Merge branch 'main' into nv/6703

* fix: add missing filtering for ip address for scalar data

In domain listing api for external api monitoring,
we have option to filter out the IP address but
it only handles timeseries and raw type data while
domain list handler returns scalar data.

* fix: switch to new derived attributes for ip filtering

---------

Co-authored-by: Nityananda Gohain <nityanandagohain@gmail.com>

.github/workflows/integrationci.yaml

@@ -54,7 +54,7 @@ jobs:
           - sqlite
         clickhouse-version:
           - 25.5.6
-          - 25.10.5
+          - 25.12.5
         schema-migrator-version:
           - v0.142.0
         postgres-version:

docs/api/openapi.yml

@@ -842,6 +842,14 @@ components:
       - temporality
       - isMonotonic
       type: object
+    MetrictypesComparisonSpaceAggregationParam:
+      properties:
+        operator:
+          type: string
+        threshold:
+          format: double
+          type: number
+      type: object
     MetrictypesSpaceAggregation:
       enum:
       - sum
@@ -1138,6 +1146,8 @@ components:
       type: object
     Querybuildertypesv5MetricAggregation:
       properties:
+        comparisonSpaceAggregationParam:
+          $ref: '#/components/schemas/MetrictypesComparisonSpaceAggregationParam'
         metricName:
           type: string
         reduceTo:

frontend/src/AppRoutes/pageComponents.ts

@@ -308,3 +308,15 @@ export const PublicDashboardPage = Loadable(
 			/* webpackChunkName: "Public Dashboard Page" */ 'pages/PublicDashboard'
 		),
 );
+
+export const AlertTypeSelectionPage = Loadable(
+	() =>
+		import(
+			/* webpackChunkName: "Alert Type Selection Page" */ 'pages/AlertTypeSelection'
+		),
+);
+
+export const MeterExplorerPage = Loadable(
+	() =>
+		import(/* webpackChunkName: "Meter Explorer Page" */ 'pages/MeterExplorer'),
+);

frontend/src/AppRoutes/routes.ts

@@ -1,12 +1,10 @@
 import { RouteProps } from 'react-router-dom';
 import ROUTES from 'constants/routes';
-import AlertTypeSelectionPage from 'pages/AlertTypeSelection';
-import MessagingQueues from 'pages/MessagingQueues';
-import MeterExplorer from 'pages/MeterExplorer';
 
 import {
 	AlertHistory,
 	AlertOverview,
+	AlertTypeSelectionPage,
 	AllAlertChannels,
 	AllErrors,
 	ApiMonitoring,
@@ -29,6 +27,8 @@ import {
 	LogsExplorer,
 	LogsIndexToFields,
 	LogsSaveViews,
+	MessagingQueuesMainPage,
+	MeterExplorerPage,
 	MetricsExplorer,
 	OldLogsExplorer,
 	Onboarding,
@@ -399,28 +399,28 @@ const routes: AppRoutes[] = [
 	{
 		path: ROUTES.MESSAGING_QUEUES_KAFKA,
 		exact: true,
-		component: MessagingQueues,
+		component: MessagingQueuesMainPage,
 		key: 'MESSAGING_QUEUES_KAFKA',
 		isPrivate: true,
 	},
 	{
 		path: ROUTES.MESSAGING_QUEUES_CELERY_TASK,
 		exact: true,
-		component: MessagingQueues,
+		component: MessagingQueuesMainPage,
 		key: 'MESSAGING_QUEUES_CELERY_TASK',
 		isPrivate: true,
 	},
 	{
 		path: ROUTES.MESSAGING_QUEUES_OVERVIEW,
 		exact: true,
-		component: MessagingQueues,
+		component: MessagingQueuesMainPage,
 		key: 'MESSAGING_QUEUES_OVERVIEW',
 		isPrivate: true,
 	},
 	{
 		path: ROUTES.MESSAGING_QUEUES_KAFKA_DETAIL,
 		exact: true,
-		component: MessagingQueues,
+		component: MessagingQueuesMainPage,
 		key: 'MESSAGING_QUEUES_KAFKA_DETAIL',
 		isPrivate: true,
 	},
@@ -463,21 +463,21 @@ const routes: AppRoutes[] = [
 	{
 		path: ROUTES.METER,
 		exact: true,
-		component: MeterExplorer,
+		component: MeterExplorerPage,
 		key: 'METER',
 		isPrivate: true,
 	},
 	{
 		path: ROUTES.METER_EXPLORER,
 		exact: true,
-		component: MeterExplorer,
+		component: MeterExplorerPage,
 		key: 'METER_EXPLORER',
 		isPrivate: true,
 	},
 	{
 		path: ROUTES.METER_EXPLORER_VIEWS,
 		exact: true,
-		component: MeterExplorer,
+		component: MeterExplorerPage,
 		key: 'METER_EXPLORER_VIEWS',
 		isPrivate: true,
 	},

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/modules/thirdpartyapi/translator.go

