes.TelemetryFieldValues),
 		TemporalityMap:     make(map[string]metrictypes.Temporality),
+		TypeMap:            make(map[string]metrictypes.Type),
 		PromotedPathsMap:   make(map[string]struct{}),
 		LogsJSONIndexesMap: make(map[string][]schemamigrator.Index),
 		LookupKeysMap:      make(map[telemetrytypes.MetricMetadataLookupKey]int64),
@@ -287,6 +289,27 @@ func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, queryTime
 	return result, nil
 }
 
+// FetchTemporalityMulti fetches the temporality for multiple metrics
+func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {
+	temporalities := make(map[string]metrictypes.Temporality)
+	types := make(map[string]metrictypes.Type)
+
+	for _, metricName := range metricNames {
+		if temporality, exists := m.TemporalityMap[metricName]; exists {
+			temporalities[metricName] = temporality
+		} else {
+			temporalities[metricName] = metrictypes.Unknown
+		}
+		if metricType, exists := m.TypeMap[metricName]; exists {
+			types[metricName] = metricType
+		} else {
+			types[metricName] = metrictypes.UnspecifiedType
+		}
+	}
+
+	return temporalities, types, nil
+}
+
 // SetTemporality sets the temporality for a metric in the mock store
 func (m *MockMetadataStore) SetTemporality(metricName string, temporality metrictypes.Temporality) {
 	m.TemporalityMap[metricName] = temporality

tests/integration/fixtures/querier.py

@@ -52,6 +52,7 @@ def build_builder_query(
     time_aggregation: str,
     space_aggregation: str,
     *,
+    comparisonSpaceAggregationParam: Optional[Dict] = None,
     temporality: Optional[str] = None,
     step_interval: int = DEFAULT_STEP_INTERVAL,
     group_by: Optional[List[str]] = None,
@@ -74,7 +75,8 @@ def build_builder_query(
     }
     if temporality:
         spec["aggregations"][0]["temporality"] = temporality
-
+    if comparisonSpaceAggregationParam:
+        spec["aggregations"][0]["comparisonSpaceAggregationParam"] = comparisonSpaceAggregationParam
     if group_by:
         spec["groupBy"] = [
             {

tests/integration/src/querier/07_metrics_multi_temporality.py

@@ -353,7 +353,7 @@ def test_for_week_long_time_range(
 
     metrics = Metrics.load_from_file(
         MULTI_TEMPORALITY_FILE_10h,
-        base_time=now - timedelta(minutes=600),
+        base_time=now - timedelta(minutes=1441),
         metric_name_override=metric_name,
     )
     insert_metrics(metrics)

