test: max parametrising of the unit tests

pkg/querier/postprocess.go

@@ -185,22 +185,6 @@ func postProcessMetricQuery(
 	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
 	req *qbtypes.QueryRangeRequest,
 ) *qbtypes.Result {
-
-	config := query.Aggregations[0]
-	spaceAggOrderBy := fmt.Sprintf("%s(%s)", config.SpaceAggregation.StringValue(), config.MetricName)
-	timeAggOrderBy := fmt.Sprintf("%s(%s)", config.TimeAggregation.StringValue(), config.MetricName)
-	timeSpaceAggOrderBy := fmt.Sprintf("%s(%s(%s))", config.SpaceAggregation.StringValue(), config.TimeAggregation.StringValue(), config.MetricName)
-
-	for idx := range query.Order {
-		if query.Order[idx].Key.Name == spaceAggOrderBy ||
-			query.Order[idx].Key.Name == timeAggOrderBy ||
-			query.Order[idx].Key.Name == timeSpaceAggOrderBy {
-			query.Order[idx].Key.Name = qbtypes.DefaultOrderByKey
-		}
-	}
-
-	result = q.applySeriesLimit(result, query.Limit, query.Order)
-
 	if len(query.Functions) > 0 {
 		step := query.StepInterval.Duration.Milliseconds()
 		functions := q.prepareFillZeroArgsWithStep(query.Functions, req, step)

pkg/querybuilder/fallback_expr.go

@@ -132,6 +132,14 @@ func GroupByKeys(keys []qbtypes.GroupByKey) []string {
 	return k
 }
 
+func OrderByKeys(keys []qbtypes.OrderBy) []string {
+	k := []string{}
+	for _, key := range keys {
+		k = append(k, "`"+key.Key.Name+"`")
+	}
+	return k
+}
+
 func FormatValueForContains(value any) string {
 	if value == nil {
 		return ""

pkg/telemetrymetrics/statement_builder.go

@@ -4,6 +4,7 @@ import (
 	"context"
 	"fmt"
 	"log/slog"
+	"strings"
 
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/flagger"
@@ -607,8 +608,73 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 			sb.Where(rewrittenExpr)
 		}
 	}
-	sb.OrderBy(querybuilder.GroupByKeys(query.GroupBy)...)
-	sb.OrderBy("ts")
+	groupByKeys := querybuilder.GroupByKeys(query.GroupBy)
+	hasOrder := len(query.Order) > 0
+	hasLimit := query.Limit > 0
+	hasGroupBy := len(groupByKeys) > 0
+
+	if hasOrder && hasLimit {
+		// order by with limit: add WHERE subquery to restrict to top N distinct key combinations
+		orderByKeys := querybuilder.OrderByKeys(query.Order)
+		var orderByClauses []string
+		for _, o := range query.Order {
+			orderByClauses = append(orderByClauses, fmt.Sprintf("`%s` %s", o.Key.Name, o.Direction.StringValue()))
+		}
+
+		subSb := sqlbuilder.NewSelectBuilder()
+		subSb.Select(fmt.Sprintf("DISTINCT %s", orderByKeys[0]))
+		if len(orderByKeys) > 1 {
+			subSb.SelectMore(orderByKeys[1:]...)
+		}
+		subSb.From("__spatial_aggregation_cte")
+		subSb.OrderBy(orderByClauses...)
+
+		subQ, _ := subSb.BuildWithFlavor(sqlbuilder.ClickHouse)
+		subQ = fmt.Sprintf("%s LIMIT %d", subQ, query.Limit)
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(orderByKeys, ", "), subQ))
+
+		sb.OrderBy(orderByClauses...)
+	} else if hasOrder {
+		// order by without limit: apply order by clauses directly
+		for _, o := range query.Order {
+			key := o.Key.Name
+			if strings.Contains(key, query.Aggregations[0].MetricName) {
+				sb.OrderBy(fmt.Sprintf("avg(value) OVER (PARTITION BY %s) %s", strings.Join(groupByKeys, ", "), o.Direction.StringValue()))
+				continue
+			}
+			sb.OrderBy(fmt.Sprintf("`%s` %s", o.Key.Name, o.Direction.StringValue()))
+		}
+	} else if hasLimit && hasGroupBy {
+		// limit without order by: default ordering by avg(value)
+		subSb := sqlbuilder.NewSelectBuilder()
+		subSb.Select(groupByKeys[0])
+		if len(groupByKeys) > 1 {
+			subSb.SelectMore(groupByKeys[1:]...)
+		}
+		subSb.From("__spatial_aggregation_cte")
+		subSb.GroupBy(groupByKeys...)
+		subSb.OrderBy("avg(value)")
+
+		subQ, _ := subSb.BuildWithFlavor(sqlbuilder.ClickHouse)
+		subQ = fmt.Sprintf("%s LIMIT %d", subQ, query.Limit)
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(groupByKeys, ", "), subQ))
+	} else if hasGroupBy {
+		// grouping without order by or limit: sort by avg(value) DESC with labels as tiebreakers
+		sb.OrderBy(fmt.Sprintf("avg(value) OVER (PARTITION BY %s) DESC", strings.Join(groupByKeys, ", ")))
+	}
+
+	// add any group-by keys not already in the order-by as tiebreakers
+	orderKeySet := make(map[string]struct{})
+	for _, o := range query.Order {
+		orderKeySet[fmt.Sprintf("`%s`", o.Key.Name)] = struct{}{}
+	}
+	for _, g := range groupByKeys {
+		if _, exists := orderKeySet[g]; !exists {
+			sb.OrderBy(g)
+		}
+	}
+
+	sb.OrderBy("ts ASC")
 	if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam == nil {
 		sb.OrderBy("toFloat64(le)")
 	}

