Merge branch 'main' into nv/6204

pkg/modules/cloudintegration/cloudintegration.go

@@ -1,65 +0,0 @@
-package cloudintegration
-
-import (
-	"context"
-	"net/http"
-
-	citypes "github.com/SigNoz/signoz/pkg/types/cloudintegrationtypes"
-	"github.com/SigNoz/signoz/pkg/types/dashboardtypes"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-type Module interface {
-	CreateAccount(ctx context.Context, account *citypes.Account) error
-
-	// GetAccount returns cloud integration account
-	GetAccount(ctx context.Context, orgID, accountID valuer.UUID) (*citypes.Account, error)
-
-	// ListAccounts lists accounts where agent is connected
-	ListAccounts(ctx context.Context, orgID valuer.UUID) ([]*citypes.Account, error)
-
-	// UpdateAccount updates the cloud integration account for a specific organization.
-	UpdateAccount(ctx context.Context, account *citypes.Account) error
-
-	// DisconnectAccount soft deletes/removes a cloud integration account.
-	DisconnectAccount(ctx context.Context, orgID, accountID valuer.UUID) error
-
-	// GetConnectionArtifact returns cloud provider specific connection information,
-	// client side handles how this information is shown
-	GetConnectionArtifact(ctx context.Context, account *citypes.Account, req *citypes.ConnectionArtifactRequest) (*citypes.ConnectionArtifact, error)
-
-	// ListServicesMetadata returns the list of services metadata for a cloud provider attached with the integrationID.
-	// This just returns a summary of the service and not the whole service definition
-	ListServicesMetadata(ctx context.Context, orgID valuer.UUID, integrationID *valuer.UUID) ([]*citypes.ServiceMetadata, error)
-
-	// GetService returns service definition details for a serviceID. This returns config and
-	// other details required to show in service details page on web client.
-	GetService(ctx context.Context, orgID valuer.UUID, integrationID *valuer.UUID, serviceID string) (*citypes.Service, error)
-
-	// UpdateService updates cloud integration service
-	UpdateService(ctx context.Context, orgID valuer.UUID, service *citypes.CloudIntegrationService) error
-
-	// AgentCheckIn is called by agent to heartbeat and get latest config in response.
-	AgentCheckIn(ctx context.Context, orgID valuer.UUID, req *citypes.AgentCheckInRequest) (*citypes.AgentCheckInResponse, error)
-
-	// GetDashboardByID returns dashboard JSON for a given dashboard id.
-	// this only returns the dashboard when the service (embedded in dashboard id) is enabled
-	// in the org for any cloud integration account
-	GetDashboardByID(ctx context.Context, orgID valuer.UUID, id string) (*dashboardtypes.Dashboard, error)
-
-	// ListDashboards returns list of dashboards across all connected cloud integration accounts
-	// for enabled services in the org. This list gets added to dashboard list page
-	ListDashboards(ctx context.Context, orgID valuer.UUID) ([]*dashboardtypes.Dashboard, error)
-}
-
-type Handler interface {
-	GetConnectionArtifact(http.ResponseWriter, *http.Request)
-	ListAccounts(http.ResponseWriter, *http.Request)
-	GetAccount(http.ResponseWriter, *http.Request)
-	UpdateAccount(http.ResponseWriter, *http.Request)
-	DisconnectAccount(http.ResponseWriter, *http.Request)
-	ListServicesMetadata(http.ResponseWriter, *http.Request)
-	GetService(http.ResponseWriter, *http.Request)
-	UpdateService(http.ResponseWriter, *http.Request)
-	AgentCheckIn(http.ResponseWriter, *http.Request)
-}

pkg/querier/consume.go

@@ -69,6 +69,7 @@ func readAsTimeSeries(rows driver.Rows, queryWindow *qbtypes.TimeRange, step qbt
 		key string // deterministic join of label values
 	}
 	seriesMap := map[sKey]*qbtypes.TimeSeries{}
+	var keyOrder []sKey // preserves ClickHouse row-arrival order
 
 	stepMs := uint64(step.Duration.Milliseconds())
 
@@ -219,6 +220,7 @@ func readAsTimeSeries(rows driver.Rows, queryWindow *qbtypes.TimeRange, step qbt
 			if !ok {
 				series = &qbtypes.TimeSeries{Labels: lblObjs}
 				seriesMap[key] = series
+				keyOrder = append(keyOrder, key)
 			}
 			series.Values = append(series.Values, &qbtypes.TimeSeriesValue{
 				Timestamp: ts,
@@ -250,8 +252,8 @@ func readAsTimeSeries(rows driver.Rows, queryWindow *qbtypes.TimeRange, step qbt
 			Alias: "__result_" + strconv.Itoa(i),
 		}
 	}
-	for k, s := range seriesMap {
-		buckets[k.agg].Series = append(buckets[k.agg].Series, s)
+	for _, k := range keyOrder {
+		buckets[k.agg].Series = append(buckets[k.agg].Series, seriesMap[k])
 	}
 
 	var nonEmpty []*qbtypes.AggregationBucket

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/query-service/agentConf/db.go

@@ -115,6 +115,7 @@ func (r *Repo) GetLatestVersion(
 func (r *Repo) insertConfig(
 	ctx context.Context, orgId valuer.UUID, userId valuer.UUID, c *opamptypes.AgentConfigVersion, elements []string,
 ) error {
+
 	if c.ElementType.StringValue() == "" {
 		return errors.NewInvalidInputf(CodeElementTypeRequired, "element type is required for creating agent config version")
 	}
@@ -228,25 +229,6 @@ func (r *Repo) updateDeployStatus(ctx context.Context,
 	return nil
 }
 
-// GetDeployStatusByHash returns the DeployStatus for the given config hash
-// (stored with orgId prefix). Returns DeployStatusUnknown when no matching row exists.
-func (r *Repo) GetDeployStatusByHash(ctx context.Context, orgId valuer.UUID, configHash string) (opamptypes.DeployStatus, error) {
-	var version opamptypes.AgentConfigVersion
-	err := r.store.BunDB().NewSelect().
-		Model(&version).
-		ColumnExpr("deploy_status").
-		Where("hash = ?", configHash).
-		Where("org_id = ?", orgId).
-		Scan(ctx)
-	if err != nil {
-		if errors.Is(err, sql.ErrNoRows) {
-			return opamptypes.DeployStatusUnknown, nil
-		}
-		return opamptypes.DeployStatusUnknown, errors.WrapInternalf(err, errors.CodeInternal, "failed to query deploy status by hash")
-	}
-	return version.DeployStatus, nil
-}
-
 func (r *Repo) updateDeployStatusByHash(
 	ctx context.Context, orgId valuer.UUID, confighash string, status string, result string,
 ) error {

pkg/query-service/agentConf/manager.go

@@ -180,12 +180,6 @@ func (m *Manager) ReportConfigDeploymentStatus(
 	}
 }
 
-// Implements model.AgentConfigProvider
-func (m *Manager) GetDeployStatusByHash(ctx context.Context, orgId valuer.UUID, configHash string) (opamptypes.DeployStatus, error) {
-	return m.Repo.GetDeployStatusByHash(ctx, orgId, configHash)
-}
-
-
 func GetLatestVersion(
 	ctx context.Context, orgId valuer.UUID, elementType opamptypes.ElementType,
 ) (*opamptypes.AgentConfigVersion, error) {

pkg/query-service/app/logparsingpipeline/controller.go

@@ -131,32 +131,38 @@ func (ic *LogParsingPipelineController) ValidatePipelines(ctx context.Context,
 	return err
 }
 
-func (ic *LogParsingPipelineController) getNormalizePipeline() pipelinetypes.GettablePipeline {
-	return pipelinetypes.GettablePipeline{
-		StoreablePipeline: pipelinetypes.StoreablePipeline{
-			Name:    "Default Pipeline - PreProcessing Body",
-			Alias:   "NormalizeBodyDefault",
-			Enabled: true,
-		},
-		Filter: &v3.FilterSet{
-			Items: []v3.FilterItem{
-				{
-					Key: v3.AttributeKey{
-						Key: "body",
+func (ic *LogParsingPipelineController) getDefaultPipelines() ([]pipelinetypes.GettablePipeline, error) {
+	defaultPipelines := []pipelinetypes.GettablePipeline{}
+	if querybuilder.BodyJSONQueryEnabled {
+		preprocessingPipeline := pipelinetypes.GettablePipeline{
+			StoreablePipeline: pipelinetypes.StoreablePipeline{
+				Name:    "Default Pipeline - PreProcessing Body",
+				Alias:   "NormalizeBodyDefault",
+				Enabled: true,
+			},
+			Filter: &v3.FilterSet{
+				Items: []v3.FilterItem{
+					{
+						Key: v3.AttributeKey{
+							Key: "body",
+						},
+						Operator: v3.FilterOperatorExists,
 					},
-					Operator: v3.FilterOperatorExists,
 				},
 			},
-		},
-		Config: []pipelinetypes.PipelineOperator{
-			{
-				ID:      uuid.NewString(),
-				Type:    "normalize",
-				Enabled: true,
-				If:      "body != nil",
+			Config: []pipelinetypes.PipelineOperator{
+				{
+					ID:      uuid.NewString(),
+					Type:    "normalize",
+					Enabled: true,
+					If:      "body != nil",
+				},
 			},
-		},
+		}
+
+		defaultPipelines = append(defaultPipelines, preprocessingPipeline)
 	}
+	return defaultPipelines, nil
 }
 
 // Returns effective list of pipelines including user created
@@ -289,10 +295,12 @@ func (pc *LogParsingPipelineController) RecommendAgentConfig(
 		return nil, "", err
 	}
 
-	if querybuilder.BodyJSONQueryEnabled {
-		// add default normalize pipeline at the beginning
-		pipelinesResp.Pipelines = append([]pipelinetypes.GettablePipeline{pc.getNormalizePipeline()}, pipelinesResp.Pipelines...)
+	// recommend default pipelines along with user created pipelines
+	defaultPipelines, err := pc.getDefaultPipelines()
+	if err != nil {
+		return nil, "", model.InternalError(fmt.Errorf("failed to get default pipelines: %w", err))
 	}
+	pipelinesResp.Pipelines = append(pipelinesResp.Pipelines, defaultPipelines...)
 
 	updatedConf, err := GenerateCollectorConfigWithPipelines(currentConfYaml, pipelinesResp.Pipelines)
 	if err != nil {

pkg/query-service/app/opamp/config_provider.go

@@ -1,8 +1,6 @@
 package opamp
 
-import (
-	"github.com/SigNoz/signoz/pkg/query-service/app/opamp/model"
-)
+import "github.com/SigNoz/signoz/pkg/query-service/app/opamp/model"
 
 // Interface for a source of otel collector config recommendations.
 type AgentConfigProvider interface {

pkg/query-service/app/opamp/mocks.go

@@ -5,7 +5,6 @@ import (
 	"log"
 	"net"
 
-	"github.com/SigNoz/signoz/pkg/types/opamptypes"
 	"github.com/SigNoz/signoz/pkg/valuer"
 	"github.com/google/uuid"
 	"github.com/knadh/koanf"
@@ -128,11 +127,6 @@ func (ta *MockAgentConfigProvider) HasReportedDeploymentStatus(orgID valuer.UUID
 	return exists
 }
 
-// AgentConfigProvider interface
-func (ta *MockAgentConfigProvider) GetDeployStatusByHash(_ context.Context, _ valuer.UUID, _ string) (opamptypes.DeployStatus, error) {
-	return opamptypes.DeployStatusUnknown, nil
-}
-
 // AgentConfigProvider interface
 func (ta *MockAgentConfigProvider) SubscribeToConfigUpdates(callback func()) func() {
 	subscriberId := uuid.NewString()

pkg/query-service/app/opamp/model/agent.go

@@ -111,99 +111,90 @@ func ExtractLbFlag(agentDescr *protobufs.AgentDescription) bool {
 	return false
 }
 
-// agentDescriptionChanged returns true when the agent sends updated properties
-// (e.g. capability flag, version) mid-connection, signalling the server to
-// recompute and push a new RemoteConfig.
-//
-// On reconnect this always returns false: handleFirstStatus pre-copies
-// AgentDescription into agent.Status so no diff is detected, avoiding a
-// redundant config recompute.
-func (agent *Agent) agentDescriptionChanged(newStatus *protobufs.AgentToServer) bool {
-	// nil AgentDescription means no change per OpAMP protocol.
-	if newStatus.AgentDescription == nil {
-		return false
+func (agent *Agent) updateAgentDescription(newStatus *protobufs.AgentToServer) (agentDescrChanged bool) {
+	prevStatus := agent.Status
+
+	if agent.Status == nil {
+		// First time this Agent reports a status, remember it.
+		agent.Status = newStatus
+		agentDescrChanged = true
+	} else {
+		// Not a new Agent. Update the Status.
+		agent.Status.SequenceNum = newStatus.SequenceNum
+
+		// Check what's changed in the AgentDescription.
+		if newStatus.AgentDescription != nil {
+			// If the AgentDescription field is set it means the Agent tells us
+			// something is changed in the field since the last status report
+			// (or this is the first report).
+			// Make full comparison of previous and new descriptions to see if it
+			// really is different.
+			if prevStatus != nil && proto.Equal(prevStatus.AgentDescription, newStatus.AgentDescription) {
+				// Agent description didn't change.
+				agentDescrChanged = false
+			} else {
+				// Yes, the description is different, update it.
+				agent.Status.AgentDescription = newStatus.AgentDescription
+				agentDescrChanged = true
+			}
+		} else {
+			// AgentDescription field is not set, which means description didn't change.
+			agentDescrChanged = false
+		}
+
+		// Update remote config status if it is included and is different from what we have.
+		if newStatus.RemoteConfigStatus != nil &&
+			!proto.Equal(agent.Status.RemoteConfigStatus, newStatus.RemoteConfigStatus) {
+			agent.Status.RemoteConfigStatus = newStatus.RemoteConfigStatus
+
+			// todo: need to address multiple agent scenario here
+			// for now, the first response will be sent back to the UI
+			if agent.Status.RemoteConfigStatus.Status == protobufs.RemoteConfigStatuses_RemoteConfigStatuses_APPLIED {
+				onConfigSuccess(agent.OrgID, agent.AgentID, string(agent.Status.RemoteConfigStatus.LastRemoteConfigHash))
+			}
+
+			if agent.Status.RemoteConfigStatus.Status == protobufs.RemoteConfigStatuses_RemoteConfigStatuses_FAILED {
+				onConfigFailure(agent.OrgID, agent.AgentID, string(agent.Status.RemoteConfigStatus.LastRemoteConfigHash), agent.Status.RemoteConfigStatus.ErrorMessage)
+			}
+		}
 	}
-	if proto.Equal(agent.Status.AgentDescription, newStatus.AgentDescription) {
-		return false
+
+	if agentDescrChanged {
+		agent.CanLB = ExtractLbFlag(newStatus.AgentDescription)
+	}
+
+	return agentDescrChanged
+}
+
+func (agent *Agent) updateHealth(newStatus *protobufs.AgentToServer) {
+	if newStatus.Health == nil {
+		return
+	}
+
+	agent.Status.Health = newStatus.Health
+
+	if agent.Status != nil && agent.Status.Health != nil && agent.Status.Health.Healthy {
+		agent.TimeAuditable.UpdatedAt = time.Unix(0, int64(agent.Status.Health.StartTimeUnixNano)).UTC()
 	}
-	agent.CanLB = ExtractLbFlag(newStatus.AgentDescription)
-	return true
 }
 
-// updateRemoteConfigStatus updates the stored RemoteConfigStatus and notifies
-// subscribers if the status has changed relative to what we have stored.
 func (agent *Agent) updateRemoteConfigStatus(newStatus *protobufs.AgentToServer) {
-	if newStatus.RemoteConfigStatus == nil ||
-		proto.Equal(agent.Status.RemoteConfigStatus, newStatus.RemoteConfigStatus) {
-		return
-	}
-
-	// todo: need to address multiple agent scenario here
-	// for now, the first response will be sent back to the UI
-	hash := string(newStatus.RemoteConfigStatus.LastRemoteConfigHash)
-	switch newStatus.RemoteConfigStatus.Status {
-	case protobufs.RemoteConfigStatuses_RemoteConfigStatuses_APPLIED:
-		onConfigSuccess(agent.OrgID, agent.AgentID, hash)
-	case protobufs.RemoteConfigStatuses_RemoteConfigStatuses_FAILED:
-		onConfigFailure(agent.OrgID, agent.AgentID, hash, newStatus.RemoteConfigStatus.ErrorMessage)
+	// Update remote config status if it is included and is different from what we have.
+	if newStatus.RemoteConfigStatus != nil {
+		agent.Status.RemoteConfigStatus = newStatus.RemoteConfigStatus
 	}
 }
 