tests/integration/src/querier/08_metrics_histogram.py

@@ -0,0 +1,322 @@
+"""
+Look at the histogram_data_1h.jsonl file for the relevant data
+"""
+
+import random
+from datetime import datetime, timedelta, timezone
+from http import HTTPStatus
+from typing import Callable, List
+
+import pytest
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metrics import Metrics
+from fixtures.querier import (
+    build_builder_query,
+    get_all_series,
+    get_series_values,
+    make_query_request,
+)
+from fixtures.utils import get_testdata_file_path
+
+FILE = get_testdata_file_path("histogram_data_1h.jsonl")
+
+@pytest.mark.parametrize(
+    "threshold, operator, first_value, last_value",
+    [
+        (1000, "<=", 11, 69),
+        (100, "<=", 1.1, 6.9),
+        (7500, "<=", 16.75, 74.75),
+        (8000, "<=", 17, 75),
+        (80000, "<=", 17, 75), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+        (1000, ">", 7, 7),
+        (100, ">", 16.9, 69.1),
+        (7500, ">", 1.25, 1.25),
+        (8000, ">", 1, 1),
+        (80000, ">", 1, 1), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+    ],
+)
+def test_histogram_count_for_one_endpoint(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    threshold: float,
+    operator: str,
+    first_value: float,
+    last_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_bucket"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+        comparisonSpaceAggregationParam={
+            "threshold": threshold,
+            "operator": operator
+        },
+        filter_expression='endpoint = "/health"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 59
+    assert result_values[0]["value"] == first_value
+    assert result_values[-1]["value"] == last_value
+
+@pytest.mark.parametrize(
+    "threshold, operator, first_value, last_value",
+    [
+        (1000, "<=", 22, 138),
+        (100, "<=", 2.2, 13.8),
+        (7500, "<=", 33.5, 149.5),
+        (8000, "<=", 34, 150),
+        (80000, "<=", 34, 150), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+        (1000, ">", 14, 14),
+        (100, ">", 33.8, 138.2),
+        (7500, ">", 2.5, 2.5),
+        (8000, ">", 2, 2),
+        (80000, ">", 2, 2), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+    ],
+)
+def test_histogram_count_for_one_service(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    threshold: float,
+    operator: str,
+    first_value: float,
+    last_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_bucket"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+        comparisonSpaceAggregationParam={
+            "threshold": threshold,
+            "operator": operator
+        },
+        filter_expression='service = "api"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 59
+    assert result_values[0]["value"] == first_value
+    assert result_values[-1]["value"] == last_value
+
+@pytest.mark.parametrize(
+    "threshold, operator, zeroth_value, first_value, last_value",
+    [
+        (1000, "<=", 12345, 11, 69),
+        (100, "<=", 1234.5, 1.1, 6.9),
+        (7500, "<=", 12345, 16.75, 74.75),
+        (8000, "<=", 12345, 17, 75),
+        (80000, "<=", 12345, 17, 75), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+        (1000, ">", 0, 7, 7),
+        (100, ">", 11110.5, 16.9, 69.1),
+        (7500, ">", 0, 1.25, 1.25),
+        (8000, ">", 0, 1, 1),
+        (80000, ">", 0, 1, 1), ## cuz we don't know the max value in infinity, all numbers beyond the biggest finite bucket will report the same answer
+    ],
+)
+def test_histogram_count_for_delta_service(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    threshold: float,
+    operator: str,
+    zeroth_value: float,
+    first_value: float,
+    last_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_bucket"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+        comparisonSpaceAggregationParam={
+            "threshold": threshold,
+            "operator": operator
+        },
+        filter_expression='service = "web"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 60 ## in delta, the value at 10:01 will also be reported
+    assert result_values[0]["value"] == zeroth_value
+    assert result_values[1]["value"] == first_value ## to keep parallel to the cumulative test cases, first_value refers to the value at 10:02
+    assert result_values[-1]["value"] == last_value
+
+@pytest.mark.parametrize(
+    "threshold, operator, zeroth_value, first_value, last_value",
+    [
+        (1000, "<=", 12345, 33, 207),
+        (100, "<=", 1234.5, 3.3, 20.7),
+        (7500, "<=", 12345, 50.25, 224.25),
+        (8000, "<=", 12345, 51, 225),
+        (80000, "<=", 12345, 51, 225),
+        (1000, ">", 0, 21, 21),
+        (100, ">", 11110.5, 50.7, 207.3),
+        (7500, ">", 0, 3.75, 3.75),
+        (8000, ">", 0, 3, 3),
+        (80000, ">", 0, 3, 3),
+    ],
+)
+def test_histogram_count_for_all_services(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    threshold: float,
+    operator: str,
+    zeroth_value: float,
+    first_value: float,
+    last_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_bucket"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+        comparisonSpaceAggregationParam={
+            "threshold": threshold,
+            "operator": operator
+        },
+        ## no services filter, this tests for multitemporality handling as well
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 60 ## in delta, the value at 10:01 will also be reported
+    assert result_values[0]["value"] == zeroth_value
+    assert result_values[1]["value"] == first_value ## to keep parallel to the cumulative test cases, first_value refers to the value at 10:02
+    assert result_values[-1]["value"] == last_value
+
+def test_histogram_count_no_param(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_bucket"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    all_series = get_all_series(data, "A")
+    assert (
+        len(all_series) == 8
+    ), f"Expected 8 series for 8 le buckets, got {len(all_series)}"
+
+    le_buckets = {}
+    for series in all_series:
+        le = series.get("labels", [{}])[0].get("value", "unknown")
+        values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
+        le_buckets[le] = values
+
+    expected_buckets = {"1000", "1500", "2000", "4000", "5000", "6000", "8000", "+Inf"}
+    assert (
+        set(le_buckets.keys()) == expected_buckets
+    ), f"Expected endpoints {expected_buckets}, got {set(le_buckets.keys())}"
+
+    first_values = {"1000": 33, "1500": 36, "2000": 39, "4000": 42, "5000": 45, "6000": 48, "8000": 51, "+Inf": 54}
+    last_values = {"1000": 207, "1500": 210, "2000": 213, "4000": 216, "5000": 219, "6000": 222, "8000": 225, "+Inf": 228}
+    for le, values in le_buckets.items():
+        assert len(values) == 60
+
+        for v in values:
+            assert (
+                v["value"] >= 0
+            ), f"Count for {le} should not be negative: {v['value']}"
+        assert values[0]["value"] == 12345
+        assert values[1]["value"] == first_values[le] ## to keep parallel to the cumulative test cases, first_value refers to the value at 10:02
+        assert values[-1]["value"] == last_values[le] 