pkg/telemetrymetrics/stmt_builder_test.go

@@ -15,16 +15,17 @@ import (
 )
 
 func TestStatementBuilder(t *testing.T) {
-	cases := []struct {
-		name        string
-		requestType qbtypes.RequestType
-		query       qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]
-		expected    qbtypes.Statement
-		expectedErr error
-	}{
+	type baseQuery struct {
+		name     string
+		query    qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]
+		orderKey string
+		args     []any
+		cte      string
+	}
+
+	bases := []baseQuery{
 		{
-			name:        "test_cumulative_rate_sum",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "cumulative_rate_sum",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -40,24 +41,16 @@ func TestStatementBuilder(t *testing.T) {
 				Filter: &qbtypes.Filter{
 					Expression: "service.name = 'cartservice'",
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "service.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, 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(30)) AS ts, `service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`) 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, `service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name`, ts",
-				Args:  []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
-			},
-			expectedErr: nil,
+			orderKey: "service.name",
+			args:     []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
+			cte:      "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, 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(30)) AS ts, `service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`) 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, `service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`)",
 		},
 		{
-			name:        "test_cumulative_rate_sum_with_mat_column",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "cumulative_rate_sum_with_mat_column",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -73,24 +66,16 @@ func TestStatementBuilder(t *testing.T) {
 				Filter: &qbtypes.Filter{
 					Expression: "materialized.key.name REGEXP 'cartservice' OR service.name = 'cartservice'",
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "service.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, 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(30)) AS ts, `service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND (match(JSONExtractString(labels, 'materialized.key.name'), ?) OR JSONExtractString(labels, 'service.name') = ?) GROUP BY fingerprint, `service.name`) 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, `service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name`, ts",
-				Args:  []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "cartservice", "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
-			},
-			expectedErr: nil,
+			orderKey: "service.name",
+			args:     []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "cartservice", "cartservice", "signoz_calls_total", uint64(1747947360000), uint64(1747983420000), 0},
+			cte:      "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, 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(30)) AS ts, `service.name`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND (match(JSONExtractString(labels, 'materialized.key.name'), ?) OR JSONExtractString(labels, 'service.name') = ?) GROUP BY fingerprint, `service.name`) 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, `service.name` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`)",
 		},
 		{
-			name:        "test_delta_rate_sum",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "delta_rate_sum",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -106,24 +91,16 @@ func TestStatementBuilder(t *testing.T) {
 				Filter: &qbtypes.Filter{
 					Expression: "service.name = 'cartservice'",
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "service.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `service.name`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name`, ts",
-				Args:  []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "delta", false, "cartservice", "signoz_calls_total", uint64(1747947390000), uint64(1747983420000)},
-			},
-			expectedErr: nil,
+			orderKey: "service.name",
+			args:     []any{"signoz_calls_total", uint64(1747936800000), uint64(1747983420000), "delta", false, "cartservice", "signoz_calls_total", uint64(1747947390000), uint64(1747983420000)},
+			cte:      "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `service.name`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `service.name`)",
 		},
 		{
-			name:        "test_histogram_percentile1",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "histogram_percentile1",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -139,24 +116,16 @@ func TestStatementBuilder(t *testing.T) {
 				Filter: &qbtypes.Filter{
 					Expression: "service.name = 'cartservice'",
