Use time spines to determine metric_time grain in no-metric queries

metricflow-semantics/metricflow_semantics/model/semantics/linkable_spec_resolver.py

@@ -40,6 +40,7 @@
 from metricflow_semantics.model.semantics.linkable_element_set import LinkableElementSet
 from metricflow_semantics.model.semantics.semantic_model_join_evaluator import SemanticModelJoinEvaluator
 from metricflow_semantics.specs.time_dimension_spec import DEFAULT_TIME_GRANULARITY
+from metricflow_semantics.time.time_spine_source import TimeSpineSource
 
 if TYPE_CHECKING:
     from metricflow_semantics.model.semantics.semantic_model_lookup import SemanticModelLookup
@@ -124,6 +125,7 @@ def __init__(
         # Sort semantic models by name for consistency in building derived objects.
         self._semantic_models = sorted(self._semantic_manifest.semantic_models, key=lambda x: x.name)
         self._join_evaluator = SemanticModelJoinEvaluator(semantic_model_lookup)
+        self._time_spine_sources = TimeSpineSource.create_from_manifest(self._semantic_manifest)
 
         assert max_entity_links >= 0
         self._max_entity_links = max_entity_links
@@ -464,7 +466,8 @@ def _get_metric_time_elements(self, measure_reference: Optional[MeasureReference
                 time_dimension_reference=measure_agg_time_dimension_reference,
             )
         else:
-            defined_granularity = DEFAULT_TIME_GRANULARITY
+            # If querying metric_time without metrics, will query from time spines.
+            defined_granularity = min(self._time_spine_sources.keys())
 
         # It's possible to aggregate measures to coarser time granularities (except with cumulative metrics).
         possible_metric_time_granularities = tuple(

metricflow-semantics/metricflow_semantics/specs/time_dimension_spec.py

@@ -101,7 +101,12 @@ def without_first_entity_link(self) -> TimeDimensionSpec:  # noqa: D102
 
     @property
     def without_entity_links(self) -> TimeDimensionSpec:  # noqa: D102
-        return TimeDimensionSpec.from_name(self.element_name)
+        return TimeDimensionSpec(
+            element_name=self.element_name,
+            time_granularity=self.time_granularity,
+            date_part=self.date_part,
+            entity_links=(),
+        )
 
     @staticmethod
     def from_name(name: str) -> TimeDimensionSpec:  # noqa: D102
@@ -203,6 +208,3 @@ def generate_possible_specs_for_time_dimension(
     @property
     def is_metric_time(self) -> bool:  # noqa: D102
         return self.element_name == METRIC_TIME_ELEMENT_NAME
-
-
-DEFAULT_TIME_GRANULARITY = TimeGranularity.DAY

metricflow-semantics/metricflow_semantics/test_helpers/metric_time_dimension.py

@@ -9,6 +9,11 @@
 # Shortcuts for referring to the metric time dimension.
 MTD = MetricFlowReservedKeywords.METRIC_TIME.value
 MTD_REFERENCE = TimeDimensionReference(element_name=MetricFlowReservedKeywords.METRIC_TIME.value)
+MTD_SPEC_NANOSECOND = TimeDimensionSpec(
+    element_name=MetricFlowReservedKeywords.METRIC_TIME.value,
+    entity_links=(),
+    time_granularity=TimeGranularity.NANOSECOND,
+)
 MTD_SPEC_DAY = TimeDimensionSpec(
     element_name=MetricFlowReservedKeywords.METRIC_TIME.value, entity_links=(), time_granularity=TimeGranularity.DAY
 )

metricflow-semantics/metricflow_semantics/test_helpers/semantic_manifest_yamls/shared/project_configuration.yaml

