(superset) 01/02: Fix filter

[be...@apache.org]

This is an automated email from the ASF dual-hosted git repository.

beto pushed a commit to branch semantic-layer-implementation
in repository https://gitbox.apache.org/repos/asf/superset.git

commit b437421a8edac1b7845a0bb72501f8e707d56617
Author: Beto Dealmeida <ro...@dealmeida.net>
AuthorDate: Thu Dec 11 15:06:13 2025 -0500

    Fix filter
---
 superset/semantic_layers/mapper.py                 | 65 +++++++++++++++-------
 .../semantic_layers/snowflake/semantic_view.py     |  5 --
 2 files changed, 46 insertions(+), 24 deletions(-)

diff --git a/superset/semantic_layers/mapper.py b/superset/semantic_layers/mapper.py
index 5c4896d395..f6bfbeb0fb 100644
--- a/superset/semantic_layers/mapper.py
+++ b/superset/semantic_layers/mapper.py
@@ -277,6 +277,8 @@ def map_query_object(query_object: ValidatedQueryObject) -> list[SemanticQuery]:
     This function maps the `QueryObject` into query objects that focus less on
     visualization and more on semantics.
     """
+    print("BETO")
+    print(query_object)
     semantic_view = query_object.datasource.implementation
 
     all_metrics = {metric.name: metric for metric in semantic_view.metrics}
@@ -321,6 +323,7 @@ def map_query_object(query_object: ValidatedQueryObject) -> list[SemanticQuery]:
             time_offset,
             all_dimensions,
         )
+        print(">>", filters)
 
         queries.append(
             SemanticQuery(
@@ -373,9 +376,15 @@ def _get_filters_from_query_object(
 
     # 4. Add all other filters from query_object.filter
     for filter_ in query_object.filter:
-        converted_filter = _convert_query_object_filter(filter_, all_dimensions)
-        if converted_filter:
-            filters.add(converted_filter)
+        # Skip temporal range filters - we're using inner bounds instead
+        if (
+            filter_.get("op") == FilterOperator.TEMPORAL_RANGE.value
+            and query_object.granularity
+        ):
+            continue
+
+        if converted_filters := _convert_query_object_filter(filter_, all_dimensions):
+            filters.update(converted_filters)
 
     return filters
 
@@ -503,17 +512,12 @@ def _get_time_bounds(
 def _convert_query_object_filter(
     filter_: ValidatedQueryObjectFilterClause,
     all_dimensions: dict[str, Dimension],
-) -> Filter | AdhocFilter | None:
+) -> set[Filter] | None:
     """
     Convert a QueryObject filter dict to a semantic layer Filter or AdhocFilter.
     """
     operator_str = filter_["op"]
 
-    # Handle TEMPORAL_RANGE filters (these are already handled by _get_time_filter)
-    if operator_str == FilterOperator.TEMPORAL_RANGE.value:
-        # Skip - already handled in _get_time_filter
-        return None
-
     # Handle simple column filters
     col = filter_.get("col")
     if col not in all_dimensions:
@@ -530,6 +534,25 @@ def _convert_query_object_filter(
     else:
         value = val_str
 
+    # Special case for temporal range
+    if operator_str == FilterOperator.TEMPORAL_RANGE.value:
+        # XXX
+        start, end = value.split(" : ")
+        return {
+            Filter(
+                type=PredicateType.WHERE,
+                column=dimension,
+                operator=Operator.GREATER_THAN_OR_EQUAL,
+                value=start,
+            ),
+            Filter(
+                type=PredicateType.WHERE,
+                column=dimension,
+                operator=Operator.LESS_THAN,
+                value=end,
+            ),
+        }
+
     # Map QueryObject operators to semantic layer operators
     operator_mapping = {
         FilterOperator.EQUALS.value: Operator.EQUALS,
@@ -551,12 +574,14 @@ def _convert_query_object_filter(
         # Unknown operator - create adhoc filter
         return None
 
-    return Filter(
-        type=PredicateType.WHERE,
-        column=dimension,
-        operator=operator,
-        value=value,
-    )
+    return {
+        Filter(
+            type=PredicateType.WHERE,
+            column=dimension,
+            operator=operator,
+            value=value,
+        )
+    }
 
 
 def _get_order_from_query_object(
@@ -693,12 +718,14 @@ def _get_group_limit_filters(
     # Add all other non-temporal filters from query_object.filter
     for filter_ in query_object.filter:
         # Skip temporal range filters - we're using inner bounds instead
-        if filter_.get("op") == FilterOperator.TEMPORAL_RANGE.value:
+        if (
+            filter_.get("op") == FilterOperator.TEMPORAL_RANGE.value
+            and query_object.granularity
+        ):
             continue
 
-        converted_filter = _convert_query_object_filter(filter_, all_dimensions)
-        if converted_filter:
-            filters.add(converted_filter)
+        if converted_filters := _convert_query_object_filter(filter_, all_dimensions):
+            filters.update(converted_filters)
 
     return filters if filters else None
 
diff --git a/superset/semantic_layers/snowflake/semantic_view.py b/superset/semantic_layers/snowflake/semantic_view.py
index 8ce849af2f..654a9e58ef 100644
--- a/superset/semantic_layers/snowflake/semantic_view.py
+++ b/superset/semantic_layers/snowflake/semantic_view.py
@@ -305,7 +305,6 @@ class SnowflakeSemanticView(SemanticViewImplementation):
         """
         Execute a query and return the results as a Pandas DataFrame.
         """
-        print("AM HERE")
         if not metrics and not dimensions:
             return DataFrame()
 
@@ -327,11 +326,7 @@ class SnowflakeSemanticView(SemanticViewImplementation):
             **{dimension.id: dimension.name for dimension in dimensions},
             **{metric.id: metric.name for metric in metrics},
         }
-        print("BETO")
-        print(df.columns)
-        print(mapping)
         df.rename(columns=mapping, inplace=True)
-        print(df.columns)
 
         return SemanticResult(
             requests=[