chore: rename vars

pkg/modules/tracefunnel/impltracefunnel/handler.go

@@ -21,7 +21,7 @@ func NewHandler(module tracefunnel.Module) tracefunnel.Handler {
 	return &handler{module: module}
 }
 
-func (handler *handler) Create(rw http.ResponseWriter, r *http.Request) {
+func (handler *handler) New(rw http.ResponseWriter, r *http.Request) {
 	var req tf.PostableFunnel
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		render.Error(rw, err)
@@ -34,7 +34,7 @@ func (handler *handler) Create(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	funnel, err := handler.module.Create(r.Context(), req.Name, claims.Email, valuer.MustNewUUID(claims.OrgID))
+	funnel, err := handler.module.Create(r.Context(), req.Timestamp, req.Name, valuer.MustNewUUID(claims.UserID), valuer.MustNewUUID(claims.OrgID))
 	if err != nil {
 		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
 			errors.CodeInvalidInput,
@@ -42,7 +42,7 @@ func (handler *handler) Create(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	response := tf.ConstructFunnelResponse(funnel)
+	response := tf.ConstructFunnelResponse(funnel, &claims)
 	render.Success(rw, http.StatusOK, response)
 }
 
@@ -59,6 +59,12 @@ func (handler *handler) UpdateSteps(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
+	updatedAt, err := tf.ValidateAndConvertTimestamp(req.Timestamp)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
 	funnel, err := handler.module.Get(r.Context(), req.FunnelID, valuer.MustNewUUID(claims.OrgID))
 	if err != nil {
 		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
@@ -73,15 +79,33 @@ func (handler *handler) UpdateSteps(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	funnel.Update(req.Name, req.Description, steps, claims.Email)
-	if err := handler.module.Update(r.Context(), funnel); err != nil {
+	funnel.Steps = steps
+	funnel.UpdatedAt = updatedAt
+	funnel.UpdatedBy = claims.UserID
+
+	if req.Name != "" {
+		funnel.Name = req.Name
+	}
+	if req.Description != "" {
+		funnel.Description = req.Description
+	}
+
+	if err := handler.module.Update(r.Context(), funnel, valuer.MustNewUUID(claims.UserID)); err != nil {
 		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
 			errors.CodeInvalidInput,
 			"failed to update funnel in database: %v", err))
 		return
 	}
 
-	response := tf.ConstructFunnelResponse(funnel)
+	updatedFunnel, err := handler.module.Get(r.Context(), funnel.ID, valuer.MustNewUUID(claims.OrgID))
+	if err != nil {
+		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"failed to get updated funnel: %v", err))
+		return
+	}
+
+	response := tf.ConstructFunnelResponse(updatedFunnel, &claims)
 	render.Success(rw, http.StatusOK, response)
 }
 
@@ -98,6 +122,12 @@ func (handler *handler) UpdateFunnel(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
+	updatedAt, err := tf.ValidateAndConvertTimestamp(req.Timestamp)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
 	vars := mux.Vars(r)
 	funnelID := vars["funnel_id"]
 
@@ -109,15 +139,32 @@ func (handler *handler) UpdateFunnel(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	funnel.Update(req.Name, req.Description, nil, claims.Email)
-	if err := handler.module.Update(r.Context(), funnel); err != nil {
+	funnel.UpdatedAt = updatedAt
+	funnel.UpdatedBy = claims.UserID
+
+	if req.Name != "" {
+		funnel.Name = req.Name
+	}
+	if req.Description != "" {
+		funnel.Description = req.Description
+	}
+
+	if err := handler.module.Update(r.Context(), funnel, valuer.MustNewUUID(claims.UserID)); err != nil {
 		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
 			errors.CodeInvalidInput,
 			"failed to update funnel in database: %v", err))
 		return
 	}
 
-	response := tf.ConstructFunnelResponse(funnel)
+	updatedFunnel, err := handler.module.Get(r.Context(), funnel.ID, valuer.MustNewUUID(claims.OrgID))
+	if err != nil {
+		render.Error(rw, errors.Newf(errors.TypeInvalidInput,
+			errors.CodeInvalidInput,
+			"failed to get updated funnel: %v", err))
+		return
+	}
+
+	response := tf.ConstructFunnelResponse(updatedFunnel, &claims)
 	render.Success(rw, http.StatusOK, response)
 }
 
@@ -138,7 +185,7 @@ func (handler *handler) List(rw http.ResponseWriter, r *http.Request) {
 
 	var response []tf.GettableFunnel
 	for _, f := range funnels {
-		response = append(response, tf.ConstructFunnelResponse(f))
+		response = append(response, tf.ConstructFunnelResponse(f, &claims))
 	}
 
 	render.Success(rw, http.StatusOK, response)
@@ -162,7 +209,7 @@ func (handler *handler) Get(rw http.ResponseWriter, r *http.Request) {
 			"funnel not found: %v", err))
 		return
 	}
-	response := tf.ConstructFunnelResponse(funnel)
+	response := tf.ConstructFunnelResponse(funnel, &claims)
 	render.Success(rw, http.StatusOK, response)
 }
 