@@ -5,3 +5,40 @@ project_configuration:
     - location: $source_schema.mf_time_spine
       column_name: ds
       grain: day
+  time_spines:
+    - node_relation:
+        alias: mf_time_spine_nanosecond
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: nanosecond
+    - node_relation:
+        alias: mf_time_spine_microsecond
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: microsecond
+    - node_relation:
+        alias: mf_time_spine_millisecond
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: millisecond
+    - node_relation:
+        alias: mf_time_spine_second
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: second
+    - node_relation:
+        alias: mf_time_spine_minute
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: minute
+    - node_relation:
+        alias: mf_time_spine_hour
+        schema_name: $source_schema
+      primary_column:
+        name: ts
+        time_granularity: hour

metricflow-semantics/tests_metricflow_semantics/query/group_by_item/test_matching_item_for_querying.py

@@ -17,7 +17,7 @@
     MetricGroupByItemResolutionNode,
 )
 from metricflow_semantics.test_helpers.config_helpers import MetricFlowTestConfiguration
-from metricflow_semantics.test_helpers.metric_time_dimension import MTD_SPEC_DAY, MTD_SPEC_MONTH, MTD_SPEC_YEAR
+from metricflow_semantics.test_helpers.metric_time_dimension import MTD_SPEC_MONTH, MTD_SPEC_NANOSECOND, MTD_SPEC_YEAR
 from metricflow_semantics.test_helpers.snapshot_helpers import assert_object_snapshot_equal
 
 from tests_metricflow_semantics.query.group_by_item.conftest import AmbiguousResolutionQueryId
@@ -46,7 +46,7 @@ def test_ambiguous_metric_time_in_query(  # noqa: D103
     )
 
     if case_id is AmbiguousResolutionQueryId.NO_METRICS:
-        assert result.spec == MTD_SPEC_DAY
+        assert result.spec == MTD_SPEC_NANOSECOND
     elif case_id is AmbiguousResolutionQueryId.SIMPLE_METRIC:
         assert result.spec == MTD_SPEC_MONTH
     elif case_id is AmbiguousResolutionQueryId.METRICS_WITH_SAME_TIME_GRAINS:

metricflow-semantics/tests_metricflow_semantics/snapshots/test_available_group_by_items.py/LinkableSpecSet/test_available_group_by_items__no_metrics__set0.txt

@@ -6,13 +6,55 @@
   "TimeDimension('metric_time', 'day', date_part_name='month')",
   "TimeDimension('metric_time', 'day', date_part_name='quarter')",
   "TimeDimension('metric_time', 'day', date_part_name='year')",
+  "TimeDimension('metric_time', 'hour')",
+  "TimeDimension('metric_time', 'hour', date_part_name='day')",
+  "TimeDimension('metric_time', 'hour', date_part_name='dow')",
+  "TimeDimension('metric_time', 'hour', date_part_name='doy')",
+  "TimeDimension('metric_time', 'hour', date_part_name='month')",
+  "TimeDimension('metric_time', 'hour', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'hour', date_part_name='year')",
+  "TimeDimension('metric_time', 'microsecond')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='day')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='dow')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='doy')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='month')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'microsecond', date_part_name='year')",
+  "TimeDimension('metric_time', 'millisecond')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='day')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='dow')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='doy')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='month')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'millisecond', date_part_name='year')",
+  "TimeDimension('metric_time', 'minute')",
+  "TimeDimension('metric_time', 'minute', date_part_name='day')",
+  "TimeDimension('metric_time', 'minute', date_part_name='dow')",
+  "TimeDimension('metric_time', 'minute', date_part_name='doy')",
+  "TimeDimension('metric_time', 'minute', date_part_name='month')",
+  "TimeDimension('metric_time', 'minute', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'minute', date_part_name='year')",
   "TimeDimension('metric_time', 'month')",
   "TimeDimension('metric_time', 'month', date_part_name='month')",
   "TimeDimension('metric_time', 'month', date_part_name='quarter')",
   "TimeDimension('metric_time', 'month', date_part_name='year')",
+  "TimeDimension('metric_time', 'nanosecond')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='day')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='dow')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='doy')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='month')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'nanosecond', date_part_name='year')",
   "TimeDimension('metric_time', 'quarter')",
   "TimeDimension('metric_time', 'quarter', date_part_name='quarter')",
   "TimeDimension('metric_time', 'quarter', date_part_name='year')",
+  "TimeDimension('metric_time', 'second')",
+  "TimeDimension('metric_time', 'second', date_part_name='day')",
+  "TimeDimension('metric_time', 'second', date_part_name='dow')",
+  "TimeDimension('metric_time', 'second', date_part_name='doy')",
+  "TimeDimension('metric_time', 'second', date_part_name='month')",
+  "TimeDimension('metric_time', 'second', date_part_name='quarter')",
+  "TimeDimension('metric_time', 'second', date_part_name='year')",
   "TimeDimension('metric_time', 'week')",
   "TimeDimension('metric_time', 'week', date_part_name='month')",
   "TimeDimension('metric_time', 'week', date_part_name='quarter')",

