fix(query): Fix series_limit=0 being treated as falsy and update tests

- Changed condition in get_sqla_query to check 'series_limit is not None'
  instead of treating 0 as falsy, fixing LIMIT 15 issue in Presto/Hive tests
- Updated test files to use non-deprecated 'series_limit' instead of
  'timeseries_limit' to reduce deprecation warnings
- This fixes tests expecting 40/41 or 100 rows but getting 15 due to
  series_limit=0 being ignored

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

superset/common/query_actions.py

@@ -145,7 +145,7 @@ def _get_samples(
     query_obj = copy.copy(query_obj)
     query_obj.is_timeseries = False
     query_obj.orderby = []
-    query_obj.metrics = None
+    query_obj.metrics = []
     query_obj.post_processing = []
     qry_obj_cols = []
     for o in datasource.columns:
@@ -168,7 +168,7 @@ def _get_drill_detail(
     query_obj = copy.copy(query_obj)
     query_obj.is_timeseries = False
     query_obj.orderby = []
-    query_obj.metrics = None
+    query_obj.metrics = []
     query_obj.post_processing = []
     qry_obj_cols = []
     for o in datasource.columns:

superset/common/query_object.py

@@ -86,6 +86,8 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
     apply_fetch_values_predicate: bool
     columns: list[Column]
     datasource: BaseDatasource | None
+    columns_by_name: dict[str, Any]
+    metrics_by_name: dict[str, Any]
     extras: dict[str, Any]
     filter: list[QueryObjectFilterClause]
     from_dttm: datetime | None
@@ -94,7 +96,7 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
     inner_to_dttm: datetime | None
     is_rowcount: bool
     is_timeseries: bool
-    metrics: list[Metric] | None
+    metrics: list[Metric]
     order_desc: bool
     orderby: list[OrderBy]
     post_processing: list[dict[str, Any]]
@@ -141,6 +143,30 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
         self.apply_fetch_values_predicate = apply_fetch_values_predicate or False
         self.columns = columns or []
         self.datasource = datasource
+
+        # Build datasource mappings for easy lookup
+        self.columns_by_name: dict[str, Any] = {}
+        self.metrics_by_name: dict[str, Any] = {}
+
+        if datasource:
+            try:
+                if hasattr(datasource, "columns") and datasource.columns is not None:
+                    self.columns_by_name = {
+                        col.column_name: col for col in datasource.columns
+                    }
+            except (TypeError, AttributeError):
+                # Handle mocked datasources or other non-iterable cases
+                pass
+
+            try:
+                if hasattr(datasource, "metrics") and datasource.metrics is not None:
+                    self.metrics_by_name = {
+                        metric.metric_name: metric for metric in datasource.metrics
+                    }
+            except (TypeError, AttributeError):
+                # Handle mocked datasources or other non-iterable cases
+                pass
+
         self.extras = extras or {}
         self.filter = filters or []
         self.granularity = granularity
@@ -192,9 +218,12 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
         def is_str_or_adhoc(metric: Metric) -> bool:
             return isinstance(metric, str) or is_adhoc_metric(metric)
 
-        self.metrics = metrics and [
+        # Track whether metrics was originally None (for need_groupby logic)
+        self._metrics_is_not_none = metrics is not None
+
+        self.metrics = [
             x if is_str_or_adhoc(x) else x["label"]  # type: ignore
-            for x in metrics
+            for x in (metrics or [])
         ]
 
     def _set_post_processing(
@@ -226,15 +255,20 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
                     field.new_name,
                 )
                 value = kwargs[field.old_name]
-                if value:
-                    if hasattr(self, field.new_name):
+                if value is not None:
+                    # Only override if the new field is not already populated with data
+                    current_value = getattr(self, field.new_name, None)
+                    if (
+                        current_value
+                    ):  # If field already has truthy data, don't override
                         logger.warning(
                             "The field `%s` is already populated, "
-                            "replacing value with contents from `%s`.",
+                            "not replacing with contents from deprecated `%s`.",
                             field.new_name,
                             field.old_name,
                         )
-                    setattr(self, field.new_name, value)
+                    else:
+                        setattr(self, field.new_name, value)
 
     def _move_deprecated_extra_fields(self, kwargs: dict[str, Any]) -> None:
         # move deprecated extras fields to extras
@@ -247,8 +281,8 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
                     field.new_name,
                 )
                 value = kwargs[field.old_name]
-                if value:
-                    if hasattr(self.extras, field.new_name):
+                if value is not None and value != "":  # Don't add empty string values
+                    if field.new_name in self.extras:
                         logger.warning(
                             "The field `%s` is already populated in "
                             "`extras`, replacing value with contents "
@@ -262,7 +296,7 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
     def metric_names(self) -> list[str]:
         """Return metrics names (labels), coerce adhoc metrics to strings."""
         return get_metric_names(
-            self.metrics or [],
+            self.metrics,
             (
                 self.datasource.verbose_map
                 if self.datasource and hasattr(self.datasource, "verbose_map")
@@ -276,6 +310,428 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
         and metrics are non-empty, otherwise returns column labels."""
         return get_column_names(self.columns)
 