pkg/modules/tracefunnel/impltracefunnel/handler_test.go

@@ -0,0 +1,173 @@
+package impltracefunnel
+
+import (
+	"context"
+	"encoding/json"
+	"net/http"
+	"net/http/httptest"
+	"testing"
+
+	"github.com/SigNoz/signoz/pkg/types"
+	"github.com/SigNoz/signoz/pkg/types/authtypes"
+	traceFunnels "github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
+	"github.com/SigNoz/signoz/pkg/valuer"
+	"github.com/gorilla/mux"
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/mock"
+)
+
+type MockModule struct {
+	mock.Mock
+}
+
+func (m *MockModule) Create(ctx context.Context, timestamp int64, name string, userID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, timestamp, name, userID, orgID)
+	return args.Get(0).(*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockModule) Get(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, funnelID, orgID)
+	return args.Get(0).(*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockModule) Update(ctx context.Context, funnel *traceFunnels.StorableFunnel, userID valuer.UUID) error {
+	args := m.Called(ctx, funnel, userID)
+	return args.Error(0)
+}
+
+func (m *MockModule) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, orgID)
+	return args.Get(0).([]*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockModule) Delete(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) error {
+	args := m.Called(ctx, funnelID, orgID)
+	return args.Error(0)
+}
+
+func (m *MockModule) Save(ctx context.Context, funnel *traceFunnels.StorableFunnel, userID valuer.UUID, orgID valuer.UUID) error {
+	args := m.Called(ctx, funnel, userID, orgID)
+	return args.Error(0)
+}
+
+func (m *MockModule) GetFunnelMetadata(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) (int64, int64, string, error) {
+	args := m.Called(ctx, funnelID, orgID)
+	return args.Get(0).(int64), args.Get(1).(int64), args.String(2), args.Error(3)
+}
+
+func TestHandler_List(t *testing.T) {
+	mockModule := new(MockModule)
+	handler := NewHandler(mockModule)
+
+	req := httptest.NewRequest(http.MethodGet, "/api/v1/trace-funnels/list", nil)
+
+	orgID := valuer.GenerateUUID()
+	claims := authtypes.Claims{
+		OrgID: orgID.String(),
+	}
+	req = req.WithContext(authtypes.NewContextWithClaims(req.Context(), claims))
+
+	rr := httptest.NewRecorder()
+
+	funnel1ID := valuer.GenerateUUID()
+	funnel2ID := valuer.GenerateUUID()
+	expectedFunnels := []*traceFunnels.StorableFunnel{
+		{
+			Identifiable: types.Identifiable{
+				ID: funnel1ID,
+			},
+			Name:  "funnel-1",
+			OrgID: orgID,
+		},
+		{
+			Identifiable: types.Identifiable{
+				ID: funnel2ID,
+			},
+			Name:  "funnel-2",
+			OrgID: orgID,
+		},
+	}
+
+	mockModule.On("List", req.Context(), orgID).Return(expectedFunnels, nil)
+
+	handler.List(rr, req)
+
+	assert.Equal(t, http.StatusOK, rr.Code)
+
+	var response struct {
+		Status string                        `json:"status"`
+		Data   []traceFunnels.GettableFunnel `json:"data"`
+	}
+	err := json.Unmarshal(rr.Body.Bytes(), &response)
+	assert.NoError(t, err)
+	assert.Equal(t, "success", response.Status)
+	assert.Len(t, response.Data, 2)
+	assert.Equal(t, "funnel-1", response.Data[0].FunnelName)
+	assert.Equal(t, "funnel-2", response.Data[1].FunnelName)
+
+	mockModule.AssertExpectations(t)
+}
+
+func TestHandler_Get(t *testing.T) {
+	mockModule := new(MockModule)
+	handler := NewHandler(mockModule)
+
+	funnelID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+	req := httptest.NewRequest(http.MethodGet, "/api/v1/trace-funnels/"+funnelID.String(), nil)
+	req = mux.SetURLVars(req, map[string]string{"funnel_id": funnelID.String()})
+	req = req.WithContext(authtypes.NewContextWithClaims(req.Context(), authtypes.Claims{
+		OrgID: orgID.String(),
+	}))
+
+	rr := httptest.NewRecorder()
+
+	expectedFunnel := &traceFunnels.StorableFunnel{
+		Identifiable: types.Identifiable{
+			ID: funnelID,
+		},
+		Name:  "test-funnel",
+		OrgID: orgID,
+	}
+
+	mockModule.On("Get", req.Context(), funnelID, orgID).Return(expectedFunnel, nil)
+
+	handler.Get(rr, req)
+
+	assert.Equal(t, http.StatusOK, rr.Code)
+
+	var response struct {
+		Status string                      `json:"status"`
+		Data   traceFunnels.GettableFunnel `json:"data"`
+	}
+	err := json.Unmarshal(rr.Body.Bytes(), &response)
+	assert.NoError(t, err)
+	assert.Equal(t, "success", response.Status)
+	assert.Equal(t, "test-funnel", response.Data.FunnelName)
+	assert.Equal(t, expectedFunnel.OrgID.String(), response.Data.OrgID)
+
+	mockModule.AssertExpectations(t)
+}
+
+func TestHandler_Delete(t *testing.T) {
+	mockModule := new(MockModule)
+	handler := NewHandler(mockModule)
+
+	funnelID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+	req := httptest.NewRequest(http.MethodDelete, "/api/v1/trace-funnels/"+funnelID.String(), nil)
+	req = mux.SetURLVars(req, map[string]string{"funnel_id": funnelID.String()})
+	req = req.WithContext(authtypes.NewContextWithClaims(req.Context(), authtypes.Claims{
+		OrgID: orgID.String(),
+	}))
+
+	rr := httptest.NewRecorder()
+
+	mockModule.On("Delete", req.Context(), funnelID, orgID).Return(nil)
+
+	handler.Delete(rr, req)
+
+	assert.Equal(t, http.StatusOK, rr.Code)
+
+	mockModule.AssertExpectations(t)
+}

pkg/modules/tracefunnel/impltracefunnel/module.go

@@ -2,10 +2,11 @@ package impltracefunnel
 
 import (
 	"context"
+	"time"
 
 	"github.com/SigNoz/signoz/pkg/errors"
 	"github.com/SigNoz/signoz/pkg/modules/tracefunnel"
-	"github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
+	"github.com/SigNoz/signoz/pkg/types"
 	traceFunnels "github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
 	"github.com/SigNoz/signoz/pkg/valuer"
 )
@@ -20,25 +21,58 @@ func NewModule(store traceFunnels.FunnelStore) tracefunnel.Module {
 	}
 }
 
-func (module *module) Create(ctx context.Context, name string, createdBy string, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
-	storable := tracefunneltypes.NewStorableFunnel(name, "", nil, "", createdBy, orgID)
+func (module *module) Create(ctx context.Context, timestamp int64, name string, userID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	funnel := &traceFunnels.StorableFunnel{
+		Name:  name,
+		OrgID: orgID,
+	}
+	funnel.CreatedAt = time.Unix(0, timestamp*1000000) // Convert to nanoseconds
+	funnel.CreatedBy = userID.String()
+
+	// Set up the user relationship
+	funnel.CreatedByUser = &types.User{
+		Identifiable: types.Identifiable{
+			ID: userID,
+		},
+	}
+
+	if funnel.ID.IsZero() {
+		funnel.ID = valuer.GenerateUUID()
+	}
+
+	if funnel.CreatedAt.IsZero() {
+		funnel.CreatedAt = time.Now()
+	}
+	if funnel.UpdatedAt.IsZero() {
+		funnel.UpdatedAt = time.Now()
+	}
+
+	// Set created_by if CreatedByUser is present
+	if funnel.CreatedByUser != nil {
+		funnel.CreatedBy = funnel.CreatedByUser.Identifiable.ID.String()
+	}
+
+	err := module.store.Create(ctx, funnel)
 
-	err := module.store.Create(ctx, storable)
 	if err != nil {
 		return nil, err
 	}
 
-	return storable, nil
+	return funnel, nil
 }
 
-func (module *module) Get(ctx context.Context, id valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
-	return module.store.Get(ctx, id, orgID)
+// Get gets a funnel by ID
+func (module *module) Get(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	return module.store.Get(ctx, funnelID, orgID)
 }
 
-func (module *module) Update(ctx context.Context, funnel *traceFunnels.StorableFunnel) error {
+// Update updates a funnel
+func (module *module) Update(ctx context.Context, funnel *traceFunnels.StorableFunnel, userID valuer.UUID) error {
+	funnel.UpdatedBy = userID.String()
 	return module.store.Update(ctx, funnel)
 }
 
+// List lists all funnels for an organization
 func (module *module) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnels.StorableFunnel, error) {
 	funnels, err := module.store.List(ctx, orgID)
 	if err != nil {
@@ -48,12 +82,14 @@ func (module *module) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunn
 	return funnels, nil
 }
 
-func (module *module) Delete(ctx context.Context, id valuer.UUID, orgID valuer.UUID) error {
-	return module.store.Delete(ctx, id, orgID)
+// Delete deletes a funnel
+func (module *module) Delete(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) error {
+	return module.store.Delete(ctx, funnelID, orgID)
 }
 