tests/integration/src/querier/09_metrics_gauge.py

@@ -0,0 +1,141 @@
+import random
+from datetime import datetime, timedelta, timezone
+from http import HTTPStatus
+from typing import Callable, List
+
+import pytest
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metrics import Metrics
+from fixtures.querier import (
+    build_builder_query,
+    get_all_series,
+    get_series_values,
+    make_query_request,
+)
+from fixtures.utils import get_testdata_file_path
+
+FILE = get_testdata_file_path("gauge_data_1h.jsonl")
+
+@pytest.mark.parametrize(
+    "time_agg, space_agg, service, num_elements, start_val, first_val, twentieth_min_val, after_twentieth_min_val",
+    [
+        ("avg", "avg", "api", 60, 400, 800, 800, 400),
+        ("avg", "avg", "web", 50, 800, 800, 800, 600),
+        ("avg", "avg", "lab", 60, 500, 700, 700, 500),
+        ("sum", "sum", "api", 60, 400, 800, 800, 400),
+        ("sum", "sum", "web", 50, 800, 800, 800, 600),
+        ("sum", "sum", "lab", 60, 1000, 1400, 1400, 1000),
+        ("max", "max", "api", 60, 400, 800, 800, 400),
+        ("max", "max", "web", 50, 800, 800, 800, 600),
+        ("max", "max", "lab", 60, 600, 800, 800, 600),
+        ("avg", "sum", "api", 60, 400, 800, 800, 400),
+        ("avg", "sum", "web", 50, 800, 800, 800, 600),
+        ("avg", "sum", "lab", 60, 500, 700, 700, 500),
+        ("max", "sum", "api", 60, 400, 800, 800, 400),
+        ("max", "sum", "web", 50, 800, 800, 800, 600),
+        ("max", "sum", "lab", 60, 600, 800, 800, 600),
+    ],
+)
+def test_for_one_service(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_agg: str,
+    space_agg: str,
+    service: str,
+    num_elements: float,
+    start_val: float,
+    first_val: float,
+    twentieth_min_val: float,
+    after_twentieth_min_val: float ## web service has a gap of 10 mins after the 20th minute
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_memory_usage"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_agg,
+        space_agg,
+        filter_expression=f'service = "{service}"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == num_elements
+    assert result_values[0]["value"] == start_val
+    assert result_values[1]["value"] == first_val
+    assert result_values[19]["value"] == twentieth_min_val
+    assert result_values[20]["value"] == after_twentieth_min_val
+
+@pytest.mark.parametrize(
+    "time_agg, space_agg, start_val, first_val, twentieth_min_val, twenty_first_min_val, thirty_first_min_val",
+    [
+        ("avg", "avg", 566.667, 766.667, 766.667, 450, 500),
+        ("avg", "sum", 1700, 2300, 2300, 900, 1500),
+        ("avg", "max", 800, 800, 800, 500, 600),
+        ("max", "avg", 600, 800, 800, 500, 533.333),
+        ("max", "sum", 1800, 2400, 2400, 1000, 1600),
+        ("max", "max", 800, 800, 800, 600, 600),
+    ],
+)
+def test_for_multiple_aggregations(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_agg: str,
+    space_agg: str,
+    start_val: float,
+    first_val: float,
+    twentieth_min_val: float,
+    twenty_first_min_val: float, ## web service has a gap of 10 mins after the 20th minute
+    thirty_first_min_val: float
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_memory_usage"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_agg,
+        space_agg,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 60
+    assert result_values[0]["value"] == start_val
+    assert result_values[1]["value"] == first_val
+    assert result_values[19]["value"] == twentieth_min_val
+    assert result_values[20]["value"] == twenty_first_min_val
+    assert result_values[30]["value"] == thirty_first_min_val