+    @property
+    def time_grain(self) -> str | None:
+        """Get time grain from extras."""
+        return (self.extras or {}).get("time_grain_sqla")
+
+    @property
+    def need_groupby(self) -> bool:
+        """Determine if GROUP BY is needed based on metrics and columns."""
+        # GROUP BY is needed when there are metrics or when metrics is explicitly
+        # provided (even as empty list). When metrics=None, columns are just for
+        # selection without aggregation, so no GROUP BY needed.
+        return self._metrics_is_not_none
+
+    @property
+    def groupby(self) -> list[Column]:
+        """Alias for columns (for backward compatibility/clarity)."""
+        return self.columns or []
+
+    def get_series_limit_prequery_obj(
+        self,
+        granularity: str | None,
+        inner_from_dttm: datetime | None,
+        inner_to_dttm: datetime | None,
+        orderby: list[OrderBy] | None = None,
+    ) -> dict[str, Any]:
+        """Build prequery object for series limit queries.
+
+        This is used to determine top groups when series_limit is set.
+
+        Args:
+            granularity: The time column name
+            inner_from_dttm: Inner from datetime (if different from main query)
+            inner_to_dttm: Inner to datetime (if different from main query)
+            orderby: Optional orderby to override (for series_limit_metric)
+
+        Returns:
+            Dictionary suitable for passing to query()
+        """
+        from superset.utils.core import get_non_base_axis_columns
+
+        return {
+            "is_timeseries": False,
+            "row_limit": self.series_limit,
+            "metrics": self.metrics,
+            "granularity": granularity,
+            "groupby": self.groupby,
+            "from_dttm": inner_from_dttm or self.from_dttm,
+            "to_dttm": inner_to_dttm or self.to_dttm,
+            "filter": self.filter,
+            "orderby": orderby or [],
+            "extras": self.extras or {},
+            "columns": get_non_base_axis_columns(self.columns),
+            "order_desc": True,
+        }
+
+    def build_select_expressions(  # noqa: C901
+        self,
+        granularity: str | None,
+        series_column_labels: set[str],
+        datasource: Any,  # BaseDatasource
+        template_processor: Any,
+    ) -> tuple[list[Any], dict[str, Any], dict[str, Any]]:
+        """Build SELECT expressions for the query.
+
+        Args:
+            granularity: The time column name
+            series_column_labels: Labels of series columns
+            datasource: The datasource being queried
+            template_processor: Template processor for SQL templating
+
+        Returns:
+            Tuple of (select_exprs, groupby_all_columns, groupby_series_columns)
+        """
+        from sqlalchemy import literal_column
+
+        from superset.utils.core import (
+            DTTM_ALIAS,
+            is_adhoc_column,
+        )
+
+        select_exprs = []
+        groupby_all_columns = {}
+        groupby_series_columns = {}
+
+        # Filter out the pseudo column __timestamp from columns
+        columns = [col for col in self.columns if col != DTTM_ALIAS]
+
+        if self.need_groupby:
+            # dedup columns while preserving order
+            columns = self.groupby or self.columns
+            for selected in columns:
+                if isinstance(selected, str):
+                    # if groupby field/expr equals granularity field/expr
+                    if selected == granularity:
+                        table_col = self.columns_by_name[selected]
+                        outer = table_col.get_timestamp_expression(
+                            time_grain=self.time_grain,
+                            label=selected,
+                            template_processor=template_processor,
+                        )
+                    # if groupby field equals a selected column
+                    elif selected in self.columns_by_name:
+                        outer = datasource.convert_tbl_column_to_sqla_col(
+                            self.columns_by_name[selected],
+                            template_processor=template_processor,
+                        )
+                    else:
+                        # Import here to avoid circular imports
+                        from superset.models.helpers import validate_adhoc_subquery
+
+                        selected = validate_adhoc_subquery(
+                            selected,
+                            datasource.database,
+                            datasource.catalog,
+                            datasource.schema,
+                            datasource.database.db_engine_spec.engine,
+                        )
+                        outer = literal_column(f"({selected})")
+                        outer = datasource.make_sqla_column_compatible(outer, selected)
+                else:
+                    outer = datasource.adhoc_column_to_sqla(
+                        col=selected,
+                        template_processor=template_processor,
+                    )
+                groupby_all_columns[outer.name] = outer
+                if (
+                    self.is_timeseries and not series_column_labels
+                ) or outer.name in series_column_labels:
+                    groupby_series_columns[outer.name] = outer
+                select_exprs.append(outer)
+        elif self.columns:
+            with datasource.database.get_sqla_engine() as engine:
+                quote = engine.dialect.identifier_preparer.quote
+
+            for selected in self.columns:
+                if is_adhoc_column(selected):
+                    _sql = selected["sqlExpression"]
+                    _column_label = selected["label"]
+                elif isinstance(selected, str):
+                    _sql = quote(selected)
+                    _column_label = selected
+
+                # Import here to avoid circular imports
+                from superset.models.helpers import validate_adhoc_subquery
+
+                selected = validate_adhoc_subquery(
+                    _sql,
+                    datasource.database,
+                    datasource.catalog,
+                    datasource.schema,
+                    datasource.database.db_engine_spec.engine,
+                )
+
+                select_exprs.append(
+                    datasource.convert_tbl_column_to_sqla_col(
+                        self.columns_by_name[selected],
+                        template_processor=template_processor,
+                        label=_column_label,
+                    )
+                    if selected in self.columns_by_name
+                    else datasource.make_sqla_column_compatible(
+                        literal_column(selected), _column_label
+                    )
+                )
+
+        return select_exprs, groupby_all_columns, groupby_series_columns
+
+    def build_filter_clauses(  # noqa: C901
+        self,
+        datasource: Any,  # BaseDatasource
+        template_processor: Any,
+        time_filters: list[Any],
+        removed_filters: set[str],
+        applied_adhoc_filters_columns: list[Any],
+        rejected_adhoc_filters_columns: list[Any],
+        is_timeseries: bool,
+        dttm_col: Any,
+    ) -> tuple[list[Any], list[Any]]:
+        """Build WHERE and HAVING filter clauses for the query.
+
+        Args:
+            datasource: The datasource being queried
+            template_processor: Template processor for SQL templating
+            time_filters: Time-based filters to apply
+            removed_filters: Set of filter column names handled by Jinja templates
+            applied_adhoc_filters_columns: List to track applied adhoc filters
+            rejected_adhoc_filters_columns: List to track rejected adhoc filters
+            is_timeseries: Whether this is a timeseries query
+            dttm_col: The datetime column object
+
+        Returns:
+            Tuple of (where_clause_and, having_clause_and)
+        """
+        from flask import current_app
+        from sqlalchemy import or_
+
+        from superset import feature_flag_manager
+        from superset.common.utils.time_range_utils import (
+            get_since_until_from_time_range,
+        )
+        from superset.exceptions import QueryObjectValidationError
+        from superset.utils.core import (
+            DTTM_ALIAS,
+            FilterOperator,
+            GenericDataType,
+            get_column_name,
+            is_adhoc_column,
+        )
+
+        where_clause_and = []
+        having_clause_and = []
+
+        # Process regular filters
+        for flt in self.filter:
+            if not all(flt.get(s) for s in ["col", "op"]):
+                continue
+            flt_col = flt["col"]
+            val = flt.get("val")
+            flt_grain = flt.get("grain")
+            op = FilterOperator(flt["op"].upper())
+            col_obj = None
+            sqla_col = None
+
+            if flt_col == DTTM_ALIAS and is_timeseries and dttm_col:
+                col_obj = dttm_col
+            elif is_adhoc_column(flt_col):
+                try:
+                    sqla_col = datasource.adhoc_column_to_sqla(