-func (module *module) GetFunnelMetadata(ctx context.Context, id valuer.UUID, orgID valuer.UUID) (int64, int64, string, error) {
-	funnel, err := module.store.Get(ctx, id, orgID)
+// GetFunnelMetadata gets metadata for a funnel
+func (module *module) GetFunnelMetadata(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) (int64, int64, string, error) {
+	funnel, err := module.store.Get(ctx, funnelID, orgID)
 	if err != nil {
 		return 0, 0, "", err
 	}

pkg/modules/tracefunnel/impltracefunnel/store.go

@@ -66,6 +66,7 @@ func (store *store) Get(ctx context.Context, uuid valuer.UUID, orgID valuer.UUID
 		BunDB().
 		NewSelect().
 		Model(funnel).
+		Relation("CreatedByUser").
 		Where("?TableAlias.id = ? AND ?TableAlias.org_id = ?", uuid.String(), orgID.String()).
 		Scan(ctx)
 	if err != nil {
@@ -126,6 +127,7 @@ func (store *store) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnel
 		BunDB().
 		NewSelect().
 		Model(&funnels).
+		Relation("CreatedByUser").
 		Where("?TableAlias.org_id = ?", orgID.String()).
 		Scan(ctx)
 	if err != nil {

pkg/modules/tracefunnel/impltracefunnel/store_duplicate_names_test.go

@@ -0,0 +1,96 @@
+package impltracefunnel
+
+import (
+	"context"
+	"fmt"
+	"testing"
+
+	"github.com/SigNoz/signoz/pkg/errors"
+	traceFunnels "github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
+	"github.com/SigNoz/signoz/pkg/valuer"
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/mock"
+)
+
+// Test that Create method properly validates duplicate names
+func TestModule_Create_DuplicateNameValidation(t *testing.T) {
+	mockStore := new(MockStore)
+	module := NewModule(mockStore)
+
+	ctx := context.Background()
+	timestamp := int64(1234567890)
+	name := "Duplicate Funnel"
+	userID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+
+	// Mock store to return "already exists" error
+	expectedErr := errors.Wrapf(nil, errors.TypeAlreadyExists, traceFunnels.ErrFunnelAlreadyExists, "a funnel with name '%s' already exists in this organization", name)
+	mockStore.On("Create", ctx, mock.MatchedBy(func(f *traceFunnels.StorableFunnel) bool {
+		return f.Name == name && f.OrgID == orgID
+	})).Return(expectedErr)
+
+	funnel, err := module.Create(ctx, timestamp, name, userID, orgID)
+	assert.Error(t, err)
+	assert.Nil(t, funnel)
+	assert.Contains(t, err.Error(), fmt.Sprintf("a funnel with name '%s' already exists in this organization", name))
+
+	mockStore.AssertExpectations(t)
+}
+
+// Test that Update method properly validates duplicate names
+func TestModule_Update_DuplicateNameValidation(t *testing.T) {
+	mockStore := new(MockStore)
+	module := NewModule(mockStore)
+
+	ctx := context.Background()
+	userID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+	funnelName := "Duplicate Name"
+
+	funnel := &traceFunnels.StorableFunnel{
+		Name:  funnelName,
+		OrgID: orgID,
+	}
+	funnel.ID = valuer.GenerateUUID()
+
+	// Mock store to return "already exists" error
+	expectedErr := errors.Wrapf(nil, errors.TypeAlreadyExists, traceFunnels.ErrFunnelAlreadyExists, "a funnel with name '%s' already exists in this organization", funnelName)
+	mockStore.On("Update", ctx, funnel).Return(expectedErr)
+
+	err := module.Update(ctx, funnel, userID)
+	assert.Error(t, err)
+	assert.Contains(t, err.Error(), fmt.Sprintf("a funnel with name '%s' already exists in this organization", funnelName))
+	assert.Equal(t, userID.String(), funnel.UpdatedBy) // Should still set UpdatedBy
+
+	mockStore.AssertExpectations(t)
+}
+
+// MockStore for testing
+type MockStore struct {
+	mock.Mock
+}
+
+func (m *MockStore) Create(ctx context.Context, funnel *traceFunnels.StorableFunnel) error {
+	args := m.Called(ctx, funnel)
+	return args.Error(0)
+}
+
+func (m *MockStore) Get(ctx context.Context, uuid valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, uuid, orgID)
+	return args.Get(0).(*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockStore) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, orgID)
+	return args.Get(0).([]*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockStore) Update(ctx context.Context, funnel *traceFunnels.StorableFunnel) error {
+	args := m.Called(ctx, funnel)
+	return args.Error(0)
+}
+
+func (m *MockStore) Delete(ctx context.Context, uuid valuer.UUID, orgID valuer.UUID) error {
+	args := m.Called(ctx, uuid, orgID)
+	return args.Error(0)
+}

pkg/modules/tracefunnel/tracefunnel.go

@@ -2,20 +2,19 @@ package tracefunnel
 
 import (
 	"context"
-	"net/http"
-
 	"github.com/SigNoz/signoz/pkg/valuer"
+	"net/http"
 
 	traceFunnels "github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
 )
 
 // Module defines the interface for trace funnel operations
 type Module interface {
-	Create(ctx context.Context, name string, userID string, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error)
+	Create(ctx context.Context, timestamp int64, name string, userID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error)
 
 	Get(ctx context.Context, funnelID valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error)
 
-	Update(ctx context.Context, funnel *traceFunnels.StorableFunnel) error
+	Update(ctx context.Context, funnel *traceFunnels.StorableFunnel, userID valuer.UUID) error
 
 	List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnels.StorableFunnel, error)
 
@@ -25,7 +24,7 @@ type Module interface {
 }
 
 type Handler interface {
-	Create(http.ResponseWriter, *http.Request)
+	New(http.ResponseWriter, *http.Request)
 
 	UpdateSteps(http.ResponseWriter, *http.Request)
 