@@ -120,6 +120,8 @@ func FilterResponse(results []*qbtypes.QueryRangeResponse) []*qbtypes.QueryRange
 					}
 				}
 				resultData.Rows = filteredRows
+			case *qbtypes.ScalarData:
+				resultData.Data = filterScalarDataIPs(resultData.Columns, resultData.Data)
 			}
 
 			filteredData = append(filteredData, result)
@@ -145,6 +147,39 @@ func shouldIncludeSeries(series *qbtypes.TimeSeries) bool {
 	return true
 }
 
+func filterScalarDataIPs(columns []*qbtypes.ColumnDescriptor, data [][]any) [][]any {
+	// Find column indices for server address fields
+	serverColIndices := make([]int, 0)
+	for i, col := range columns {
+		if col.Name == derivedKeyHTTPHost {
+			serverColIndices = append(serverColIndices, i)
+		}
+	}
+
+	if len(serverColIndices) == 0 {
+		return data
+	}
+
+	filtered := make([][]any, 0, len(data))
+	for _, row := range data {
+		includeRow := true
+		for _, colIdx := range serverColIndices {
+			if colIdx < len(row) {
+				if strVal, ok := row[colIdx].(string); ok {
+					if net.ParseIP(strVal) != nil {
+						includeRow = false
+						break
+					}
+				}
+			}
+		}
+		if includeRow {
+			filtered = append(filtered, row)
+		}
+	}
+	return filtered
+}
+
 func shouldIncludeRow(row *qbtypes.RawRow) bool {
 	if row.Data != nil {
 		if domainVal, ok := row.Data[derivedKeyHTTPHost]; ok {

pkg/modules/thirdpartyapi/translator_test.go

@@ -117,6 +117,59 @@ func TestFilterResponse(t *testing.T) {
 				},
 			},
 		},
+		{
+			name: "should filter out IP addresses from scalar data",
+			input: []*qbtypes.QueryRangeResponse{
+				{
+					Data: qbtypes.QueryData{
+						Results: []any{
+							&qbtypes.ScalarData{
+								QueryName: "endpoints",
+								Columns: []*qbtypes.ColumnDescriptor{
+									{
+										TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: derivedKeyHTTPHost},
+										Type:              qbtypes.ColumnTypeGroup,
+									},
+									{
+										TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "endpoints"},
+										Type:              qbtypes.ColumnTypeAggregation,
+									},
+								},
+								Data: [][]any{
+									{"192.168.1.1", 10},
+									{"example.com", 20},
+									{"10.0.0.1", 5},
+								},
+							},
+						},
+					},
+				},
+			},
+			expected: []*qbtypes.QueryRangeResponse{
+				{
+					Data: qbtypes.QueryData{
+						Results: []any{
+							&qbtypes.ScalarData{
+								QueryName: "endpoints",
+								Columns: []*qbtypes.ColumnDescriptor{
+									{
+										TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: derivedKeyHTTPHost},
+										Type:              qbtypes.ColumnTypeGroup,
+									},
+									{
+										TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "endpoints"},
+										Type:              qbtypes.ColumnTypeAggregation,
+									},
+								},
+								Data: [][]any{
+									{"example.com", 20},
+								},
+							},
+						},
+					},
+				},
+			},
+		},
 	}
 
 	for _, tt := range tests {

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 +1616,53 @@ 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]
 			}
+		} else if temporality, exists := meterMetricsTemporality[metricName]; exists {
+			temporalities[metricName] = temporality
 			continue
+		} 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 +1673,7 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryT
 	sb := sqlbuilder.Select(
 		"metric_name",
 		"temporality",
+		"any(type) AS type",
 	).
 		From(t.metricsDBName + "." + tsTableName)
 
@@ -1678,15 +1692,15 @@ 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")
+		var metricName, temporalityStr, metricTypeStr string
+		if err := rows.Scan(&metricName, &temporalityStr, &metricTypeStr); err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
 		}
 
 		// Convert string to Temporality type
@@ -1703,22 +1717,30 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryT
 			temporality = metrictypes.Unknown
 		}
 		if temporality != metrictypes.Unknown {
-			result[metricName] = append(result[metricName], temporality)
+			temporalities[metricName] = append(temporalities[metricName], temporality)
 		}
+		var metricType metrictypes.Type
+		err = metricType.Scan(metricTypeStr)
+		if err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan metric-type result")
+		}
+		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)
@@ -1733,15 +1755,15 @@ 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")
+		var metricName, temporalityStr, meterMetricTypeStr string
+		if err := rows.Scan(&metricName, &temporalityStr, &meterMetricTypeStr); err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
 		}
 
 		// Convert string to Temporality type
@@ -1758,10 +1780,16 @@ func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Cont
 			temporality = metrictypes.Unknown
 		}
 
-		result[metricName] = temporality
+		temporalities[metricName] = temporality
+		var metricType metrictypes.Type
+		err = metricType.Scan(meterMetricTypeStr)
+		if err != nil {
+			return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan metric-type result")
+		}
+		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"`
+	Threshold float64 `json:"threshold"`
+}
+
+func (param ComparisonSpaceAggregationParam) StringValue() string {
+	return fmt.Sprintf("{\"operator\": \"%s\", \"limit\": \"%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 multi_temporality_counters_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/testdata/gauge_data_1h.jsonl

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