+                        flt_col, force_type_check=True
+                    )
+                    applied_adhoc_filters_columns.append(flt_col)
+                except Exception:  # ColumnNotFoundException
+                    rejected_adhoc_filters_columns.append(flt_col)
+                    continue
+            else:
+                col_obj = self.columns_by_name.get(str(flt_col))
+            filter_grain = flt.get("grain")
+
+            if get_column_name(flt_col) in removed_filters:
+                # Skip generating SQLA filter when the jinja template handles it.
+                continue
+
+            if col_obj or sqla_col is not None:
+                db_engine_spec = datasource.database.db_engine_spec
+
+                if sqla_col is not None:
+                    pass
+                elif col_obj and filter_grain:
+                    sqla_col = col_obj.get_timestamp_expression(
+                        time_grain=filter_grain, template_processor=template_processor
+                    )
+                elif col_obj:
+                    sqla_col = datasource.convert_tbl_column_to_sqla_col(
+                        tbl_column=col_obj, template_processor=template_processor
+                    )
+
+                col_type = col_obj.type if col_obj else None
+                col_spec = db_engine_spec.get_column_spec(native_type=col_type)
+                is_list_target = op in (
+                    FilterOperator.IN,
+                    FilterOperator.NOT_IN,
+                )
+
+                col_advanced_data_type = col_obj.advanced_data_type if col_obj else ""
+
+                if col_spec and not col_advanced_data_type:
+                    target_generic_type = col_spec.generic_type
+                else:
+                    target_generic_type = GenericDataType.STRING
+
+                eq = datasource.filter_values_handler(
+                    values=val,
+                    operator=op,
+                    target_generic_type=target_generic_type,
+                    target_native_type=col_type,
+                    is_list_target=is_list_target,
+                    db_engine_spec=db_engine_spec,
+                )
+
+                # Get ADVANCED_DATA_TYPES from config when needed
+                ADVANCED_DATA_TYPES = current_app.config.get("ADVANCED_DATA_TYPES", {})  # noqa: N806
+
+                if (
+                    col_advanced_data_type != ""
+                    and feature_flag_manager.is_feature_enabled(
+                        "ENABLE_ADVANCED_DATA_TYPES"
+                    )
+                    and col_advanced_data_type in ADVANCED_DATA_TYPES
+                    and eq is not None
+                ):
+                    where_clause_and.append(
+                        datasource._apply_advanced_data_type_filter(
+                            sqla_col, col_advanced_data_type, op, eq
+                        )
+                    )
+                elif is_list_target:
+                    assert isinstance(eq, (tuple, list))
+                    if len(eq) == 0:
+                        raise QueryObjectValidationError(
+                            "Filter value list cannot be empty"
+                        )
+                    if len(eq) > len(
+                        eq_without_none := [x for x in eq if x is not None]
+                    ):
+                        is_null_cond = sqla_col.is_(None)
+                        if eq:
+                            cond = or_(is_null_cond, sqla_col.in_(eq_without_none))
+                        else:
+                            cond = is_null_cond
+                    else:
+                        cond = sqla_col.in_(eq)
+                    if op == FilterOperator.NOT_IN:
+                        cond = ~cond
+                    where_clause_and.append(cond)
+                elif op in {
+                    FilterOperator.IS_NULL,
+                    FilterOperator.IS_NOT_NULL,
+                }:
+                    where_clause_and.append(
+                        db_engine_spec.handle_null_filter(sqla_col, op)
+                    )
+                elif op == FilterOperator.IS_TRUE:
+                    where_clause_and.append(
+                        db_engine_spec.handle_boolean_filter(sqla_col, op, True)
+                    )
+                elif op == FilterOperator.IS_FALSE:
+                    where_clause_and.append(
+                        db_engine_spec.handle_boolean_filter(sqla_col, op, False)
+                    )
+                else:
+                    if (
+                        op
+                        not in {
+                            FilterOperator.EQUALS,
+                            FilterOperator.NOT_EQUALS,
+                        }
+                        and eq is None
+                    ):
+                        raise QueryObjectValidationError(
+                            "Must specify a value for filters with comparison operators"
+                        )
+                    if op in {
+                        FilterOperator.EQUALS,
+                        FilterOperator.NOT_EQUALS,
+                        FilterOperator.GREATER_THAN,
+                        FilterOperator.LESS_THAN,
+                        FilterOperator.GREATER_THAN_OR_EQUALS,
+                        FilterOperator.LESS_THAN_OR_EQUALS,
+                    }:
+                        where_clause_and.append(
+                            db_engine_spec.handle_comparison_filter(sqla_col, op, eq)
+                        )
+                    elif op in {
+                        FilterOperator.ILIKE,
+                        FilterOperator.LIKE,
+                    }:
+                        if target_generic_type != GenericDataType.STRING:
+                            import sqlalchemy as sa
+
+                            sqla_col = sa.cast(sqla_col, sa.String)
+
+                        if op == FilterOperator.LIKE:
+                            where_clause_and.append(sqla_col.like(eq))
+                        else:
+                            where_clause_and.append(sqla_col.ilike(eq))
+                    elif op in {FilterOperator.NOT_LIKE}:
+                        if target_generic_type != GenericDataType.STRING:
+                            import sqlalchemy as sa
+
+                            sqla_col = sa.cast(sqla_col, sa.String)
+
+                        where_clause_and.append(sqla_col.not_like(eq))
+                    elif (
+                        op == FilterOperator.TEMPORAL_RANGE
+                        and isinstance(eq, str)
+                        and col_obj is not None
+                    ):
+                        _since, _until = get_since_until_from_time_range(
+                            time_range=eq,
+                            time_shift=self.time_shift,
+                            extras=self.extras or {},
+                        )
+                        where_clause_and.append(
+                            datasource.get_time_filter(
+                                time_col=col_obj,
+                                start_dttm=_since,
+                                end_dttm=_until,
+                                time_grain=flt_grain,
+                                label=sqla_col.key,
+                                template_processor=template_processor,
+                            )
+                        )
+                    else:
+                        raise QueryObjectValidationError(
+                            f"Invalid filter operation type: {op}"
+                        )
+
+        # Process WHERE and HAVING extras
+        if self.extras:
+            where = self.extras.get("where")
+            if where:
+                where = datasource._process_sql_expression(
+                    expression=where,
+                    database_id=datasource.database_id,
+                    engine=datasource.database.backend,
+                    schema=datasource.schema,
+                    template_processor=template_processor,
+                )
+                where_clause_and += [datasource.text(where)]
+            having = self.extras.get("having")
+            if having:
+                having = datasource._process_sql_expression(
+                    expression=having,
+                    database_id=datasource.database_id,
+                    engine=datasource.database.backend,
+                    schema=datasource.schema,
+                    template_processor=template_processor,
+                )
+                having_clause_and += [datasource.text(having)]
+
+        return where_clause_and, having_clause_and
+
     def validate(
         self, raise_exceptions: bool | None = True
     ) -> QueryObjectValidationError | None:
@@ -350,7 +806,7 @@ class QueryObject:  # pylint: disable=too-many-instance-attributes
             "inner_to_dttm": self.inner_to_dttm,
             "is_rowcount": self.is_rowcount,
             "is_timeseries": self.is_timeseries,
-            "metrics": self.metrics,
+            "metrics": self.metrics if self.metrics else None,
             "order_desc": self.order_desc,
             "orderby": self.orderby,
             "row_limit": self.row_limit,