-// handleFirstStatus initializes agent.Status on the first message received from
-// this agent instance. It is a no-op for all subsequent messages.
-func (agent *Agent) handleFirstStatus(newStatus *protobufs.AgentToServer, configProvider AgentConfigProvider) {
-	if agent.Status != nil {
-		return
+func (agent *Agent) updateStatusField(newStatus *protobufs.AgentToServer) (agentDescrChanged bool) {
+	if agent.Status == nil {
+		// First time this Agent reports a status, remember it.
+		agent.Status = newStatus
+		agentDescrChanged = true
 	}
 
-	// Initialize with a clean slate.
-	agent.Status = &protobufs.AgentToServer{
-		RemoteConfigStatus: &protobufs.RemoteConfigStatus{
-			Status: protobufs.RemoteConfigStatuses_RemoteConfigStatuses_UNSET,
-		},
-	}
-
-	if newStatus.RemoteConfigStatus == nil ||
-		newStatus.RemoteConfigStatus.Status == protobufs.RemoteConfigStatuses_RemoteConfigStatuses_UNSET {
-		// Agent just started fresh — no prior deployment to reconcile with the DB.
-		return
-	}
-
-	// Since the server's connection is restarted;
-	// copy the agent description; so no change is detected by agentDescriptionChanged
-	agent.Status.AgentDescription = newStatus.AgentDescription
-
-	// Server reconnected while the agent was already running.
-	// Reconcile deployment status with DB; DB is the source of truth.
-	// If DB says in_progress but agent now reports APPLIED/FAILED,
-	// updateRemoteConfigStatus will detect the transition and notify subscribers.
-	rawHash := string(newStatus.RemoteConfigStatus.LastRemoteConfigHash)
-	deployStatus, err := configProvider.GetDeployStatusByHash(context.Background(), agent.OrgID, agent.OrgID.String()+rawHash)
-	if err != nil {
-		return
-	}
-
-	agent.Status.RemoteConfigStatus.Status = opamptypes.DeployStatusToProtoStatus[deployStatus]
-
-	// If the deployment is still in-flight, rehydrate the subscriber so that
-	// updateRemoteConfigStatus can fire onConfigSuccess/onConfigFailure when
-	// the agent next reports a terminal status.
-	if deployStatus != opamptypes.Deployed && deployStatus != opamptypes.DeployFailed {
-		ListenToConfigUpdate(agent.OrgID, agent.AgentID, rawHash, configProvider.ReportConfigDeploymentStatus)
-	}
-}
-
-func (agent *Agent) updateStatusField(newStatus *protobufs.AgentToServer, configProvider AgentConfigProvider) bool {
-	agent.handleFirstStatus(newStatus, configProvider)
-	agentDescrChanged := agent.agentDescriptionChanged(newStatus)
-	// record healthy timestamp
-	if newStatus.Health != nil && newStatus.Health.Healthy {
-		agent.TimeAuditable.UpdatedAt = time.Unix(0, int64(newStatus.Health.StartTimeUnixNano)).UTC()
-	}
-	// notify subscribers first; this will update the status in the DB
+	agentDescrChanged = agent.updateAgentDescription(newStatus) || agentDescrChanged
 	agent.updateRemoteConfigStatus(newStatus)
-	// update local reference in last.
-	agent.Status = newStatus
+	agent.updateHealth(newStatus)
 	return agentDescrChanged
 }
 
@@ -246,7 +237,7 @@ func (agent *Agent) processStatusUpdate(
 	// current status is not up-to-date.
 	lostPreviousUpdate := (agent.Status == nil) || (agent.Status != nil && agent.Status.SequenceNum+1 != newStatus.SequenceNum)
 
-	agentDescrChanged := agent.updateStatusField(newStatus, configProvider)
+	agentDescrChanged := agent.updateStatusField(newStatus)
 
 	// Check if any fields were omitted in the status report.
 	effectiveConfigOmitted := newStatus.EffectiveConfig == nil &&

pkg/query-service/app/opamp/model/config.go

@@ -1,11 +1,6 @@
 package model
 
-import (
-	"context"
-
-	"github.com/SigNoz/signoz/pkg/types/opamptypes"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
+import "github.com/SigNoz/signoz/pkg/valuer"
 
 // Interface for source of otel collector config recommendations.
 type AgentConfigProvider interface {
@@ -25,10 +20,4 @@ type AgentConfigProvider interface {
 		configId string,
 		err error,
 	)
-
-	// GetDeployStatusByHash returns the DeployStatus for the given config hash
-	// (with orgId prefix as stored in the DB). Returns DeployStatusUnknown when
-	// no matching row exists. Used by the agent's first-connect handler to
-	// determine whether the reported RemoteConfigStatus resolves a pending deployment.
-	GetDeployStatusByHash(ctx context.Context, orgId valuer.UUID, configHash string) (opamptypes.DeployStatus, error)
 }

pkg/query-service/app/opamp/model/coordinator.go

@@ -66,7 +66,6 @@ func ListenToConfigUpdate(orgId valuer.UUID, agentId string, hash string, ss OnC
 	defer coordinator.mutex.Unlock()
 
 	key := getSubscriberKey(orgId, hash)
-
 	if subs, ok := coordinator.subscribers[key]; ok {
 		subs = append(subs, ss)
 		coordinator.subscribers[key] = subs

pkg/telemetrymeter/stmt_builder_test.go

@@ -51,7 +51,7 @@ func TestStatementBuilder(t *testing.T) {
 				},
 			},
 			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(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, max(value) AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) 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",
+				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(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, max(value) AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) 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 WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
 				Args:  []any{"signoz_calls_total", uint64(1747785600000), uint64(1747983420000), "cartservice", "cumulative", 0},
 			},
 			expectedErr: nil,
@@ -84,7 +84,7 @@ func TestStatementBuilder(t *testing.T) {
 				},
 			},
 			expected: qbtypes.Statement{
-				Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, sum(value)/86400 AS value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name`, ts",
+				Query: "WITH __spatial_aggregation_cte AS (SELECT toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, sum(value)/86400 AS value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
 				Args:  []any{"signoz_calls_total", uint64(1747872000000), uint64(1747983420000), "cartservice", "delta"},
 			},
 			expectedErr: nil,
@@ -117,7 +117,7 @@ func TestStatementBuilder(t *testing.T) {
 				},
 			},
 			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, sum(value)/86400 AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, ts, `service.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `service.name`, avg(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",
+				Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'service.name') AS `service.name`, sum(value)/86400 AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'service.name') = ? AND LOWER(temporality) LIKE LOWER(?) GROUP BY fingerprint, ts, `service.name` ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, `service.name`, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `service.name`) SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY avg(value) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
 				Args:  []any{"signoz_calls_total", uint64(1747872000000), uint64(1747983420000), "cartservice", "delta", 0},
 			},
 			expectedErr: nil,
@@ -150,7 +150,7 @@ func TestStatementBuilder(t *testing.T) {
 				},
 			},
 			expected: qbtypes.Statement{
-				Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'host.name') AS `host.name`, avg(value) AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'host.name') = ? AND LOWER(temporality) LIKE LOWER(?) 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",
+				Query: "WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(86400)) AS ts, JSONExtractString(labels, 'host.name') AS `host.name`, avg(value) AS per_series_value FROM signoz_meter.distributed_samples AS points WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? AND JSONExtractString(labels, 'host.name') = ? AND LOWER(temporality) LIKE LOWER(?) 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 WHERE (`host.name`) IN (SELECT `host.name` FROM __spatial_aggregation_cte GROUP BY `host.name` ORDER BY avg(value) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `host.name`) DESC, `host.name`, ts ASC",
 				Args:  []any{"system.memory.usage", uint64(1747872000000), uint64(1747983420000), "big-data-node-1", "unspecified", 0},
 			},
 			expectedErr: nil,

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"
@@ -546,6 +547,16 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 ) (*qbtypes.Statement, error) {
 	metricType := query.Aggregations[0].Type
 	spaceAgg := query.Aggregations[0].SpaceAggregation
+	finalCTE := "__spatial_aggregation_cte"
+	if metricType == metrictypes.HistogramType {
+		histogramCTE, histogramCTEArgs, err := b.buildHistogramCTE(query)
+		if err != nil {
+			return nil, err
+		}
+		cteFragments = append(cteFragments, histogramCTE)
+		cteArgs = append(cteArgs, histogramCTEArgs)
+		finalCTE = "__histogram_cte"
+	}
 
 	combined := querybuilder.CombineCTEs(cteFragments)
 
@@ -555,60 +566,104 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 	}
 
 	sb := sqlbuilder.NewSelectBuilder()
+	sb.Select("*")
+	sb.From(finalCTE)
+	if query.Having != nil && query.Having.Expression != "" {
+		rewriter := querybuilder.NewHavingExpressionRewriter()
+		rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
+		sb.Where(rewrittenExpr)
+	}
 
-	if metricType == metrictypes.HistogramType && spaceAgg.IsPercentile() {
-		quantile := query.Aggregations[0].SpaceAggregation.Percentile()
-		sb.Select("ts")
-		for _, g := range query.GroupBy {
-			sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+	groupByKeys := querybuilder.GroupByKeys(query.GroupBy)
+	hasOrder := len(query.Order) > 0
+	hasLimit := query.Limit > 0
+	hasGroupBy := len(groupByKeys) > 0
+
+	isMetricAggOrderByKey := func(key string, config qbtypes.MetricAggregation) bool {
+		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)
+		return key == spaceAggOrderBy || key == timeAggOrderBy || key == timeSpaceAggOrderBy
+	}
+
+	if !hasGroupBy {
+		// do nothing, limits and orders don't mean anything
+	} else if hasOrder && hasLimit {
+		labelSelectorSubQueryBuilder := sqlbuilder.NewSelectBuilder()
+		labelSelectorSubQueryBuilder.Select(groupByKeys...)
+		labelSelectorSubQueryBuilder.From(finalCTE)
+		labelSelectorOrderClauses := []string{}
+		orderedKeys := map[string]struct{}{} // this will be used to add the remaining keys as tie breakers in the end
+		for _, o := range query.Order {
+			key := o.Key.Name
+			var clause string
+			if isMetricAggOrderByKey(key, query.Aggregations[0]) {
+				clause = fmt.Sprintf("avg(value) %s", o.Direction.StringValue())
+			} else {
+				clause = fmt.Sprintf("`%s` %s", key, o.Direction.StringValue())
+				orderedKeys[fmt.Sprintf("`%s`", key)] = struct{}{}
+			}
+			labelSelectorOrderClauses = append(labelSelectorOrderClauses, clause)
 		}
-		sb.SelectMore(fmt.Sprintf(
-			"histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), %.3f) AS value",
-			quantile,
-		))
-		sb.From("__spatial_aggregation_cte")
-		sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
-		sb.GroupBy("ts")
-		if query.Having != nil && query.Having.Expression != "" {
-			rewriter := querybuilder.NewHavingExpressionRewriter()
-			rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
-			sb.Having(rewrittenExpr)
+		for _, gk := range groupByKeys { // keys that haven't been added via order by keys will be added at the end as tie breakers
+			if _, ok := orderedKeys[gk]; !ok {
+				labelSelectorOrderClauses = append(labelSelectorOrderClauses, fmt.Sprintf("%s ASC", gk))
+			}
 		}
-	} else if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam != nil {
-		sb.Select("ts")
+		labelSelectorSubQueryBuilder.GroupBy(groupByKeys...)
+		labelSelectorSubQueryBuilder.OrderBy(labelSelectorOrderClauses...)
+		labelSelectorSubQuery, _ := labelSelectorSubQueryBuilder.BuildWithFlavor(sqlbuilder.ClickHouse)
+		labelSelectorSubQuery = fmt.Sprintf("%s LIMIT %d", labelSelectorSubQuery, query.Limit)
 
-		for _, g := range query.GroupBy {
-			sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(groupByKeys, ", "), labelSelectorSubQuery))
+		for _, o := range query.Order {
+			key := o.Key.Name
+			var clause string
+			if isMetricAggOrderByKey(key, query.Aggregations[0]) {
+				clause = fmt.Sprintf("avg(value) OVER (PARTITION BY %s) %s", strings.Join(groupByKeys, ", "), o.Direction.StringValue())
+			} else {
+				clause = fmt.Sprintf("`%s` %s", key, o.Direction.StringValue())
+			}
+			sb.OrderBy(clause)
 		}
-
-		aggQuery, err := AggregationQueryForHistogramCountWithParams(query.Aggregations[0].ComparisonSpaceAggregationParam)
-		if err != nil {
-			return nil, err
+	} else if hasOrder {
+		// order by without limit: apply order by clauses directly
+		for _, o := range query.Order {
+			key := o.Key.Name
+			if isMetricAggOrderByKey(key, query.Aggregations[0]) {
+				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()))
 		}
-		sb.SelectMore(aggQuery)
+	} else if hasLimit {
+		labelSelectorSubQueryBuilder := sqlbuilder.NewSelectBuilder()
+		labelSelectorSubQueryBuilder.Select(groupByKeys...)
+		labelSelectorSubQueryBuilder.From(finalCTE)
+		labelSelectorSubQueryBuilder.GroupBy(groupByKeys...)
+		labelSelectorSubQueryBuilder.OrderBy("avg(value) DESC")
+		labelSelectorSubQuery, _ := labelSelectorSubQueryBuilder.BuildWithFlavor(sqlbuilder.ClickHouse)
+		labelSelectorSubQuery = fmt.Sprintf("%s LIMIT %d", labelSelectorSubQuery, query.Limit)
 
-		sb.From("__spatial_aggregation_cte")
-
-		sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
-		sb.GroupBy("ts")
-
-		if query.Having != nil && query.Having.Expression != "" {
-			rewriter := querybuilder.NewHavingExpressionRewriter()
-			rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
-			sb.Having(rewrittenExpr)
-		}
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(groupByKeys, ", "), labelSelectorSubQuery))
+		sb.OrderBy(fmt.Sprintf("avg(value) OVER (PARTITION BY %s) DESC", strings.Join(groupByKeys, ", ")))
 	} else {
-		// for count aggregation on histograms with no params, the exact result of spatial aggregation can be sent forward
-		sb.Select("*")
-		sb.From("__spatial_aggregation_cte")
-		if query.Having != nil && query.Having.Expression != "" {
-			rewriter := querybuilder.NewHavingExpressionRewriter()
-			rewrittenExpr := rewriter.RewriteForMetrics(query.Having.Expression, query.Aggregations)
-			sb.Where(rewrittenExpr)
+		// 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(querybuilder.GroupByKeys(query.GroupBy)...)
-	sb.OrderBy("ts")
+
+	sb.OrderBy("ts ASC")
 	if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam == nil {
 		sb.OrderBy("toFloat64(le)")
 	}
@@ -616,3 +671,45 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 	q, a := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
 	return &qbtypes.Statement{Query: combined + q, Args: append(args, a...)}, nil
 }
+
+func (b *MetricQueryStatementBuilder) buildHistogramCTE(
+	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+) (string, []any, error) {
+	spaceAgg := query.Aggregations[0].SpaceAggregation
+	histogramCTEQueryBuilder := sqlbuilder.NewSelectBuilder()
+	if spaceAgg.IsPercentile() {
+		histogramCTEQueryBuilder.Select("ts")
+		for _, g := range query.GroupBy {
+			histogramCTEQueryBuilder.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+		}
+		quantile := spaceAgg.Percentile()
+		histogramCTEQueryBuilder.SelectMore(fmt.Sprintf(
+			"histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), %.3f) AS value",
+			quantile,
+		))
+		histogramCTEQueryBuilder.From("__spatial_aggregation_cte")
+		histogramCTEQueryBuilder.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+		histogramCTEQueryBuilder.GroupBy("ts")
+	} else if spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam != nil {
+		histogramCTEQueryBuilder.Select("ts")
+		for _, g := range query.GroupBy {
+			histogramCTEQueryBuilder.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+		}
+		aggQuery, err := AggregationQueryForHistogramCountWithParams(query.Aggregations[0].ComparisonSpaceAggregationParam)
+		if err != nil {
+			return "", nil, err
+		}
+		histogramCTEQueryBuilder.SelectMore(aggQuery)
+		histogramCTEQueryBuilder.From("__spatial_aggregation_cte")
+		histogramCTEQueryBuilder.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+		histogramCTEQueryBuilder.GroupBy("ts")
+	} else {
+		// for count aggregation on histograms with no params, the exact result of spatial aggregation can be sent forward
+		histogramCTEQueryBuilder.Select("*")
+		histogramCTEQueryBuilder.From("__spatial_aggregation_cte")
+	}
+	histogramQueryCTE, histogramQueryCTEArgs := histogramCTEQueryBuilder.BuildWithFlavor(sqlbuilder.ClickHouse)
+	histogramCTE := fmt.Sprintf("__histogram_cte AS (%s)", histogramQueryCTE)
+
+	return histogramCTE, histogramQueryCTEArgs, nil
+}