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "service.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `service.name`, `le`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `service.name`, `le`) SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY `service.name`, ts",
-				Args:  []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", false, "cartservice", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
-			},
-			expectedErr: nil,
+			orderKey: "service.name",
+			args:     []any{"signoz_latency", uint64(1747936800000), uint64(1747983420000), "delta", false, "cartservice", "signoz_latency", uint64(1747947390000), uint64(1747983420000)},
+			cte:      "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `service.name`, `le`, sum(value)/30 AS value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'service.name') = ? GROUP BY fingerprint, `service.name`, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY ts, `service.name`, `le`)",
 		},
 		{
-			name:        "test_gauge_avg_sum",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "gauge_avg_sum",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -172,24 +141,16 @@ func TestStatementBuilder(t *testing.T) {
 				Filter: &qbtypes.Filter{
 					Expression: "host.name = 'big-data-node-1'",
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "host.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "host.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `host.name`, avg(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'host.name') AS `host.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY fingerprint, `host.name`) 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, `host.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `host.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `host.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `host.name`, ts",
-				Args:  []any{"system.memory.usage", uint64(1747936800000), uint64(1747983420000), "unspecified", false, "big-data-node-1", "system.memory.usage", uint64(1747947390000), uint64(1747983420000), 0},
-			},
-			expectedErr: nil,
+			orderKey: "host.name",
+			args:     []any{"system.memory.usage", uint64(1747936800000), uint64(1747983420000), "unspecified", false, "big-data-node-1", "system.memory.usage", uint64(1747947390000), uint64(1747983420000), 0},
+			cte:      "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(30)) AS ts, `host.name`, avg(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'host.name') AS `host.name` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY fingerprint, `host.name`) 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, `host.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `host.name`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `host.name`)",
 		},
 		{
-			name:        "test_histogram_percentile2",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "histogram_percentile2",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -202,23 +163,69 @@ func TestStatementBuilder(t *testing.T) {
 						SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
 					},
 				},
-				Limit: 10,
 				GroupBy: []qbtypes.GroupByKey{
-					{
-						TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{
-							Name: "service.name",
-						},
-					},
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
 				},
 			},
-			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, `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(30)) AS ts, `service.name`, `le`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `service.name`, `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, `service.name`, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`, `le`) SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY `service.name`, ts",
-				Args:  []any{"http_server_duration_bucket", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "http_server_duration_bucket", uint64(1747947360000), uint64(1747983420000), 0},
-			},
-			expectedErr: nil,
+			orderKey: "service.name",
+			args:     []any{"http_server_duration_bucket", uint64(1747936800000), uint64(1747983420000), "cumulative", false, "http_server_duration_bucket", uint64(1747947360000), uint64(1747983420000), 0},
+			cte:      "WITH __temporal_aggregation_cte AS (SELECT ts, `service.name`, `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(30)) AS ts, `service.name`, `le`, max(value) AS per_series_value FROM signoz_metrics.distributed_samples_v4 AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'service.name') AS `service.name`, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_6hrs WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `service.name`, `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, `service.name`, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `service.name`, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`, `le`)",
 		},
 	}
 