metricflow-semantics/tests_metricflow_semantics/snapshots/test_matching_item_for_filters.py/GroupByItemResolution/test_ambiguous_metric_time_in_query_filter__no_metrics__result.txt

@@ -1,11 +1,11 @@
 GroupByItemResolution(
-  spec=TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),
+  spec=TimeDimensionSpec(element_name='metric_time', time_granularity=NANOSECOND),
   linkable_element_set=LinkableElementSet(
     path_key_to_linkable_dimensions={
       ElementPathKey(
         element_name='metric_time',
         element_type=TIME_DIMENSION,
-        time_granularity=DAY,
+        time_granularity=NANOSECOND,
       ): (
         LinkableDimension(
           properties=(METRIC_TIME,),
@@ -16,7 +16,7 @@ GroupByItemResolution(
               semantic_model_name='__VIRTUAL__',
             ),
           ),
-          time_granularity=DAY,
+          time_granularity=NANOSECOND,
         ),
       ),
     },

metricflow-semantics/tests_metricflow_semantics/snapshots/test_semantic_model_container.py/tuple/test_linkable_elements_for_no_metrics_query__result0.txt

@@ -435,7 +435,7 @@
   'lux_listing__listing__lux_listing__twice_bookings_fill_nulls_with_0_without_time_spine',
   'lux_listing__listing__lux_listing__views',
   'lux_listing__listing__lux_listing__views_times_booking_value',
-  'metric_time__day',
+  'metric_time__nanosecond',
   'revenue_instance__ds__day',
   'revenue_instance__ds__extract_day',
   'revenue_instance__ds__extract_dow',

metricflow/dataflow/builder/node_evaluator.py

@@ -200,23 +200,26 @@ def _find_joinable_candidate_nodes_that_can_satisfy_linkable_specs(
         candidates_for_join: List[JoinLinkableInstancesRecipe] = []
         left_node_spec_set = left_node_instance_set.spec_set
         for right_node in self._nodes_available_for_joins:
+            data_set_in_right_node: SqlDataSet = self._node_data_set_resolver.get_output_data_set(right_node)
+            linkable_specs_in_right_node = data_set_in_right_node.instance_set.spec_set.linkable_specs
+
             # If right node is time spine source node, use cross join.
             if right_node in self._time_spine_nodes:
-                needed_metric_time_specs = group_specs_by_type(needed_linkable_specs).metric_time_specs
+                satisfiable_metric_time_specs = set(needed_linkable_specs).intersection(
+                    set(linkable_specs_in_right_node)
+                )
                 candidates_for_join.append(
                     JoinLinkableInstancesRecipe(
                         node_to_join=right_node,
                         join_on_entity=None,
-                        satisfiable_linkable_specs=list(needed_metric_time_specs),
+                        satisfiable_linkable_specs=list(satisfiable_metric_time_specs),
                         join_on_partition_dimensions=(),
                         join_on_partition_time_dimensions=(),
                         join_type=SqlJoinType.CROSS_JOIN,
                     )
                 )
                 continue
 