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 +116,38 @@ 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`), __histogram_cte AS (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)",
 		},
 		{
-			name:        "test_gauge_avg_sum",
-			requestType: qbtypes.RequestTypeTimeSeries,
+			name: "histogram_percentile2",
+			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
+				Signal:       telemetrytypes.SignalMetrics,
+				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
+				Aggregations: []qbtypes.MetricAggregation{
+					{
+						MetricName:       "http_server_duration_bucket",
+						Type:             metrictypes.HistogramType,
+						Temporality:      metrictypes.Cumulative,
+						TimeAggregation:  metrictypes.TimeAggregationRate,
+						SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
+					},
+				},
+				GroupBy: []qbtypes.GroupByKey{
+					{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "service.name"}},
+				},
+			},
+			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`), __histogram_cte AS (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)",
+		},
+		{
+			name: "gauge_avg_sum",
 			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
 				Signal:       telemetrytypes.SignalMetrics,
 				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
@@ -172,53 +163,83 @@ 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,
-		},
-		{
-			name:        "test_histogram_percentile2",
-			requestType: qbtypes.RequestTypeTimeSeries,
-			query: qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation]{
-				Signal:       telemetrytypes.SignalMetrics,
-				StepInterval: qbtypes.Step{Duration: 30 * time.Second},
-				Aggregations: []qbtypes.MetricAggregation{
-					{
-						MetricName:       "http_server_duration_bucket",
-						Type:             metrictypes.HistogramType,
-						Temporality:      metrictypes.Cumulative,
-						TimeAggregation:  metrictypes.TimeAggregationRate,
-						SpaceAggregation: metrictypes.SpaceAggregationPercentile95,
-					},
-				},
-				Limit: 10,
-				GroupBy: []qbtypes.GroupByKey{
-					{
-						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: "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`)",
 		},
 	}
 
+	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},
+	}
+
+	sumMetricsFinalSelects := map[string]string{
+		"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) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"without_limits":           " SELECT * FROM __spatial_aggregation_cte ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"with_order_by":            " SELECT * FROM __spatial_aggregation_cte ORDER BY `service.name` asc, ts ASC",
+		"with_order_by_and_limits": " SELECT * FROM __spatial_aggregation_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __spatial_aggregation_cte GROUP BY `service.name` ORDER BY `service.name` asc LIMIT 10) ORDER BY `service.name` asc, ts ASC",
+	}
+
+	histogramMetricsFinalSelects := map[string]string{
+		"with_limits":              " SELECT * FROM __histogram_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __histogram_cte GROUP BY `service.name` ORDER BY avg(value) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"without_limits":           " SELECT * FROM __histogram_cte ORDER BY avg(value) OVER (PARTITION BY `service.name`) DESC, `service.name`, ts ASC",
+		"with_order_by":            " SELECT * FROM __histogram_cte ORDER BY `service.name` asc, ts ASC",
+		"with_order_by_and_limits": " SELECT * FROM __histogram_cte WHERE (`service.name`) IN (SELECT `service.name` FROM __histogram_cte GROUP BY `service.name` ORDER BY `service.name` asc LIMIT 10) ORDER BY `service.name` asc, ts ASC",
+	}
+
+	// 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":              sumMetricsFinalSelects["with_limits"],
+		"cumulative_rate_sum/without_limits":           sumMetricsFinalSelects["without_limits"],
+		"cumulative_rate_sum/with_order_by":            sumMetricsFinalSelects["with_order_by"],
+		"cumulative_rate_sum/with_order_by_and_limits": sumMetricsFinalSelects["with_order_by_and_limits"],
+
+		// cumulative_rate_sum_with_mat_column
+		"cumulative_rate_sum_with_mat_column/with_limits":              sumMetricsFinalSelects["with_limits"],
+		"cumulative_rate_sum_with_mat_column/without_limits":           sumMetricsFinalSelects["without_limits"],
+		"cumulative_rate_sum_with_mat_column/with_order_by":            sumMetricsFinalSelects["with_order_by"],
+		"cumulative_rate_sum_with_mat_column/with_order_by_and_limits": sumMetricsFinalSelects["with_order_by_and_limits"],
+
+		// delta_rate_sum
+		"delta_rate_sum/with_limits":              sumMetricsFinalSelects["with_limits"],
+		"delta_rate_sum/without_limits":           sumMetricsFinalSelects["without_limits"],
+		"delta_rate_sum/with_order_by":            sumMetricsFinalSelects["with_order_by"],
+		"delta_rate_sum/with_order_by_and_limits": sumMetricsFinalSelects["with_order_by_and_limits"],
+
+		// histogram_percentile1
+		"histogram_percentile1/with_limits":              histogramMetricsFinalSelects["with_limits"],
+		"histogram_percentile1/without_limits":           histogramMetricsFinalSelects["without_limits"],
+		"histogram_percentile1/with_order_by":            histogramMetricsFinalSelects["with_order_by"],
+		"histogram_percentile1/with_order_by_and_limits": histogramMetricsFinalSelects["with_order_by_and_limits"],
+
+		// histogram_percentile2
+		"histogram_percentile2/with_limits":              histogramMetricsFinalSelects["with_limits"],
+		"histogram_percentile2/without_limits":           histogramMetricsFinalSelects["without_limits"],
+		"histogram_percentile2/with_order_by":            histogramMetricsFinalSelects["with_order_by"],
+		"histogram_percentile2/with_order_by_and_limits": histogramMetricsFinalSelects["with_order_by_and_limits"],
+
+		// 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) DESC LIMIT 10) ORDER BY avg(value) OVER (PARTITION BY `host.name`) DESC, `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 `host.name` FROM __spatial_aggregation_cte GROUP BY `host.name` ORDER BY `host.name` asc LIMIT 10) ORDER BY `host.name` asc, ts ASC",
+	}
+
 	fm := NewFieldMapper()
 	cb := NewConditionBuilder(fm)
 	mockMetadataStore := telemetrytypestest.NewMockMetadataStore()
@@ -227,15 +248,13 @@ 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 +264,30 @@ 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)
+			})
+		}
 	}
 }

pkg/types/cloudintegrationtypes/account.go

@@ -1,43 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"time"
-
-	"github.com/SigNoz/signoz/pkg/types"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-type Account struct {
-	types.Identifiable
-	types.TimeAuditable
-	ProviderAccountId *string           `json:"providerAccountID,omitempty"`
-	Provider          CloudProviderType `json:"provider"`
-	RemovedAt         *time.Time        `json:"removedAt,omitempty"`
-	AgentReport       *AgentReport      `json:"agentReport,omitempty"`
-	OrgID             valuer.UUID       `json:"orgID"`
-	Config            *AccountConfig    `json:"config,omitempty"`
-}
-
-// AgentReport represents heartbeats sent by the agent.
-type AgentReport struct {
-	TimestampMillis int64          `json:"timestampMillis"`
-	Data            map[string]any `json:"data"`
-}
-
-type GettableAccounts struct {
-	Accounts []*Account `json:"accounts"`
-}
-
-type GettableAccount = Account
-
-type UpdatableAccount struct {
-	Config *AccountConfig `json:"config"`
-}
-
-type AccountConfig struct {
-	AWS *AWSAccountConfig `json:"aws,omitempty"`
-}
-
-type AWSAccountConfig struct {
-	Regions []string `json:"regions"`
-}

pkg/types/cloudintegrationtypes/cloudintegration.go

@@ -1,80 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"database/sql/driver"
-	"encoding/json"
-	"time"
-
-	"github.com/SigNoz/signoz/pkg/errors"
-	"github.com/uptrace/bun"
-
-	"github.com/SigNoz/signoz/pkg/types"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-var (
-	ErrCodeCloudIntegrationNotFound = errors.MustNewCode("cloud_integration_not_found")
-)
-
-// StorableCloudIntegration represents a cloud integration stored in the database.
-// This is also referred as "Account" in the context of cloud integrations.
-type StorableCloudIntegration struct {
-	bun.BaseModel `bun:"table:cloud_integration"`
-	types.Identifiable
-	types.TimeAuditable
-
-	Provider        CloudProviderType    `bun:"provider,type:text"`
-	Config          string               `bun:"config,type:text"` // Config is provider-specific data in JSON string format
-	AccountID       *string              `bun:"account_id,type:text"`
-	LastAgentReport *StorableAgentReport `bun:"last_agent_report,type:text"`
-	RemovedAt       *time.Time           `bun:"removed_at,type:timestamp,nullzero"`
-	OrgID           valuer.UUID          `bun:"org_id,type:text"`
-}
-
-// StorableAgentReport represents the last heartbeat and arbitrary data sent by the agent
-// as of now there is no use case for Data field, but keeping it for backwards compatibility with older structure.
-type StorableAgentReport struct {
-	TimestampMillis int64          `json:"timestamp_millis"` // backward compatibility
-	Data            map[string]any `json:"data"`
-}
-
-// StorableCloudIntegrationService is to store service config for a cloud integration, which is a cloud provider specific configuration.
-type StorableCloudIntegrationService struct {
-	bun.BaseModel `bun:"table:cloud_integration_service,alias:cis"`
-	types.Identifiable
-	types.TimeAuditable
-
-	Type               ServiceID   `bun:"type,type:text,notnull"` // Keeping Type field name as is, but it is a service id
-	Config             string      `bun:"config,type:text"`       // Config is cloud provider's service specific data in JSON string format
-	CloudIntegrationID valuer.UUID `bun:"cloud_integration_id,type:text"`
-}
-
-// Scan scans value from DB.
-func (r *StorableAgentReport) Scan(src any) error {
-	var data []byte
-	switch v := src.(type) {
-	case []byte:
-		data = v
-	case string:
-		data = []byte(v)
-	default:
-		return errors.NewInternalf(errors.CodeInternal, "tried to scan from %T instead of string or bytes", src)
-	}
-	return json.Unmarshal(data, r)
-}
-
-// Value creates value to be stored in DB.
-func (r *StorableAgentReport) Value() (driver.Value, error) {
-	if r == nil {
-		return nil, errors.NewInternalf(errors.CodeInternal, "agent report is nil")
-	}
-
-	serialized, err := json.Marshal(r)
-	if err != nil {
-		return nil, errors.WrapInternalf(
-			err, errors.CodeInternal, "couldn't serialize agent report to JSON",
-		)
-	}
-	// Return as string instead of []byte to ensure PostgreSQL stores as text, not bytes
-	return string(serialized), nil
-}

pkg/types/cloudintegrationtypes/cloudprovider.go

@@ -1,41 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"github.com/SigNoz/signoz/pkg/errors"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-// CloudProviderType type alias.
-type CloudProviderType struct{ valuer.String }
-
-var (
-	// cloud providers.
-	CloudProviderTypeAWS   = CloudProviderType{valuer.NewString("aws")}
-	CloudProviderTypeAzure = CloudProviderType{valuer.NewString("azure")}
-
-	// errors.
-	ErrCodeCloudProviderInvalidInput = errors.MustNewCode("invalid_cloud_provider")
-
-	AWSIntegrationUserEmail   = valuer.MustNewEmail("aws-integration@signoz.io")
-	AzureIntegrationUserEmail = valuer.MustNewEmail("azure-integration@signoz.io")
-)
-
-// CloudIntegrationUserEmails is the list of valid emails for Cloud One Click integrations.
-// This is used for validation and restrictions in different contexts, across codebase.
-var CloudIntegrationUserEmails = []valuer.Email{
-	AWSIntegrationUserEmail,
-	AzureIntegrationUserEmail,
-}
-
-// NewCloudProvider returns a new CloudProviderType from a string.
-// It validates the input and returns an error if the input is not valid cloud provider.
-func NewCloudProvider(provider string) (CloudProviderType, error) {
-	switch provider {
-	case CloudProviderTypeAWS.StringValue():
-		return CloudProviderTypeAWS, nil
-	case CloudProviderTypeAzure.StringValue():
-		return CloudProviderTypeAzure, nil
-	default:
-		return CloudProviderType{}, errors.NewInvalidInputf(ErrCodeCloudProviderInvalidInput, "invalid cloud provider: %s", provider)
-	}
-}

pkg/types/cloudintegrationtypes/connection.go

@@ -1,88 +0,0 @@
-package cloudintegrationtypes
-
-import "github.com/SigNoz/signoz/pkg/types/integrationtypes"
-
-type ConnectionArtifactRequest struct {
-	Aws *AWSConnectionArtifactRequest `json:"aws"`
-}
-
-type AWSConnectionArtifactRequest struct {
-	DeploymentRegion string   `json:"deploymentRegion"`
-	Regions          []string `json:"regions"`
-}
-
-type PostableConnectionArtifact = ConnectionArtifactRequest
-
-type ConnectionArtifact struct {
-	Aws *AWSConnectionArtifact `json:"aws"`
-}
-
-type AWSConnectionArtifact struct {
-	ConnectionUrl string `json:"connectionURL"`
-}
-
-type GettableConnectionArtifact = ConnectionArtifact
-
-type AccountStatus struct {
-	Id                string                         `json:"id"`
-	ProviderAccountId *string                        `json:"providerAccountID,omitempty"`
-	Status            integrationtypes.AccountStatus `json:"status"`
-}
-
-type GettableAccountStatus = AccountStatus
-
-type AgentCheckInRequest struct {
-	// older backward compatible fields are mapped to new fields
-	// CloudIntegrationId string `json:"cloudIntegrationId"`
-	// AccountId          string `json:"accountId"`
-
-	// New fields
-	ProviderAccountId string `json:"providerAccountId"`
-	CloudAccountId    string `json:"cloudAccountId"`
-
-	Data map[string]any `json:"data,omitempty"`
-}
-
-type PostableAgentCheckInRequest struct {
-	AgentCheckInRequest
-	// following are backward compatible fields for older running agents
-	// which gets mapped to new fields in AgentCheckInRequest
-	CloudIntegrationId string `json:"cloud_integration_id"`
-	CloudAccountId     string `json:"cloud_account_id"`
-}
-
-type GettableAgentCheckInResponse struct {
-	AgentCheckInResponse
-
-	// For backward compatibility
-	CloudIntegrationId string `json:"cloud_integration_id"`
-	AccountId          string `json:"account_id"`
-}
-
-type AgentCheckInResponse struct {
-	// Older fields for backward compatibility are mapped to new fields below
-	// CloudIntegrationId string `json:"cloud_integration_id"`
-	// AccountId          string `json:"account_id"`
-
-	// New fields
-	ProviderAccountId string `json:"providerAccountId"`
-	CloudAccountId    string `json:"cloudAccountId"`
-
-	// IntegrationConfig populates data related to integration that is required for an agent
-	// to start collecting telemetry data
-	// keeping JSON key snake_case for backward compatibility
-	IntegrationConfig *IntegrationConfig `json:"integration_config,omitempty"`
-}
-
-type IntegrationConfig struct {
-	EnabledRegions []string               `json:"enabledRegions"`      // backward compatible
-	Telemetry      *AWSCollectionStrategy `json:"telemetry,omitempty"` // backward compatible
-
-	// new fields
-	AWS *AWSIntegrationConfig `json:"aws,omitempty"`
-}
-
-type AWSIntegrationConfig struct {
-	EnabledRegions []string               `json:"enabledRegions"`
-	Telemetry      *AWSCollectionStrategy `json:"telemetry,omitempty"`
-}