pkg/modules/tracefunnel/tracefunneltest/module_test.go

@@ -0,0 +1,183 @@
+package tracefunneltest
+
+import (
+	"context"
+	"testing"
+	"time"
+
+	"github.com/SigNoz/signoz/pkg/modules/tracefunnel/impltracefunnel"
+	"github.com/SigNoz/signoz/pkg/types"
+	traceFunnels "github.com/SigNoz/signoz/pkg/types/tracefunneltypes"
+	"github.com/SigNoz/signoz/pkg/valuer"
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/mock"
+)
+
+type MockStore struct {
+	mock.Mock
+}
+
+func (m *MockStore) Create(ctx context.Context, funnel *traceFunnels.StorableFunnel) error {
+	args := m.Called(ctx, funnel)
+	return args.Error(0)
+}
+
+func (m *MockStore) Get(ctx context.Context, uuid valuer.UUID, orgID valuer.UUID) (*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, uuid, orgID)
+	return args.Get(0).(*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockStore) List(ctx context.Context, orgID valuer.UUID) ([]*traceFunnels.StorableFunnel, error) {
+	args := m.Called(ctx, orgID)
+	return args.Get(0).([]*traceFunnels.StorableFunnel), args.Error(1)
+}
+
+func (m *MockStore) Update(ctx context.Context, funnel *traceFunnels.StorableFunnel) error {
+	args := m.Called(ctx, funnel)
+	return args.Error(0)
+}
+
+func (m *MockStore) Delete(ctx context.Context, uuid valuer.UUID, orgID valuer.UUID) error {
+	args := m.Called(ctx, uuid, orgID)
+	return args.Error(0)
+}
+
+func TestModule_Create(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	timestamp := time.Now().UnixMilli()
+	name := "test-funnel"
+	userID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+
+	mockStore.On("Create", ctx, mock.MatchedBy(func(f *traceFunnels.StorableFunnel) bool {
+		return f.Name == name &&
+			f.CreatedBy == userID.String() &&
+			f.OrgID == orgID &&
+			f.CreatedByUser != nil &&
+			f.CreatedByUser.ID == userID &&
+			f.CreatedAt.UnixNano()/1000000 == timestamp
+	})).Return(nil)
+
+	funnel, err := module.Create(ctx, timestamp, name, userID, orgID)
+	assert.NoError(t, err)
+	assert.NotNil(t, funnel)
+	assert.Equal(t, name, funnel.Name)
+	assert.Equal(t, userID.String(), funnel.CreatedBy)
+	assert.Equal(t, orgID, funnel.OrgID)
+	assert.NotNil(t, funnel.CreatedByUser)
+	assert.Equal(t, userID, funnel.CreatedByUser.ID)
+
+	mockStore.AssertExpectations(t)
+}
+
+func TestModule_Get(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	funnelID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+	expectedFunnel := &traceFunnels.StorableFunnel{
+		Name: "test-funnel",
+	}
+
+	mockStore.On("Get", ctx, funnelID, orgID).Return(expectedFunnel, nil)
+
+	funnel, err := module.Get(ctx, funnelID, orgID)
+	assert.NoError(t, err)
+	assert.Equal(t, expectedFunnel, funnel)
+
+	mockStore.AssertExpectations(t)
+}
+
+func TestModule_Update(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	userID := valuer.GenerateUUID()
+	funnel := &traceFunnels.StorableFunnel{
+		Name: "test-funnel",
+	}
+
+	mockStore.On("Update", ctx, funnel).Return(nil)
+
+	err := module.Update(ctx, funnel, userID)
+	assert.NoError(t, err)
+	assert.Equal(t, userID.String(), funnel.UpdatedBy)
+
+	mockStore.AssertExpectations(t)
+}
+
+func TestModule_List(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	orgID := valuer.GenerateUUID()
+	expectedFunnels := []*traceFunnels.StorableFunnel{
+		{
+			Name:  "funnel-1",
+			OrgID: orgID,
+		},
+		{
+			Name:  "funnel-2",
+			OrgID: orgID,
+		},
+	}
+
+	mockStore.On("List", ctx, orgID).Return(expectedFunnels, nil)
+
+	funnels, err := module.List(ctx, orgID)
+	assert.NoError(t, err)
+	assert.Len(t, funnels, 2)
+	assert.Equal(t, expectedFunnels, funnels)
+
+	mockStore.AssertExpectations(t)
+}
+
+func TestModule_Delete(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	funnelID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+
+	mockStore.On("Delete", ctx, funnelID, orgID).Return(nil)
+
+	err := module.Delete(ctx, funnelID, orgID)
+	assert.NoError(t, err)
+
+	mockStore.AssertExpectations(t)
+}
+
+func TestModule_GetFunnelMetadata(t *testing.T) {
+	mockStore := new(MockStore)
+	module := impltracefunnel.NewModule(mockStore)
+
+	ctx := context.Background()
+	funnelID := valuer.GenerateUUID()
+	orgID := valuer.GenerateUUID()
+	now := time.Now()
+	expectedFunnel := &traceFunnels.StorableFunnel{
+		Description: "test description",
+		TimeAuditable: types.TimeAuditable{
+			CreatedAt: now,
+			UpdatedAt: now,
+		},
+	}
+
+	mockStore.On("Get", ctx, funnelID, orgID).Return(expectedFunnel, nil)
+
+	createdAt, updatedAt, description, err := module.GetFunnelMetadata(ctx, funnelID, orgID)
+	assert.NoError(t, err)
+	assert.Equal(t, now.UnixNano()/1000000, createdAt)
+	assert.Equal(t, now.UnixNano()/1000000, updatedAt)
+	assert.Equal(t, "test description", description)
+
+	mockStore.AssertExpectations(t)
+}

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

@@ -38,7 +38,9 @@ func (r *Repo) GetConfigHistory(
 	var c []opamptypes.AgentConfigVersion
 	err := r.store.BunDB().NewSelect().
 		Model(&c).
-		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at,created_by").
+		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at").
+		ColumnExpr("COALESCE(created_by, '') as created_by").
+		ColumnExpr(`COALESCE((SELECT display_name FROM users WHERE users.id = acv.created_by), 'unknown') as created_by_name`).
 		ColumnExpr("COALESCE(hash, '') as hash, COALESCE(config, '{}') as config").
 		Where("acv.element_type = ?", typ).
 		Where("acv.org_id = ?", orgId).
@@ -52,7 +54,6 @@ func (r *Repo) GetConfigHistory(
 
 	incompleteStatuses := []opamptypes.DeployStatus{opamptypes.DeployInitiated, opamptypes.Deploying}
 	for idx := 1; idx < len(c); idx++ {
-		c[idx].CreatedByName = c[idx].CreatedBy
 		if slices.Contains(incompleteStatuses, c[idx].DeployStatus) {
 			c[idx].DeployStatus = opamptypes.DeployStatusUnknown
 		}
@@ -67,7 +68,9 @@ func (r *Repo) GetConfigVersion(
 	var c opamptypes.AgentConfigVersion
 	err := r.store.BunDB().NewSelect().
 		Model(&c).
-		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at,created_by").
+		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at").
+		ColumnExpr("COALESCE(created_by, '') as created_by").
+		ColumnExpr(`COALESCE((SELECT display_name FROM users WHERE users.id = acv.created_by), 'unknown') as created_by_name`).
 		ColumnExpr("COALESCE(hash, '') as hash, COALESCE(config, '{}') as config").
 		Where("acv.element_type = ?", typ).
 		Where("acv.version = ?", v).
@@ -81,7 +84,6 @@ func (r *Repo) GetConfigVersion(
 		return nil, errors.WrapInternalf(err, errors.CodeInternal, "failed to get config version")
 	}
 
-	c.CreatedByName = c.CreatedBy
 	return &c, nil
 }
 
@@ -91,7 +93,9 @@ func (r *Repo) GetLatestVersion(
 	var c opamptypes.AgentConfigVersion
 	err := r.store.BunDB().NewSelect().
 		Model(&c).
-		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at,created_by").
+		ColumnExpr("id, version, element_type, deploy_status, deploy_result, created_at").
+		ColumnExpr("COALESCE(created_by, '') as created_by").
+		ColumnExpr(`COALESCE((SELECT display_name FROM users WHERE users.id = acv.created_by), 'unknown') as created_by_name`).
 		Where("acv.element_type = ?", typ).
 		Where("acv.org_id = ?", orgId).
 		Where("version = (SELECT MAX(version) FROM agent_config_version WHERE acv.element_type = ?)", typ).
@@ -104,12 +108,11 @@ func (r *Repo) GetLatestVersion(
 		return nil, errors.WrapInternalf(err, errors.CodeInternal, "failed to get latest config version")
 	}
 
-	c.CreatedByName = c.CreatedBy
 	return &c, nil
 }
 
 func (r *Repo) insertConfig(
-	ctx context.Context, orgId valuer.UUID, c *opamptypes.AgentConfigVersion, elements []string,
+	ctx context.Context, orgId valuer.UUID, userId valuer.UUID, c *opamptypes.AgentConfigVersion, elements []string,
 ) error {
 
 	if c.ElementType.StringValue() == "" {

pkg/query-service/agentConf/manager.go

@@ -198,14 +198,14 @@ func GetConfigHistory(
 
 // StartNewVersion launches a new config version for given set of elements
 func StartNewVersion(
-	ctx context.Context, orgId valuer.UUID, createdBy string, eleType opamptypes.ElementType, elementIds []string,
+	ctx context.Context, orgId valuer.UUID, userId valuer.UUID, eleType opamptypes.ElementType, elementIds []string,
 ) (*opamptypes.AgentConfigVersion, error) {
 
 	// create a new version
-	cfg := opamptypes.NewAgentConfigVersion(orgId, createdBy, eleType)
+	cfg := opamptypes.NewAgentConfigVersion(orgId, userId, eleType)
 