-            data_set_in_right_node: SqlDataSet = self._node_data_set_resolver.get_output_data_set(right_node)
-            linkable_specs_in_right_node = data_set_in_right_node.instance_set.spec_set.linkable_specs
             entity_specs_in_right_node = data_set_in_right_node.instance_set.spec_set.entity_specs
 
             # For each unlinked entity in the data set, create a candidate for joining.

metricflow/dataset/convert_semantic_model.py

@@ -104,7 +104,7 @@ def _create_time_dimension_instance(
         self,
         element_name: str,
         entity_links: Tuple[EntityReference, ...],
-        time_granularity: TimeGranularity = DEFAULT_TIME_GRANULARITY,
+        time_granularity: TimeGranularity,
         date_part: Optional[DatePart] = None,
         semantic_model_name: Optional[str] = None,
     ) -> TimeDimensionInstance:
@@ -332,7 +332,7 @@ def _build_time_dimension_instances_and_columns(
     ) -> Tuple[List[TimeDimensionInstance], List[SqlSelectColumn]]:
         time_dimension_instances: List[TimeDimensionInstance] = []
         select_columns: List[SqlSelectColumn] = []
-        # Add time dimensions with a smaller granularity for ease in query resolution
+        # Add time dimensions with a larger granularity for ease in query resolution
         for time_granularity in TimeGranularity:
             if time_granularity.to_int() > defined_time_granularity.to_int():
                 time_dimension_instance = self._create_time_dimension_instance(

tests_metricflow/fixtures/source_table_snapshots/time_spine_table/mf_time_spine_hour.yaml

@@ -0,0 +1,42 @@
+table_snapshot:
+  table_name: mf_time_spine_hour
+  column_definitions:
+    - name: ts
+      type: TIME
+  rows:
+    - ["2020-01-01 01:00:00"]
+    - ["2020-01-01 02:00:00"]
+    - ["2020-01-01 03:00:00"]
+    - ["2020-01-01 04:00:00"]
+    - ["2020-01-01 05:00:00"]
+    - ["2020-01-01 06:00:00"]
+    - ["2020-01-01 07:00:00"]
+    - ["2020-01-01 08:00:00"]
+    - ["2020-01-01 09:00:00"]
+    - ["2020-01-01 010:00:00"]
+    - ["2020-01-01 11:00:00"]
+    - ["2020-01-01 12:00:00"]
+    - ["2020-01-02 01:00:00"]
+    - ["2020-01-02 02:00:00"]
+    - ["2020-01-02 03:00:00"]
+    - ["2020-01-02 04:00:00"]
+    - ["2020-01-02 05:00:00"]
+    - ["2020-01-02 06:00:00"]
+    - ["2020-01-02 07:00:00"]
+    - ["2020-01-02 08:00:00"]
+    - ["2020-01-02 09:00:00"]
+    - ["2020-01-02 010:00:00"]
+    - ["2020-01-02 11:00:00"]
+    - ["2020-01-02 12:00:00"]
+    - ["2020-01-03 01:00:00"]
+    - ["2020-01-03 02:00:00"]
+    - ["2020-01-03 03:00:00"]
+    - ["2020-01-03 04:00:00"]
+    - ["2020-01-03 05:00:00"]
+    - ["2020-01-03 06:00:00"]
+    - ["2020-01-03 07:00:00"]
+    - ["2020-01-03 08:00:00"]
+    - ["2020-01-03 09:00:00"]
+    - ["2020-01-03 010:00:00"]
+    - ["2020-01-03 11:00:00"]
+    - ["2020-01-03 12:00:00"]

tests_metricflow/fixtures/source_table_snapshots/time_spine_table/mf_time_spine_microsecond.yaml