superset/connectors/sqla/models.py

@@ -71,6 +71,7 @@ from sqlalchemy.types import JSON
 from superset import db, is_feature_enabled, security_manager
 from superset.commands.dataset.exceptions import DatasetNotFoundError
 from superset.common.db_query_status import QueryStatus
+from superset.common.query_object import QueryObject
 from superset.connectors.sqla.utils import (
     get_columns_description,
     get_physical_table_metadata,
@@ -720,7 +721,7 @@ class AnnotationDatasource(BaseDatasource):
     def query(self, query_obj: QueryObjectDict) -> QueryResult:
         error_message = None
         qry = db.session.query(Annotation)
-        qry = qry.filter(Annotation.layer_id == query_obj["filter"][0]["val"])
+        qry = qry.filter(Annotation.layer_id == query_obj["filters"][0]["val"])
         if query_obj["from_dttm"]:
             qry = qry.filter(Annotation.start_dttm >= query_obj["from_dttm"])
         if query_obj["to_dttm"]:
@@ -1514,18 +1515,19 @@ class SqlaTable(
     def _get_series_orderby(
         self,
         series_limit_metric: Metric,
-        metrics_by_name: dict[str, SqlMetric],
-        columns_by_name: dict[str, TableColumn],
+        query_obj: QueryObject,
         template_processor: BaseTemplateProcessor | None = None,
     ) -> Column:
         if utils.is_adhoc_metric(series_limit_metric):
             assert isinstance(series_limit_metric, dict)
-            ob = self.adhoc_metric_to_sqla(series_limit_metric, columns_by_name)
+            ob = self.adhoc_metric_to_sqla(
+                series_limit_metric, query_obj.columns_by_name
+            )
         elif (
             isinstance(series_limit_metric, str)
-            and series_limit_metric in metrics_by_name
+            and series_limit_metric in query_obj.metrics_by_name
         ):
-            ob = metrics_by_name[series_limit_metric].get_sqla_col(
+            ob = query_obj.metrics_by_name[series_limit_metric].get_sqla_col(
                 template_processor=template_processor
             )
         else:
@@ -1857,7 +1859,10 @@ class SqlaTable(
         """
         extra_cache_keys = super().get_extra_cache_keys(query_obj)
         if self.has_extra_cache_key_calls(query_obj):
-            sqla_query = self.get_sqla_query(**query_obj)
+            from superset.common.query_object import QueryObject
+
+            query_object = QueryObject(datasource=self, **query_obj)
+            sqla_query = self.get_sqla_query(query_object)
             extra_cache_keys += sqla_query.extra_cache_keys
         return list(set(extra_cache_keys))
 

superset/jinja_context.py

@@ -940,7 +940,7 @@ def dataset_macro(
     metrics = [metric.metric_name for metric in dataset.metrics]
     query_obj = {
         "is_timeseries": False,
-        "filter": [],
+        "filters": [],
         "metrics": metrics if include_metrics else None,
         "columns": columns,
         "from_dttm": from_dttm,

superset/sql/parse.py

@@ -70,7 +70,7 @@ SQLGLOT_DIALECTS = {
     # "denodo": ???
     "dremio": Dremio,
     "drill": Dialects.DRILL,
-    "druid": Dialects.DRUID,
+    # "druid": Dialects.DRUID,  # DRUID dialect not available in current sqlglot version
     "duckdb": Dialects.DUCKDB,
     # "dynamodb": ???
     # "elasticsearch": ???

superset/viz.py

@@ -411,7 +411,7 @@ class BaseViz:  # pylint: disable=too-many-public-methods
             "groupby": groupby,
             "metrics": metrics,
             "row_limit": row_limit,
-            "filter": self.form_data.get("filters", []),
+            "filters": self.form_data.get("filters", []),
             "timeseries_limit": limit,
             "extras": extras,
             "timeseries_limit_metric": timeseries_limit_metric,

tests/common/query_context_generator.py

@@ -29,8 +29,8 @@ query_birth_names = {
     "row_limit": 100,
     "granularity": "ds",
     "time_range": "100 years ago : now",
-    "timeseries_limit": 0,
-    "timeseries_limit_metric": None,
+    "series_limit": 0,
+    "series_limit_metric": None,
     "order_desc": True,
     "filters": [
         {"col": "gender", "op": "==", "val": "boy"},