 	// insert new config and elements into database
-	err := m.insertConfig(ctx, orgId, cfg, elementIds)
+	err := m.insertConfig(ctx, orgId, userId, cfg, elementIds)
 	if err != nil {
 		return nil, err
 	}

pkg/query-service/app/http_handler.go

@@ -4237,8 +4237,14 @@ func (aH *APIHandler) CreateLogsPipeline(w http.ResponseWriter, r *http.Request)
 		render.Error(w, errv2)
 		return
 	}
+	userID, errv2 := valuer.NewUUID(claims.UserID)
+	if errv2 != nil {
+		render.Error(w, errv2)
+		return
+	}
 
 	req := pipelinetypes.PostablePipelines{}
+
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		RespondError(w, model.BadRequest(err), nil)
 		return
@@ -4257,7 +4263,7 @@ func (aH *APIHandler) CreateLogsPipeline(w http.ResponseWriter, r *http.Request)
 			return nil, err
 		}
 
-		return aH.LogsParsingPipelineController.ApplyPipelines(ctx, orgID, claims.Email, postable)
+		return aH.LogsParsingPipelineController.ApplyPipelines(ctx, orgID, userID, postable)
 	}
 
 	res, err := createPipeline(r.Context(), req.Pipelines)
@@ -5132,7 +5138,7 @@ func (aH *APIHandler) RegisterTraceFunnelsRoutes(router *mux.Router, am *middlew
 
 	// API endpoints
 	traceFunnelsRouter.HandleFunc("/new",
-		am.EditAccess(aH.Signoz.Handlers.TraceFunnel.Create)).
+		am.EditAccess(aH.Signoz.Handlers.TraceFunnel.New)).
 		Methods(http.MethodPost)
 	traceFunnelsRouter.HandleFunc("/list",
 		am.ViewAccess(aH.Signoz.Handlers.TraceFunnel.List)).

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

@@ -58,7 +58,7 @@ type PipelinesResponse struct {
 func (ic *LogParsingPipelineController) ApplyPipelines(
 	ctx context.Context,
 	orgID valuer.UUID,
-	createdBy string,
+	userID valuer.UUID,
 	postable []pipelinetypes.PostablePipeline,
 ) (*PipelinesResponse, error) {
 	var pipelines []pipelinetypes.GettablePipeline
@@ -89,7 +89,7 @@ func (ic *LogParsingPipelineController) ApplyPipelines(
 		elements[i] = p.ID.StringValue()
 	}
 
-	cfg, err := agentConf.StartNewVersion(ctx, orgID, createdBy, opamptypes.ElementTypeLogPipelines, elements)
+	cfg, err := agentConf.StartNewVersion(ctx, orgID, userID, opamptypes.ElementTypeLogPipelines, elements)
 	if err != nil || cfg == nil {
 		return nil, model.InternalError(fmt.Errorf("failed to start new version: %w", err))
 	}

pkg/querybuilder/fallback_expr.go

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

pkg/signoz/provider.go

@@ -172,7 +172,6 @@ func NewSQLMigrationProviderFactories(
 		sqlmigration.NewMigrateRulesV4ToV5Factory(sqlstore, telemetryStore),
 		sqlmigration.NewAddStatusUserFactory(sqlstore, sqlschema),
 		sqlmigration.NewDeprecateUserInviteFactory(sqlstore, sqlschema),
-		sqlmigration.NewUpdateCreatedByWithEmailFactory(sqlstore, sqlschema),
 	)
 }
 

pkg/sqlmigration/069_update_created_by_with_email.go

@@ -1,184 +0,0 @@
-package sqlmigration
-
-import (
-	"context"
-	"database/sql"
-
-	"github.com/SigNoz/signoz/pkg/factory"
-	"github.com/SigNoz/signoz/pkg/sqlschema"
-	"github.com/SigNoz/signoz/pkg/sqlstore"
-	"github.com/uptrace/bun"
-	"github.com/uptrace/bun/migrate"
-)
-
-type updateCreatedByWithEmail struct {
-	sqlstore  sqlstore.SQLStore
-	sqlschema sqlschema.SQLSchema
-}
-
-func NewUpdateCreatedByWithEmailFactory(sqlstore sqlstore.SQLStore, sqlschema sqlschema.SQLSchema) factory.ProviderFactory[SQLMigration, Config] {
-	return factory.NewProviderFactory(
-		factory.MustNewName("update_created_by_with_email"),
-		func(ctx context.Context, ps factory.ProviderSettings, c Config) (SQLMigration, error) {
-			return &updateCreatedByWithEmail{
-				sqlstore:  sqlstore,
-				sqlschema: sqlschema,
-			}, nil
-		},
-	)
-}
-
-func (migration *updateCreatedByWithEmail) Register(migrations *migrate.Migrations) error {
-	if err := migrations.Register(migration.Up, migration.Down); err != nil {
-		return err
-	}
-
-	return nil
-}
-
-func (migration *updateCreatedByWithEmail) Up(ctx context.Context, db *bun.DB) error {
-	tx, err := db.BeginTx(ctx, nil)
-	if err != nil {
-		return err
-	}
-
-	defer func() {
-		_ = tx.Rollback()
-	}()
-
-	type userRow struct {
-		ID    string `bun:"id"`
-		Email string `bun:"email"`
-	}
-
-	var users []userRow
-	err = tx.NewSelect().TableExpr("users").Column("id", "email").Scan(ctx, &users)
-	if err != nil && err != sql.ErrNoRows {
-		return err
-	}
-
-	userEmailMap := make(map[string]string, len(users))
-	for _, u := range users {
-		userEmailMap[u.ID] = u.Email
-	}
-
-	emails := make([]string, 0, len(userEmailMap))
-	for _, email := range userEmailMap {
-		emails = append(emails, email)
-	}
-
-	for id, email := range userEmailMap {
-		_, err = tx.NewUpdate().
-			TableExpr("agent_config_version").
-			Set("created_by = ?", email).
-			Where("created_by = ?", id).
-			Exec(ctx)
-		if err != nil {
-			return err
-		}
-
-		_, err = tx.NewUpdate().
-			TableExpr("agent_config_version").
-			Set("updated_by = ?", email).
-			Where("updated_by = ?", id).
-			Exec(ctx)
-		if err != nil {
-			return err
-		}
-	}
-
-	agentCreatedByQuery := tx.NewUpdate().
-		TableExpr("agent_config_version").
-		Set("created_by = ''").
-		Where("created_by != ''")
-	if len(emails) > 0 {
-		agentCreatedByQuery = agentCreatedByQuery.Where("created_by NOT IN (?)", bun.In(emails))
-	}
-	if _, err = agentCreatedByQuery.Exec(ctx); err != nil {
-		return err
-	}
-
-	agentUpdatedByQuery := tx.NewUpdate().
-		TableExpr("agent_config_version").
-		Set("updated_by = ''").
-		Where("updated_by != ''")
-	if len(emails) > 0 {
-		agentUpdatedByQuery = agentUpdatedByQuery.Where("updated_by NOT IN (?)", bun.In(emails))
-	}
-	if _, err = agentUpdatedByQuery.Exec(ctx); err != nil {
-		return err
-	}
-
-	for id, email := range userEmailMap {
-		_, err = tx.NewUpdate().
-			TableExpr("trace_funnel").
-			Set("created_by = ?", email).
-			Where("created_by = ?", id).
-			Exec(ctx)
-		if err != nil {
-			return err
-		}
-
-		_, err = tx.NewUpdate().
-			TableExpr("trace_funnel").
-			Set("updated_by = ?", email).
-			Where("updated_by = ?", id).
-			Exec(ctx)
-		if err != nil {
-			return err
-		}
-	}
-
-	funnelCreatedByQuery := tx.NewUpdate().
-		TableExpr("trace_funnel").
-		Set("created_by = ''").
-		Where("created_by != ''")
-	if len(emails) > 0 {
-		funnelCreatedByQuery = funnelCreatedByQuery.Where("created_by NOT IN (?)", bun.In(emails))
-	}
-	if _, err = funnelCreatedByQuery.Exec(ctx); err != nil {
-		return err
-	}
-
-	funnelUpdatedByQuery := tx.NewUpdate().
-		TableExpr("trace_funnel").
-		Set("updated_by = ''").
-		Where("updated_by != ''")
-	if len(emails) > 0 {
-		funnelUpdatedByQuery = funnelUpdatedByQuery.Where("updated_by NOT IN (?)", bun.In(emails))
-	}
-	if _, err = funnelUpdatedByQuery.Exec(ctx); err != nil {
-		return err
-	}
-
-	quickFilterTable, _, err := migration.sqlschema.GetTable(ctx, sqlschema.TableName("quick_filter"))
-	if err != nil {
-		return err
-	}
-
-	sqls := [][]byte{}
-
-	createdByCol := &sqlschema.Column{Name: "created_by"}
-	dropSQLS := migration.sqlschema.Operator().DropColumn(quickFilterTable, createdByCol)
-	sqls = append(sqls, dropSQLS...)
-
-	updatedByCol := &sqlschema.Column{Name: "updated_by"}
-	dropSQLS = migration.sqlschema.Operator().DropColumn(quickFilterTable, updatedByCol)
-	sqls = append(sqls, dropSQLS...)
-
-	for _, sql := range sqls {
-		if _, err := tx.ExecContext(ctx, string(sql)); err != nil {
-			return err
-		}
-	}
-
-	if err := tx.Commit(); err != nil {
-		return err
-	}
-
-	return nil
-}
-
-func (migration *updateCreatedByWithEmail) Down(ctx context.Context, db *bun.DB) error {
-	return nil
-}

