chore(querier): route metric reads to buffer/reduced tables behind a flag

Fixes https://github.com/SigNoz/engineering-pod/issues/5341

frontend/src/api/v5/queryRange/convertV5Response.test.ts

@@ -274,110 +274,4 @@ describe('convertV5ResponseToLegacy', () => {
 			},
 		});
 	});
-
-	it('clickhouse_sql scalar keeps each value column distinct (regression: all-"A" collapse)', () => {
-		const scalar: ScalarData = {
-			columns: [
-				{
-					name: 'service.name',
-					queryName: 'A',
-					aggregationIndex: 0,
-					columnType: 'group',
-				} as unknown as ScalarData['columns'][number],
-				{
-					name: 'current_availability',
-					queryName: 'A',
-					aggregationIndex: 0,
-					columnType: 'aggregation',
-				} as unknown as ScalarData['columns'][number],
-				{
-					name: 'error_budget_remaining',
-					queryName: 'A',
-					aggregationIndex: 1,
-					columnType: 'aggregation',
-				} as unknown as ScalarData['columns'][number],
-				{
-					name: 'budget_status',
-					queryName: 'A',
-					aggregationIndex: 2,
-					columnType: 'group',
-				} as unknown as ScalarData['columns'][number],
-				{
-					name: 'total_requests',
-					queryName: 'A',
-					aggregationIndex: 4,
-					columnType: 'aggregation',
-				} as unknown as ScalarData['columns'][number],
-			],
-			data: [['kuja-api_gateway-service', 99.985, 0.985, 'Healthy ✅', 2181216]],
-		};
-
-		const v5Data: QueryRangeResponseV5 = {
-			type: 'scalar',
-			data: { results: [scalar] },
-			meta: { rowsScanned: 0, bytesScanned: 0, durationMs: 0, stepIntervals: {} },
-		};
-
-		// A clickhouse_sql envelope contributes no aggregation metadata.
-		const params = makeBaseParams('scalar', [
-			{
-				type: 'clickhouse_sql',
-				spec: {
-					name: 'A',
-					query: 'SELECT ...',
-					disabled: false,
-				},
-			} as unknown as QueryRangeRequestV5['compositeQuery']['queries'][number],
-		]);
-
-		const input: SuccessResponse<MetricRangePayloadV5, QueryRangeRequestV5> =
-			makeBaseSuccess({ data: v5Data }, params);
-		// formatForWeb=true is the table-panel path.
-		const result = convertV5ResponseToLegacy(input, { A: '' }, true);
-
-		const [tableEntry] = result.payload.data.result;
-		// Headers keep their real names instead of collapsing to "A".
-		expect(tableEntry.table?.columns).toStrictEqual([
-			{
-				name: 'service.name',
-				queryName: 'A',
-				isValueColumn: false,
-				id: 'service.name',
-			},
-			{
-				name: 'current_availability',
-				queryName: 'A',
-				isValueColumn: true,
-				id: 'current_availability',
-			},
-			{
-				name: 'error_budget_remaining',
-				queryName: 'A',
-				isValueColumn: true,
-				id: 'error_budget_remaining',
-			},
-			{
-				name: 'budget_status',
-				queryName: 'A',
-				isValueColumn: false,
-				id: 'budget_status',
-			},
-			{
-				name: 'total_requests',
-				queryName: 'A',
-				isValueColumn: true,
-				id: 'total_requests',
-			},
-		]);
-		// Ids are unique, so value columns don't overwrite each other in the row.
-		expect(tableEntry.table?.rows?.[0]).toStrictEqual({
-			data: {
-				'service.name': 'kuja-api_gateway-service',
-				current_availability: 99.985,
-				error_budget_remaining: 0.985,
-				budget_status: 'Healthy ✅',
-				total_requests: 2181216,
-			},
-		});
-	});
 });

frontend/src/api/v5/queryRange/convertV5Response.ts

@@ -15,7 +15,6 @@ function getColName(
 	col: ScalarData['columns'][number],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
-	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
@@ -40,32 +39,16 @@ function getColName(
 		return alias || expression || col.queryName;
 	}
 
-	// clickhouse_sql value columns carry their real SQL alias in col.name — use
-	// it so each value column keeps its own header instead of collapsing onto
-	// the query name. Formulas/promql use placeholder names, so they fall back
-	// to legend || queryName.
-	if (clickhouseQueryNames.has(col.queryName)) {
-		return col.name;
-	}
 	return legend || col.queryName;
 }
 
 function getColId(
 	col: ScalarData['columns'][number],
 	aggregationPerQuery: Record<string, any>,
-	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
 	}
-
-	// clickhouse_sql value columns are keyed by their real SQL alias so multiple
-	// value columns stay unique instead of all collapsing onto the query name
-	// (which would overwrite every cell in the row with the last column's value).
-	if (clickhouseQueryNames.has(col.queryName)) {
-		return col.name;
-	}
-
 	const aggregation =
 		aggregationPerQuery?.[col.queryName]?.[col.aggregationIndex];
 	const expression = aggregation?.expression || '';
@@ -158,7 +141,6 @@ function convertScalarDataArrayToTable(
 	scalarDataArray: ScalarData[],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
-	clickhouseQueryNames: Set<string>,
 ): QueryDataV3[] {
 	// If no scalar data, return empty structure
 
@@ -184,10 +166,10 @@ function convertScalarDataArrayToTable(
 
 		// Collect columns for this specific query
 		const columns = scalarData?.columns?.map((col) => ({
-			name: getColName(col, legendMap, aggregationPerQuery, clickhouseQueryNames),
+			name: getColName(col, legendMap, aggregationPerQuery),
 			queryName: col.queryName,
 			isValueColumn: col.columnType === 'aggregation',
-			id: getColId(col, aggregationPerQuery, clickhouseQueryNames),
+			id: getColId(col, aggregationPerQuery),
 		}));
 
 		// Process rows for this specific query
@@ -195,13 +177,8 @@ function convertScalarDataArrayToTable(
 			const rowData: Record<string, any> = {};
 
 			scalarData?.columns?.forEach((col, colIndex) => {
-				const columnName = getColName(
-					col,
-					legendMap,
-					aggregationPerQuery,
-					clickhouseQueryNames,
-				);
-				const columnId = getColId(col, aggregationPerQuery, clickhouseQueryNames);
+				const columnName = getColName(col, legendMap, aggregationPerQuery);
+				const columnId = getColId(col, aggregationPerQuery);
 				rowData[columnId || columnName] = dataRow[colIndex];
 			});
 
@@ -225,7 +202,6 @@ function convertScalarWithFormatForWeb(
 	scalarDataArray: ScalarData[],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
-	clickhouseQueryNames: Set<string>,
 ): QueryDataV3[] {
 	if (!scalarDataArray || scalarDataArray.length === 0) {
 		return [];
@@ -234,18 +210,13 @@ function convertScalarWithFormatForWeb(
 	return scalarDataArray.map((scalarData) => {
 		const columns =
 			scalarData.columns?.map((col) => {
-				const colName = getColName(
-					col,
-					legendMap,
-					aggregationPerQuery,
-					clickhouseQueryNames,
-				);
+				const colName = getColName(col, legendMap, aggregationPerQuery);
 
 				return {
 					name: colName,
 					queryName: col.queryName,
 					isValueColumn: col.columnType === 'aggregation',
-					id: getColId(col, aggregationPerQuery, clickhouseQueryNames),
+					id: getColId(col, aggregationPerQuery),
 				};
 			}) || [];
 
@@ -318,7 +289,6 @@ function convertV5DataByType(
 	v5Data: any,
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
-	clickhouseQueryNames: Set<string>,
 ): MetricRangePayloadV3['data'] {
 	switch (v5Data?.type) {
 		case 'time_series': {
@@ -337,7 +307,6 @@ function convertV5DataByType(
 				scalarData,
 				legendMap,
 				aggregationPerQuery,
-				clickhouseQueryNames,
 			);
 			return {
 				resultType: 'scalar',
@@ -404,15 +373,6 @@ export function convertV5ResponseToLegacy(
 				{} as Record<string, any>,
 			) || {};
 