+	type variant struct {
+		name     string
+		limit    int
+		hasOrder bool
+	}
+
+	variants := []variant{
+		{"with_limits", 10, false},
+		{"without_limits", 0, false},
+		{"with_order_by", 0, true},
+		{"with_order_by_and_limits", 10, true},
+	}
+
+	// expectedFinalSelects maps "base/variant" to the final SELECT portion after the CTE.
+	// The full expected query is: base.cte + expectedFinalSelects[name]
+	expectedFinalSelects := map[string]string{
+		// cumulative_rate_sum
+		"cumulative_rate_sum/with_limits":              " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) LIMIT 10) ORDER BY `service.name`, ts ASC",
+		"cumulative_rate_sum/without_limits":           " SELECT * FROM __spatial_aggregation_cte ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"cumulative_rate_sum/with_order_by":            " SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name` asc, ts ASC",
+		"cumulative_rate_sum/with_order_by_and_limits": " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT DISTINCT `service.name` FROM __spatial_aggregation_cte ORDER BY `service.name` asc LIMIT 10) ORDER BY `service.name` asc, ts ASC",
+
+		// cumulative_rate_sum_with_mat_column
+		"cumulative_rate_sum_with_mat_column/with_limits":              " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) LIMIT 10) ORDER BY `service.name`, ts ASC",
+		"cumulative_rate_sum_with_mat_column/without_limits":           " SELECT * FROM __spatial_aggregation_cte ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"cumulative_rate_sum_with_mat_column/with_order_by":            " SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name` asc, ts ASC",
+		"cumulative_rate_sum_with_mat_column/with_order_by_and_limits": " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT DISTINCT `service.name` FROM __spatial_aggregation_cte ORDER BY `service.name` asc LIMIT 10) ORDER BY `service.name` asc, ts ASC",
+
+		// delta_rate_sum
+		"delta_rate_sum/with_limits":              " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) LIMIT 10) ORDER BY `service.name`, ts ASC",
+		"delta_rate_sum/without_limits":           " SELECT * FROM __spatial_aggregation_cte ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"delta_rate_sum/with_order_by":            " SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name` asc, ts ASC",
+		"delta_rate_sum/with_order_by_and_limits": " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT DISTINCT `service.name` FROM __spatial_aggregation_cte ORDER BY `service.name` asc LIMIT 10) ORDER BY `service.name` asc, ts ASC",
+
+		// histogram_percentile1
+		"histogram_percentile1/with_limits":              " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) LIMIT 10) GROUP BY `service.name`, ts ORDER BY `service.name`, ts ASC",
+		"histogram_percentile1/without_limits":           " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"histogram_percentile1/with_order_by":            " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY `service.name` asc, ts ASC",
+		"histogram_percentile1/with_order_by_and_limits": " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT DISTINCT `service.name` FROM __spatial_aggregation_cte ORDER BY `service.name` asc LIMIT 10) GROUP BY `service.name`, ts ORDER BY `service.name` asc, ts ASC",
+
+		// gauge_avg_sum
+		"gauge_avg_sum/with_limits":              " SELECT * FROM __spatial_aggregation_cte WHERE (`host.name`) IN (SELECT `host.name` FROM __spatial_aggregation_cte GROUP BY `host.name` ORDER BY avg(value) LIMIT 10) ORDER BY `host.name`, ts ASC",
+		"gauge_avg_sum/without_limits":           " SELECT * FROM __spatial_aggregation_cte ORDER BY avg(value) OVER (PARTITION BY `host.name`) DESC, `host.name`, ts ASC",
+		"gauge_avg_sum/with_order_by":            " SELECT * FROM __spatial_aggregation_cte ORDER BY `host.name` asc, ts ASC",
+		"gauge_avg_sum/with_order_by_and_limits": " SELECT * FROM __spatial_aggregation_cte WHERE (`host.name`) IN (SELECT DISTINCT `host.name` FROM __spatial_aggregation_cte ORDER BY `host.name` asc LIMIT 10) ORDER BY `host.name` asc, ts ASC",
+
+		// histogram_percentile2
+		"histogram_percentile2/with_limits":              " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) LIMIT 10) GROUP BY `service.name`, ts ORDER BY `service.name`, ts ASC",
+		"histogram_percentile2/without_limits":           " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"histogram_percentile2/with_order_by":            " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte GROUP BY `service.name`, ts ORDER BY `service.name` asc, ts ASC",
+		"histogram_percentile2/with_order_by_and_limits": " SELECT ts, `service.name`, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.950) AS value FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT DISTINCT `service.name` FROM __spatial_aggregation_cte ORDER BY `service.name` asc LIMIT 10) GROUP BY `service.name`, ts ORDER BY `service.name` asc, ts ASC",
+	}
+
 	fm := NewFieldMapper()
 	cb := NewConditionBuilder(fm)
 	mockMetadataStore := telemetrytypestest.NewMockMetadataStore()
@@ -227,15 +234,13 @@ func TestStatementBuilder(t *testing.T) {
 		t.Fatalf("failed to load field keys: %v", err)
 	}
 	mockMetadataStore.KeysMap = keys
-	// NOTE: LoadFieldKeysFromJSON doesn't set Materialized field
-	// for keys, so we have to set it manually here for testing
 	if _, ok := mockMetadataStore.KeysMap["materialized.key.name"]; ok {
 		if len(mockMetadataStore.KeysMap["materialized.key.name"]) > 0 {
 			mockMetadataStore.KeysMap["materialized.key.name"][0].Materialized = true
 		}
 	}
 