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) LIMIT 10) ORDER BY `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) LIMIT 10) ORDER BY `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) LIMIT 10) ORDER BY `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) LIMIT 10) ORDER BY `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"
@@ -607,8 +608,73 @@ func (b *MetricQueryStatementBuilder) BuildFinalSelect(
 			sb.Where(rewrittenExpr)
 		}
 	}
-	sb.OrderBy(querybuilder.GroupByKeys(query.GroupBy)...)
-	sb.OrderBy("ts")
+	groupByKeys := querybuilder.GroupByKeys(query.GroupBy)
+	hasOrder := len(query.Order) > 0
+	hasLimit := query.Limit > 0
+	hasGroupBy := len(groupByKeys) > 0
+
+	if hasOrder && hasLimit {
+		// order by with limit: add WHERE subquery to restrict to top N distinct key combinations
+		orderByKeys := querybuilder.OrderByKeys(query.Order)
+		var orderByClauses []string
+		for _, o := range query.Order {
+			orderByClauses = append(orderByClauses, fmt.Sprintf("`%s` %s", o.Key.Name, o.Direction.StringValue()))
+		}
+
+		subSb := sqlbuilder.NewSelectBuilder()
+		subSb.Select(fmt.Sprintf("DISTINCT %s", orderByKeys[0]))
+		if len(orderByKeys) > 1 {
+			subSb.SelectMore(orderByKeys[1:]...)
+		}
+		subSb.From("__spatial_aggregation_cte")
+		subSb.OrderBy(orderByClauses...)
+
+		subQ, _ := subSb.BuildWithFlavor(sqlbuilder.ClickHouse)
+		subQ = fmt.Sprintf("%s LIMIT %d", subQ, query.Limit)
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(orderByKeys, ", "), subQ))
+
+		sb.OrderBy(orderByClauses...)
+	} else if hasOrder {
+		// order by without limit: apply order by clauses directly
+		for _, o := range query.Order {
+			key := o.Key.Name
+			if strings.Contains(key, query.Aggregations[0].MetricName) {
+				sb.OrderBy(fmt.Sprintf("avg(value) OVER (PARTITION BY %s) %s", strings.Join(groupByKeys, ", "), o.Direction.StringValue()))
+				continue
+			}
+			sb.OrderBy(fmt.Sprintf("`%s` %s", o.Key.Name, o.Direction.StringValue()))
+		}
+	} else if hasLimit && hasGroupBy {
+		// limit without order by: default ordering by avg(value)
+		subSb := sqlbuilder.NewSelectBuilder()
+		subSb.Select(groupByKeys[0])
+		if len(groupByKeys) > 1 {
+			subSb.SelectMore(groupByKeys[1:]...)
+		}
+		subSb.From("__spatial_aggregation_cte")
+		subSb.GroupBy(groupByKeys...)
+		subSb.OrderBy("avg(value)")
+
+		subQ, _ := subSb.BuildWithFlavor(sqlbuilder.ClickHouse)
+		subQ = fmt.Sprintf("%s LIMIT %d", subQ, query.Limit)
+		sb.Where(fmt.Sprintf("(%s) IN (%s)", strings.Join(groupByKeys, ", "), subQ))
+	} else if hasGroupBy {
+		// grouping without order by or limit: sort by avg(value) DESC with labels as tiebreakers
+		sb.OrderBy(fmt.Sprintf("avg(value) OVER (PARTITION BY %s) DESC", strings.Join(groupByKeys, ", ")))
+	}
+
+	// add any group-by keys not already in the order-by as tiebreakers
+	orderKeySet := make(map[string]struct{})
+	for _, o := range query.Order {
+		orderKeySet[fmt.Sprintf("`%s`", o.Key.Name)] = struct{}{}
+	}
+	for _, g := range groupByKeys {
+		if _, exists := orderKeySet[g]; !exists {
+			sb.OrderBy(g)
+		}
+	}
+
+	sb.OrderBy("ts ASC")
 	if metricType == metrictypes.HistogramType && spaceAgg == metrictypes.SpaceAggregationCount && query.Aggregations[0].ComparisonSpaceAggregationParam == nil {
 		sb.OrderBy("toFloat64(le)")
 	}

pkg/telemetrymetrics/stmt_builder_test.go

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

pkg/types/opamptypes/agent.go

@@ -81,7 +81,10 @@ var (
 type AgentConfigVersion struct {
 	bun.BaseModel `bun:"table:agent_config_version,alias:acv"`
 
+	// this is only for reading
+	// keeping it here since we query the actual data from users table
 	CreatedByName string `json:"createdByName" bun:"created_by_name,scanonly"`
+
 	types.Identifiable
 	types.TimeAuditable
 	types.UserAuditable
@@ -95,13 +98,13 @@ type AgentConfigVersion struct {
 	Config         string       `json:"config" bun:"config,type:text"`
 }
 