-	// clickhouse_sql queries have no aggregation metadata; their value columns
-	// are named/keyed by the real SQL alias the response carries (see getColId).
-	const clickhouseQueryNames = new Set<string>(
-		(params?.compositeQuery?.queries ?? [])
-			.filter((query) => query.type === 'clickhouse_sql')
-			.map((query) => (query.spec as { name?: string })?.name)
-			.filter((name): name is string => !!name),
-	);
-
 	// If formatForWeb is true, return as-is (like existing logic)
 	if (formatForWeb && v5Data?.type === 'scalar') {
 		const scalarData = v5Data.data.results as ScalarData[];
@@ -420,7 +380,6 @@ export function convertV5ResponseToLegacy(
 			scalarData,
 			legendMap,
 			aggregationPerQuery,
-			clickhouseQueryNames,
 		);
 
 		return {
@@ -443,7 +402,6 @@ export function convertV5ResponseToLegacy(
 		v5Data,
 		legendMap,
 		aggregationPerQuery,
-		clickhouseQueryNames,
 	);
 
 	// Create legacy-compatible response structure

frontend/src/pages/DashboardPageV2/DashboardContainer/queryV5/__tests__/prepareScalarTables.test.ts

@@ -5,7 +5,6 @@ import type {
 
 import {
 	extractAggregationsPerQuery,
-	extractClickhouseQueryNames,
 	prepareScalarTables,
 } from '../prepareScalarTables';
 
@@ -57,24 +56,6 @@ describe('extractAggregationsPerQuery', () => {
 	});
 });
 
-describe('extractClickhouseQueryNames', () => {
-	it('collects names of clickhouse_sql queries, ignoring other envelope types', () => {
-		const request = requestWith([
-			{ type: 'clickhouse_sql', spec: { name: 'A', query: 'SELECT 1' } },
-			{
-				type: 'builder_query',
-				spec: { name: 'B', aggregations: [{ expression: 'count()' }] },
-			},
-			{ type: 'promql', spec: { name: 'P', query: 'up' } },
-		]);
-		expect(extractClickhouseQueryNames(request)).toStrictEqual(new Set(['A']));
-	});
-
-	it('returns an empty set for an undefined payload', () => {
-		expect(extractClickhouseQueryNames(undefined)).toStrictEqual(new Set());
-	});
-});
-
 describe('prepareScalarTables', () => {
 	it('builds keyed rows with group + aggregation columns (V1 getColName/getColId parity)', () => {
 		const [table] = prepareScalarTables({
@@ -213,115 +194,18 @@ describe('prepareScalarTables', () => {
 		expect(tables.map((t) => t.queryName)).toStrictEqual(['A', 'B']);
 	});
 
-	it('clickhouse_sql single value column uses the SQL alias over the legend', () => {
+	it('queries without aggregation metadata fall back to legend || queryName', () => {
 		const [table] = prepareScalarTables({
 			results: [
-				scalarResult(
-					[
-						{
-							name: 'current_availability',
-							queryName: 'A',
-							columnType: 'aggregation',
-						},
-					],
-					[],
-				),
-			],
-			legendMap: { A: 'Legend' },
-			requestPayload: requestWith([
-				{ type: 'clickhouse_sql', spec: { name: 'A', query: 'SELECT ...' } },
-			]),
-		});
-		// The query is clickhouse_sql, so the response column's real SQL alias is
-		// used for both header and key (a single legend can't be the column name).
-		expect(table.columns[0].name).toBe('current_availability');
-		expect(table.columns[0].id).toBe('current_availability');
-	});
-
-	it('non-clickhouse query without aggregation metadata falls back to legend || queryName', () => {
-		const [table] = prepareScalarTables({
-			results: [
-				// Formulas/promql carry placeholder names and are not clickhouse_sql,
-				// so they must not adopt the response column name.
 				scalarResult(
 					[{ name: '__result_0', queryName: 'A', columnType: 'aggregation' }],
 					[],
 				),
 			],
 			legendMap: { A: 'Legend' },
-			requestPayload: requestWith([
-				{ type: 'promql', spec: { name: 'A', query: 'up' } },
-			]),
+			requestPayload: requestWith([]),
 		});
 		expect(table.columns[0].name).toBe('Legend');
 		expect(table.columns[0].id).toBe('A');
 	});
-
-	it('clickhouse_sql query keeps each value column distinct (regression: all-"A" collapse)', () => {
-		const [table] = prepareScalarTables({
-			results: [
-				scalarResult(
-					[
-						{ name: 'service.name', queryName: 'A', columnType: 'group' },
-						{
-							name: 'current_availability',
-							queryName: 'A',
-							columnType: 'aggregation',
-							aggregationIndex: 0,
-						},
-						{
-							name: 'error_budget_remaining',
-							queryName: 'A',
-							columnType: 'aggregation',
-							aggregationIndex: 1,
-						},
-						{ name: 'budget_status', queryName: 'A', columnType: 'group' },
-						{
-							name: 'total_requests',
-							queryName: 'A',
-							columnType: 'aggregation',
-							aggregationIndex: 4,
-						},
-					],
-					[['kuja-api_gateway-service', 99.985, 0.985, 'Healthy ✅', 2181216]],
-				),
-			],
-			legendMap: { A: '' },
-			// A clickhouse_sql envelope contributes no aggregation metadata.
-			requestPayload: requestWith([
-				{
-					type: 'clickhouse_sql',
-					spec: { name: 'A', query: 'SELECT ...' },
-				},
-			]),
-		});
-
-		// Headers keep their real names instead of collapsing to "A".
-		expect(table.columns.map((col) => col.name)).toStrictEqual([
-			'service.name',
-			'current_availability',
-			'error_budget_remaining',
-			'budget_status',
-			'total_requests',
-		]);
-		// Ids are unique, so value columns don't overwrite each other in the row.
-		expect(table.columns.map((col) => col.id)).toStrictEqual([
-			'service.name',
-			'current_availability',
-			'error_budget_remaining',
-			'budget_status',
-			'total_requests',
-		]);
-		expect(table.rows).toStrictEqual([
-			{
-				data: {
-					'service.name': 'kuja-api_gateway-service',
-					current_availability: 99.985,
-					error_budget_remaining: 0.985,
-					budget_status: 'Healthy ✅',
-					total_requests: 2181216,
-				},
-			},
-		]);
-	});
 });

frontend/src/pages/DashboardPageV2/DashboardContainer/queryV5/prepareScalarTables.ts

@@ -1,6 +1,5 @@
 import type {
 	Querybuildertypesv5ColumnDescriptorDTO,
-	Querybuildertypesv5QueryEnvelopeClickHouseSQLDTO,
 	Querybuildertypesv5QueryRangeRequestDTO,
 	Querybuildertypesv5ScalarDataDTO,
 } from 'api/generated/services/sigNoz.schemas';
@@ -45,43 +44,16 @@ export function extractAggregationsPerQuery(
 	return perQuery;
 }
 
-/**
- * Names of the request's clickhouse_sql queries. These have no aggregation
- * metadata, but their value columns carry the user's real SQL alias in the
- * response `col.name` — so columns of these queries are named/keyed by that
- * alias rather than collapsing onto the query name. Builder/formula/promql use
- * placeholder names (`__result`/`__result_N`) and are excluded here.
- */
-export function extractClickhouseQueryNames(
-	requestPayload: Querybuildertypesv5QueryRangeRequestDTO | undefined,
-): Set<string> {
-	const names = new Set<string>();
-	(requestPayload?.compositeQuery?.queries ?? []).forEach((envelope) => {
-		if (envelope.type !== Querybuildertypesv5QueryTypeDTO.clickhouse_sql) {
-			return;
-		}
-		const spec = (envelope as Querybuildertypesv5QueryEnvelopeClickHouseSQLDTO)
-			.spec;
-		if (spec?.name) {
-			names.add(spec.name);
-		}
-	});
-	return names;
-}
-
 /**
  * Column display name. Group columns keep their field name; aggregation
  * columns resolve alias > legend > expression > queryName — with the legend
  * skipped when the query has multiple aggregations, because one legend can't
- * label several value columns. clickhouse_sql columns have no aggregation
- * metadata, so their value columns are named by the real SQL alias the
- * response carries in `col.name`. (Port of V1 `getColName`.)
+ * label several value columns. (Port of V1 `getColName`.)
  */
 function getColName(
 	col: Querybuildertypesv5ColumnDescriptorDTO,
 	legendMap: Record<string, string>,
 	aggregationsPerQuery: AggregationsPerQuery,
-	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
@@ -102,13 +74,6 @@ function getColName(
 		return alias || expression || queryName;
 	}
 