@@ -0,0 +1,38 @@
+table_snapshot:
+  table_name: mf_time_spine_microsecond
+  column_definitions:
+    - name: ts
+      type: TIME
+  rows:
+    - ["2020-01-01 00:00:00.000000"]
+    - ["2020-01-01 00:00:00.000001"]
+    - ["2020-01-01 00:00:00.000002"]
+    - ["2020-01-01 00:00:00.000003"]
+    - ["2020-01-01 00:00:00.000004"]
+    - ["2020-01-01 00:00:00.000005"]
+    - ["2020-01-01 00:00:00.000006"]
+    - ["2020-01-01 00:00:00.000007"]
+    - ["2020-01-01 00:00:00.000008"]
+    - ["2020-01-01 00:00:00.000009"]
+    - ["2020-01-01 00:00:00.000010"]
+    - ["2020-01-01 00:00:00.000011"]
+    - ["2020-01-01 00:00:00.000012"]
+    - ["2020-01-01 00:00:00.000013"]
+    - ["2020-01-01 00:00:00.000014"]
+    - ["2020-01-01 00:00:00.000015"]
+    - ["2020-01-01 00:00:00.000016"]
+    - ["2020-01-01 00:00:00.000017"]
+    - ["2020-01-01 00:00:00.000018"]
+    - ["2020-01-01 00:00:00.000019"]
+    - ["2020-01-01 00:00:00.000020"]
+    - ["2020-01-01 00:00:00.000021"]
+    - ["2020-01-01 00:00:00.000022"]
+    - ["2020-01-01 00:00:00.000023"]
+    - ["2020-01-01 00:00:00.000024"]
+    - ["2020-01-01 00:00:00.000025"]
+    - ["2020-01-01 00:00:00.000026"]
+    - ["2020-01-01 00:00:00.000027"]
+    - ["2020-01-01 00:00:00.000028"]
+    - ["2020-01-01 00:00:00.000029"]
+    - ["2020-01-01 00:00:00.000030"]
+

tests_metricflow/fixtures/source_table_snapshots/time_spine_table/mf_time_spine_millisecond.yaml

@@ -0,0 +1,37 @@
+table_snapshot:
+  table_name: mf_time_spine_millisecond
+  column_definitions:
+    - name: ts
+      type: TIME
+  rows:
+    - ["2020-01-01 00:00:00.001"]
+    - ["2020-01-01 00:00:00.002"]
+    - ["2020-01-01 00:00:00.003"]
+    - ["2020-01-01 00:00:00.004"]
+    - ["2020-01-01 00:00:00.005"]
+    - ["2020-01-01 00:00:00.006"]
+    - ["2020-01-01 00:00:00.007"]
+    - ["2020-01-01 00:00:00.008"]
+    - ["2020-01-01 00:00:00.009"]
+    - ["2020-01-01 00:00:00.010"]
+    - ["2020-01-01 00:00:00.011"]
+    - ["2020-01-01 00:00:00.012"]
+    - ["2020-01-01 00:00:00.013"]
+    - ["2020-01-01 00:00:00.014"]
+    - ["2020-01-01 00:00:00.015"]
+    - ["2020-01-01 00:00:00.016"]
+    - ["2020-01-01 00:00:00.017"]
+    - ["2020-01-01 00:00:00.018"]
+    - ["2020-01-01 00:00:00.019"]
+    - ["2020-01-01 00:00:00.020"]
+    - ["2020-01-01 00:00:00.021"]
+    - ["2020-01-01 00:00:00.022"]
+    - ["2020-01-01 00:00:00.023"]
+    - ["2020-01-01 00:00:00.024"]
+    - ["2020-01-01 00:00:00.025"]
+    - ["2020-01-01 00:00:00.026"]
+    - ["2020-01-01 00:00:00.027"]
+    - ["2020-01-01 00:00:00.028"]
+    - ["2020-01-01 00:00:00.029"]
+    - ["2020-01-01 00:00:00.030"]
+