-func NewAgentConfigVersion(orgId valuer.UUID, createdBy string, elementType ElementType) *AgentConfigVersion {
+func NewAgentConfigVersion(orgId valuer.UUID, userId valuer.UUID, elementType ElementType) *AgentConfigVersion {
 	return &AgentConfigVersion{
 		TimeAuditable: types.TimeAuditable{
 			CreatedAt: time.Now(),
 			UpdatedAt: time.Now(),
 		},
-		UserAuditable: types.UserAuditable{CreatedBy: createdBy, UpdatedBy: createdBy},
+		UserAuditable: types.UserAuditable{CreatedBy: userId.String(), UpdatedBy: userId.String()},
 		OrgID:         orgId,
 		Identifiable:  types.Identifiable{ID: valuer.GenerateUUID()},
 		ElementType:   elementType,

pkg/types/tracefunneltypes/tracefunnel.go

@@ -1,8 +1,6 @@
 package tracefunneltypes
 
 import (
-	"time"
-
 	"github.com/SigNoz/signoz/pkg/errors"
 	v3 "github.com/SigNoz/signoz/pkg/query-service/model/v3"
 	"github.com/SigNoz/signoz/pkg/types"
@@ -25,6 +23,7 @@ type StorableFunnel struct {
 	OrgID         valuer.UUID   `json:"org_id" bun:"org_id,type:varchar,notnull"`
 	Steps         []*FunnelStep `json:"steps" bun:"steps,type:text,notnull"`
 	Tags          string        `json:"tags" bun:"tags,type:text"`
+	CreatedByUser *types.User   `json:"user" bun:"rel:belongs-to,join:created_by=id"`
 }
 
 type FunnelStep struct {
@@ -84,6 +83,12 @@ type StepTransitionRequest struct {
 	StepEnd   int64 `json:"step_end,omitempty"`
 }
 
+// UserInfo represents basic user information
+type UserInfo struct {
+	ID    string `json:"id"`
+	Email string `json:"email"`
+}
+
 type FunnelStepFilter struct {
 	StepNumber     int
 	ServiceName    string
@@ -91,41 +96,3 @@ type FunnelStepFilter struct {
 	LatencyPointer string // "start" or "end"
 	CustomFilters  *v3.FilterSet
 }
-
-func NewStorableFunnel(name string, description string, steps []*FunnelStep, tags string, createdBy string, orgID valuer.UUID) *StorableFunnel {
-	return &StorableFunnel{
-		Identifiable: types.Identifiable{
-			ID: valuer.GenerateUUID(),
-		},
-		TimeAuditable: types.TimeAuditable{
-			CreatedAt: time.Now(),
-			UpdatedAt: time.Now(),
-		},
-		UserAuditable: types.UserAuditable{
-			CreatedBy: createdBy,
-			UpdatedBy: createdBy,
-		},
-		Name:        name,
-		Description: description,
-		Steps:       steps,
-		Tags:        tags,
-		OrgID:       orgID,
-	}
-}
-
-func (tf *StorableFunnel) Update(name string, description string, steps []*FunnelStep, updatedBy string) {
-	if name != "" {
-		tf.Name = name
-	}
-
-	if description != "" {
-		tf.Description = description
-	}
-
-	if steps != nil {
-		tf.Steps = steps
-	}
-
-	tf.UpdatedBy = updatedBy
-	tf.UpdatedAt = time.Now()
-}

pkg/types/tracefunneltypes/utils.go

@@ -5,6 +5,7 @@ import (
 	"time"
 
 	"github.com/SigNoz/signoz/pkg/errors"
+	"github.com/SigNoz/signoz/pkg/types/authtypes"
 	"github.com/SigNoz/signoz/pkg/valuer"
 )
 
@@ -93,7 +94,7 @@ func ValidateAndConvertTimestamp(timestamp int64) (time.Time, error) {
 	return time.Unix(0, timestamp*1000000), nil // Convert to nanoseconds
 }
 
-func ConstructFunnelResponse(funnel *StorableFunnel) GettableFunnel {
+func ConstructFunnelResponse(funnel *StorableFunnel, claims *authtypes.Claims) GettableFunnel {
 	resp := GettableFunnel{
 		FunnelName:  funnel.Name,
 		FunnelID:    funnel.ID.String(),
@@ -104,7 +105,12 @@ func ConstructFunnelResponse(funnel *StorableFunnel) GettableFunnel {
 		UpdatedBy:   funnel.UpdatedBy,
 		UpdatedAt:   funnel.UpdatedAt.UnixNano() / 1000000,
 		Description: funnel.Description,
-		UserEmail:   funnel.CreatedBy,
+	}
+
+	if funnel.CreatedByUser != nil {
+		resp.UserEmail = funnel.CreatedByUser.Email.String()
+	} else if claims != nil {
+		resp.UserEmail = claims.Email
 	}
 
 	return resp

pkg/types/tracefunneltypes/utils_test.go

@@ -5,6 +5,7 @@ import (
 	"time"
 
 	"github.com/SigNoz/signoz/pkg/types"
+	"github.com/SigNoz/signoz/pkg/types/authtypes"
 	"github.com/SigNoz/signoz/pkg/valuer"
 	"github.com/stretchr/testify/assert"
 )
@@ -418,10 +419,12 @@ func TestConstructFunnelResponse(t *testing.T) {
 	now := time.Now()
 	funnelID := valuer.GenerateUUID()
 	orgID := valuer.GenerateUUID()
+	userID := valuer.GenerateUUID()
 
 	tests := []struct {
 		name     string
 		funnel   *StorableFunnel
+		claims   *authtypes.Claims
 		expected GettableFunnel
 	}{
 		{
@@ -435,11 +438,17 @@ func TestConstructFunnelResponse(t *testing.T) {
 					UpdatedAt: now,
 				},
 				UserAuditable: types.UserAuditable{
-					CreatedBy: valuer.MustNewEmail("funnel@example.com").String(),
-					UpdatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+					CreatedBy: userID.String(),
+					UpdatedBy: userID.String(),
 				},
 				Name:  "test-funnel",
 				OrgID: orgID,
+				CreatedByUser: &types.User{
+					Identifiable: types.Identifiable{
+						ID: userID,
+					},
+					Email: valuer.MustNewEmail("funnel@example.com"),
+				},
 				Steps: []*FunnelStep{
 					{
 						ID:          valuer.GenerateUUID(),
@@ -450,6 +459,11 @@ func TestConstructFunnelResponse(t *testing.T) {
 					},
 				},
 			},
+			claims: &authtypes.Claims{
+				UserID: userID.String(),
+				OrgID:  orgID.String(),
+				Email:  "claims@example.com",
+			},
 			expected: GettableFunnel{
 				FunnelName: "test-funnel",
 				FunnelID:   funnelID.String(),
@@ -462,11 +476,11 @@ func TestConstructFunnelResponse(t *testing.T) {
 					},
 				},
 				CreatedAt: now.UnixNano() / 1000000,
-				CreatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+				CreatedBy: userID.String(),
 				UpdatedAt: now.UnixNano() / 1000000,
-				UpdatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+				UpdatedBy: userID.String(),
 				OrgID:     orgID.String(),
-				UserEmail: valuer.MustNewEmail("funnel@example.com").String(),
+				UserEmail: "funnel@example.com",
 			},
 		},
 		{
@@ -480,8 +494,8 @@ func TestConstructFunnelResponse(t *testing.T) {
 					UpdatedAt: now,
 				},
 				UserAuditable: types.UserAuditable{
-					CreatedBy: valuer.MustNewEmail("funnel@example.com").String(),
-					UpdatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+					CreatedBy: userID.String(),
+					UpdatedBy: userID.String(),
 				},
 				Name:  "test-funnel",
 				OrgID: orgID,
@@ -495,6 +509,11 @@ func TestConstructFunnelResponse(t *testing.T) {
 					},
 				},
 			},
+			claims: &authtypes.Claims{
+				UserID: userID.String(),
+				OrgID:  orgID.String(),
+				Email:  "claims@example.com",
+			},
 			expected: GettableFunnel{
 				FunnelName: "test-funnel",
 				FunnelID:   funnelID.String(),
@@ -507,18 +526,18 @@ func TestConstructFunnelResponse(t *testing.T) {
 					},
 				},
 				CreatedAt: now.UnixNano() / 1000000,
-				CreatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+				CreatedBy: userID.String(),
 				UpdatedAt: now.UnixNano() / 1000000,
-				UpdatedBy: valuer.MustNewEmail("funnel@example.com").String(),
+				UpdatedBy: userID.String(),
 				OrgID:     orgID.String(),
-				UserEmail: valuer.MustNewEmail("funnel@example.com").String(),
+				UserEmail: "claims@example.com",
 			},
 		},
 	}
 
 	for _, tt := range tests {
 		t.Run(tt.name, func(t *testing.T) {
-			result := ConstructFunnelResponse(tt.funnel)
+			result := ConstructFunnelResponse(tt.funnel, tt.claims)
 