-	// clickhouse_sql value columns carry their real SQL alias in col.name — use
-	// it so each value column keeps its own header instead of collapsing onto
-	// the query name. Formulas/promql use placeholder names, so they fall back
-	// to legend || queryName.
-	if (clickhouseQueryNames.has(queryName)) {
-		return col.name;
-	}
 	return legend || queryName;
 }
 
@@ -120,23 +85,15 @@ function getColName(
 function getColId(
 	col: Querybuildertypesv5ColumnDescriptorDTO,
 	aggregationsPerQuery: AggregationsPerQuery,
-	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
 	}
 
 	const queryName = col.queryName ?? '';
-
-	// clickhouse_sql value columns are keyed by their real SQL alias so multiple
-	// value columns stay unique instead of all collapsing onto the query name
-	// (which would overwrite every cell in the row with the last column's value).
-	if (clickhouseQueryNames.has(queryName)) {
-		return col.name;
-	}
-
 	const aggregations = aggregationsPerQuery[queryName];
 	const expression = aggregations?.[col.aggregationIndex ?? 0]?.expression || '';
+
 	if ((aggregations?.length || 0) > 1 && expression) {
 		return `${queryName}.${expression}`;
 	}
@@ -162,7 +119,6 @@ export function prepareScalarTables({
 	requestPayload,
 }: PrepareScalarTablesArgs): PanelTable[] {
 	const aggregationsPerQuery = extractAggregationsPerQuery(requestPayload);
-	const clickhouseQueryNames = extractClickhouseQueryNames(requestPayload);
 
 	return results.map((scalarData) => {
 		if (!scalarData) {
@@ -176,10 +132,10 @@ export function prepareScalarTables({
 		const queryName = scalarData.columns?.[0]?.queryName ?? '';
 
 		const columns: PanelTableColumn[] = (scalarData.columns ?? []).map((col) => ({
-			name: getColName(col, legendMap, aggregationsPerQuery, clickhouseQueryNames),
+			name: getColName(col, legendMap, aggregationsPerQuery),
 			queryName: col.queryName ?? '',
 			isValueColumn: col.columnType === 'aggregation',
-			id: getColId(col, aggregationsPerQuery, clickhouseQueryNames),
+			id: getColId(col, aggregationsPerQuery),
 		}));
 
 		const rows = (scalarData.data ?? []).map((dataRow) => {

pkg/flagger/registry.go

@@ -3,15 +3,16 @@ package flagger
 import "github.com/SigNoz/signoz/pkg/types/featuretypes"
 
 var (
-	FeatureUseSpanMetrics      = featuretypes.MustNewName("use_span_metrics")
-	FeatureKafkaSpanEval       = featuretypes.MustNewName("kafka_span_eval")
-	FeatureHideRootUser        = featuretypes.MustNewName("hide_root_user")
-	FeatureGetMetersFromZeus   = featuretypes.MustNewName("get_meters_from_zeus")
-	FeaturePutMetersInZeus     = featuretypes.MustNewName("put_meters_in_zeus")
-	FeatureUseMeterReporter    = featuretypes.MustNewName("use_meter_reporter")
-	FeatureUseJSONBody         = featuretypes.MustNewName("use_json_body")
-	FeatureUseFineGrainedAuthz = featuretypes.MustNewName("use_fine_grained_authz")
-	FeatureUseDashboardV2      = featuretypes.MustNewName("use_dashboard_v2")
+	FeatureUseSpanMetrics         = featuretypes.MustNewName("use_span_metrics")
+	FeatureKafkaSpanEval          = featuretypes.MustNewName("kafka_span_eval")
+	FeatureHideRootUser           = featuretypes.MustNewName("hide_root_user")
+	FeatureGetMetersFromZeus      = featuretypes.MustNewName("get_meters_from_zeus")
+	FeaturePutMetersInZeus        = featuretypes.MustNewName("put_meters_in_zeus")
+	FeatureUseMeterReporter       = featuretypes.MustNewName("use_meter_reporter")
+	FeatureUseJSONBody            = featuretypes.MustNewName("use_json_body")
+	FeatureUseFineGrainedAuthz    = featuretypes.MustNewName("use_fine_grained_authz")
+	FeatureUseDashboardV2         = featuretypes.MustNewName("use_dashboard_v2")
+	FeatureEnableMetricsReduction = featuretypes.MustNewName("enable_metrics_reduction")
 )
 
 func MustNewRegistry() featuretypes.Registry {
@@ -88,6 +89,14 @@ func MustNewRegistry() featuretypes.Registry {
 			DefaultVariant: featuretypes.MustNewName("disabled"),
 			Variants:       featuretypes.NewBooleanVariants(),
 		},
+		&featuretypes.Feature{
+			Name:           FeatureEnableMetricsReduction,
+			Kind:           featuretypes.KindBoolean,
+			Stage:          featuretypes.StageExperimental,
+			Description:    "Controls whether metrics cardinality reduction (buffer/reduced tables) is read by the querier",
+			DefaultVariant: featuretypes.MustNewName("disabled"),
+			Variants:       featuretypes.NewBooleanVariants(),
+		},
 	)
 	if err != nil {
 		panic(err)

pkg/modules/inframonitoring/implinframonitoring/helpers.go

@@ -341,12 +341,12 @@ func alignedMetricWindow(startMs, endMs int64) (
 	}
 
 	tsAdjustedStartMs, _, distributedTSTable, localTSTable := telemetrymetrics.WhichTSTableToUse(
-		samplesAdjustedStartMs, flooredEndMs, nil,
+		samplesAdjustedStartMs, flooredEndMs, false, nil,
 	)
 
 	distributedSamplesTable, localSamplesTable := telemetrymetrics.WhichSamplesTableToUse(
 		samplesAdjustedStartMs, flooredEndMs,
-		metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil,
+		metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil,
 	)
 
 	return samplesAdjustedStartMs, flooredEndMs, tsAdjustedStartMs, distributedTSTable, localTSTable, distributedSamplesTable, localSamplesTable

pkg/modules/metricsexplorer/implmetricsexplorer/module.go

@@ -141,7 +141,7 @@ func (m *module) listMetrics(ctx context.Context, orgID valuer.UUID, params *met
 	sb.Select("DISTINCT metric_name")
 
 	if params.Start != nil && params.End != nil {
-		start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(*params.Start), uint64(*params.End), nil)
+		start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(*params.Start), uint64(*params.End), false, nil)
 		sb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedTsTable))
 		sb.Where(sb.Between("unix_milli", start, end))
 	} else {
@@ -527,7 +527,7 @@ func (m *module) InspectMetrics(
 		return nil, err
 	}
 
-	tsStart, _, tsTable, _ := telemetrymetrics.WhichTSTableToUse(start, end, nil)
+	tsStart, _, tsTable, _ := telemetrymetrics.WhichTSTableToUse(start, end, false, nil)
 	tsSb := sqlbuilder.NewSelectBuilder()
 	tsSb.Select("fingerprint", "labels")
 	tsSb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, tsTable))
@@ -971,8 +971,8 @@ func (m *module) fetchMetricsStatsWithSamples(
 		}
 	}
 
-	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
-	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
+	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
+	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil)
 	countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
 
 	// Timeseries counts per metric
@@ -1100,7 +1100,7 @@ func (m *module) computeTimeseriesTreemap(ctx context.Context, req *metricsexplo
 		}
 	}
 
-	start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
+	start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
 
 	totalTSBuilder := sqlbuilder.NewSelectBuilder()
 	totalTSBuilder.Select("uniq(fingerprint) AS total_time_series")
@@ -1176,8 +1176,8 @@ func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorer
 		}
 	}
 