-	flagger, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
+	fl, err := flagger.New(context.Background(), instrumentationtest.New().ToProviderSettings(), flagger.Config{}, flagger.MustNewRegistry())
 	if err != nil {
 		t.Fatalf("failed to create flagger: %v", err)
 	}
@@ -245,23 +250,30 @@ func TestStatementBuilder(t *testing.T) {
 		mockMetadataStore,
 		fm,
 		cb,
-		flagger,
+		fl,
 	)
 
-	for _, c := range cases {
-		t.Run(c.name, func(t *testing.T) {
+	for _, b := range bases {
+		for _, v := range variants {
+			name := b.name + "/" + v.name
+			t.Run(name, func(t *testing.T) {
+				q := b.query
+				q.Limit = v.limit
+				if v.hasOrder {
+					q.Order = []qbtypes.OrderBy{
+						{
+							Key:       qbtypes.OrderByKey{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: b.orderKey}},
+							Direction: qbtypes.OrderDirectionAsc,
+						},
+					}
+				}
 
-			q, err := statementBuilder.Build(context.Background(), 1747947419000, 1747983448000, c.requestType, c.query, nil)
+				result, err := statementBuilder.Build(context.Background(), 1747947419000, 1747983448000, qbtypes.RequestTypeTimeSeries, q, nil)
 
-			if c.expectedErr != nil {
-				require.Error(t, err)
-				require.Contains(t, err.Error(), c.expectedErr.Error())
-			} else {
 				require.NoError(t, err)
-				require.Equal(t, c.expected.Query, q.Query)
-				require.Equal(t, c.expected.Args, q.Args)
-				require.Equal(t, c.expected.Warnings, q.Warnings)
-			}
-		})
+				require.Equal(t, b.cte+expectedFinalSelects[name], result.Query)
+				require.Equal(t, b.args, result.Args)
+			})
+		}
 	}
 }