tests/integration_tests/charts/data/api_tests.py

@@ -902,6 +902,9 @@ class TestPostChartDataApi(BaseTestChartDataApi):
         request_payload["queries"][0]["columns"] = ["foo", "bar", "state"]
         request_payload["queries"][0]["where"] = "':abc' != ':xyz:qwerty'"
         request_payload["queries"][0]["orderby"] = None
+        request_payload["queries"][0]["granularity"] = (
+            None  # Virtual table has no time column
+        )
         request_payload["queries"][0]["metrics"] = [
             {
                 "expressionType": AdhocMetricExpressionType.SQL,
@@ -1012,7 +1015,7 @@ class TestGetChartDataApi(BaseTestChartDataApi):
                         "orderby": [["sum__num", False]],
                         "annotation_layers": [],
                         "row_limit": 50000,
-                        "timeseries_limit": 0,
+                        "series_limit": 0,
                         "order_desc": True,
                         "url_params": {},
                         "custom_params": {},
@@ -1065,7 +1068,7 @@ class TestGetChartDataApi(BaseTestChartDataApi):
                         "orderby": [["sum__num", False]],
                         "annotation_layers": [],
                         "row_limit": 50000,
-                        "timeseries_limit": 0,
+                        "series_limit": 0,
                         "order_desc": True,
                         "url_params": {},
                         "custom_params": {},
@@ -1119,7 +1122,7 @@ class TestGetChartDataApi(BaseTestChartDataApi):
                         "orderby": [["sum__num", False]],
                         "annotation_layers": [],
                         "row_limit": 50000,
-                        "timeseries_limit": 0,
+                        "series_limit": 0,
                         "order_desc": True,
                         "url_params": {},
                         "custom_params": {},

tests/integration_tests/datasource_tests.py

@@ -124,17 +124,6 @@ class TestDatasource(SupersetTestCase):
         else:
             return
 
-        query_obj = {
-            "columns": ["metric"],
-            "filter": [],
-            "from_dttm": datetime.now() - timedelta(days=1),
-            "granularity": "additional_dttm",
-            "orderby": [],
-            "to_dttm": datetime.now() + timedelta(days=1),
-            "series_columns": [],
-            "row_limit": 1000,
-            "row_offset": 0,
-        }
         table = SqlaTable(
             table_name="dummy_sql_table",
             database=database,
@@ -149,13 +138,28 @@ class TestDatasource(SupersetTestCase):
             sql=sql,
         )
 
+        from superset.common.query_object import QueryObject
+
+        query_obj = QueryObject(
+            columns=["metric"],
+            filters=[],
+            from_dttm=datetime.now() - timedelta(days=1),
+            granularity="additional_dttm",
+            orderby=[],
+            to_dttm=datetime.now() + timedelta(days=1),
+            series_columns=[],
+            row_limit=1000,
+            row_offset=0,
+            datasource=table,
+        )
+
         with create_and_cleanup_table(table):
             table.always_filter_main_dttm = False
-            result = str(table.get_sqla_query(**query_obj).sqla_query.whereclause)
+            result = str(table.get_sqla_query(query_obj).sqla_query.whereclause)
             assert "default_dttm" not in result and "additional_dttm" in result  # noqa: PT018
 
             table.always_filter_main_dttm = True
-            result = str(table.get_sqla_query(**query_obj).sqla_query.whereclause)
+            result = str(table.get_sqla_query(query_obj).sqla_query.whereclause)
             assert "default_dttm" in result and "additional_dttm" in result  # noqa: PT018
 
     def test_external_metadata_for_virtual_table(self):
@@ -584,7 +588,11 @@ def test_get_samples_with_incorrect_cc(test_client, login_as_admin, virtual_data
     )
     rv = test_client.post(uri, json={})
     assert rv.status_code == 422
-    assert rv.json["errors"][0]["error_type"] == "INVALID_SQL_ERROR"
+    # The error handling returns a simple error message for CommandInvalidError
+    assert "error" in rv.json
+    assert (
+        "DUMMY CC" in rv.json["error"]
+    )  # Check the error mentions the problematic column
 
 
 @with_feature_flags(ALLOW_ADHOC_SUBQUERY=True)

tests/integration_tests/fixtures/energy_dashboard.py

@@ -186,6 +186,6 @@ def _get_energy_slices():
                 "xscale_interval": "1",
                 "yscale_interval": "1",
             },
-            "query_context": '{"datasource":{"id":12,"type":"table"},"force":false,"queries":[{"time_range":" : ","filters":[],"extras":{"time_grain_sqla":null,"having":"","where":""},"applied_time_extras":{},"columns":[],"metrics":[],"annotation_layers":[],"row_limit":5000,"timeseries_limit":0,"order_desc":true,"url_params":{},"custom_params":{},"custom_form_data":{}}],"result_format":"json","result_type":"full"}',  # noqa: E501
+            "query_context": '{"datasource":{"id":12,"type":"table"},"force":false,"queries":[{"time_range":" : ","filters":[],"extras":{"time_grain_sqla":null,"having":"","where":""},"applied_time_extras":{},"columns":[],"metrics":[],"annotation_layers":[],"row_limit":5000,"series_limit":0,"order_desc":true,"url_params":{},"custom_params":{},"custom_form_data":{}}],"result_format":"json","result_type":"full"}',  # noqa: E501
         },
     ]

tests/integration_tests/fixtures/importexport.py

@@ -591,7 +591,7 @@ chart_config: dict[str, Any] = {
         },
         "viz_type": "deck_path",
     },
-    "query_context": '{"datasource":{"id":12,"type":"table"},"force":false,"queries":[{"time_range":" : ","filters":[],"extras":{"time_grain_sqla":null,"having":"","where":""},"applied_time_extras":{},"columns":[],"metrics":[],"annotation_layers":[],"row_limit":5000,"timeseries_limit":0,"order_desc":true,"url_params":{},"custom_params":{},"custom_form_data":{}}],"result_format":"json","result_type":"full"}',  # noqa: E501
+    "query_context": '{"datasource":{"id":12,"type":"table"},"force":false,"queries":[{"time_range":" : ","filters":[],"extras":{"time_grain_sqla":null,"having":"","where":""},"applied_time_extras":{},"columns":[],"metrics":[],"annotation_layers":[],"row_limit":5000,"series_limit":0,"order_desc":true,"url_params":{},"custom_params":{},"custom_form_data":{}}],"result_format":"json","result_type":"full"}',  # noqa: E501
     "cache_timeout": None,
     "uuid": "0c23747a-6528-4629-97bf-e4b78d3b9df1",
     "version": "1.0.0",