-	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
-	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
+	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), false, nil)
+	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, false, nil)
 	countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
 
 	candidateLimit := req.Limit + 50

pkg/querier/builder_query.go

@@ -91,13 +91,22 @@ func (q *builderQuery[T]) Fingerprint() string {
 				if a.ComparisonSpaceAggregationParam != nil {
 					spaceAggParamStr = a.ComparisonSpaceAggregationParam.StringValue()
 				}
-				aggParts = append(aggParts, fmt.Sprintf("%s:%s:%s:%s:%s",
+				part := fmt.Sprintf("%s:%s:%s:%s:%s",
 					a.MetricName,
 					a.Temporality.StringValue(),
 					a.TimeAggregation.StringValue(),
 					a.SpaceAggregation.StringValue(),
 					spaceAggParamStr,
-				))
+				)
+				if a.Reduced {
+					oneDay := uint64(24 * time.Hour.Milliseconds())
+					route := "reduced"
+					if q.toMS-q.fromMS < oneDay && q.fromMS >= uint64(time.Now().UnixMilli())-oneDay {
+						route = "buffer"
+					}
+					part += ":" + route
+				}
+				aggParts = append(aggParts, part)
 			}
 		}
 		parts = append(parts, fmt.Sprintf("aggs=[%s]", strings.Join(aggParts, ",")))

pkg/querier/querier.go

@@ -119,7 +119,7 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
 	queries := make(map[string]qbtypes.Query)
 	steps := make(map[string]qbtypes.Step)
 
-	missingMetricQueries, metricWarnings, err := q.resolveMetricMetadata(ctx, req.CompositeQuery.Queries, req.Start, req.End)
+	missingMetricQueries, metricWarnings, err := q.resolveMetricMetadata(ctx, orgID, req.CompositeQuery.Queries, req.Start, req.End)
 	if err != nil {
 		return nil, err
 	}
@@ -304,7 +304,7 @@ func (q *querier) populateQBEvent(event *qbtypes.QBEvent, queries []qbtypes.Quer
 //     resolved: never-seen metrics and dormant metrics (seen but no data in
 //     the query window).
 //   - err: Internal when a metadata fetch fails.
-func (q *querier) resolveMetricMetadata(ctx context.Context, queries []qbtypes.QueryEnvelope, start, end uint64) (missingMetricQueries []string, metricWarnings []string, err error) {
+func (q *querier) resolveMetricMetadata(ctx context.Context, orgID valuer.UUID, queries []qbtypes.QueryEnvelope, start, end uint64) (missingMetricQueries []string, metricWarnings []string, err error) {
 	metricNames := make([]string, 0)
 	for idx := range queries {
 		if queries[idx].Type != qbtypes.QueryTypeBuilder {
@@ -325,7 +325,7 @@ func (q *querier) resolveMetricMetadata(ctx context.Context, queries []qbtypes.Q
 		return nil, nil, nil
 	}
 
-	metricTemporality, metricTypes, err := q.metadataStore.FetchTemporalityAndTypeMulti(ctx, start, end, metricNames...)
+	metricTemporality, metricTypes, reducedMetricsSet, err := q.metadataStore.FetchTemporalityAndTypeMulti(ctx, orgID, start, end, metricNames...)
 	if err != nil {
 		q.logger.WarnContext(ctx, "failed to fetch metric temporality", errors.Attr(err), slog.Any("metrics", metricNames))
 		return nil, nil, errors.NewInternalf(errors.CodeInternal, "failed to fetch metrics temporality")
@@ -362,6 +362,9 @@ func (q *querier) resolveMetricMetadata(ctx context.Context, queries []qbtypes.Q
 			if err := spec.Aggregations[i].ValidateForType(); err != nil {
 				return nil, nil, err
 			}
+			if reducedMetricsSet[spec.Aggregations[i].MetricName] {
+				spec.Aggregations[i].Reduced = true
+			}
 			presentAggregations = append(presentAggregations, spec.Aggregations[i])
 		}
 		if len(presentAggregations) == 0 {

pkg/telemetrymetadata/metadata.go

@@ -2136,12 +2136,12 @@ func (t *telemetryMetaStore) GetAllValues(ctx context.Context, fieldValueSelecto
 	return values, complete, nil
 }
 
-func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
+func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
 	if metricName == "" {
 		return metrictypes.Unknown, errors.Newf(errors.TypeInternal, errors.CodeInternal, "metric name cannot be empty")
 	}
 
-	temporalityMap, err := t.FetchTemporalityMulti(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricName)
+	temporalityMap, err := t.FetchTemporalityMulti(ctx, orgID, queryTimeRangeStartTs, queryTimeRangeEndTs, metricName)
 	if err != nil {
 		return metrictypes.Unknown, err
 	}
@@ -2154,25 +2154,27 @@ func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, queryTimeRang
 	return temporality, nil
 }
 
-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...)
+func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
+	temporalities, _, _, err := t.FetchTemporalityAndTypeMulti(ctx, orgID, 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) {
+func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
 	if len(metricNames) == 0 {
-		return make(map[string]metrictypes.Temporality), make(map[string]metrictypes.Type), nil
+		return make(map[string]metrictypes.Temporality), make(map[string]metrictypes.Type), make(map[string]bool), nil
 	}
 
+	reductionEnabled := t.fl.BooleanOrEmpty(ctx, flagger.FeatureEnableMetricsReduction, featuretypes.NewFlaggerEvaluationContext(orgID))
+
 	temporalities := make(map[string]metrictypes.Temporality)
 	types := make(map[string]metrictypes.Type)
-	metricsTemporality, metricTypes, err := t.fetchMetricsTemporalityAndType(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
+	metricsTemporality, metricTypes, reduced, err := t.fetchMetricsTemporalityAndType(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, reductionEnabled, metricNames...)
 	if err != nil {
-		return nil, nil, err
+		return nil, nil, nil, err
 	}
 	meterMetricsTemporality, meterMetricsTypes, err := t.fetchMeterSourceMetricsTemporalityAndType(ctx, metricNames...)
 	if err != nil {
-		return nil, nil, err
+		return nil, nil, nil, err
 	}
 
 	// For metrics not found in the database, set to Unknown
@@ -2197,10 +2199,10 @@ func (t *telemetryMetaStore) FetchTemporalityAndTypeMulti(ctx context.Context, q
 		}
 	}
 
-	return temporalities, types, nil
+	return temporalities, types, reduced, nil
 }
 
-func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, map[string]metrictypes.Type, error) {
+func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, reductionEnabled bool, metricNames ...string) (map[string][]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
 	ctx = ctxtypes.NewContextWithCommentVals(ctx, map[string]string{
 		instrumentationtypes.TelemetrySignal:  telemetrytypes.SignalMetrics.StringValue(),
 		instrumentationtypes.CodeNamespace:    "metadata",
@@ -2208,48 +2210,58 @@ func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context,
 	})
 	temporalities := make(map[string][]metrictypes.Temporality)
 	types := make(map[string]metrictypes.Type)
+	reduced := make(map[string]bool)
 
-	adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, nil)
+	adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, false, nil)
 
-	// Build query to fetch temporality for all metrics
-	// We use attr_string_value where attr_name = '__temporality__'
-	// Note: The columns are mixed in the current data - temporality column contains metric_name
-	// and metric_name column contains temporality value, so we use the correct mapping
-	sb := sqlbuilder.Select(
-		"metric_name",
-		"temporality",
-		"any(type) AS type",
-		"any(is_monotonic) as is_monotonic",
-	).
-		From(t.metricsDBName + "." + tsTableName)
+	cols := []string{"metric_name", "temporality", "any(type) AS type", "any(is_monotonic) as is_monotonic"}
 
-	// Filter by metric names (in the temporality column due to data mix-up)
+	// When reduction is enabled, fold the reduced-catalog presence check into the
+	// same query so a metric's reduced status comes back in one round trip.
+	var reducedArgs []any
+	if reductionEnabled {
+		rs := sqlbuilder.NewSelectBuilder()
+		rs.Select("metric_name")
+		rs.From(t.metricsDBName + "." + telemetrymetrics.TimeseriesV4ReducedTableName)
+		rs.Where(rs.In("metric_name", metricNames), rs.GTE("unix_milli", adjustedStartTs), rs.LT("unix_milli", adjustedEndTs))
+		rs.GroupBy("metric_name")
+		rsQuery, rsArgs := rs.BuildWithFlavor(sqlbuilder.ClickHouse)
+		cols = append(cols, fmt.Sprintf("metric_name GLOBAL IN (%s) AS reduced", rsQuery))
+		reducedArgs = rsArgs
+	}
+
+	sb := sqlbuilder.NewSelectBuilder()
+	sb.Select(cols...)
+	sb.From(t.metricsDBName + "." + tsTableName)
 	sb.Where(
 		sb.In("metric_name", metricNames),
 		sb.GTE("unix_milli", adjustedStartTs),
 		sb.LT("unix_milli", adjustedEndTs),
 	)
-
 	sb.GroupBy("metric_name", "temporality")
 