 			// Compare top-level fields
 			assert.Equal(t, tt.expected.FunnelName, result.FunnelName)

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

@@ -5,13 +5,16 @@ Look at the cumulative_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,
@@ -71,16 +74,61 @@ def test_rate_with_steady_values_and_reset(
         assert v["value"] >= 0, f"Rate should not be negative: {v['value']}"
 
 
+@pytest.mark.parametrize(
+    "metric_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],
+    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 +145,8 @@ 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 +155,23 @@ 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 +180,6 @@ 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:
@@ -131,101 +189,102 @@ 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) >= 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']}"
+    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
-    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:
+    if "/products" in endpoint_values:
+        products_values = endpoint_values["/products"]
         assert (
-            0 < val < 0.333
-        ), f"Gap boundary values should be between 0 and 0.333, got {val}"
+            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)):
+    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) >= 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
-    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}"
+    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
-    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}"
+    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}"

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 +92,46 @@ def test_with_steady_values_and_reset(
         ), f"{time_aggregation} 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"],
+        ),
+    ],
+)
 @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 +151,16 @@ def test_group_by_endpoint(
     spike_checkout_value: float,
     stable_orders_value: float,
     spike_users_value: float,
+    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_{time_aggregation}_groupby"
+    metric_name = f"test_{time_aggregation}_groupby_{order_suffix}"
 
     metrics = Metrics.load_from_file(
         MULTI_TEMPORALITY_FILE,
@@ -130,6 +176,8 @@ 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 +185,23 @@ 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 +210,6 @@ 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:
@@ -162,116 +218,117 @@ def test_group_by_endpoint(
             ), 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 (
-        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]:
+    if "/health" in endpoint_values:
+        health_values = endpoint_values["/health"]
         assert (
-            v["value"] == stable_health_value
-        ), f"Expected /health rate {stable_health_value}, got {v['value']}"
+            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
-    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:
+    if "/products" in endpoint_values:
+        products_values = endpoint_values["/products"]
         assert (
-            0 < val < stable_products_value
-        ), f"Gap boundary values should be between 0 and {stable_products_value}, got {val}"
+            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)):
+    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) >= 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
-    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}"
+    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
-    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}"
+    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(

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
 
@@ -13,6 +13,7 @@ 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,
@@ -521,4 +522,186 @@ 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
+
+
+@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"],
+        ),
+    ],
+)
+def test_histogram_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_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,
+    )
+    query_p90 = build_builder_query(
+        "B",
+        metric_name,
+        "doesnotreallymatter",
+        "p90",
+        group_by=["endpoint"],
+        order_by=order_by,
+        limit=limit,
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query_count, query_p90])
+    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)}"
+
+    endpoint_labels_in_count = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in count_all_series
+    ]
+
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(endpoint_labels_in_count) == expected_endpoints
+        ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_labels_in_count)}"
+    else:
+        assert endpoint_labels_in_count == expected_endpoints, (
+            f"Expected endpoints in order {expected_endpoints}, got {endpoint_labels_in_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"]
+        )
+
+    p90_series = get_all_series(data, "B")
+    assert (
+        len(p90_series) == expected_count
+    ), f"Expected {expected_count} p90 series, got {len(p90_series)}"
+
+    p90_endpoint_labels = [
+        series.get("labels", [{}])[0].get("value", "unknown")
+        for series in p90_series
+    ]
+
+    if isinstance(expected_endpoints, set):
+        assert (
+            set(p90_endpoint_labels) == expected_endpoints
+        ), f"Expected p90 endpoints {expected_endpoints}, got {set(p90_endpoint_labels)}"
+    else:
+        assert p90_endpoint_labels == expected_endpoints, (
+            f"Expected p90 endpoints in order {expected_endpoints}, got {p90_endpoint_labels}"
+        )
+
+    p90_values = {}
+    for series in p90_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        p90_values[endpoint] = sorted(
+            series.get("values", []), key=lambda x: x["timestamp"]
+        )
+
+    # values should be non-negative
+    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']}"
+    for endpoint, values in p90_values.items():
+        for v in values:
+            assert v["value"] >= 0, f"p90 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']}"
+    if "/health" in p90_values:
+        vals = p90_values["/health"]
+        assert vals[0]["value"] == 6400, f"Expected /health p90 first=6400, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 991.304, f"Expected /health p90 last=991.304, 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']}"
+    if "/orders" in p90_values:
+        vals = p90_values["/orders"]
+        assert vals[0]["value"] == 6400, f"Expected /orders p90 first=6400, got {vals[0]['value']}"
+        assert vals[-1]["value"] == 991.304, f"Expected /orders p90 last=991.304, 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']}"
+    if "/checkout" in p90_values:
+        vals = p90_values["/checkout"]
+        assert vals[0]["value"] == 900, f"Expected /checkout p90 zeroth=900, got {vals[0]['value']}"
+        assert vals[1]["value"] == 6400, f"Expected /checkout p90 first=6400, got {vals[1]['value']}"
+        assert vals[-1]["value"] == 991.304, f"Expected /checkout p90 last=991.304, got {vals[-1]['value']}"

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 59 values for /orders, got {len(orders_values)}"
+        count_steady_orders = sum(1 for v in orders_values if v["value"] == 0.0833)
+        assert (
+            count_steady_orders == 58
+        ), f"Expected 58 steady rate values (0.0833) for /orders, got {count_steady_orders}"
+        # check for counter reset effects - there should be some non-standard values
+        non_standard_orders = [v["value"] for v in orders_values if v["value"] != 0.0833]
+        assert (
+            len(non_standard_orders) == 2
+        ), f"Expected 2 non-standard values due to counter reset, got {non_standard_orders}"
+        # post-reset value should be higher (new counter value / interval)
+        high_rate_orders = [v for v in non_standard_orders if v > 0.0833]
+        assert (
+            len(high_rate_orders) == 1
+        ), f"Expected one high rate value after counter reset, got {non_standard_orders}"
 
     # /users: 56 data points (t05-t60), sparse +1 every 5 minutes (12 of them)
     # Rate = 1/60 = 0.0167 during increment, 0 during flat periods
-    users_values = endpoint_values["/users"]
-    assert (
-        len(users_values) == 56
-    ), f"Expected 56 values for /users, got {len(users_values)}"
-    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
-    # most values should be 0 (flat periods between increments)
-    assert (
-        count_zero_users == 44
-    ), f"Expected 44 zero rate values for /users (sparse data), got {count_zero_users}"
-    # non-zero values should be 0.0167 (1/60 increment rate)
-    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
-    count_increment_rate = sum(1 for v in non_zero_users if v == 0.0167)
-    assert (
-        count_increment_rate == 12
-    ), f"Expected 12 increment rate values (0.0167) for /users, got {count_increment_rate}"
+    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}"