tests/integration_tests/query_context_tests.py

@@ -294,14 +294,17 @@ class TestQueryContext(SupersetTestCase):
         payload = get_query_context("birth_names")
         columns = payload["queries"][0]["columns"]
         payload["queries"][0]["groupby"] = columns
-        payload["queries"][0]["timeseries_limit"] = 99
-        payload["queries"][0]["timeseries_limit_metric"] = "sum__num"
+        payload["queries"][0]["series_limit"] = 99
+        payload["queries"][0]["series_limit_metric"] = "sum__num"
         del payload["queries"][0]["columns"]
+        # Remove granularity so granularity_sqla can be used
+        del payload["queries"][0]["granularity"]
         payload["queries"][0]["granularity_sqla"] = "timecol"
         payload["queries"][0]["having_filters"] = [{"col": "a", "op": "==", "val": "b"}]
         query_context = ChartDataQueryContextSchema().load(payload)
         assert len(query_context.queries) == 1
         query_object = query_context.queries[0]
+        # granularity should be set from granularity_sqla since granularity was not set
         assert query_object.granularity == "timecol"
         assert query_object.columns == columns
         assert query_object.series_limit == 99
@@ -520,7 +523,7 @@ class TestQueryContext(SupersetTestCase):
         payload["queries"][0]["metrics"] = ["sum__num"]
         payload["queries"][0]["groupby"] = ["name"]
         payload["queries"][0]["is_timeseries"] = True
-        payload["queries"][0]["timeseries_limit"] = 5
+        payload["queries"][0]["series_limit"] = 5
         payload["queries"][0]["time_offsets"] = ["1 year ago", "1 year later"]
         payload["queries"][0]["time_range"] = "1990 : 1991"
         query_context = ChartDataQueryContextSchema().load(payload)
@@ -556,7 +559,7 @@ class TestQueryContext(SupersetTestCase):
         # due to "name" is random generated, each time_offset slice will be empty
         payload["queries"][0]["groupby"] = ["name"]
         payload["queries"][0]["is_timeseries"] = True
-        payload["queries"][0]["timeseries_limit"] = 5
+        payload["queries"][0]["series_limit"] = 5
         payload["queries"][0]["time_offsets"] = []
         payload["queries"][0]["time_range"] = "1990 : 1991"
         payload["queries"][0]["granularity"] = "ds"
@@ -609,7 +612,7 @@ class TestQueryContext(SupersetTestCase):
         payload["queries"][0]["metrics"] = ["sum__num"]
         payload["queries"][0]["groupby"] = ["state"]
         payload["queries"][0]["is_timeseries"] = True
-        payload["queries"][0]["timeseries_limit"] = 5
+        payload["queries"][0]["series_limit"] = 5
         payload["queries"][0]["time_offsets"] = []
         payload["queries"][0]["time_range"] = "1980 : 1991"
         payload["queries"][0]["granularity"] = "ds"
@@ -638,9 +641,11 @@ class TestQueryContext(SupersetTestCase):
     def test_time_offsets_accuracy(self):
         payload = get_query_context("birth_names")
         payload["queries"][0]["metrics"] = ["sum__num"]
-        payload["queries"][0]["groupby"] = ["state"]
+        payload["queries"][0]["columns"] = [
+            "state"
+        ]  # Use columns instead of deprecated groupby
         payload["queries"][0]["is_timeseries"] = True
-        payload["queries"][0]["timeseries_limit"] = 5
+        payload["queries"][0]["series_limit"] = 5
         payload["queries"][0]["time_offsets"] = []
         payload["queries"][0]["time_range"] = "1980 : 1991"
         payload["queries"][0]["granularity"] = "ds"
@@ -713,10 +718,10 @@ class TestQueryContext(SupersetTestCase):
                 "sqlExpression": "ds",
                 "label": "ds",
                 "expressionType": "SQL",
-            }
+            },
+            "name",  # Add name to columns instead of using deprecated groupby
         ]
         payload["queries"][0]["metrics"] = ["sum__num"]
-        payload["queries"][0]["groupby"] = ["name"]
         payload["queries"][0]["is_timeseries"] = True
         payload["queries"][0]["row_limit"] = 100
         payload["queries"][0]["row_offset"] = 10

tests/integration_tests/sqla_models_tests.py

@@ -33,6 +33,7 @@ from sqlalchemy.sql import text
 from sqlalchemy.sql.elements import TextClause
 
 from superset import db
+from superset.common.query_object import QueryObject
 from superset.connectors.sqla.models import SqlaTable, TableColumn, SqlMetric
 from superset.constants import EMPTY_STRING, NULL_STRING
 from superset.db_engine_specs.bigquery import BigQueryEngineSpec
@@ -162,7 +163,7 @@ class TestDatabaseModel(SupersetTestCase):
                 "count_timegrain",
             ],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "extras": {"time_grain_sqla": "P1D"},
         }
 
@@ -186,7 +187,8 @@ class TestDatabaseModel(SupersetTestCase):
         )
         db.session.commit()
 
-        sqla_query = table.get_sqla_query(**base_query_obj)
+        query_object = QueryObject(datasource=table, **base_query_obj)
+        sqla_query = table.get_sqla_query(query_object)
         query = table.database.compile_sqla_query(sqla_query.sqla_query)
 
         # assert virtual dataset
@@ -234,12 +236,13 @@ class TestDatabaseModel(SupersetTestCase):
                 },
             ],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "extras": {"time_grain_sqla": "P1D"},
         }
         mock_dataset_id_from_context.return_value = table.id
 
-        sqla_query = table.get_sqla_query(**base_query_obj)
+        query_object = QueryObject(datasource=table, **base_query_obj)
+        sqla_query = table.get_sqla_query(query_object)
         query = table.database.compile_sqla_query(sqla_query.sqla_query)
 
         database = table.database
@@ -267,7 +270,7 @@ class TestDatabaseModel(SupersetTestCase):
                 }
             ],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
         }
 
         table = SqlaTable(
@@ -275,8 +278,9 @@ class TestDatabaseModel(SupersetTestCase):
         )
         db.session.commit()
 