-	query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
+	query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, reducedArgs...)
 
 	t.logger.DebugContext(ctx, "fetching metric temporality", slog.String("query", query), slog.Any("args", args))
 
 	rows, err := t.telemetrystore.ClickhouseDB().Query(ctx, query, args...)
 	if err != nil {
-		return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
+		return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to fetch metric temporality")
 	}
 	defer rows.Close()
 
-	// Process results
 	for rows.Next() {
 		var metricName string
 		var temporality metrictypes.Temporality
 		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")
+		var isReduced uint8
+		dest := []any{&metricName, &temporality, &metricType, &isMonotonic}
+		if reductionEnabled {
+			dest = append(dest, &isReduced)
+		}
+		if err := rows.Scan(dest...); err != nil {
+			return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "failed to scan temporality result")
 		}
 		if temporality != metrictypes.Unknown {
 			temporalities[metricName] = append(temporalities[metricName], temporality)
@@ -2258,12 +2270,15 @@ func (t *telemetryMetaStore) fetchMetricsTemporalityAndType(ctx context.Context,
 			metricType = metrictypes.GaugeType
 		}
 		types[metricName] = metricType
+		if isReduced != 0 {
+			reduced[metricName] = true
+		}
 	}
 	if err := rows.Err(); err != nil {
-		return nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
+		return nil, nil, nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
 	}
 
-	return temporalities, types, nil
+	return temporalities, types, reduced, nil
 }
 
 func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporalityAndType(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, error) {

pkg/telemetrymetrics/reduced_test.go

@@ -0,0 +1,157 @@
+package telemetrymetrics
+
+import (
+	"context"
+	"testing"
+	"time"
+
+	"github.com/SigNoz/signoz/pkg/flagger"
+	"github.com/SigNoz/signoz/pkg/instrumentation/instrumentationtest"
+	"github.com/SigNoz/signoz/pkg/types/metrictypes"
+	qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
+	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
+	"github.com/SigNoz/signoz/pkg/types/telemetrytypes/telemetrytypestest"
+	"github.com/stretchr/testify/require"
+)
+
+func reducedQuery(metric string, ty metrictypes.Type, temp metrictypes.Temporality, ta metrictypes.TimeAggregation, sa metrictypes.SpaceAggregation) qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation] {
+	return qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
+		Signal:       telemetrytypes.SignalMetrics,
+		StepInterval: qbtypes.Step{Duration: 5 * time.Minute},
+		Aggregations: []qbtypes.MetricAggregation{{
+			MetricName:       metric,
+			Type:             ty,
+			Temporality:      temp,
+			TimeAggregation:  ta,
+			SpaceAggregation: sa,
+			Reduced:          true,
+		}},
+	}
+}
+
+func TestReducedStatementBuilder(t *testing.T) {
+	cases := []struct {
+		name     string
+		query    qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]
+		expected qbtypes.Statement
+	}{
+		{
+			name:  "gauge_sum_latest",
+			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, anyLast(last) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, argMax(value, unix_milli) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "gauge_avg_avg",
+			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "gauge_min_min",
+			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMin, metrictypes.SpaceAggregationMin),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(min) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`min`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "gauge_max_max",
+			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMax, metrictypes.SpaceAggregationMax),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`max`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "counter_sum_rate",
+			query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationSum),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), "test.metric", uint64(1746999600000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "counter_avg_increase",
+			query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationIncrease, metrictypes.SpaceAggregationAvg),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), "test.metric", uint64(1746999600000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "counter_min_omitted",
+			query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationMin),
+			expected: qbtypes.Statement{
+				Query: "WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0},
+			},
+		},
+		{
+			name:  "counter_max_omitted",
+			query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationMax),
+			expected: qbtypes.Statement{
+				Query: "WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0},
+			},
+		},
+		{
+			name:  "histogram_p99",
+			query: reducedQuery("test.metric", metrictypes.HistogramType, metrictypes.Cumulative, metrictypes.TimeAggregationUnspecified, metrictypes.SpaceAggregationPercentile99),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts, `le`), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+		{
+			name:  "summary_avg",
+			query: reducedQuery("test.metric", metrictypes.SummaryType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
+			expected: qbtypes.Statement{
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.distributed_time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+			},
+		},
+	}
+
+	fm := NewFieldMapper()
+	cb := NewConditionBuilder(fm)
+	fl, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
+	require.NoError(t, err)
+	sb := NewMetricQueryStatementBuilder(instrumentationtest.New().ToProviderSettings(), telemetrytypestest.NewMockMetadataStore(), fm, cb, fl)
+
+	const start, end = uint64(1747000000000), uint64(1747172800000)
+
+	for _, c := range cases {
+		t.Run(c.name, func(t *testing.T) {
+			got, err := sb.Build(context.Background(), start, end, qbtypes.RequestTypeTimeSeries, c.query, nil)
+			require.NoError(t, err)
+			require.Equal(t, c.expected.Query, got.Query)
+			require.Equal(t, c.expected.Args, got.Args)
+		})
+	}
+
+	t.Run("buffer_recent_window", func(t *testing.T) {
+		now := time.Now().UnixMilli()
+		q := reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum)
+		got, err := sb.Build(context.Background(), uint64(now-2*time.Hour.Milliseconds()), uint64(now), qbtypes.RequestTypeTimeSeries, q, nil)
+		require.NoError(t, err)
+		require.Contains(t, got.Query, "signoz_metrics.distributed_samples_v4_buffer")
+		require.Contains(t, got.Query, "signoz_metrics.time_series_v4_buffer")
+		require.Contains(t, got.Query, "is_reduced")
+		require.NotContains(t, got.Query, "UNION ALL")
+	})
+
+	t.Run("not_reduced", func(t *testing.T) {
+		q := reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum)
+		q.Aggregations[0].Reduced = false
+		got, err := sb.Build(context.Background(), start, end, qbtypes.RequestTypeTimeSeries, q, nil)
+		require.NoError(t, err)
+		require.NotContains(t, got.Query, "UNION ALL")
+		require.NotContains(t, got.Query, "reduced")
+		require.NotContains(t, got.Query, "buffer")
+	})
+}

pkg/telemetrymetrics/statement_builder.go

@@ -4,6 +4,7 @@ import (
 	"context"
 	"fmt"
 	"log/slog"
+	"time"
 
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/flagger"
@@ -180,19 +181,30 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 		query.Aggregations[0].SpaceAggregation = metrictypes.SpaceAggregationSum
 	}
 
+	agg := query.Aggregations[0]
+
+	// A reduced metric reads the raw buffer for recent short windows, and
+	// samples_v4/agg (unioned with the reduced tables) otherwise. The buffer is
+	// shaped exactly like samples_v4 / time_series_v4, so once the table names are
+	// chosen the rest of the pipeline is unchanged.
+	useBuffer := agg.Reduced &&
+		end-start < oneDayInMilliseconds &&
+		start >= uint64(time.Now().UnixMilli())-oneDayInMilliseconds
+
+	samplesTable, _ := WhichSamplesTableToUse(start, end, agg.Type, agg.TimeAggregation, useBuffer, agg.TableHints)
+	tsStart, tsEnd, _, tsTable := WhichTSTableToUse(start, end, useBuffer, agg.TableHints)
+
 	var timeSeriesCTE string
 	var timeSeriesCTEArgs []any
 	var err error
 