pkg/types/cloudintegrationtypes/regions.go

@@ -1,103 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"github.com/SigNoz/signoz/pkg/errors"
-)
-
-var (
-	ErrCodeInvalidCloudRegion    = errors.MustNewCode("invalid_cloud_region")
-	ErrCodeMismatchCloudProvider = errors.MustNewCode("cloud_provider_mismatch")
-)
-
-// List of all valid cloud regions on Amazon Web Services.
-var ValidAWSRegions = map[string]struct{}{
-	"af-south-1":     {}, // Africa (Cape Town).
-	"ap-east-1":      {}, // Asia Pacific (Hong Kong).
-	"ap-northeast-1": {}, // Asia Pacific (Tokyo).
-	"ap-northeast-2": {}, // Asia Pacific (Seoul).
-	"ap-northeast-3": {}, // Asia Pacific (Osaka).
-	"ap-south-1":     {}, // Asia Pacific (Mumbai).
-	"ap-south-2":     {}, // Asia Pacific (Hyderabad).
-	"ap-southeast-1": {}, // Asia Pacific (Singapore).
-	"ap-southeast-2": {}, // Asia Pacific (Sydney).
-	"ap-southeast-3": {}, // Asia Pacific (Jakarta).
-	"ap-southeast-4": {}, // Asia Pacific (Melbourne).
-	"ca-central-1":   {}, // Canada (Central).
-	"ca-west-1":      {}, // Canada West (Calgary).
-	"eu-central-1":   {}, // Europe (Frankfurt).
-	"eu-central-2":   {}, // Europe (Zurich).
-	"eu-north-1":     {}, // Europe (Stockholm).
-	"eu-south-1":     {}, // Europe (Milan).
-	"eu-south-2":     {}, // Europe (Spain).
-	"eu-west-1":      {}, // Europe (Ireland).
-	"eu-west-2":      {}, // Europe (London).
-	"eu-west-3":      {}, // Europe (Paris).
-	"il-central-1":   {}, // Israel (Tel Aviv).
-	"me-central-1":   {}, // Middle East (UAE).
-	"me-south-1":     {}, // Middle East (Bahrain).
-	"sa-east-1":      {}, // South America (Sao Paulo).
-	"us-east-1":      {}, // US East (N. Virginia).
-	"us-east-2":      {}, // US East (Ohio).
-	"us-west-1":      {}, // US West (N. California).
-	"us-west-2":      {}, // US West (Oregon).
-}
-
-// List of all valid cloud regions for Microsoft Azure.
-var ValidAzureRegions = map[string]struct{}{
-	"australiacentral":   {}, // Australia Central
-	"australiacentral2":  {}, // Australia Central 2
-	"australiaeast":      {}, // Australia East
-	"australiasoutheast": {}, // Australia Southeast
-	"austriaeast":        {}, // Austria East
-	"belgiumcentral":     {}, // Belgium Central
-	"brazilsouth":        {}, // Brazil South
-	"brazilsoutheast":    {}, // Brazil Southeast
-	"canadacentral":      {}, // Canada Central
-	"canadaeast":         {}, // Canada East
-	"centralindia":       {}, // Central India
-	"centralus":          {}, // Central US
-	"chilecentral":       {}, // Chile Central
-	"denmarkeast":        {}, // Denmark East
-	"eastasia":           {}, // East Asia
-	"eastus":             {}, // East US
-	"eastus2":            {}, // East US 2
-	"francecentral":      {}, // France Central
-	"francesouth":        {}, // France South
-	"germanynorth":       {}, // Germany North
-	"germanywestcentral": {}, // Germany West Central
-	"indonesiacentral":   {}, // Indonesia Central
-	"israelcentral":      {}, // Israel Central
-	"italynorth":         {}, // Italy North
-	"japaneast":          {}, // Japan East
-	"japanwest":          {}, // Japan West
-	"koreacentral":       {}, // Korea Central
-	"koreasouth":         {}, // Korea South
-	"malaysiawest":       {}, // Malaysia West
-	"mexicocentral":      {}, // Mexico Central
-	"newzealandnorth":    {}, // New Zealand North
-	"northcentralus":     {}, // North Central US
-	"northeurope":        {}, // North Europe
-	"norwayeast":         {}, // Norway East
-	"norwaywest":         {}, // Norway West
-	"polandcentral":      {}, // Poland Central
-	"qatarcentral":       {}, // Qatar Central
-	"southafricanorth":   {}, // South Africa North
-	"southafricawest":    {}, // South Africa West
-	"southcentralus":     {}, // South Central US
-	"southindia":         {}, // South India
-	"southeastasia":      {}, // Southeast Asia
-	"spaincentral":       {}, // Spain Central
-	"swedencentral":      {}, // Sweden Central
-	"switzerlandnorth":   {}, // Switzerland North
-	"switzerlandwest":    {}, // Switzerland West
-	"uaecentral":         {}, // UAE Central
-	"uaenorth":           {}, // UAE North
-	"uksouth":            {}, // UK South
-	"ukwest":             {}, // UK West
-	"westcentralus":      {}, // West Central US
-	"westeurope":         {}, // West Europe
-	"westindia":          {}, // West India
-	"westus":             {}, // West US
-	"westus2":            {}, // West US 2
-	"westus3":            {}, // West US 3
-}

pkg/types/cloudintegrationtypes/service.go

@@ -1,248 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"fmt"
-	"time"
-
-	"github.com/SigNoz/signoz/pkg/errors"
-	"github.com/SigNoz/signoz/pkg/types"
-	"github.com/SigNoz/signoz/pkg/types/dashboardtypes"
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-var (
-	S3Sync = valuer.NewString("s3sync")
-	// ErrCodeInvalidServiceID is the error code for invalid service id.
-	ErrCodeInvalidServiceID = errors.MustNewCode("invalid_service_id")
-)
-
-type ServiceID struct{ valuer.String }
-
-type CloudIntegrationService struct {
-	types.Identifiable
-	types.TimeAuditable
-	Type               ServiceID      `json:"type"`
-	Config             *ServiceConfig `json:"config"`
-	CloudIntegrationID valuer.UUID    `json:"cloudIntegrationID"`
-}
-
-// ServiceMetadata helps to quickly list available services and whether it is enabled or not.
-// As getting complete service definition is a heavy operation and the response is also large,
-// initial integration page load can be very slow.
-type ServiceMetadata struct {
-	ServiceDefinitionMetadata
-	// if the service is enabled for the account
-	Enabled bool `json:"enabled"`
-}
-
-type GettableServicesMetadata struct {
-	Services []*ServiceMetadata `json:"services"`
-}
-
-type Service struct {
-	ServiceDefinition
-	ServiceConfig *ServiceConfig `json:"serviceConfig"`
-}
-
-type GettableService = Service
-
-type UpdatableService struct {
-	Config *ServiceConfig `json:"config"`
-}
-
-type ServiceConfig struct {
-	AWS *AWSServiceConfig `json:"aws,omitempty"`
-}
-
-type AWSServiceConfig struct {
-	Logs    *AWSServiceLogsConfig    `json:"logs"`
-	Metrics *AWSServiceMetricsConfig `json:"metrics"`
-}
-
-// AWSServiceLogsConfig is AWS specific logs config for a service
-// NOTE: the JSON keys are snake case for backward compatibility with existing agents.
-type AWSServiceLogsConfig struct {
-	Enabled   bool                `json:"enabled"`
-	S3Buckets map[string][]string `json:"s3_buckets,omitempty"`
-}
-
-type AWSServiceMetricsConfig struct {
-	Enabled bool `json:"enabled"`
-}
-
-// ServiceDefinitionMetadata represents service definition metadata. This is useful for showing service tab in frontend.
-type ServiceDefinitionMetadata struct {
-	Id    string `json:"id"`
-	Title string `json:"title"`
-	Icon  string `json:"icon"`
-}
-
-type ServiceDefinition struct {
-	ServiceDefinitionMetadata
-	Overview         string              `json:"overview"` // markdown
-	Assets           Assets              `json:"assets"`
-	SupportedSignals SupportedSignals    `json:"supported_signals"`
-	DataCollected    DataCollected       `json:"dataCollected"`
-	Strategy         *CollectionStrategy `json:"telemetryCollectionStrategy"`
-}
-
-// CollectionStrategy is cloud provider specific configuration for signal collection,
-// this is used by agent to understand the nitty-gritty for collecting telemetry for the cloud provider.
-type CollectionStrategy struct {
-	AWS *AWSCollectionStrategy `json:"aws,omitempty"`
-}
-
-// Assets represents the collection of dashboards.
-type Assets struct {
-	Dashboards []Dashboard `json:"dashboards"`
-}
-
-// SupportedSignals for cloud provider's service.
-type SupportedSignals struct {
-	Logs    bool `json:"logs"`
-	Metrics bool `json:"metrics"`
-}
-
-// DataCollected is curated static list of metrics and logs, this is shown as part of service overview.
-type DataCollected struct {
-	Logs    []CollectedLogAttribute `json:"logs"`
-	Metrics []CollectedMetric       `json:"metrics"`
-}
-
-// CollectedLogAttribute represents a log attribute that is present in all log entries for a service,
-// this is shown as part of service overview.
-type CollectedLogAttribute struct {
-	Name string `json:"name"`
-	Path string `json:"path"`
-	Type string `json:"type"`
-}
-
-// CollectedMetric represents a metric that is collected for a service, this is shown as part of service overview.
-type CollectedMetric struct {
-	Name        string `json:"name"`
-	Type        string `json:"type"`
-	Unit        string `json:"unit"`
-	Description string `json:"description"`
-}
-
-// AWSCollectionStrategy represents signal collection strategy for AWS services.
-// this is AWS specific.
-// NOTE: this structure is still using snake case, for backward compatibility,
-// with existing agents.
-type AWSCollectionStrategy struct {
-	Metrics   *AWSMetricsStrategy `json:"aws_metrics,omitempty"`
-	Logs      *AWSLogsStrategy    `json:"aws_logs,omitempty"`
-	S3Buckets map[string][]string `json:"s3_buckets,omitempty"` // Only available in S3 Sync Service Type in AWS
-}
-
-// AWSMetricsStrategy represents metrics collection strategy for AWS services.
-// this is AWS specific.
-// NOTE: this structure is still using snake case, for backward compatibility,
-// with existing agents.
-type AWSMetricsStrategy struct {
-	// to be used as https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-cloudwatch-metricstream.html#cfn-cloudwatch-metricstream-includefilters
-	StreamFilters []struct {
-		// json tags here are in the shape expected by AWS API as detailed at
-		// https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-metricstream-metricstreamfilter.html
-		Namespace   string   `json:"Namespace"`
-		MetricNames []string `json:"MetricNames,omitempty"`
-	} `json:"cloudwatch_metric_stream_filters"`
-}
-
-// AWSLogsStrategy represents logs collection strategy for AWS services.
-// this is AWS specific.
-// NOTE: this structure is still using snake case, for backward compatibility,
-// with existing agents.
-type AWSLogsStrategy struct {
-	Subscriptions []struct {
-		// subscribe to all logs groups with specified prefix.
-		// eg: `/aws/rds/`
-		LogGroupNamePrefix string `json:"log_group_name_prefix"`
-
-		// https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/FilterAndPatternSyntax.html
-		// "" implies no filtering is required.
-		FilterPattern string `json:"filter_pattern"`
-	} `json:"cloudwatch_logs_subscriptions"`
-}
-
-// Dashboard represents a dashboard definition for cloud integration.
-// This is used to show available pre-made dashboards for a service,
-// hence has additional fields like id, title and description
-type Dashboard struct {
-	Id          string                               `json:"id"`
-	Title       string                               `json:"title"`
-	Description string                               `json:"description"`
-	Definition  dashboardtypes.StorableDashboardData `json:"definition,omitempty"`
-}
-
-// SupportedServices is the map of supported services for each cloud provider.
-var SupportedServices = map[CloudProviderType][]ServiceID{
-	CloudProviderTypeAWS: {
-		{valuer.NewString("alb")},
-		{valuer.NewString("api-gateway")},
-		{valuer.NewString("dynamodb")},
-		{valuer.NewString("ec2")},
-		{valuer.NewString("ecs")},
-		{valuer.NewString("eks")},
-		{valuer.NewString("elasticache")},
-		{valuer.NewString("lambda")},
-		{valuer.NewString("msk")},
-		{valuer.NewString("rds")},
-		{valuer.NewString("s3sync")},
-		{valuer.NewString("sns")},
-		{valuer.NewString("sqs")},
-	},
-}
-
-// NewServiceID returns a new ServiceID from a string, validated against the supported services for the given cloud provider.
-func NewServiceID(provider CloudProviderType, service string) (ServiceID, error) {
-	services, ok := SupportedServices[provider]
-	if !ok {
-		return ServiceID{}, errors.NewInvalidInputf(ErrCodeInvalidServiceID, "no services defined for cloud provider: %s", provider)
-	}
-	for _, s := range services {
-		if s.StringValue() == service {
-			return s, nil
-		}
-	}
-	return ServiceID{}, errors.NewInvalidInputf(ErrCodeInvalidServiceID, "invalid service id %q for cloud provider %s", service, provider)
-}
-
-// UTILS
-
-// GetCloudIntegrationDashboardID returns the dashboard id for a cloud integration, given the cloud provider, service id, and dashboard id.
-// This is used to generate unique dashboard ids for cloud integration, and also to parse the dashboard id to get the cloud provider and service id when needed.
-func GetCloudIntegrationDashboardID(cloudProvider CloudProviderType, svcId, dashboardId string) string {
-	return fmt.Sprintf("cloud-integration--%s--%s--%s", cloudProvider, svcId, dashboardId)
-}
-
-// GetDashboardsFromAssets returns the list of dashboards for the cloud provider service from definition.
-func GetDashboardsFromAssets(
-	svcId string,
-	orgID valuer.UUID,
-	cloudProvider CloudProviderType,
-	createdAt time.Time,
-	assets Assets,
-) []*dashboardtypes.Dashboard {
-	dashboards := make([]*dashboardtypes.Dashboard, 0)
-
-	for _, d := range assets.Dashboards {
-		author := fmt.Sprintf("%s-integration", cloudProvider)
-		dashboards = append(dashboards, &dashboardtypes.Dashboard{
-			ID:     GetCloudIntegrationDashboardID(cloudProvider, svcId, d.Id),
-			Locked: true,
-			OrgID:  orgID,
-			Data:   d.Definition,
-			TimeAuditable: types.TimeAuditable{
-				CreatedAt: createdAt,
-				UpdatedAt: createdAt,
-			},
-			UserAuditable: types.UserAuditable{
-				CreatedBy: author,
-				UpdatedBy: author,
-			},
-		})
-	}
-
-	return dashboards
-}

pkg/types/cloudintegrationtypes/store.go

@@ -1,41 +0,0 @@
-package cloudintegrationtypes
-
-import (
-	"context"
-
-	"github.com/SigNoz/signoz/pkg/valuer"
-)
-
-type Store interface {
-	// GetAccountByID returns a cloud integration account by id
-	GetAccountByID(ctx context.Context, orgID, id valuer.UUID, provider CloudProviderType) (*StorableCloudIntegration, error)
-
-	// CreateAccount creates a new cloud integration account
-	CreateAccount(ctx context.Context, account *StorableCloudIntegration) (*StorableCloudIntegration, error)
-
-	// UpdateAccount updates an existing cloud integration account
-	UpdateAccount(ctx context.Context, account *StorableCloudIntegration) error
-
-	// RemoveAccount marks a cloud integration account as removed by setting the RemovedAt field
-	RemoveAccount(ctx context.Context, orgID, id valuer.UUID, provider CloudProviderType) error
-
-	// ListConnectedAccounts returns all the cloud integration accounts for the org and cloud provider
-	ListConnectedAccounts(ctx context.Context, orgID valuer.UUID, provider CloudProviderType) ([]*StorableCloudIntegration, error)
-
-	// GetConnectedAccount for a given provider
-	GetConnectedAccount(ctx context.Context, orgID valuer.UUID, provider CloudProviderType, providerAccountID string) (*StorableCloudIntegration, error)
-
-	// cloud_integration_service related methods
-
-	// GetServiceByServiceID returns the cloud integration service for the given cloud integration id and service id
-	GetServiceByServiceID(ctx context.Context, cloudIntegrationID valuer.UUID, serviceID ServiceID) (*StorableCloudIntegrationService, error)
-
-	// CreateService creates a new cloud integration service
-	CreateService(ctx context.Context, service *StorableCloudIntegrationService) (*StorableCloudIntegrationService, error)
-
-	// UpdateService updates an existing cloud integration service
-	UpdateService(ctx context.Context, service *StorableCloudIntegrationService) error
-
-	// ListServices returns all the cloud integration services for the given cloud integration id
-	ListServices(ctx context.Context, cloudIntegrationID valuer.UUID) ([]*StorableCloudIntegrationService, error)
-}

pkg/types/opamptypes/agent.go

@@ -6,7 +6,6 @@ import (
 	"github.com/SigNoz/signoz/pkg/sqlstore"
 	"github.com/SigNoz/signoz/pkg/types"
 	"github.com/SigNoz/signoz/pkg/valuer"
-	"github.com/open-telemetry/opamp-go/protobufs"
 	"github.com/uptrace/bun"
 )
 
@@ -18,15 +17,6 @@ const (
 	AgentStatusDisconnected
 )
 
-var DeployStatusToProtoStatus = map[DeployStatus]protobufs.RemoteConfigStatuses{
-	PendingDeploy:       protobufs.RemoteConfigStatuses_RemoteConfigStatuses_UNSET,
-	Deploying:           protobufs.RemoteConfigStatuses_RemoteConfigStatuses_APPLYING,
-	Deployed:            protobufs.RemoteConfigStatuses_RemoteConfigStatuses_APPLIED,
-	DeployInitiated:     protobufs.RemoteConfigStatuses_RemoteConfigStatuses_APPLYING,
-	DeployFailed:        protobufs.RemoteConfigStatuses_RemoteConfigStatuses_FAILED,
-	DeployStatusUnknown: protobufs.RemoteConfigStatuses_RemoteConfigStatuses_UNSET,
-}
-
 type StorableAgent struct {
 	bun.BaseModel `bun:"table:agent"`
 