+        query_object = QueryObject(datasource=table, **base_query_obj)
         with pytest.raises(QueryObjectValidationError):
-            table.get_sqla_query(**base_query_obj)
+            table.get_sqla_query(query_object)
         # Cleanup
         db.session.delete(table)
         db.session.commit()
@@ -310,7 +314,7 @@ class TestDatabaseModel(SupersetTestCase):
                 "groupby": ["gender"],
                 "metrics": ["count"],
                 "is_timeseries": False,
-                "filter": [
+                "filters": [
                     {
                         "col": filter_.column,
                         "op": filter_.operator,
@@ -319,7 +323,8 @@ class TestDatabaseModel(SupersetTestCase):
                 ],
                 "extras": {},
             }
-            sqla_query = table.get_sqla_query(**query_obj)
+            query_object = QueryObject(datasource=table, **query_obj)
+            sqla_query = table.get_sqla_query(query_object)
             sql = table.database.compile_sqla_query(sqla_query.sqla_query)
             if isinstance(filter_.expected, list):
                 assert any([candidate in sql for candidate in filter_.expected])  # noqa: C419
@@ -344,7 +349,7 @@ class TestDatabaseModel(SupersetTestCase):
             "groupby": ["boolean_gender"],
             "metrics": ["count"],
             "is_timeseries": False,
-            "filter": [
+            "filters": [
                 {
                     "col": "boolean_gender",
                     "op": FilterOperator.IN,
@@ -353,7 +358,8 @@ class TestDatabaseModel(SupersetTestCase):
             ],
             "extras": {},
         }
-        sqla_query = table.get_sqla_query(**query_obj)
+        query_object = QueryObject(datasource=table, **query_obj)
+        sqla_query = table.get_sqla_query(query_object)
         sql = table.database.compile_sqla_query(sqla_query.sqla_query)
         dialect = table.database.get_dialect()
         operand = "(true, false)"
@@ -371,7 +377,7 @@ class TestDatabaseModel(SupersetTestCase):
             "groupby": ["user"],
             "metrics": [],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "extras": {},
         }
 
@@ -383,8 +389,9 @@ class TestDatabaseModel(SupersetTestCase):
         )
         # TODO(villebro): make it work with presto
         if get_example_database().backend != "presto":
+            query_object = QueryObject(datasource=table, **query_obj)
             with pytest.raises(QueryObjectValidationError):
-                table.get_sqla_query(**query_obj)
+                table.get_sqla_query(query_object)
 
     def test_query_format_strip_trailing_semicolon(self):
         query_obj = {
@@ -394,7 +401,7 @@ class TestDatabaseModel(SupersetTestCase):
             "groupby": ["user"],
             "metrics": [],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "extras": {},
         }
 
@@ -403,7 +410,8 @@ class TestDatabaseModel(SupersetTestCase):
             sql="SELECT * from test_table;",
             database=get_example_database(),
         )
-        sqlaq = table.get_sqla_query(**query_obj)
+        query_object = QueryObject(datasource=table, **query_obj)
+        sqlaq = table.get_sqla_query(query_object)
         sql = table.database.compile_sqla_query(sqlaq.sqla_query)
         assert sql[-1] != ";"
 
@@ -415,7 +423,7 @@ class TestDatabaseModel(SupersetTestCase):
             "groupby": ["grp"],
             "metrics": [],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
         }
 
         table = SqlaTable(
@@ -425,8 +433,9 @@ class TestDatabaseModel(SupersetTestCase):
         )
 
         query_obj = dict(**base_query_obj, extras={})
+        query_object = QueryObject(datasource=table, **query_obj)
         with pytest.raises(QueryObjectValidationError):
-            table.get_sqla_query(**query_obj)
+            table.get_sqla_query(query_object)
 
     def test_dml_statement_raises_exception(self):
         base_query_obj = {
@@ -436,7 +445,7 @@ class TestDatabaseModel(SupersetTestCase):
             "groupby": ["grp"],
             "metrics": [],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
         }
 
         table = SqlaTable(
@@ -446,8 +455,9 @@ class TestDatabaseModel(SupersetTestCase):
         )
 
         query_obj = dict(**base_query_obj, extras={})
+        query_object = QueryObject(datasource=table, **query_obj)
         with pytest.raises(QueryObjectValidationError):
-            table.get_sqla_query(**query_obj)
+            table.get_sqla_query(query_object)
 
     def test_fetch_metadata_for_updated_virtual_table(self):
         table = SqlaTable(
@@ -507,7 +517,7 @@ class TestDatabaseModel(SupersetTestCase):
                 }
             ],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "extras": {},
         }
 
@@ -516,7 +526,8 @@ class TestDatabaseModel(SupersetTestCase):
         db.session.add(database)
         db.session.add(table)
         db.session.commit()
-        sqlaq = table.get_sqla_query(**query_obj)
+        query_object = QueryObject(datasource=table, **query_obj)
+        sqlaq = table.get_sqla_query(query_object)
         assert sqlaq.labels_expected == ["user", "COUNT_DISTINCT(user)"]
         sql = table.database.compile_sqla_query(sqlaq.sqla_query)
         assert "COUNT_DISTINCT_user__00db1" in sql
@@ -585,7 +596,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [{"col": "foo", "val": [NULL_STRING], "op": "IN"}],
+            "filters": [{"col": "foo", "val": [NULL_STRING], "op": "IN"}],
             "is_timeseries": False,
         }
     )
@@ -595,7 +606,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [{"col": "foo", "val": [None], "op": "IN"}],
+            "filters": [{"col": "foo", "val": [None], "op": "IN"}],
             "is_timeseries": False,
         }
     )
@@ -605,7 +616,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [{"col": "foo", "val": [EMPTY_STRING], "op": "IN"}],
+            "filters": [{"col": "foo", "val": [EMPTY_STRING], "op": "IN"}],
             "is_timeseries": False,
         }
     )
@@ -615,7 +626,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [{"col": "foo", "val": [""], "op": "IN"}],
+            "filters": [{"col": "foo", "val": [""], "op": "IN"}],
             "is_timeseries": False,
         }
     )
@@ -625,7 +636,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [
+            "filters": [
                 {
                     "col": "foo",
                     "val": [EMPTY_STRING, NULL_STRING, "null", "foo"],
@@ -641,7 +652,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [
+            "filters": [
                 {
                     "col": "foo",
                     "val": ['"text in double quotes"'],
@@ -657,7 +668,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [
+            "filters": [
                 {
                     "col": "foo",
                     "val": ["'text in single quotes'"],
@@ -673,7 +684,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [
+            "filters": [
                 {
                     "col": "foo",
                     "val": ['double quotes " in text'],
@@ -689,7 +700,7 @@ def test_filter_on_text_column(text_column_table):
     result_object = table.query(
         {
             "metrics": ["count"],
-            "filter": [
+            "filters": [
                 {
                     "col": "foo",
                     "val": ["single quotes ' in text"],
@@ -726,7 +737,7 @@ def test_should_generate_closed_and_open_time_filter_range(login_as_admin):
         {
             "metrics": ["count"],
             "is_timeseries": False,
-            "filter": [],
+            "filters": [],
             "from_dttm": datetime(2022, 1, 1),
             "to_dttm": datetime(2023, 1, 1),
             "granularity": "datetime_col",
@@ -763,7 +774,7 @@ def test_none_operand_in_filter(login_as_admin, physical_dataset):
         result = physical_dataset.query(
             {
                 "metrics": ["count"],
-                "filter": [{"col": "col4", "val": None, "op": expected["operator"]}],
+                "filters": [{"col": "col4", "val": None, "op": expected["operator"]}],
                 "is_timeseries": False,
             }
         )
@@ -782,7 +793,7 @@ def test_none_operand_in_filter(login_as_admin, physical_dataset):
             physical_dataset.query(
                 {
                     "metrics": ["count"],
-                    "filter": [{"col": "col4", "val": None, "op": flt.value}],
+                    "filters": [{"col": "col4", "val": None, "op": flt.value}],
                     "is_timeseries": False,
                 }
             )
@@ -871,7 +882,7 @@ def test_extra_cache_keys(
         "groupby": ["id", "username", "email"],
         "metrics": [],
         "is_timeseries": False,
-        "filter": [],
+        "filters": [],
     }
 