-	// time_series_cte
-	// this is applicable for all the queries
-	if timeSeriesCTE, timeSeriesCTEArgs, err = b.buildTimeSeriesCTE(ctx, start, end, query, keys, variables); err != nil {
+	if timeSeriesCTE, timeSeriesCTEArgs, err = b.buildTimeSeriesCTE(ctx, tsStart, tsEnd, query, keys, variables, tsTable); err != nil {
 		return nil, err
 	}
 
 	if qbtypes.CanShortCircuitDelta(query.Aggregations[0]) {
 		// spatial_aggregation_cte directly for certain delta queries
-		if frag, args, err := b.buildTemporalAggDeltaFastPath(start, end, query, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
+		if frag, args, err := b.buildTemporalAggDeltaFastPath(start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
 			return nil, err
 		} else if frag != "" {
 			cteFragments = append(cteFragments, frag)
@@ -200,7 +212,7 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 		}
 	} else {
 		// temporal_aggregation_cte
-		if frag, args, err := b.buildTemporalAggregationCTE(ctx, start, end, query, keys, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
+		if frag, args, err := b.buildTemporalAggregationCTE(ctx, start, end, query, keys, samplesTable, timeSeriesCTE, timeSeriesCTEArgs); err != nil {
 			return nil, err
 		} else if frag != "" {
 			cteFragments = append(cteFragments, frag)
@@ -214,18 +226,188 @@ func (b *MetricQueryStatementBuilder) buildPipelineStatement(
 		}
 	}
 
+	var reducedFragments []string
+	var reducedArgs [][]any
+	if agg.Reduced && !useBuffer {
+		var tsCTE string
+		var tsArgs []any
+		if tsCTE, tsArgs, err = b.buildReducedTimeSeriesCTE(ctx, start, end, query, keys, variables); err != nil {
+			return nil, err
+		}
+		if temporalFrag, temporalArgs, ok := b.buildReducedTemporalAggregationCTE(start, end, query, tsCTE, tsArgs); ok {
+			spatialFrag, spatialArgs := b.buildReducedSpatialAggregationCTE(query)
+			reducedFragments = []string{temporalFrag, spatialFrag}
+			reducedArgs = [][]any{temporalArgs, spatialArgs}
+		}
+	}
+
 	// reset the query to the original state
 	query.Aggregations[0].SpaceAggregation = origSpaceAgg
 	query.Aggregations[0].TimeAggregation = origTimeAgg
 	query.GroupBy = origGroupBy
 
-	// final SELECT
-	return b.BuildFinalSelect(cteFragments, cteArgs, query)
+	mainStmt, err := b.BuildFinalSelect(cteFragments, cteArgs, query)
+	if err != nil {
+		return nil, err
+	}
+	if reducedFragments == nil {
+		return mainStmt, nil
+	}
+	reducedStmt, err := b.BuildFinalSelect(reducedFragments, reducedArgs, query)
+	if err != nil {
+		return nil, err
+	}
+	return unionStatements(mainStmt, reducedStmt, query)
+}
+
+func unionStatements(main, reduced *qbtypes.Statement, query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]) (*qbtypes.Statement, error) {
+	orderBy := "ts"
+	for _, g := range query.GroupBy {
+		orderBy = fmt.Sprintf("`%s`, ", g.Name) + orderBy
+	}
+	q := fmt.Sprintf("SELECT * FROM (%s) UNION ALL SELECT * FROM (%s) ORDER BY %s", main.Query, reduced.Query, orderBy)
+	args := append(append([]any{}, main.Args...), reduced.Args...)
+	warnings := append(append([]string{}, main.Warnings...), reduced.Warnings...)
+	return &qbtypes.Statement{Query: q, Args: args, Warnings: warnings}, nil
+}
+
+func (b *MetricQueryStatementBuilder) buildReducedTimeSeriesCTE(
+	ctx context.Context,
+	start, end uint64,
+	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	keys map[string][]*telemetrytypes.TelemetryFieldKey,
+	variables map[string]qbtypes.VariableItem,
+) (string, []any, error) {
+	sb := sqlbuilder.NewSelectBuilder()
+
+	var preparedWhereClause querybuilder.PreparedWhereClause
+	var err error
+	if query.Filter != nil && query.Filter.Expression != "" {
+		preparedWhereClause, err = querybuilder.PrepareWhereClause(query.Filter.Expression, querybuilder.FilterExprVisitorOpts{
+			Context:          ctx,
+			Logger:           b.logger,
+			FieldMapper:      b.fm,
+			ConditionBuilder: b.cb,
+			FieldKeys:        keys,
+			FullTextColumn:   &telemetrytypes.TelemetryFieldKey{Name: "labels"},
+			Variables:        variables,
+			StartNs:          start,
+			EndNs:            end,
+		})
+		if err != nil {
+			return "", nil, err
+		}
+	}
+
+	sb.From(fmt.Sprintf("%s.%s", DBName, TimeseriesV4ReducedTableName))
+	sb.Select("fingerprint")
+	for _, g := range query.GroupBy {
+		col, err := b.fm.ColumnExpressionFor(ctx, start, end, &g.TelemetryFieldKey, keys)
+		if err != nil {
+			return "", nil, err
+		}
+		sb.SelectMore(col)
+	}
+	sb.Where(
+		sb.In("metric_name", query.Aggregations[0].MetricName),
+		sb.GTE("unix_milli", start),
+		sb.LTE("unix_milli", end),
+		sb.EQ("__normalized", false),
+	)
+
+	if !preparedWhereClause.IsEmpty() {
+		sb.AddWhereClause(preparedWhereClause.WhereClause)
+	}
+	sb.GroupBy("fingerprint")
+	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+
+	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
+	return fmt.Sprintf("(%s) AS filtered_time_series", q), args, nil
+}
+
+func (b *MetricQueryStatementBuilder) buildReducedTemporalAggregationCTE(
+	start, end uint64,
+	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	timeSeriesCTE string,
+	timeSeriesCTEArgs []any,
+) (string, []any, bool) {
+	agg := query.Aggregations[0]
+	stepSec := int64(query.StepInterval.Seconds())
+
+	value, weight, ok := ReducedValueColumn(agg.Type, agg.SpaceAggregation)
+	if !ok {
+		return "", nil, false
+	}
+
+	// dedup recomputed buckets: latest computed_at wins per (series, 60s bucket)
+	dedup := sqlbuilder.NewSelectBuilder()
+	dedup.Select("reduced_fingerprint AS fingerprint", "unix_milli")
+	dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS value", value))
+	if weight != "" {
+		dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS weight", weight))
+	}
+	dedup.From(fmt.Sprintf("%s.%s", DBName, WhichReducedSamplesTableToUse(agg.Type)))
+	dedup.Where(
+		dedup.In("metric_name", agg.MetricName),
+		dedup.GTE("unix_milli", start),
+		dedup.LT("unix_milli", end),
+	)
+	dedup.GroupBy("reduced_fingerprint", "unix_milli")
+	dedupQuery, dedupArgs := dedup.BuildWithFlavor(sqlbuilder.ClickHouse)
+
+	sb := sqlbuilder.NewSelectBuilder()
+	sb.Select("fingerprint")
+	sb.SelectMore(fmt.Sprintf("toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(%d)) AS ts", stepSec))
+	for _, g := range query.GroupBy {
+		sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
+	}
+	sb.SelectMore(fmt.Sprintf("%s AS per_series_value", ReducedTimeAggregationColumn(agg.TimeAggregation, stepSec)))
+	if weight != "" {
+		// count_series is a series count, not additive over time, so the avg
+		// denominator is reduced with avg
+		sb.SelectMore("avg(weight) AS per_series_weight")
+	}
+	sb.From(fmt.Sprintf("(%s) AS points", dedupQuery))
+	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
+	sb.GroupBy("fingerprint", "ts")
+	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+
+	initArgs := append(append([]any{}, dedupArgs...), timeSeriesCTEArgs...)
+	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, initArgs...)
+	return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, true
+}
+
+func (b *MetricQueryStatementBuilder) buildReducedSpatialAggregationCTE(
+	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+) (string, []any) {
+	spatial := "sum(per_series_value)"
+	switch query.Aggregations[0].SpaceAggregation {
+	case metrictypes.SpaceAggregationAvg:
+		spatial = "sum(per_series_value) / sum(per_series_weight)"
+	case metrictypes.SpaceAggregationMin:
+		spatial = "min(per_series_value)"
+	case metrictypes.SpaceAggregationMax:
+		spatial = "max(per_series_value)"
+	}
+
+	sb := sqlbuilder.NewSelectBuilder()
+	sb.Select("ts")
+	for _, g := range query.GroupBy {
+		sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
+	}
+	sb.SelectMore(spatial + " AS value")
+	sb.From("__temporal_aggregation_cte")
+	sb.GroupBy("ts")
+	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+
+	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
+	return fmt.Sprintf("__spatial_aggregation_cte AS (%s)", q), args
 }
 
 func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	samplesTable string,
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
 ) (string, []any, error) {
@@ -242,8 +424,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 	}
 
 	aggCol, err := AggregationColumnForSamplesTable(
-		start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality,
-		query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints,
+		samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation,
 	)
 	if err != nil {
 		return "", nil, err
@@ -260,8 +441,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDeltaFastPath(
 
 	sb.SelectMore(fmt.Sprintf("%s AS value", aggCol))
 