@@ -40,6 +30,16 @@ type StorableAgent struct {
 	Config       string      `bun:"config,type:text,notnull"`
 }
 
+func NewStorableAgent(store sqlstore.SQLStore, orgID valuer.UUID, agentID string, status AgentStatus) StorableAgent {
+	return StorableAgent{
+		OrgID:         orgID,
+		Identifiable:  types.Identifiable{ID: valuer.GenerateUUID()},
+		AgentID:       agentID,
+		TimeAuditable: types.TimeAuditable{CreatedAt: time.Now(), UpdatedAt: time.Now()},
+		Status:        status,
+	}
+}
+
 type ElementType struct{ valuer.String }
 
 var (
@@ -49,6 +49,24 @@ var (
 	ElementTypeLbExporter    = ElementType{valuer.NewString("lb_exporter")}
 )
 
+// NewElementType creates a new ElementType from a string value.
+// Returns the corresponding ElementType constant if the string matches,
+// otherwise returns an empty ElementType.
+func NewElementType(value string) ElementType {
+	switch valuer.NewString(value) {
+	case ElementTypeSamplingRules.String:
+		return ElementTypeSamplingRules
+	case ElementTypeDropRules.String:
+		return ElementTypeDropRules
+	case ElementTypeLogPipelines.String:
+		return ElementTypeLogPipelines
+	case ElementTypeLbExporter.String:
+		return ElementTypeLbExporter
+	default:
+		return ElementType{valuer.NewString("")}
+	}
+}
+
 type DeployStatus struct{ valuer.String }
 
 var (
@@ -80,26 +98,6 @@ type AgentConfigVersion struct {
 	Config         string       `json:"config" bun:"config,type:text"`
 }
 
-type AgentConfigElement struct {
-	bun.BaseModel `bun:"table:agent_config_element"`
-
-	types.Identifiable
-	types.TimeAuditable
-	ElementID   string      `bun:"element_id,type:text,notnull,unique:element_type_version_idx"`
-	ElementType string      `bun:"element_type,type:text,notnull,unique:element_type_version_idx"`
-	VersionID   valuer.UUID `bun:"version_id,type:text,notnull,unique:element_type_version_idx"`
-}
-
-func NewStorableAgent(store sqlstore.SQLStore, orgID valuer.UUID, agentID string, status AgentStatus) StorableAgent {
-	return StorableAgent{
-		OrgID:         orgID,
-		Identifiable:  types.Identifiable{ID: valuer.GenerateUUID()},
-		AgentID:       agentID,
-		TimeAuditable: types.TimeAuditable{CreatedAt: time.Now(), UpdatedAt: time.Now()},
-		Status:        status,
-	}
-}
-
 func NewAgentConfigVersion(orgId valuer.UUID, userId valuer.UUID, elementType ElementType) *AgentConfigVersion {
 	return &AgentConfigVersion{
 		TimeAuditable: types.TimeAuditable{
@@ -120,20 +118,12 @@ func (a *AgentConfigVersion) IncrementVersion(lastVersion int) {
 	a.Version = lastVersion + 1
 }
 
-// NewElementType creates a new ElementType from a string value.
-// Returns the corresponding ElementType constant if the string matches,
-// otherwise returns an empty ElementType.
-func NewElementType(value string) ElementType {
-	switch valuer.NewString(value) {
-	case ElementTypeSamplingRules.String:
-		return ElementTypeSamplingRules
-	case ElementTypeDropRules.String:
-		return ElementTypeDropRules
-	case ElementTypeLogPipelines.String:
-		return ElementTypeLogPipelines
-	case ElementTypeLbExporter.String:
-		return ElementTypeLbExporter
-	default:
-		return ElementType{valuer.NewString("")}
-	}
+type AgentConfigElement struct {
+	bun.BaseModel `bun:"table:agent_config_element"`
+
+	types.Identifiable
+	types.TimeAuditable
+	ElementID   string      `bun:"element_id,type:text,notnull,unique:element_type_version_idx"`
+	ElementType string      `bun:"element_type,type:text,notnull,unique:element_type_version_idx"`
+	VersionID   valuer.UUID `bun:"version_id,type:text,notnull,unique:element_type_version_idx"`
 }

tests/integration/fixtures/querier.py

@@ -58,6 +58,8 @@ def build_builder_query(
     step_interval: int = DEFAULT_STEP_INTERVAL,
     group_by: Optional[List[str]] = None,
     filter_expression: Optional[str] = None,
+    order_by: Optional[List[Dict]] = None,
+    limit: Optional[int] = None,
     functions: Optional[List[Dict]] = None,
     disabled: bool = False,
 ) -> Dict:
@@ -93,6 +95,12 @@ def build_builder_query(
     if filter_expression:
         spec["filter"] = {"expression": filter_expression}
 
+    if order_by:
+        spec["order"] = order_by
+
+    if limit is not None:
+        spec["limit"] = limit
+
     if functions:
         spec["functions"] = functions
 

tests/integration/src/querier/05_metrics_rate_cumulative_counter.py

@@ -2,16 +2,20 @@
 Look at the cumulative_counters_1h.jsonl file for the relevant data
 """
 
+import logging
 import os
 from datetime import datetime, timedelta, timezone
 from http import HTTPStatus
-from typing import Any, Callable, List
+from typing import Any, Callable, List, Optional, Union
+
+import pytest
 
 from fixtures import types
 from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
 from fixtures.metrics import Metrics
 from fixtures.querier import (
     build_builder_query,
+    build_order_by,
     get_all_series,
     get_series_values,
     make_query_request,
@@ -71,16 +75,200 @@ def test_rate_with_steady_values_and_reset(
         assert v["value"] >= 0, f"Rate should not be negative: {v['value']}"
 
 
+def _assert_endpoint_rate_values(endpoint_values: dict) -> None:
+    # /health: 60 data points (t01-t60), steady +10/min
+    # rate = 10/60 = 0.167
+    if "/health" in endpoint_values:
+        health_values = endpoint_values["/health"]
+        assert (
+            len(health_values) >= 58
+        ), f"Expected >= 58 values for /health, got {len(health_values)}"
+        count_steady_health = sum(1 for v in health_values if v["value"] == 0.167)
+        assert (
+            count_steady_health >= 57
+        ), f"Expected >= 57 steady rate values (0.167) for /health, got {count_steady_health}"
+        # all /health rates should be 0.167 except possibly first/last due to boundaries
+        for v in health_values[1:-1]:
+            assert v["value"] == 0.167, f"Expected /health rate 0.167, got {v['value']}"
+
+    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
+    # rate = 20/60 = 0.333, gap causes lower averaged rate at boundary
+    if "/products" in endpoint_values:
+        products_values = endpoint_values["/products"]
+        assert (
+            len(products_values) >= 49
+        ), f"Expected >= 49 values for /products, got {len(products_values)}"
+        count_steady_products = sum(1 for v in products_values if v["value"] == 0.333)
+        # most values should be 0.333, some boundary values differ due to 10-min gap
+        assert (
+            count_steady_products >= 46
+        ), f"Expected >= 46 steady rate values (0.333) for /products, got {count_steady_products}"
+        # check that non-0.333 values are due to gap averaging (should be lower)
+        gap_boundary_values = [v["value"] for v in products_values if v["value"] != 0.333]
+        for val in gap_boundary_values:
+            assert (
+                0 < val < 0.333
+            ), f"Gap boundary values should be between 0 and 0.333, got {val}"
+
+    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
+    # normal rate = 1/60 = 0.0167, spike rate = 50/60 = 0.833
+    if "/checkout" in endpoint_values:
+        checkout_values = endpoint_values["/checkout"]
+        assert (
+            len(checkout_values) >= 59
+        ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
+        count_steady_checkout = sum(1 for v in checkout_values if v["value"] == 0.0167)
+        assert (
+            count_steady_checkout >= 53
+        ), f"Expected >= 53 steady rate values (0.0167) for /checkout, got {count_steady_checkout}"
+        # check that spike values exist (traffic spike +50/min at t40-t44)
+        count_spike_checkout = sum(1 for v in checkout_values if v["value"] == 0.833)
+        assert (
+            count_spike_checkout >= 4
+        ), f"Expected >= 4 spike rate values (0.833) for /checkout, got {count_spike_checkout}"
+        # spike values should be consecutive
+        spike_indices = [
+            i for i, v in enumerate[Any](checkout_values) if v["value"] == 0.833
+        ]
+        assert len(spike_indices) >= 4, f"Expected >= 4 spike indices, got {spike_indices}"
+        for i in range(1, len(spike_indices)):
+            assert (
+                spike_indices[i] == spike_indices[i - 1] + 1
+            ), f"Spike indices should be consecutive, got {spike_indices}"
+
+    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
+    # rate = 5/60 = 0.0833
+    # reset at t31 causes: rate at t30 includes gap (lower), t31 has high rate after reset
+    if "/orders" in endpoint_values:
+        orders_values = endpoint_values["/orders"]
+        assert (
+            len(orders_values) >= 58
+        ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
+        count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
+        assert (
+            count_steady_orders >= 55
+        ), f"Expected >= 55 steady rate values (0.0833) for /orders, got {count_steady_orders}"
+        # check for counter reset effects - there should be some non-standard values
+        non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
+        assert (
+            len(non_standard_orders) >= 2
+        ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
+        # post-reset value should be higher (new counter value / interval)
+        high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
+        assert (
+            len(high_rate_orders) >= 1
+        ), f"Expected at least one high rate value after counter reset, got {non_standard_orders}"
+
+    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes
+    # Rate = 1/60 = 0.0167 during increment, 0 during flat periods
+    if "/users" in endpoint_values:
+        users_values = endpoint_values["/users"]
+        assert (
+            len(users_values) >= 54
+        ), f"Expected >= 54 values for /users, got {len(users_values)}"
+        count_zero_users = sum(1 for v in users_values if v["value"] == 0)
+        # most values should be 0 (flat periods between increments)
+        assert (
+            count_zero_users >= 40
+        ), f"Expected >= 40 zero rate values for /users (sparse data), got {count_zero_users}"
+        # non-zero values should be 0.0167 (1/60 increment rate)
+        non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
+        count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
+        assert (
+            count_increment_rate >= 8
+        ), f"Expected >= 8 increment rate values (0.0167) for /users, got {count_increment_rate}"
+
+
+@pytest.mark.parametrize(
+    "metric_suffix,order_by,limit,expected_count,expected_endpoints",
+    [
+        (
+            "no_order",
+            None, # this is equivalent to sum(metric_name)
+            None,
+            5,
+            ["/products", "/health", "/checkout", "/orders", "/users"],
+        ),
+        (
+            "only_limit",
+            None, # this is equivalent to sum(metric_name)
+            3,
+            3,
+            ["/products", "/health", "/checkout"],
+        ),
+        (
+            "asc",
+            [build_order_by("endpoint", "asc")],
+            None,
+            5,
+            ["/checkout", "/health", "/orders", "/products", "/users"],
+        ),
+        (
+            "asc_lim3",
+            [build_order_by("endpoint", "asc")],
+            3,
+            3,
+            ["/checkout", "/health", "/orders"],
+        ),
+        (
+            "desc",
+            [build_order_by("endpoint", "desc")],
+            None,
+            5,
+            ["/users", "/products", "/orders", "/health", "/checkout"],
+        ),
+        (
+            "desc_lim3",
+            [build_order_by("endpoint", "desc")],
+            3,
+            3,
+            ["/users", "/products", "/orders"],
+        ),
+        (
+            "asc_metric_name",
+            [build_order_by("sum(test_rate_groupby_asc_metric_name)", "asc")],
+            None,
+            5,
+            ["/users", "/orders", "/checkout", "/health", "/products"],
+        ),
+        (
+            "asc_metric_name_lim3",
+            [build_order_by("sum(test_rate_groupby_asc_metric_name_lim3)", "asc")],
+            3,
+            3,
+            ["/users", "/orders", "/checkout"],
+        ),
+        (
+            "desc_metric_name",
+            [build_order_by("sum(test_rate_groupby_desc_metric_name)", "desc")],
+            None,
+            5,
+            ["/products", "/health", "/checkout", "/orders", "/users"],
+        ),
+        (
+            "desc_metric_name_lim3",
+            [build_order_by("sum(test_rate_groupby_desc_metric_name_lim3)", "desc")],
+            3,
+            3,
+            ["/products", "/health", "/checkout"],
+        ),
+    ],
+)
 def test_rate_group_by_endpoint(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token: Callable[[str, str], str],
     insert_metrics: Callable[[List[Metrics]], None],
+    metric_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
 ) -> None:
     now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
     start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
     end_ms = int(now.timestamp() * 1000)
-    metric_name = "test_rate_groupby"
+    metric_name = f"test_rate_groupby_{metric_suffix}"
 
     metrics = Metrics.load_from_file(
         CUMULATIVE_COUNTERS_FILE,
@@ -97,6 +285,8 @@ def test_rate_group_by_endpoint(
         "sum",
         temporality="cumulative",
         group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
     )
 
     response = make_query_request(signoz, token, start_ms, end_ms, [query])
@@ -105,10 +295,23 @@ def test_rate_group_by_endpoint(
     data = response.json()
     all_series = get_all_series(data, "A")
 
-    # Should have 5 different endpoints
     assert (
-        len(all_series) == 5
-    ), f"Expected 5 series for 5 endpoints, got {len(all_series)}"
+        len(all_series) == expected_count
+    ), f"Expected {expected_count} series, got {len(all_series)}"
+
+    endpoint_labels = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in all_series
+    ]
+
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(endpoint_labels) == expected_endpoints
+        ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_labels)}"
+    else:
+        assert endpoint_labels == expected_endpoints, (
+            f"Expected endpoints {expected_endpoints}, got {endpoint_labels}"
+        )
 
     # endpoint -> values
     endpoint_values = {}
@@ -117,11 +320,6 @@ def test_rate_group_by_endpoint(
         values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
         endpoint_values[endpoint] = values
 
-    expected_endpoints = {"/products", "/health", "/checkout", "/orders", "/users"}
-    assert (
-        set(endpoint_values.keys()) == expected_endpoints
-    ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_values.keys())}"
-
     # at no point rate should be negative
     for endpoint, values in endpoint_values.items():
         for v in values:
@@ -129,103 +327,4 @@ def test_rate_group_by_endpoint(
                 v["value"] >= 0
             ), f"Rate for {endpoint} should not be negative: {v['value']}"
 
-    # /health: 60 data points (t01-t60), steady +10/min
-    # rate = 10/60 = 0.167
-    health_values = endpoint_values["/health"]
-    assert (
-        len(health_values) >= 58
-    ), f"Expected >= 58 values for /health, got {len(health_values)}"
-    count_steady_health = sum(1 for v in health_values if v["value"] == 0.167)
-    assert (
-        count_steady_health >= 57
-    ), f"Expected >= 57 steady rate values (0.167) for /health, got {count_steady_health}"
-    # all /health rates should be 0.167 except possibly first/last due to boundaries
-    for v in health_values[1:-1]:
-        assert v["value"] == 0.167, f"Expected /health rate 0.167, got {v['value']}"
-
-    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
-    # rate = 20/60 = 0.333, gap causes lower averaged rate at boundary
-    products_values = endpoint_values["/products"]
-    assert (
-        len(products_values) >= 49
-    ), f"Expected >= 49 values for /products, got {len(products_values)}"
-    count_steady_products = sum(1 for v in products_values if v["value"] == 0.333)
-
-    # most values should be 0.333, some boundary values differ due to 10-min gap
-    assert (
-        count_steady_products >= 46
-    ), f"Expected >= 46 steady rate values (0.333) for /products, got {count_steady_products}"
-
-    # check that non-0.333 values are due to gap averaging (should be lower)
-    gap_boundary_values = [v["value"] for v in products_values if v["value"] != 0.333]
-    for val in gap_boundary_values:
-        assert (
-            0 < val < 0.333
-        ), f"Gap boundary values should be between 0 and 0.333, got {val}"
-
-    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
-    # normal rate = 1/60 = 0.0167, spike rate = 50/60 = 0.833
-    checkout_values = endpoint_values["/checkout"]
-    assert (
-        len(checkout_values) >= 59
-    ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
-    count_steady_checkout = sum(1 for v in checkout_values if v["value"] == 0.0167)
-    assert (
-        count_steady_checkout >= 53
-    ), f"Expected >= 53 steady rate values (0.0167) for /checkout, got {count_steady_checkout}"
-    # check that spike values exist (traffic spike +50/min at t40-t44)
-    count_spike_checkout = sum(1 for v in checkout_values if v["value"] == 0.833)
-    assert (
-        count_spike_checkout >= 4
-    ), f"Expected >= 4 spike rate values (0.833) for /checkout, got {count_spike_checkout}"
-
-    # spike values should be consecutive
-    spike_indices = [
-        i for i, v in enumerate[Any](checkout_values) if v["value"] == 0.833
-    ]
-    assert len(spike_indices) >= 4, f"Expected >= 4 spike indices, got {spike_indices}"
-    # consecutiveness
-    for i in range(1, len(spike_indices)):
-        assert (
-            spike_indices[i] == spike_indices[i - 1] + 1
-        ), f"Spike indices should be consecutive, got {spike_indices}"
-
-    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
-    # rate = 5/60 = 0.0833
-    # reset at t31 causes: rate at t30 includes gap (lower), t31 has high rate after reset
-    orders_values = endpoint_values["/orders"]
-    assert (
-        len(orders_values) >= 58
-    ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
-    count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
-    assert (
-        count_steady_orders >= 55
-    ), f"Expected >= 55 steady rate values (0.0833) for /orders, got {count_steady_orders}"
-    # check for counter reset effects - there should be some non-standard values
-    non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
-    assert (
-        len(non_standard_orders) >= 2
-    ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
-    # post-reset value should be higher (new counter value / interval)
-    high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
-    assert (
-        len(high_rate_orders) >= 1
-    ), f"Expected at least one high rate value after counter reset, got {non_standard_orders}"
-
-    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes
-    # Rate = 1/60 = 0.0167 during increment, 0 during flat periods
-    users_values = endpoint_values["/users"]
-    assert (
-        len(users_values) >= 54
-    ), f"Expected >= 54 values for /users, got {len(users_values)}"
-    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
-    # most values should be 0 (flat periods between increments)
-    assert (
-        count_zero_users >= 40
-    ), f"Expected >= 40 zero rate values for /users (sparse data), got {count_zero_users}"
-    # non-zero values should be 0.0167 (1/60 increment rate)
-    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
-    count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
-    assert (
-        count_increment_rate >= 8
-    ), f"Expected >= 8 increment rate values (0.0167) for /users, got {count_increment_rate}"
+    _assert_endpoint_rate_values(endpoint_values)