tests/integration/src/querier/10_metrics_rate_delta_counter.py

@@ -0,0 +1,220 @@
+"""
+Look at the delta_counters_1h.jsonl file for the relevant data
+"""
+
+import os
+from datetime import datetime, timedelta, timezone
+from http import HTTPStatus
+from typing import Any, Callable, List
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metrics import Metrics
+from fixtures.querier import (
+    build_builder_query,
+    get_all_series,
+    get_series_values,
+    make_query_request,
+)
+
+TESTDATA_DIR = os.path.join(os.path.dirname(__file__), "..", "..", "testdata")
+DELTA_COUNTERS_FILE = os.path.join(TESTDATA_DIR, "delta_counters_1h.jsonl")
+
+
+def test_rate_with_steady_values_and_reset(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = "test_rate_stale"
+
+    metrics = Metrics.load_from_file(
+        DELTA_COUNTERS_FILE,
+        base_time=now - timedelta(minutes=61),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "rate",
+        "sum",
+        filter_expression='endpoint = "/orders"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) == 60 ## total 61 minutes covered, and 30th minute is missing
+    assert (
+        result_values[30]["value"] == 0.0333
+    )  # reset happens and [30] is for 31st minute. 2/60 cuz delta divides by step interval
+    assert (
+        result_values[31]["value"] == 0.133
+    )  # i.e 8/60 i.e 31st to 32nd minute changes
+    count_of_steady_rate = sum(1 for v in result_values if v["value"] == 0.0833)
+    assert (
+        count_of_steady_rate == 58
+    )  # 1 reset + 1 high rate are excluded
+    # All rates should be non-negative (stale periods = 0 rate)
+    for v in result_values:
+        assert v["value"] >= 0, f"Rate should not be negative: {v['value']}"
+
+
+def test_rate_group_by_endpoint(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = "test_rate_groupby"
+
+    metrics = Metrics.load_from_file(
+        DELTA_COUNTERS_FILE,
+        base_time=now - timedelta(minutes=61),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "rate",
+        "sum",
+        group_by=["endpoint"],
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    all_series = get_all_series(data, "A")
+
+    # Should have 5 different endpoints
+    assert (
+        len(all_series) == 5
+    ), f"Expected 5 series for 5 endpoints, got {len(all_series)}"
+
+    # endpoint -> values
+    endpoint_values = {}
+    for series in all_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
+        endpoint_values[endpoint] = values
+
+    expected_endpoints = {"/products", "/health", "/checkout", "/orders", "/users"}
+    assert (
+        set(endpoint_values.keys()) == expected_endpoints
+    ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_values.keys())}"
+
+    # at no point rate should be negative
+    for endpoint, values in endpoint_values.items():
+        for v in values:
+            assert (
+                v["value"] >= 0
+            ), f"Rate for {endpoint} should not be negative: {v['value']}"
+
+    # /health: 60 data points (t01-t60), steady +10/min
+    # rate = 10/60 = 0.167
+    health_values = endpoint_values["/health"]
+    assert (
+        len(health_values) == 60
+    ), f"Expected 60 values for /health, got {len(health_values)}"
+    count_steady_health = sum(1 for v in health_values if v["value"] == 0.167)
+    assert (
+        count_steady_health == 60
+    ), f"Expected == 60 steady rate values (0.167) for /health, got {count_steady_health}"
+    # all /health rates should be 0.167 except possibly first/last due to boundaries
+    for v in health_values[1:-1]:
+        assert v["value"] == 0.167, f"Expected /health rate 0.167, got {v['value']}"
+
+    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
+    # rate = 20/60 = 0.333, gap causes lower averaged rate at boundary