-	tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
+	sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
 	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
 	sb.Where(
 		sb.In("metric_name", query.Aggregations[0].MetricName),
@@ -281,6 +461,7 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	keys map[string][]*telemetrytypes.TelemetryFieldKey,
 	variables map[string]qbtypes.VariableItem,
+	tsTable string,
 ) (string, []any, error) {
 	sb := sqlbuilder.NewSelectBuilder()
 
@@ -304,8 +485,7 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
 		}
 	}
 
-	start, end, _, tbl := WhichTSTableToUse(start, end, query.Aggregations[0].TableHints)
-	sb.From(fmt.Sprintf("%s.%s", DBName, tbl))
+	sb.From(fmt.Sprintf("%s.%s", DBName, tsTable))
 
 	sb.Select("fingerprint")
 	for _, g := range query.GroupBy {
@@ -331,6 +511,12 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
 		sb.EQ("__normalized", false),
 	)
 
+	// the buffer holds both raw rows and the reduced catalog rows; the raw read
+	// only wants the original series
+	if tsTable == TimeseriesV4BufferLocalTableName {
+		sb.Where(sb.EQ("is_reduced", false))
+	}
+
 	if !preparedWhereClause.IsEmpty() {
 		sb.AddWhereClause(preparedWhereClause.WhereClause)
 	}
@@ -347,21 +533,23 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggregationCTE(
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	_ map[string][]*telemetrytypes.TelemetryFieldKey,
+	samplesTable string,
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
 ) (string, []any, error) {
 	if query.Aggregations[0].Temporality == metrictypes.Delta {
-		return b.buildTemporalAggDelta(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
+		return b.buildTemporalAggDelta(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
 	} else if query.Aggregations[0].Temporality != metrictypes.Multiple {
-		return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
+		return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
 	}
-	return b.buildTemporalAggForMultipleTemporalities(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
+	return b.buildTemporalAggForMultipleTemporalities(ctx, start, end, query, samplesTable, timeSeriesCTE, timeSeriesCTEArgs)
 }
 
 func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
 	_ context.Context,
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	samplesTable string,
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
 ) (string, []any, error) {
@@ -378,7 +566,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
 		sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
 	}
 
-	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation)
 	if err != nil {
 		return "", nil, err
 	}
@@ -389,8 +577,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
 
 	sb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
 
-	tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
+	sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
 	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
 	sb.Where(
 		sb.In("metric_name", query.Aggregations[0].MetricName),
@@ -409,6 +596,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 	_ context.Context,
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	samplesTable string,
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
 ) (string, []any, error) {
@@ -424,14 +612,13 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 		baseSb.SelectMore(fmt.Sprintf("`%s`", g.Name))
 	}
 
-	aggCol, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggCol, err := AggregationColumnForSamplesTable(samplesTable, query.Aggregations[0].Temporality, query.Aggregations[0].TimeAggregation)
 	if err != nil {
 		return "", nil, err
 	}
 	baseSb.SelectMore(fmt.Sprintf("%s AS per_series_value", aggCol))
 
-	tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	baseSb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
+	baseSb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
 	baseSb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
 	baseSb.Where(
 		baseSb.In("metric_name", query.Aggregations[0].MetricName),
@@ -475,6 +662,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
 	_ context.Context,
 	start, end uint64,
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	samplesTable string,
 	timeSeriesCTE string,
 	timeSeriesCTEArgs []any,
 ) (string, []any, error) {
@@ -489,11 +677,11 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
 		sb.SelectMore(fmt.Sprintf("`%s`", g.Name))
 	}
 
-	aggForDeltaTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Delta, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggForDeltaTemporality, err := AggregationColumnForSamplesTable(samplesTable, metrictypes.Delta, query.Aggregations[0].TimeAggregation)
 	if err != nil {
 		return "", nil, err
 	}
-	aggForCumulativeTemporality, err := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggForCumulativeTemporality, err := AggregationColumnForSamplesTable(samplesTable, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation)
 	if err != nil {
 		return "", nil, err
 	}
@@ -521,8 +709,7 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
 		sb.SelectMore(expr)
 	}
 
-	tbl, _ := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
-	sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
+	sb.From(fmt.Sprintf("%s.%s AS points", DBName, samplesTable))
 	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
 	sb.Where(
 		sb.In("metric_name", query.Aggregations[0].MetricName),

pkg/telemetrymetrics/tables.go

@@ -30,6 +30,17 @@ const (
 	TimeseriesV41weekLocalTableName  = "time_series_v4_1week"
 	AttributesMetadataTableName      = "distributed_metadata"
 	AttributesMetadataLocalTableName = "metadata"
+
+	// The buffer holds raw points for ~24h; the reduced tables hold 60s
+	// aggregates of dropped-label series.
+	SamplesV4BufferTableName          = "distributed_samples_v4_buffer"
+	SamplesV4BufferLocalTableName     = "samples_v4_buffer"
+	TimeseriesV4BufferTableName       = "distributed_time_series_v4_buffer"
+	TimeseriesV4BufferLocalTableName  = "time_series_v4_buffer"
+	SamplesV4ReducedLastTableName     = "distributed_samples_v4_reduced_last_60s"
+	SamplesV4ReducedSumTableName      = "distributed_samples_v4_reduced_sum_60s"
+	TimeseriesV4ReducedTableName      = "distributed_time_series_v4_reduced"
+	TimeseriesV4ReducedLocalTableName = "time_series_v4_reduced"
 )
 
 var (
@@ -49,8 +60,16 @@ var (
 // in that order.
 func WhichTSTableToUse(
 	start, end uint64,
+	useBuffer bool,
 	tableHints *metrictypes.MetricTableHints,
 ) (uint64, uint64, string, string) {
+	// the buffer holds the recent raw window for reduced metrics and has the same
+	// shape as time_series_v4; round the start to the hour like the v4 table.
+	if useBuffer {
+		start = start - (start % (oneHourInMilliseconds))
+		return start, end, TimeseriesV4BufferTableName, TimeseriesV4BufferLocalTableName
+	}
+
 	// if we have a hint for the table, we need to use it
 	// the hint will be used to override the default table selection logic
 	if tableHints != nil {
@@ -149,14 +168,20 @@ func WhichSamplesTableToUse(
 	start, end uint64,
 	metricType metrictypes.Type,
 	timeAggregation metrictypes.TimeAggregation,
+	useBuffer bool,
 	tableHints *metrictypes.MetricTableHints,
 ) (string, string) {
+	// the buffer holds the recent raw window for reduced metrics; same shape as samples_v4
+	if useBuffer {
+		return SamplesV4BufferTableName, SamplesV4BufferLocalTableName
+	}
+
 	// if we have a hint for the table, we need to use it
 	// the hint will be used to override the default table selection logic.
 	// SamplesTableName is the distributed name; derive the local via switch.
 	if tableHints != nil && tableHints.SamplesTableName != "" {
 		switch tableHints.SamplesTableName {
-		case SamplesV4TableName:
+		case SamplesV4TableName, SamplesV4BufferTableName:
 			return SamplesV4TableName, SamplesV4LocalTableName
 		case SamplesV4Agg5mTableName:
 			return SamplesV4Agg5mTableName, SamplesV4Agg5mLocalTableName
@@ -188,13 +213,10 @@ func WhichSamplesTableToUse(
 }
 