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

@@ -5,7 +5,7 @@ Look at the multi_temporality_counters_1h.jsonl file for the relevant data
 import random
 from datetime import datetime, timedelta, timezone
 from http import HTTPStatus
-from typing import Callable, List
+from typing import Callable, List, Optional, Union
 
 import pytest
 
@@ -14,6 +14,7 @@ from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
 from fixtures.metrics import Metrics
 from fixtures.querier import (
     build_builder_query,
+    build_order_by,
     get_all_series,
     get_series_values,
     make_query_request,
@@ -91,6 +92,198 @@ def test_with_steady_values_and_reset(
         ), f"{time_aggregation} should not be negative: {v['value']}"
 
 
+def _assert_endpoint_group_values(  # pylint: disable=too-many-arguments
+    endpoint_values: dict,
+    stable_health_value: float,
+    stable_products_value: float,
+    stable_checkout_value: float,
+    spike_checkout_value: float,
+    stable_orders_value: float,
+    spike_users_value: float,
+    time_aggregation: str,
+) -> None:
+    # /health: 60 data points (t01-t60), steady +10/min
+    if "/health" in endpoint_values:
+        health_values = endpoint_values["/health"]
+        assert (
+            len(health_values) >= 58
+        ), f"Expected >= 58 values for /health, got {len(health_values)}"
+        count_steady_health = sum(
+            1 for v in health_values if v["value"] == stable_health_value
+        )
+        assert (
+            count_steady_health >= 57
+        ), f"Expected >= 57 steady rate values ({stable_health_value}) for /health, got {count_steady_health}"
+        # all /health rates should be stable except possibly first/last due to boundaries
+        for v in health_values[1:-1]:
+            assert (
+                v["value"] == stable_health_value
+            ), f"Expected /health rate {stable_health_value}, got {v['value']}"
+
+    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
+    if "/products" in endpoint_values:
+        products_values = endpoint_values["/products"]
+        assert (
+            len(products_values) >= 49
+        ), f"Expected >= 49 values for /products, got {len(products_values)}"
+        count_steady_products = sum(
+            1 for v in products_values if v["value"] == stable_products_value
+        )
+        # most values should be stable, some boundary values differ due to 10-min gap
+        assert (
+            count_steady_products >= 46
+        ), f"Expected >= 46 steady rate values ({stable_products_value}) for /products, got {count_steady_products}"
+        # check that non-stable values are due to gap averaging (should be lower)
+        gap_boundary_values = [
+            v["value"] for v in products_values if v["value"] != stable_products_value
+        ]
+        for val in gap_boundary_values:
+            assert (
+                0 < val < stable_products_value
+            ), f"Gap boundary values should be between 0 and {stable_products_value}, got {val}"
+
+    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
+    if "/checkout" in endpoint_values:
+        checkout_values = endpoint_values["/checkout"]
+        assert (
+            len(checkout_values) >= 59
+        ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
+        count_steady_checkout = sum(
+            1 for v in checkout_values if v["value"] == stable_checkout_value
+        )
+        assert (
+            count_steady_checkout >= 53
+        ), f"Expected >= 53 steady {time_aggregation} values ({stable_checkout_value}) for /checkout, got {count_steady_checkout}"
+        # check that spike values exist (traffic spike +50/min at t40-t44)
+        count_spike_checkout = sum(
+            1 for v in checkout_values if v["value"] == spike_checkout_value
+        )
+        assert (
+            count_spike_checkout >= 4
+        ), f"Expected >= 4 spike {time_aggregation} values ({spike_checkout_value}) for /checkout, got {count_spike_checkout}"
+        # spike values should be consecutive
+        spike_indices = [
+            i for i, v in enumerate(checkout_values) if v["value"] == spike_checkout_value
+        ]
+        assert len(spike_indices) >= 4, f"Expected >= 4 spike indices, got {spike_indices}"
+        for i in range(1, len(spike_indices)):
+            assert (
+                spike_indices[i] == spike_indices[i - 1] + 1
+            ), f"Spike indices should be consecutive, got {spike_indices}"
+
+    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
+    # reset at t31 causes: rate/increase at t30 includes gap (lower), t31 has high rate after reset
+    if "/orders" in endpoint_values:
+        orders_values = endpoint_values["/orders"]
+        assert (
+            len(orders_values) >= 58
+        ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
+        count_steady_orders = sum(
+            1 for v in orders_values if v["value"] == stable_orders_value
+        )
+        assert (
+            count_steady_orders >= 55
+        ), f"Expected >= 55 steady {time_aggregation} values ({stable_orders_value}) for /orders, got {count_steady_orders}"
+        # check for counter reset effects - there should be some non-standard values
+        non_standard_orders = [
+            v["value"] for v in orders_values if v["value"] != stable_orders_value
+        ]
+        assert (
+            len(non_standard_orders) >= 2
+        ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
+        # post-reset value should be higher (new counter value / interval)
+        high_rate_orders = [v for v in non_standard_orders if v > stable_orders_value]
+        assert (
+            len(high_rate_orders) >= 1
+        ), f"Expected at least one high {time_aggregation} value after counter reset, got {non_standard_orders}"
+
+    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes
+    if "/users" in endpoint_values:
+        users_values = endpoint_values["/users"]
+        assert (
+            len(users_values) >= 54
+        ), f"Expected >= 54 values for /users, got {len(users_values)}"
+        count_zero_users = sum(1 for v in users_values if v["value"] == 0)
+        # most values should be 0 (flat periods between increments)
+        assert (
+            count_zero_users >= 40
+        ), f"Expected >= 40 zero {time_aggregation} values for /users (sparse data), got {count_zero_users}"
+        # non-zero values should be stable increment rate
+        non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
+        count_increment_rate = sum(1 for v in non_zero_users if v == spike_users_value)
+        assert (
+            count_increment_rate >= 8
+        ), f"Expected >= 8 increment {time_aggregation} values ({spike_users_value}) for /users, got {count_increment_rate}"
+
+
+@pytest.mark.parametrize(
+    "order_suffix,order_by_spec,limit,expected_count,expected_endpoints",
+    [
+        (
+            "no_order",
+            None,
+            None,
+            5,
+            ["/products", "/health", "/checkout", "/orders", "/users"],
+        ),
+        (
+            "asc",
+            ("endpoint", "asc"),
+            None,
+            5,
+            ["/checkout", "/health", "/orders", "/products", "/users"],
+        ),
+        (
+            "asc_lim3",
+            ("endpoint", "asc"),
+            3,
+            3,
+            ["/checkout", "/health", "/orders"],
+        ),
+        (
+            "desc",
+            ("endpoint", "desc"),
+            None,
+            5,
+            ["/users", "/products", "/orders", "/health", "/checkout"],
+        ),
+        (
+            "desc_lim3",
+            ("endpoint", "desc"),
+            3,
+            3,
+            ["/users", "/products", "/orders"],
+        ),
+        (
+            "asc_metric_name",
+            ("sum_metric", "asc"),
+            None,
+            5,
+            ["/users", "/orders", "/checkout", "/health", "/products"],
+        ),
+        (
+            "asc_metric_name_lim3",
+            ("sum_metric", "asc"),
+            3,
+            3,
+            ["/users", "/orders", "/checkout"],
+        ),
+        (
+            "desc_metric_name",
+            ("sum_metric", "desc"),
+            None,
+            5,
+            ["/products", "/health", "/checkout", "/orders", "/users"],
+        ),
+        (
+            "desc_metric_name_lim3",
+            ("sum_metric", "desc"),
+            3,
+            3,
+            ["/products", "/health", "/checkout"],
+        ),
+    ],
+)
 @pytest.mark.parametrize(
     "time_aggregation, stable_health_value, stable_products_value, stable_checkout_value, spike_checkout_value, stable_orders_value, spike_users_value",
     [
@@ -110,11 +303,24 @@ def test_group_by_endpoint(
     spike_checkout_value: float,
     stable_orders_value: float,
     spike_users_value: float,
+    order_suffix: str,
+    order_by_spec: Optional[tuple],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
 ) -> None:
     now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
     start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
     end_ms = int(now.timestamp() * 1000)
-    metric_name = f"test_{time_aggregation}_groupby"
+    metric_name = f"test_{time_aggregation}_groupby_{order_suffix}"
+
+    # Build order_by at runtime so metric name reflects actual time_aggregation
+    order_by = None
+    if order_by_spec is not None:
+        key, direction = order_by_spec
+        if key == "sum_metric":
+            key = f"sum({metric_name})"
+        order_by = [build_order_by(key, direction)]
 
     metrics = Metrics.load_from_file(
         MULTI_TEMPORALITY_FILE,
@@ -130,6 +336,8 @@ def test_group_by_endpoint(
         time_aggregation,
         "sum",
         group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
     )
 
     response = make_query_request(signoz, token, start_ms, end_ms, [query])
@@ -137,10 +345,23 @@ def test_group_by_endpoint(
 
     data = response.json()
     all_series = get_all_series(data, "A")
-    # Should have 5 different endpoints
     assert (
-        len(all_series) == 5
-    ), f"Expected 5 series for 5 endpoints, got {len(all_series)}"
+        len(all_series) == expected_count
+    ), f"Expected {expected_count} series, got {len(all_series)}"
+
+    endpoint_labels = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in all_series
+    ]
+
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(endpoint_labels) == expected_endpoints
+        ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_labels)}"
+    else:
+        assert endpoint_labels == expected_endpoints, (
+            f"Expected endpoints {expected_endpoints}, got {endpoint_labels}"
+        )
 
     # endpoint -> values
     endpoint_values = {}
@@ -149,11 +370,6 @@ def test_group_by_endpoint(
         values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
         endpoint_values[endpoint] = values
 
-    expected_endpoints = {"/products", "/health", "/checkout", "/orders", "/users"}
-    assert (
-        set(endpoint_values.keys()) == expected_endpoints
-    ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_values.keys())}"
-
     # at no point rate should be negative
     for endpoint, values in endpoint_values.items():
         for v in values:
@@ -161,117 +377,16 @@ def test_group_by_endpoint(
                 v["value"] >= 0
             ), f"Rate for {endpoint} should not be negative: {v['value']}"
 
-    # /health: 60 data points (t01-t60), steady +10/min
-    health_values = endpoint_values["/health"]
-    assert (
-        len(health_values) >= 58
-    ), f"Expected >= 58 values for /health, got {len(health_values)}"
-    count_steady_health = sum(
-        1 for v in health_values if v["value"] == stable_health_value
+    _assert_endpoint_group_values(
+        endpoint_values,
+        stable_health_value,
+        stable_products_value,
+        stable_checkout_value,
+        spike_checkout_value,
+        stable_orders_value,
+        spike_users_value,
+        time_aggregation,
     )
-    assert (
-        count_steady_health >= 57
-    ), f"Expected >= 57 steady rate values ({stable_health_value}) for /health, got {count_steady_health}"
-    # all /health rates should be state except possibly first/last due to boundaries
-    for v in health_values[1:-1]:
-        assert (
-            v["value"] == stable_health_value
-        ), f"Expected /health rate {stable_health_value}, got {v['value']}"
-
-    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
-    products_values = endpoint_values["/products"]
-    assert (
-        len(products_values) >= 49
-    ), f"Expected >= 49 values for /products, got {len(products_values)}"
-    count_steady_products = sum(
-        1 for v in products_values if v["value"] == stable_products_value
-    )
-
-    # most values should be stable, some boundary values differ due to 10-min gap
-    assert (
-        count_steady_products >= 46
-    ), f"Expected >= 46 steady rate values ({stable_products_value}) for /products, got {count_steady_products}"
-
-    # check that non-stable values are due to gap averaging (should be lower)
-    gap_boundary_values = [
-        v["value"] for v in products_values if v["value"] != stable_products_value
-    ]
-    for val in gap_boundary_values:
-        assert (
-            0 < val < stable_products_value
-        ), f"Gap boundary values should be between 0 and {stable_products_value}, got {val}"
-
-    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
-    checkout_values = endpoint_values["/checkout"]
-    assert (
-        len(checkout_values) >= 59
-    ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
-    count_steady_checkout = sum(
-        1 for v in checkout_values if v["value"] == stable_checkout_value
-    )
-    assert (
-        count_steady_checkout >= 53
-    ), f"Expected >= 53 steady {time_aggregation} values ({stable_checkout_value}) for /checkout, got {count_steady_checkout}"
-    # check that spike values exist (traffic spike +50/min at t40-t44)
-    count_spike_checkout = sum(
-        1 for v in checkout_values if v["value"] == spike_checkout_value
-    )
-    assert (
-        count_spike_checkout >= 4
-    ), f"Expected >= 4 spike {time_aggregation} values ({spike_checkout_value}) for /checkout, got {count_spike_checkout}"
-
-    # spike values should be consecutive
-    spike_indices = [
-        i for i, v in enumerate(checkout_values) if v["value"] == spike_checkout_value
-    ]
-    assert len(spike_indices) >= 4, f"Expected >= 4 spike indices, got {spike_indices}"
-    # consecutiveness
-    for i in range(1, len(spike_indices)):
-        assert (
-            spike_indices[i] == spike_indices[i - 1] + 1
-        ), f"Spike indices should be consecutive, got {spike_indices}"
-
-    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
-    # reset at t31 causes: rate/increase at t30 includes gap (lower), t31 has high rate after reset
-    orders_values = endpoint_values["/orders"]
-    assert (
-        len(orders_values) >= 58
-    ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
-    count_steady_orders = sum(
-        1 for v in orders_values if v["value"] == stable_orders_value
-    )
-    assert (
-        count_steady_orders >= 55
-    ), f"Expected >= 55 steady {time_aggregation} values ({stable_orders_value}) for /orders, got {count_steady_orders}"
-    # check for counter reset effects - there should be some non-standard values
-    non_standard_orders = [
-        v["value"] for v in orders_values if v["value"] != stable_orders_value
-    ]
-    assert (
-        len(non_standard_orders) >= 2
-    ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
-    # post-reset value should be higher (new counter value / interval)
-    high_rate_orders = [v for v in non_standard_orders if v > stable_orders_value]
-    assert (
-        len(high_rate_orders) >= 1
-    ), f"Expected at least one high {time_aggregation} value after counter reset, got {non_standard_orders}"
-
-    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes
-    users_values = endpoint_values["/users"]
-    assert (
-        len(users_values) >= 54
-    ), f"Expected >= 54 values for /users, got {len(users_values)}"
-    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
-    # most values should be 0 (flat periods between increments)
-    assert (
-        count_zero_users >= 40
-    ), f"Expected >= 40 zero {time_aggregation} values for /users (sparse data), got {count_zero_users}"
-    # non-zero values should be 0.0167 (1/60 increment rate)
-    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
-    count_increment_rate = sum(1 for v in non_zero_users if v == spike_users_value)
-    assert (
-        count_increment_rate >= 8
-    ), f"Expected >= 8 increment {time_aggregation} values ({spike_users_value}) for /users, got {count_increment_rate}"
 