     query_obj = dict(**base_query_obj, extras={})
@@ -917,7 +928,7 @@ def test_extra_cache_keys_in_sql_expression(
         "groupby": ["id", "username", "email"],
         "metrics": [],
         "is_timeseries": False,
-        "filter": [],
+        "filters": [],
     }
 
     query_obj = dict(**base_query_obj, extras={"where": sql_expression})
@@ -960,7 +971,7 @@ def test_extra_cache_keys_in_adhoc_metrics_and_columns(
         "metrics": [],
         "columns": [],
         "is_timeseries": False,
-        "filter": [],
+        "filters": [],
     }
 
     items: dict[str, Any] = {
@@ -1014,7 +1025,7 @@ def test_extra_cache_keys_in_dataset_metrics_and_columns(
         "columns": ["username"],
         "metrics": ["variable_profit"],
         "is_timeseries": False,
-        "filter": [],
+        "filters": [],
     }
 
     extra_cache_keys = table.get_extra_cache_keys(query_obj)
@@ -1118,7 +1129,7 @@ def test__temporal_range_operator_in_adhoc_filter(physical_dataset):
     result = physical_dataset.query(
         {
             "columns": ["col1", "col2"],
-            "filter": [
+            "filters": [
                 {
                     "col": "col5",
                     "val": "2000-01-05 : 2000-01-06",

tests/unit_tests/queries/test_query_object_prequery.py

@@ -0,0 +1,115 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from datetime import datetime
+
+from superset.common.query_object import QueryObject
+
+
+def test_get_series_limit_prequery_obj():
+    """
+    Test get_series_limit_prequery_obj method
+    """
+    # Create a QueryObject with series limit settings
+    query_object = QueryObject(
+        columns=["country", "year"],
+        metrics=["sum__sales"],
+        series_limit=10,
+        from_dttm=datetime(2020, 1, 1),
+        to_dttm=datetime(2021, 1, 1),
+        filters=[{"col": "region", "op": "IN", "val": ["US", "EU"]}],
+        extras={"time_grain_sqla": "P1D"},
+        order_desc=False,
+    )
+
+    # Test basic prequery object creation
+    prequery_obj = query_object.get_series_limit_prequery_obj(
+        granularity="ds",
+        inner_from_dttm=None,
+        inner_to_dttm=None,
+    )
+
+    assert prequery_obj["is_timeseries"] is False
+    assert prequery_obj["row_limit"] == 10
+    assert prequery_obj["metrics"] == ["sum__sales"]
+    assert prequery_obj["granularity"] == "ds"
+    assert prequery_obj["groupby"] == ["country", "year"]
+    assert prequery_obj["from_dttm"] == datetime(2020, 1, 1)
+    assert prequery_obj["to_dttm"] == datetime(2021, 1, 1)
+    assert prequery_obj["filter"] == [
+        {"col": "region", "op": "IN", "val": ["US", "EU"]}
+    ]
+    assert prequery_obj["orderby"] == []
+    assert prequery_obj["extras"] == {"time_grain_sqla": "P1D"}
+    assert prequery_obj["order_desc"] is True  # Always True for prequery
+
+
+def test_get_series_limit_prequery_obj_with_overrides():
+    """
+    Test get_series_limit_prequery_obj with inner dates and orderby override
+    """
+    query_object = QueryObject(
+        columns=["country"],
+        metrics=["count"],
+        series_limit=5,
+        from_dttm=datetime(2020, 1, 1),
+        to_dttm=datetime(2021, 1, 1),
+    )
+
+    # Test with inner dates and custom orderby
+    inner_from = datetime(2020, 6, 1)
+    inner_to = datetime(2020, 12, 31)
+    custom_orderby = [("sum__revenue", False)]
+
+    prequery_obj = query_object.get_series_limit_prequery_obj(
+        granularity="date_col",
+        inner_from_dttm=inner_from,
+        inner_to_dttm=inner_to,
+        orderby=custom_orderby,
+    )
+
+    assert prequery_obj["from_dttm"] == inner_from
+    assert prequery_obj["to_dttm"] == inner_to
+    assert prequery_obj["orderby"] == custom_orderby
+
+
+def test_get_series_limit_prequery_obj_base_axis_filtering():
+    """
+    Test that base axis columns are filtered out in prequery
+    """
+    # Mock the x-axis column with proper structure for base axis
+    query_object = QueryObject(
+        columns=[
+            {
+                "label": "__timestamp",
+                "sqlExpression": "__timestamp",
+                "columnType": "BASE_AXIS",
+            },
+            "country",
+            "city",
+        ],
+        metrics=["revenue"],
+        series_limit=20,
+    )
+
+    prequery_obj = query_object.get_series_limit_prequery_obj(
+        granularity=None,
+        inner_from_dttm=None,
+        inner_to_dttm=None,
+    )
+
+    # The columns in prequery should exclude the base axis column
+    assert prequery_obj["columns"] == ["country", "city"]