+    products_values = endpoint_values["/products"]
+    assert (
+        len(products_values) == 51
+    ), f"Expected 51 values for /products, got {len(products_values)}"
+    count_steady_products = sum(1 for v in products_values if v["value"] == 0.333)
+
+    assert (
+        count_steady_products == 51
+    ), f"Expected 51 steady rate values (0.333) for /products, got {count_steady_products}"
+
+    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
+    # normal rate = 1/60 = 0.0167, spike rate = 50/60 = 0.833
+    checkout_values = endpoint_values["/checkout"]
+    assert (
+        len(checkout_values) == 61
+    ), f"Expected 61 values for /checkout, got {len(checkout_values)}"
+    count_steady_checkout = sum(1 for v in checkout_values if v["value"] == 0.0167)
+    assert (
+        count_steady_checkout == 56
+    ), f"Expected 56 steady rate values (0.0167) for /checkout, got {count_steady_checkout}"
+    # check that spike values exist (traffic spike +50/min at t40-t44)
+    count_spike_checkout = sum(1 for v in checkout_values if v["value"] == 0.833)
+    assert (
+        count_spike_checkout == 5
+    ), f"Expected 5 spike rate values (0.833) for /checkout, got {count_spike_checkout}"
+
+    # spike values should be consecutive
+    spike_indices = [
+        i for i, v in enumerate[Any](checkout_values) if v["value"] == 0.833
+    ]
+    assert len(spike_indices) == 5, f"Expected 5 spike indices, got {spike_indices}"
+    # consecutiveness
+    for i in range(1, len(spike_indices)):
+        assert (
+            spike_indices[i] == spike_indices[i - 1] + 1
+        ), f"Spike indices should be consecutive, got {spike_indices}"
+
+    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
+    # rate = 5/60 = 0.0833
+    # reset at t31 causes: rate at t30 includes gap (lower), t31 has high rate after reset
+    orders_values = endpoint_values["/orders"]
+    assert (
+        len(orders_values) == 60
+    ), f"Expected 59 values for /orders, got {len(orders_values)}"
+    count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
+    assert (
+        count_steady_orders == 58
+    ), f"Expected 58 steady rate values (0.0833) for /orders, got {count_steady_orders}"
+    # check for counter reset effects - there should be some non-standard values
+    non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
+    assert (
+        len(non_standard_orders) == 2
+    ), f"Expected 2 non-standard values due to counter reset, got {non_standard_orders}"
+    # post-reset value should be higher (new counter value / interval)
+    high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
+    assert (
+        len(high_rate_orders) == 1
+    ), f"Expected one high rate value after counter reset, got {non_standard_orders}"
+
+    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes (12 of them)
+    # Rate = 1/60 = 0.0167 during increment, 0 during flat periods
+    users_values = endpoint_values["/users"]
+    assert (
+        len(users_values) == 56
+    ), f"Expected 56 values for /users, got {len(users_values)}"
+    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
+    # most values should be 0 (flat periods between increments)
+    assert (
+        count_zero_users == 44
+    ), f"Expected 44 zero rate values for /users (sparse data), got {count_zero_users}"
+    # non-zero values should be 0.0167 (1/60 increment rate)
+    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
+    count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
+    assert (
+        count_increment_rate == 12
+    ), f"Expected 12 increment rate values (0.0167) for /users, got {count_increment_rate}"

tests/integration/testdata/delta_counters_1h.jsonl

@@ -0,0 +1,288 @@
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