 
 @pytest.mark.parametrize(

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

@@ -4,7 +4,7 @@ Look at the histogram_data_1h.jsonl file for the relevant data
 
 from datetime import datetime, timedelta, timezone
 from http import HTTPStatus
-from typing import Callable, List
+from typing import Callable, List, Optional, Union
 
 import pytest
 
@@ -13,13 +13,16 @@ from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
 from fixtures.metrics import Metrics
 from fixtures.querier import (
     build_builder_query,
+    build_order_by,
     get_all_series,
     get_series_values,
     make_query_request,
 )
 from fixtures.utils import get_testdata_file_path
 
+
 FILE = get_testdata_file_path("histogram_data_1h.jsonl")
+FILE_WITH_MANY_GROUPS = get_testdata_file_path("histogram_data_1h_many_groups.jsonl")
 
 
 @pytest.mark.parametrize(
@@ -521,4 +524,564 @@ def test_histogram_percentile_for_delta_service(
     assert len(result_values) == 60
     assert result_values[0]["value"] == zeroth_value
     assert result_values[1]["value"] == first_value
-    assert result_values[-1]["value"] == last_value
+    assert result_values[-1]["value"] == last_value
+
+
+def _assert_series_endpoint_labels(
+    series: list,
+    expected_endpoints: Union[set, List[str]],
+    prefix: str,
+) -> None:
+    labels = [s.get("labels", [{}])[0].get("value", "unknown") for s in series]
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(labels) == expected_endpoints
+        ), f"Expected {prefix} endpoints {expected_endpoints}, got {set(labels)}"
+    else:
+        assert labels == expected_endpoints, (
+            f"Expected {prefix} endpoints in order {expected_endpoints}, got {labels}"
+        )
+
+
+@pytest.mark.parametrize(
+    "order_suffix,order_by,limit,expected_count,expected_endpoints",
+    [
+        (
+            "no_order",
+            None,
+            None,
+            3,
+            ["/checkout", "/health", "/orders"],
+        ),
+        (
+            "asc",
+            [build_order_by("endpoint", "asc")],
+            None,
+            3,
+            ["/checkout", "/health", "/orders"],
+        ),
+        (
+            "asc_lim2",
+            [build_order_by("endpoint", "asc")],
+            2,
+            2,
+            ["/checkout", "/health"],
+        ),
+        (
+            "desc",
+            [build_order_by("endpoint", "desc")],
+            None,
+            3,
+            ["/orders", "/health", "/checkout"],
+        ),
+        (
+            "desc_lim2",
+            [build_order_by("endpoint", "desc")],
+            2,
+            2,
+            ["/orders", "/health"],
+        ),
+        (
+            "asc_metric_name",
+            [build_order_by("count(test_histogram_count_groupby_asc_metric_name)", "asc")],
+            None,
+            3,
+            ["/health", "/orders", "/checkout"], ## health and orders have the same size so they are then sorted endpoint as a tiebreaker
+        ),
+        (
+            "asc_metric_name_lim2",
+            [build_order_by("count(test_histogram_count_groupby_asc_metric_name_lim2)", "asc")],
+            2,
+            2,
+            ["/health", "/orders"],
+        ),
+        (
+            "desc_metric_name",
+            [build_order_by("count(test_histogram_count_groupby_desc_metric_name)", "desc")],
+            None,
+            3,
+            ["/checkout", "/health", "/orders"], ## health and orders have the same size so they are then sorted endpoint as a tiebreaker
+        ),
+        (
+            "desc_metric_name_lim2",
+            [build_order_by("count(test_histogram_count_groupby_desc_metric_name_lim2)", "desc")],
+            2,
+            2,
+            ["/checkout", "/health"],
+        ),
+    ],
+)
+def test_histogram_count_group_by_endpoint(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    order_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_histogram_count_groupby_{order_suffix}"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query_count = build_builder_query(
+        "A",
+        metric_name,
+        "increase",
+        "count",
+        comparisonSpaceAggregationParam={"threshold": 1000, "operator": "<="},
+        group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query_count])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    count_all_series = get_all_series(data, "A")
+
+    assert (
+        len(count_all_series) == expected_count
+    ), f"Expected {expected_count} series, got {len(count_all_series)}"
+
+    _assert_series_endpoint_labels(count_all_series, expected_endpoints, "count")
+
+    count_values = {}
+    for series in count_all_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        count_values[endpoint] = sorted(
+            series.get("values", []), key=lambda x: x["timestamp"]
+        )
+
+    for endpoint, values in count_values.items():
+        for v in values:
+            assert v["value"] >= 0, f"Count for {endpoint} should not be negative: {v['value']}"
+
+    # /health (cumulative, service=api): 59 points, increase starts at 11/min → 69/min
+    if "/health" in count_values:
+        vals = count_values["/health"]
+        assert vals[0]["value"] == 11, f"Expected /health count first=11, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 69, f"Expected /health count last=69, got {vals[-1]['value']}"
+
+    # /orders (cumulative, service=api): same distribution as /health
+    if "/orders" in count_values:
+        vals = count_values["/orders"]
+        assert vals[0]["value"] == 11, f"Expected /orders count first=11, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 69, f"Expected /orders count last=69, got {vals[-1]['value']}"
+
+    # /checkout (delta, service=web): 60 points, zeroth=12345 (raw delta), then 11/min → 69/min
+    if "/checkout" in count_values:
+        vals = count_values["/checkout"]
+        assert vals[0]["value"] == 12345, f"Expected /checkout count zeroth=12345, got {vals[0]['value']}"
+        assert vals[1]["value"] == 11, f"Expected /checkout count first=11, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 69, f"Expected /checkout count last=69, got {vals[-1]['value']}"
+
+
+@pytest.mark.parametrize(
+    "order_suffix,order_by,limit,expected_count,expected_endpoints",
+    [
+        (
+            "no_order",
+            None,
+            None,
+            4,
+            [ "/checkout", "/health", "/orders", "/coupon"],
+        ),
+        (
+            "only_limit",
+            None,
+            1,
+            1,
+            [ "/checkout"], ##health and checkout have the same size so they are then sorted endpoint as a tiebreaker, and only checkout makes the limit
+        ),
+        (
+            "asc",
+            [build_order_by("endpoint", "asc")],
+            None,
+            4,
+            [ "/checkout", "/coupon", "/health", "/orders"],
+        ),
+        (
+            "asc_lim2",
+            [build_order_by("endpoint", "asc")],
+            2,
+            2,
+            ["/checkout", "/coupon"],
+        ),
+        (
+            "desc",
+            [build_order_by("endpoint", "desc")],
+            None,
+            4,
+            ["/orders", "/health", "/coupon", "/checkout"],
+        ),
+        (
+            "desc_lim2",
+            [build_order_by("endpoint", "desc")],
+            2,
+            2,
+            ["/orders", "/health"],
+        ),
+        (
+            "asc_metric_name",
+            [build_order_by("p75(test_histogram_p75_groupby_asc_metric_name)", "asc")],
+            None,
+            4,
+            ["/coupon", "/orders", "/checkout", "/health"], ## health and checkout have the same size so they are then sorted endpoint as a tiebreaker
+        ),
+        (
+            "asc_metric_name_lim2",
+            [build_order_by("p75(test_histogram_p75_groupby_asc_metric_name_lim2)", "asc")],
+            2,
+            2,
+            ["/coupon", "/orders"],
+        ),
+        (
+            "asc_metric_name_lim3",
+            [build_order_by("p75(test_histogram_p75_groupby_asc_metric_name_lim3)", "asc")],
+            3,
+            3,
+            ["/coupon", "/orders", "/checkout"], ##health and checkout have the same size so they are then sorted endpoint as a tiebreaker, and only checkout makes the limit
+        ),
+        (
+            "desc_metric_name",
+            [build_order_by("p75(test_histogram_p75_groupby_desc_metric_name)", "desc")],
+            None,
+            4,
+            [ "/checkout", "/health", "/orders", "/coupon"],
+        ),
+        (
+            "desc_metric_name_lim2",
+            [build_order_by("p75(test_histogram_p75_groupby_desc_metric_name_lim2)", "desc")],
+            2,
+            2,
+            [ "/checkout", "/health"],
+        ),
+        (
+            "desc_metric_name_lim2",
+            [build_order_by("p75(test_histogram_p75_groupby_desc_metric_name_lim2)", "desc")],
+            1,
+            1,
+            [ "/checkout"], ##health and checkout have the same size so they are then sorted endpoint as a tiebreaker, and only checkout makes the limit
+        ),
+    ],
+)
+def test_histogram_percentile_group_by_endpoint(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    order_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_histogram_p75_groupby_{order_suffix}"
+
+    metrics = Metrics.load_from_file(
+        FILE_WITH_MANY_GROUPS,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query_p75 = build_builder_query(
+        "A",
+        metric_name,
+        "doesnotreallymatter",
+        "p75",
+        group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query_p75])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    p75_series = get_all_series(data, "A")
+
+    for series in p75_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+
+    assert (
+        len(p75_series) == expected_count
+    ), f"Expected {expected_count} p75 series, got {len(p75_series)}"
+
+    _assert_series_endpoint_labels(p75_series, expected_endpoints, "p75")
+
+    p75_values = {}
+    for series in p75_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        p75_values[endpoint] = sorted(
+            series.get("values", []), key=lambda x: x["timestamp"]
+        )
+
+    for endpoint, values in p75_values.items():
+        for v in values:
+            assert v["value"] >= 0, f"p75 for {endpoint} should not be negative: {v['value']}"
+
+    # /health (cumulative, service=api)
+    if "/health" in p75_values:
+        vals = p75_values["/health"]
+        assert vals[0]["value"] == 6000, f"Expected /health p75 first=6000, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 6000, f"Expected /health p75 last=6000, got {vals[-1]['value']}"
+
+    # /orders (cumulative, service=api): same distribution as /health
+    if "/orders" in p75_values:
+        vals = p75_values["/orders"]
+        assert vals[0]["value"] == 4500, f"Expected /orders p75 first=4500, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 4500, f"Expected /orders p75 last=4500, got {vals[-1]['value']}"
+
+    # /checkout (delta, service=web): 60 points
+    if "/checkout" in p75_values:
+        vals = p75_values["/checkout"]
+        assert vals[0]["value"] == 6000, f"Expected /checkout p75 zeroth=6000, got {vals[0]['value']}"
+        assert vals[1]["value"] == 6000, f"Expected /checkout p75 first=6000, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 6000, f"Expected /checkout p75 last=6000, got {vals[-1]['value']}"
+
+    # /coupon (delta, service=web): 60 points
+    if "/coupon" in p75_values:
+        vals = p75_values["/coupon"]
+        assert vals[0]["value"] == 1125, f"Expected /coupon p75 zeroth=1125, got {vals[0]['value']}"
+        assert vals[1]["value"] == 1125, f"Expected /coupon p75 first=1125, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 1125, f"Expected /coupon p75 last=1125, got {vals[-1]['value']}"
+
+
+@pytest.mark.parametrize(
+    "order_suffix,order_by,limit,expected_count,expected_endpoints, expected_status_codes",
+    [
+        (
+            "no_order",
+            None,
+            None,
+            5,
+            [ "/checkout", "/health", "/orders", "/coupon", "/coupon"], ## coupon has 200 and 500 status codes so it will appear twice
+            [ "200", "200", "200", "200", "500"],
+        ),
+        (
+            "only_limit",
+            None,
+            1,
+            1,
+            [ "/checkout"], ##health and checkout have the same size so they are then sorted endpoint as a tiebreaker, and only checkout makes the limit
+            [ "200"]
+        ),
+        (
+            "asc_endpoint",
+            [build_order_by("endpoint", "asc")],
+            None,
+            5,
+            [ "/checkout", "/coupon", "/coupon", "/health", "/orders"],
+            [ "200", "200", "500", "200", "200"],
+        ),
+        (
+            "asc_endpoint_status_code",
+            [build_order_by("endpoint", "asc"), build_order_by("status_code", "asc")],
+            None,
+            5,
+            [ "/checkout", "/coupon", "/coupon", "/health", "/orders"],
+            [ "200", "200", "500", "200", "200"],
+        ),
+        (
+            "asc_status_code_endpoint",
+            [build_order_by("status_code", "asc"), build_order_by("endpoint", "asc")],
+            None,
+            5,
+            [ "/checkout", "/coupon", "/health", "/orders", "/coupon"],
+            [ "200", "200", "200", "200", "500"],
+        ),
+        (
+            "asc_endpoint_limit_2",
+            [build_order_by("endpoint", "asc")],
+            2,
+            2,
+            [ "/checkout", "/coupon"],
+            [ "200", "200"],
+        ),
+        (
+            "asc_endpoint_status_code_limit_2",
+            [build_order_by("endpoint", "asc"), build_order_by("status_code", "asc")],
+            2,
+            2,
+            [ "/checkout", "/coupon"],
+            [ "200", "200"],
+        ),
+        (
+            "asc_status_code_endpoint_limit_4",
+            [build_order_by("status_code", "asc"), build_order_by("endpoint", "asc")],
+            4,
+            4,
+            [ "/checkout", "/coupon", "/health", "/orders"],
+            [ "200", "200", "200", "200"],
+        ),
+        (
+            "desc_endpoint",
+            [build_order_by("endpoint", "desc")],
+            None,
+            5,
+            ["/orders", "/health", "/coupon", "/coupon", "/checkout"],
+            [ "200", "200", "200", "500", "200"],
+        ),
+        (
+            "desc_endpoint_status_code",
+            [build_order_by("endpoint", "desc"), build_order_by("status_code", "desc")],
+            None,
+            5,
+            ["/orders", "/health", "/coupon", "/coupon", "/checkout"],
+            [ "200", "200", "500", "200", "200"],
+        ),
+        (
+            "desc_status_code_endpoint",
+            [build_order_by("status_code", "desc"), build_order_by("endpoint", "desc")],
+            None,
+            5,
+            ["/coupon", "/orders", "/health", "/coupon", "/checkout"],
+            [ "500", "200", "200", "200", "200"],
+        ),
+        (
+            "desc_endpoint_limit2",
+            [build_order_by("endpoint", "desc")],
+            3,
+            3,
+            ["/orders", "/health", "/coupon"],
+            [ "200", "200", "200"],
+        ),
+        (
+            "desc_endpoint_status_code_limit3",
+            [build_order_by("endpoint", "desc"), build_order_by("status_code", "desc")],
+            3,
+            3,
+            ["/orders", "/health", "/coupon"],
+            [ "200", "200", "500"],
+        ),
+        (
+            "desc_status_code_endpoint_limit2",
+            [build_order_by("status_code", "desc"), build_order_by("endpoint", "desc")],
+            2,
+            2,
+            ["/coupon", "/orders"],
+            [ "500", "200"],
+        ),
+    ],
+)
+def test_histogram_percentile_group_by_endpoint_and_status_code(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    order_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
+    expected_status_codes: Union[set, List[str]],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_histogram_p75_groupby_{order_suffix}"
+
+    metrics = Metrics.load_from_file(
+        FILE_WITH_MANY_GROUPS,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query_p75 = build_builder_query(
+        "A",
+        metric_name,
+        "doesnotreallymatter",
+        "p75",
+        group_by=["endpoint", "status_code"],
+        order_by=order_by,
+        limit=limit,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query_p75])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    p75_series = get_all_series(data, "A")
+
+    for series in p75_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        status_code = series.get("labels", [{}])[1].get("value", "unknown")
+
+    assert (
+        len(p75_series) == expected_count
+    ), f"Expected {expected_count} p75 series, got {len(p75_series)}"
+
+    _assert_series_endpoint_labels(p75_series, expected_endpoints, "p75")
+    
+    endpoints = [s.get("labels", [{}])[0].get("value", "unknown") for s in p75_series]
+    assert endpoints == expected_endpoints, (
+        f"Expected p75 endpoints in order {expected_endpoints}, got {endpoints}"
+    )
+    status_codes = [s.get("labels", [{}])[1].get("value", "unknown") for s in p75_series]
+    assert status_codes == expected_status_codes, (
+        f"Expected p75 endpoints in order {expected_status_codes}, got {status_codes}"
+    )
+
+    p75_values = {}
+    for series in p75_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        status_code = series.get("labels", [{}])[1].get("value", "unknown")
+        p75_values[endpoint+status_code] = sorted(
+            series.get("values", []), key=lambda x: x["timestamp"]
+        )
+
+    for endpoint, values in p75_values.items():
+        for v in values:
+            assert v["value"] >= 0, f"p75 for {endpoint} should not be negative: {v['value']}"
+
+    # /health (cumulative, service=api)
+    if "/health200" in p75_values:
+        vals = p75_values["/health200"]
+        assert vals[0]["value"] == 6000, f"Expected /health p75 first=6000, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 6000, f"Expected /health p75 last=6000, got {vals[-1]['value']}"
+
+    # /orders (cumulative, service=api): same distribution as /health
+    if "/orders200" in p75_values:
+        vals = p75_values["/orders200"]
+        assert vals[0]["value"] == 4500, f"Expected /orders p75 first=4500, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 4500, f"Expected /orders p75 last=4500, got {vals[-1]['value']}"
+
+    # /checkout (delta, service=web): 60 points
+    if "/checkout200" in p75_values:
+        vals = p75_values["/checkout200"]
+        assert vals[0]["value"] == 6000, f"Expected /checkout p75 zeroth=6000, got {vals[0]['value']}"
+        assert vals[1]["value"] == 6000, f"Expected /checkout p75 first=6000, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 6000, f"Expected /checkout p75 last=6000, got {vals[-1]['value']}"
+
+    # /coupon (delta, service=web): 60 points
+    if "/coupon200" in p75_values:
+        vals = p75_values["/coupon200"]
+        assert vals[0]["value"] == 1250, f"Expected /coupon200 p75 zeroth=1250, got {vals[0]['value']}"
+        assert vals[1]["value"] == 1250, f"Expected /coupon200 p75 first=1250, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 1250, f"Expected /coupon200 p75 last=1250, got {vals[-1]['value']}"
+
+    if "/coupon500" in p75_values:
+        vals = p75_values["/coupon500"]
+        assert vals[0]["value"] == 750, f"Expected /coupon500 p75 zeroth=750, got {vals[0]['value']}"
+        assert vals[1]["value"] == 750, f"Expected /coupon500 p75 first=750, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 750, f"Expected /coupon500 p75 last=750, got {vals[-1]['value']}"