 func AggregationColumnForSamplesTable(
-	start, end uint64,
-	metricType metrictypes.Type,
+	tableName string,
 	temporality metrictypes.Temporality,
 	timeAggregation metrictypes.TimeAggregation,
-	tableHints *metrictypes.MetricTableHints,
 ) (string, error) {
-	tableName, _ := WhichSamplesTableToUse(start, end, metricType, timeAggregation, tableHints)
 	var aggregationColumn string
 	switch temporality {
 	case metrictypes.Delta:
@@ -202,7 +224,7 @@ func AggregationColumnForSamplesTable(
 		// although it doesn't make sense to use anyLast, avg, min, max, count on delta metrics,
 		// we are keeping it here to make sure that query will not be invalid
 		switch tableName {
-		case SamplesV4TableName:
+		case SamplesV4TableName, SamplesV4BufferTableName:
 			switch timeAggregation {
 			case metrictypes.TimeAggregationLatest:
 				aggregationColumn = "anyLast(value)"
@@ -244,7 +266,7 @@ func AggregationColumnForSamplesTable(
 		// for cumulative metrics, we only support `RATE`/`INCREASE`. The max value in window is
 		// used to calculate the sum which is then divided by the window size to get the rate
 		switch tableName {
-		case SamplesV4TableName:
+		case SamplesV4TableName, SamplesV4BufferTableName:
 			switch timeAggregation {
 			case metrictypes.TimeAggregationLatest:
 				aggregationColumn = "anyLast(value)"
@@ -284,7 +306,7 @@ func AggregationColumnForSamplesTable(
 		}
 	case metrictypes.Unspecified:
 		switch tableName {
-		case SamplesV4TableName:
+		case SamplesV4TableName, SamplesV4BufferTableName:
 			switch timeAggregation {
 			case metrictypes.TimeAggregationLatest:
 				aggregationColumn = "anyLast(value)"
@@ -332,6 +354,65 @@ func AggregationColumnForSamplesTable(
 	return aggregationColumn, nil
 }
 
+// WhichReducedSamplesTableToUse returns the 60s reduced samples table for a metric
+// type: the last_60s table for gauge-like series, the sum_60s table for counters
+// and histograms.
+func WhichReducedSamplesTableToUse(metricType metrictypes.Type) string {
+	if metricType == metrictypes.SumType || metricType == metrictypes.HistogramType {
+		return SamplesV4ReducedSumTableName
+	}
+	return SamplesV4ReducedLastTableName
+}
+
+// ReducedValueColumn returns the reduced value column (and the avg-denominator
+// weight) for a space aggregation. The reduced columns are pre-aggregated across
+// the original series, so the space aggregation picks the underlying value; the
+// sum table only has `sum`, so min/max across series have no column (ok=false).
+func ReducedValueColumn(metricType metrictypes.Type, space metrictypes.SpaceAggregation) (value, weight string, ok bool) {
+	if metricType == metrictypes.SumType || metricType == metrictypes.HistogramType {
+		switch space {
+		case metrictypes.SpaceAggregationSum:
+			return "`sum`", "", true
+		case metrictypes.SpaceAggregationAvg:
+			return "`sum`", "`count_series`", true
+		}
+		return "", "", false
+	}
+	switch space {
+	case metrictypes.SpaceAggregationSum:
+		return "`sum_last`", "", true
+	case metrictypes.SpaceAggregationAvg:
+		return "`sum_last`", "`count_series`", true
+	case metrictypes.SpaceAggregationMin:
+		return "`min`", "", true
+	case metrictypes.SpaceAggregationMax:
+		return "`max`", "", true
+	}
+	return "", "", false
+}
+
+// ReducedTimeAggregationColumn applies the time aggregation to the reduced `value`
+// column over the step's 60s buckets. latest uses argMax over the bucket timestamp
+// (the buckets have no read order); rate divides the per-step sum by the step.
+func ReducedTimeAggregationColumn(timeAggregation metrictypes.TimeAggregation, stepSec int64) string {
+	switch timeAggregation {
+	case metrictypes.TimeAggregationLatest:
+		return "argMax(value, unix_milli)"
+	case metrictypes.TimeAggregationAvg:
+		return "avg(value)"
+	case metrictypes.TimeAggregationMin:
+		return "min(value)"
+	case metrictypes.TimeAggregationMax:
+		return "max(value)"
+	case metrictypes.TimeAggregationCount:
+		return "count(value)"
+	case metrictypes.TimeAggregationRate:
+		return fmt.Sprintf("sum(value) / %d", stepSec)
+	default: // sum, increase
+		return "sum(value)"
+	}
+}
+
 func AggregationQueryForHistogramCountWithParams(param *metrictypes.ComparisonSpaceAggregationParam) (string, error) {
 	if param == nil {
 		return "", errors.NewInvalidInputf(errors.CodeInvalidInput, "no aggregation param provided for histogram count")

pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go

@@ -480,7 +480,9 @@ type MetricAggregation struct {
 	// value filter to apply to the query
 	ValueFilter *metrictypes.MetricValueFilter `json:"-"`
 	// reduce to operator for metric scalar requests
-	ReduceTo ReduceTo `json:"reduceTo,omitempty"`
+	ReduceTo ReduceTo `json:"reduceTo,omitzero"`
+
+	Reduced bool `json:"-"`
 }
 
 // Copy creates a deep copy of MetricAggregation.

pkg/types/telemetrytypes/store.go

@@ -4,6 +4,7 @@ import (
 	"context"
 
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
+	"github.com/SigNoz/signoz/pkg/valuer"
 )
 
 // MetadataStore is the interface for the telemetry metadata store.
@@ -26,12 +27,12 @@ type MetadataStore interface {
 	GetAllValues(ctx context.Context, fieldValueSelector *FieldValueSelector) (*TelemetryFieldValues, bool, error)
 
 	// FetchTemporality fetches the temporality for metric
-	FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error)
+	FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error)
 
 	// FetchTemporalityMulti fetches the temporality for multiple metrics
-	FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error)
+	FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, 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)
+	FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error)
 
 	// ListLogsJSONIndexes lists the JSON indexes for the logs table.
 	ListLogsJSONIndexes(ctx context.Context, filters ...string) ([]TelemetryFieldKeySkipIndex, error)

pkg/types/telemetrytypes/telemetrytypestest/metadata_store.go

@@ -6,6 +6,7 @@ import (
 
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
+	"github.com/SigNoz/signoz/pkg/valuer"
 )
 
 // MockMetadataStore implements the MetadataStore interface for testing purposes.
@@ -16,6 +17,7 @@ type MockMetadataStore struct {
 	AllValuesMap               map[string]*telemetrytypes.TelemetryFieldValues
 	TemporalityMap             map[string]metrictypes.Temporality
 	TypeMap                    map[string]metrictypes.Type
+	ReducedMap                 map[string]bool
 	PromotedPathsMap           map[string]bool
 	LogsJSONIndexes            []telemetrytypes.TelemetryFieldKeySkipIndex
 	ColumnEvolutionMetadataMap map[string][]*telemetrytypes.EvolutionEntry
@@ -306,7 +308,7 @@ func (m *MockMetadataStore) SetAllValues(lookupKey string, values *telemetrytype
 }
 
 // FetchTemporality fetches the temporality for a metric.
-func (m *MockMetadataStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
+func (m *MockMetadataStore) FetchTemporality(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
 	if temporality, exists := m.TemporalityMap[metricName]; exists {
 		return temporality, nil
 	}
@@ -314,7 +316,7 @@ func (m *MockMetadataStore) FetchTemporality(ctx context.Context, queryTimeRange
 }
 
 // FetchTemporalityMulti fetches the temporality for multiple metrics.
-func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
+func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
 	result := make(map[string]metrictypes.Temporality)
 
 	for _, metricName := range metricNames {
@@ -329,9 +331,10 @@ func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, queryTime
 }
 
 // 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) {
+func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, orgID valuer.UUID, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, map[string]metrictypes.Type, map[string]bool, error) {
 	temporalities := make(map[string]metrictypes.Temporality)
 	types := make(map[string]metrictypes.Type)
+	reduced := make(map[string]bool)
 
 	for _, metricName := range metricNames {
 		if temporality, exists := m.TemporalityMap[metricName]; exists {
@@ -344,9 +347,12 @@ func (m *MockMetadataStore) FetchTemporalityAndTypeMulti(ctx context.Context, qu
 		} else {
 			types[metricName] = metrictypes.UnspecifiedType
 		}
+		if m.ReducedMap[metricName] {
+			reduced[metricName] = true
+		}
 	}
 
-	return temporalities, types, nil
+	return temporalities, types, reduced, nil
 }
 
 // SetTemporality sets the temporality for a metric in the mock store.