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

@@ -1,6 +1,6 @@
 from datetime import datetime, timedelta, timezone
 from http import HTTPStatus
-from typing import Callable, List
+from typing import Callable, List, Optional, Union
 
 import pytest
 
@@ -9,6 +9,8 @@ from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
 from fixtures.metrics import Metrics
 from fixtures.querier import (
     build_builder_query,
+    build_order_by,
+    get_all_series,
     get_series_values,
     make_query_request,
 )
@@ -139,3 +141,137 @@ def test_for_multiple_aggregations(
     assert result_values[19]["value"] == twentieth_min_val
     assert result_values[20]["value"] == twenty_first_min_val
     assert result_values[30]["value"] == thirty_first_min_val
+
+
+@pytest.mark.parametrize(
+    "metric_suffix,order_by,limit,expected_count,expected_services",
+    [
+        (
+            "no_order",
+            None,  # default ordering: desc by avg of all metric values for a group
+            None,
+            3,
+            ["lab", "web", "api"],  # sum of all values: lab=42000, api=36000, web=34000. avg of all sums: lab=700, api=600, web=680
+        ),
+        (
+            "only_limit",
+            None,
+            2,
+            2,
+            ["lab", "web"],  # top 2 by default desc: lab=42000, api=36000
+        ),
+        (
+            "asc",
+            [build_order_by("service", "asc")],
+            None,
+            3,
+            ["api", "lab", "web"],
+        ),
+        (
+            "asc_lim2",
+            [build_order_by("service", "asc")],
+            2,
+            2,
+            ["api", "lab"],
+        ),
+        (
+            "desc",
+            [build_order_by("service", "desc")],
+            None,
+            3,
+            ["web", "lab", "api"],
+        ),
+        (
+            "desc_lim2",
+            [build_order_by("service", "desc")],
+            2,
+            2,
+            ["web", "lab"],
+        ),
+        (
+            "asc_metric_name",
+            [build_order_by("sum(test_gauge_groupby_asc_metric_name)", "asc")],
+            None,
+            3,
+            ["api", "web", "lab"],
+        ),
+        (
+            "asc_metric_name_lim2",
+            [build_order_by("sum(test_gauge_groupby_asc_metric_name_lim2)", "asc")],
+            2,
+            2,
+            ["api", "web"],
+        ),
+        (
+            "desc_metric_name",
+            [build_order_by("sum(test_gauge_groupby_desc_metric_name)", "desc")],
+            None,
+            3,
+            ["lab", "web", "api"], 
+        ),
+        (
+            "desc_metric_name_lim2",
+            [build_order_by("sum(test_gauge_groupby_desc_metric_name_lim2)", "desc")],
+            2,
+            2,
+            ["lab", "web"],
+        ),
+    ],
+)
+def test_gauge_group_by_service(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    metric_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_services: Union[set, List[str]],
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_gauge_groupby_{metric_suffix}"
+
+    metrics = Metrics.load_from_file(
+        FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        "max",
+        "sum",
+        group_by=["service"],
+        order_by=order_by,
+        limit=limit,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    all_series = get_all_series(data, "A")
+
+    assert (
+        len(all_series) == expected_count
+    ), f"Expected {expected_count} series, got {len(all_series)}"
+
+    service_labels = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in all_series
+    ]
+
+    if isinstance(expected_services, set):
+        assert (
+            set(service_labels) == expected_services
+        ), f"Expected services {expected_services}, got {set(service_labels)}"
+    else:
+        assert service_labels == expected_services, (
+            f"Expected services {expected_services}, got {service_labels}"
+        )

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

@@ -5,13 +5,16 @@ Look at the delta_counters_1h.jsonl file for the relevant data
 import os
 from datetime import datetime, timedelta, timezone
 from http import HTTPStatus
-from typing import Any, Callable, List
+from typing import Any, Callable, List, Optional, Union
+
+import pytest
 
 from fixtures import types
 from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
 from fixtures.metrics import Metrics
 from fixtures.querier import (
     build_builder_query,
+    build_order_by,
     get_all_series,
     get_series_values,
     make_query_request,
@@ -69,16 +72,61 @@ def test_rate_with_steady_values_and_reset(
         assert v["value"] >= 0, f"Rate should not be negative: {v['value']}"
 
 
+@pytest.mark.parametrize(
+    "order_suffix,order_by,limit,expected_count,expected_endpoints",
+    [
+        (
+            "no_order",
+            None,
+            None,
+            5,
+            {"/products", "/health", "/checkout", "/orders", "/users"},
+        ),
+        (
+            "asc",
+            [build_order_by("endpoint", "asc")],
+            None,
+            5,
+            ["/checkout", "/health", "/orders", "/products", "/users"],
+        ),
+        (
+            "asc_lim3",
+            [build_order_by("endpoint", "asc")],
+            3,
+            3,
+            ["/checkout", "/health", "/orders"],
+        ),
+        (
+            "desc",
+            [build_order_by("endpoint", "desc")],
+            None,
+            5,
+            ["/users", "/products", "/orders", "/health", "/checkout"],
+        ),
+        (
+            "desc_lim3",
+            [build_order_by("endpoint", "desc")],
+            3,
+            3,
+            ["/users", "/products", "/orders"],
+        ),
+    ],
+)
 def test_rate_group_by_endpoint(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token: Callable[[str, str], str],
     insert_metrics: Callable[[List[Metrics]], None],
+    order_suffix: str,
+    order_by: Optional[List],
+    limit: Optional[int],
+    expected_count: int,
+    expected_endpoints: Union[set, List[str]],
 ) -> None:
     now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
     start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
     end_ms = int(now.timestamp() * 1000)
-    metric_name = "test_rate_groupby"
+    metric_name = f"test_rate_groupby_{order_suffix}"
 
     metrics = Metrics.load_from_file(
         DELTA_COUNTERS_FILE,
@@ -94,6 +142,8 @@ def test_rate_group_by_endpoint(
         "rate",
         "sum",
         group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
     )
 
     response = make_query_request(signoz, token, start_ms, end_ms, [query])
@@ -102,10 +152,23 @@ def test_rate_group_by_endpoint(
     data = response.json()
     all_series = get_all_series(data, "A")
 
-    # Should have 5 different endpoints
     assert (
-        len(all_series) == 5
-    ), f"Expected 5 series for 5 endpoints, got {len(all_series)}"
+        len(all_series) == expected_count
+    ), f"Expected {expected_count} series, got {len(all_series)}"
+
+    endpoint_labels = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in all_series
+    ]
+
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(endpoint_labels) == expected_endpoints
+        ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_labels)}"
+    else:
+        assert endpoint_labels == expected_endpoints, (
+            f"Expected endpoints {expected_endpoints}, got {endpoint_labels}"
+        )
 
     # endpoint -> values
     endpoint_values = {}
@@ -114,11 +177,6 @@ def test_rate_group_by_endpoint(
         values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
         endpoint_values[endpoint] = values
 
-    expected_endpoints = {"/products", "/health", "/checkout", "/orders", "/users"}
-    assert (
-        set(endpoint_values.keys()) == expected_endpoints
-    ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_values.keys())}"
-
     # at no point rate should be negative
     for endpoint, values in endpoint_values.items():
         for v in values:
@@ -128,93 +186,95 @@ def test_rate_group_by_endpoint(
 
     # /health: 60 data points (t01-t60), steady +10/min
     # rate = 10/60 = 0.167
-    health_values = endpoint_values["/health"]
-    assert (
-        len(health_values) == 60
-    ), f"Expected 60 values for /health, got {len(health_values)}"
-    count_steady_health = sum(1 for v in health_values if v["value"] == 0.167)
-    assert (
-        count_steady_health == 60
-    ), f"Expected == 60 steady rate values (0.167) for /health, got {count_steady_health}"
-    # all /health rates should be 0.167 except possibly first/last due to boundaries
-    for v in health_values[1:-1]:
-        assert v["value"] == 0.167, f"Expected /health rate 0.167, got {v['value']}"
+    if "/health" in endpoint_values:
+        health_values = endpoint_values["/health"]
+        assert (
+            len(health_values) == 60
+        ), f"Expected 60 values for /health, got {len(health_values)}"
+        count_steady_health = sum(1 for v in health_values if v["value"] == 0.167)
+        assert (
+            count_steady_health == 60
+        ), f"Expected == 60 steady rate values (0.167) for /health, got {count_steady_health}"
+        # all /health rates should be 0.167 except possibly first/last due to boundaries
+        for v in health_values[1:-1]:
+            assert v["value"] == 0.167, f"Expected /health rate 0.167, got {v['value']}"
 
     # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
     # rate = 20/60 = 0.333, gap causes lower averaged rate at boundary
-    products_values = endpoint_values["/products"]
-    assert (
-        len(products_values) == 51
-    ), f"Expected 51 values for /products, got {len(products_values)}"
-    count_steady_products = sum(1 for v in products_values if v["value"] == 0.333)
-
-    assert (
-        count_steady_products == 51
-    ), f"Expected 51 steady rate values (0.333) for /products, got {count_steady_products}"
+    if "/products" in endpoint_values:
+        products_values = endpoint_values["/products"]
+        assert (
+            len(products_values) == 51
+        ), f"Expected 51 values for /products, got {len(products_values)}"
+        count_steady_products = sum(1 for v in products_values if v["value"] == 0.333)
+        assert (
+            count_steady_products == 51
+        ), f"Expected 51 steady rate values (0.333) for /products, got {count_steady_products}"
 
     # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
     # normal rate = 1/60 = 0.0167, spike rate = 50/60 = 0.833
-    checkout_values = endpoint_values["/checkout"]
-    assert (
-        len(checkout_values) == 61
-    ), f"Expected 61 values for /checkout, got {len(checkout_values)}"
-    count_steady_checkout = sum(1 for v in checkout_values if v["value"] == 0.0167)
-    assert (
-        count_steady_checkout == 56
-    ), f"Expected 56 steady rate values (0.0167) for /checkout, got {count_steady_checkout}"
-    # check that spike values exist (traffic spike +50/min at t40-t44)
-    count_spike_checkout = sum(1 for v in checkout_values if v["value"] == 0.833)
-    assert (
-        count_spike_checkout == 5
-    ), f"Expected 5 spike rate values (0.833) for /checkout, got {count_spike_checkout}"
-
-    # spike values should be consecutive
-    spike_indices = [
-        i for i, v in enumerate[Any](checkout_values) if v["value"] == 0.833
-    ]
-    assert len(spike_indices) == 5, f"Expected 5 spike indices, got {spike_indices}"
-    # consecutiveness
-    for i in range(1, len(spike_indices)):
+    if "/checkout" in endpoint_values:
+        checkout_values = endpoint_values["/checkout"]
         assert (
-            spike_indices[i] == spike_indices[i - 1] + 1
-        ), f"Spike indices should be consecutive, got {spike_indices}"
+            len(checkout_values) == 61
+        ), f"Expected 61 values for /checkout, got {len(checkout_values)}"
+        count_steady_checkout = sum(1 for v in checkout_values if v["value"] == 0.0167)
+        assert (
+            count_steady_checkout == 56
+        ), f"Expected 56 steady rate values (0.0167) for /checkout, got {count_steady_checkout}"
+        # check that spike values exist (traffic spike +50/min at t40-t44)
+        count_spike_checkout = sum(1 for v in checkout_values if v["value"] == 0.833)
+        assert (
+            count_spike_checkout == 5
+        ), f"Expected 5 spike rate values (0.833) for /checkout, got {count_spike_checkout}"
+        # spike values should be consecutive
+        spike_indices = [
+            i for i, v in enumerate[Any](checkout_values) if v["value"] == 0.833
+        ]
+        assert len(spike_indices) == 5, f"Expected 5 spike indices, got {spike_indices}"
+        for i in range(1, len(spike_indices)):
+            assert (
+                spike_indices[i] == spike_indices[i - 1] + 1
+            ), f"Spike indices should be consecutive, got {spike_indices}"
 
     # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
     # rate = 5/60 = 0.0833
     # reset at t31 causes: rate at t30 includes gap (lower), t31 has high rate after reset
-    orders_values = endpoint_values["/orders"]
-    assert (
-        len(orders_values) == 60
-    ), f"Expected 59 values for /orders, got {len(orders_values)}"
-    count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
-    assert (
-        count_steady_orders == 58
-    ), f"Expected 58 steady rate values (0.0833) for /orders, got {count_steady_orders}"
-    # check for counter reset effects - there should be some non-standard values
-    non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
-    assert (
-        len(non_standard_orders) == 2
-    ), f"Expected 2 non-standard values due to counter reset, got {non_standard_orders}"
-    # post-reset value should be higher (new counter value / interval)
-    high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
-    assert (
-        len(high_rate_orders) == 1
-    ), f"Expected one high rate value after counter reset, got {non_standard_orders}"
+    if "/orders" in endpoint_values:
+        orders_values = endpoint_values["/orders"]
+        assert (
+            len(orders_values) == 60
+        ), f"Expected 60 values for /orders, got {len(orders_values)}"
+        count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
+        assert (
+            count_steady_orders == 58
+        ), f"Expected 58 steady rate values (0.0833) for /orders, got {count_steady_orders}"
+        # check for counter reset effects - there should be some non-standard values
+        non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
+        assert (
+            len(non_standard_orders) == 2
+        ), f"Expected 2 non-standard values due to counter reset, got {non_standard_orders}"
+        # post-reset value should be higher (new counter value / interval)
+        high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
+        assert (
+            len(high_rate_orders) == 1
+        ), f"Expected one high rate value after counter reset, got {non_standard_orders}"
 
     # /users: 56 data points (t05-t60), sparse +1 every 5 minutes (12 of them)
     # Rate = 1/60 = 0.0167 during increment, 0 during flat periods
-    users_values = endpoint_values["/users"]
-    assert (
-        len(users_values) == 56
-    ), f"Expected 56 values for /users, got {len(users_values)}"
-    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
-    # most values should be 0 (flat periods between increments)
-    assert (
-        count_zero_users == 44
-    ), f"Expected 44 zero rate values for /users (sparse data), got {count_zero_users}"
-    # non-zero values should be 0.0167 (1/60 increment rate)
-    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
-    count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
-    assert (
-        count_increment_rate == 12
-    ), f"Expected 12 increment rate values (0.0167) for /users, got {count_increment_rate}"
+    if "/users" in endpoint_values:
+        users_values = endpoint_values["/users"]
+        assert (
+            len(users_values) == 56
+        ), f"Expected 56 values for /users, got {len(users_values)}"
+        count_zero_users = sum(1 for v in users_values if v["value"] == 0)
+        # most values should be 0 (flat periods between increments)
+        assert (
+            count_zero_users == 44
+        ), f"Expected 44 zero rate values for /users (sparse data), got {count_zero_users}"
+        # non-zero values should be 0.0167 (1/60 increment rate)
+        non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
+        count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
+        assert (
+            count_increment_rate == 12
+        ), f"Expected 12 increment rate values (0.0167) for /users, got {count_increment_rate}"