From fc669107a70470a2a38b4b331116439dce9df5c4 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Thu, 18 Jan 2024 11:33:48 -0800
Subject: [PATCH 01/22] WIP

---
 .../dataflow/builder/dataflow_plan_builder.py | 12 ++--
 .../model/semantics/semantic_model_lookup.py  | 17 ++---
 metricflow/protocols/semantics.py             |  2 +-
 .../cumulative_metric_requires_metric_time.py |  4 +-
 .../metric_time_requirements.py               | 71 +++++++++++++++----
 .../test_cases/itest_cumulative_metric.yaml   | 28 ++++++++
 .../test/integration/test_configured_cases.py |  3 +-
 .../model/test_semantic_model_container.py    | 24 +++----
 8 files changed, 117 insertions(+), 44 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index d602c38bb9..8d1e1fbc33 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -704,16 +704,18 @@ def _contains_multihop_linkables(linkable_specs: Sequence[LinkableInstanceSpec])
         """Returns true if any of the linkable specs requires a multi-hop join to realize."""
         return any(len(x.entity_links) > 1 for x in linkable_specs)
 
-    def _get_semantic_model_names_for_measures(self, measure_names: Sequence[MeasureSpec]) -> Set[str]:
+    def _get_semantic_model_names_for_measures(self, measures: Sequence[MeasureSpec]) -> Set[str]:
         """Return the names of the semantic models needed to compute the input measures.
 
         This is a temporary method for use in assertion boundaries while we implement support for multiple semantic models
         """
         semantic_model_names: Set[str] = set()
-        for measure_name in measure_names:
-            semantic_model_names = semantic_model_names.union(
-                {d.name for d in self._semantic_model_lookup.get_semantic_models_for_measure(measure_name.reference)}
-            )
+        for measure in measures:
+            semantic_model = self._semantic_model_lookup.get_semantic_model_for_measure(measure.reference)
+            if not semantic_model:
+                raise ValueError(f"Could not find measure with name {measure.reference} in configured semantic models.")
+            semantic_model_names.add(semantic_model.name)
+
         return semantic_model_names
 
     def _sort_by_suitability(self, nodes: Sequence[BaseOutput]) -> Sequence[BaseOutput]:
diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 9aceec4582..3d68d460a8 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -52,12 +52,13 @@ def __init__(  # noqa: D
         model: SemanticManifest,
     ) -> None:
         self._model = model
-        self._measure_index: Dict[MeasureReference, List[SemanticModel]] = defaultdict(list)
+        self._measure_index: Dict[MeasureReference, SemanticModel] = {}
         self._measure_aggs: Dict[
             MeasureReference, AggregationType
         ] = {}  # maps measures to their one consistent aggregation
         self._measure_agg_time_dimension: Dict[MeasureReference, TimeDimensionReference] = {}
         self._measure_non_additive_dimension_specs: Dict[MeasureReference, NonAdditiveDimensionSpec] = {}
+        # TODO: remove defaultdicts. Will add fake elements to the dict that might get referenced.
         self._dimension_index: Dict[DimensionReference, List[SemanticModel]] = defaultdict(list)
         self._linkable_reference_index: Dict[LinkableElementReference, List[SemanticModel]] = defaultdict(list)
         self._entity_index: Dict[Optional[str], List[SemanticModel]] = defaultdict(list)
@@ -141,12 +142,10 @@ def get_measure_from_semantic_model(semantic_model: SemanticModel, measure_refer
         )
 
     def get_measure(self, measure_reference: MeasureReference) -> Measure:  # noqa: D
-        if measure_reference not in self._measure_index:
+        semantic_model = self._measure_index.get(measure_reference)
+        if not semantic_model:
             raise ValueError(f"Could not find measure with name ({measure_reference}) in configured semantic models")
 
-        assert len(self._measure_index[measure_reference]) >= 1
-        # Measures should be consistent across semantic models, so just use the first one.
-        semantic_model = list(self._measure_index[measure_reference])[0]
         return SemanticModelLookup.get_measure_from_semantic_model(
             semantic_model=semantic_model, measure_reference=measure_reference
         )
@@ -155,10 +154,8 @@ def get_entity_references(self) -> Sequence[EntityReference]:  # noqa: D
         return list(self._entity_ref_to_entity.keys())
 
     # DSC interface
-    def get_semantic_models_for_measure(  # noqa: D
-        self, measure_reference: MeasureReference
-    ) -> Sequence[SemanticModel]:
-        return self._measure_index[measure_reference]
+    def get_semantic_model_for_measure(self, measure_reference: MeasureReference) -> Optional[SemanticModel]:  # noqa: D
+        return self._measure_index.get(measure_reference)
 
     def get_agg_time_dimension_for_measure(  # noqa: D
         self, measure_reference: MeasureReference
@@ -202,7 +199,7 @@ def _add_semantic_model(self, semantic_model: SemanticModel) -> None:
 
         for measure in semantic_model.measures:
             self._measure_aggs[measure.reference] = measure.agg
-            self._measure_index[measure.reference].append(semantic_model)
+            self._measure_index[measure.reference] = semantic_model
             agg_time_dimension_reference = semantic_model.checked_agg_time_dimension_for_measure(measure.reference)
 
             matching_dimensions = tuple(
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index cdaeeaa9a6..291eb1d25a 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -85,7 +85,7 @@ def get_entity_references(self) -> Sequence[EntityReference]:
         raise NotImplementedError
 
     @abstractmethod
-    def get_semantic_models_for_measure(self, measure_reference: MeasureReference) -> Sequence[SemanticModel]:
+    def get_semantic_model_for_measure(self, measure_reference: MeasureReference) -> Optional[SemanticModel]:
         """Retrieve a list of all semantic model model objects associated with the measure reference."""
         raise NotImplementedError
 
diff --git a/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py b/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
index 484cd5131e..60893c6b98 100644
--- a/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
+++ b/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
@@ -24,7 +24,9 @@ class CumulativeMetricRequiresMetricTimeIssue(MetricFlowQueryResolutionIssue):
     def ui_description(self, associated_input: MetricFlowQueryResolverInput) -> str:
         return (
             f"The query includes a cumulative metric {repr(self.metric_reference.element_name)} that does not "
-            f"accumulate over all-time, but the group-by items do not include {repr(METRIC_TIME_ELEMENT_NAME)}"
+            f"accumulate over all-time, but the group-by items do not include {repr(METRIC_TIME_ELEMENT_NAME)} "
+            "or the metric's agg_time_dimension."
+            # TODO: add name of agg_time_dim?
         )
 
     @override
diff --git a/metricflow/query/validation_rules/metric_time_requirements.py b/metricflow/query/validation_rules/metric_time_requirements.py
index fe75f6854c..61c8e506aa 100644
--- a/metricflow/query/validation_rules/metric_time_requirements.py
+++ b/metricflow/query/validation_rules/metric_time_requirements.py
@@ -1,11 +1,11 @@
 from __future__ import annotations
 
-from typing import List, Sequence
+from typing import List, Sequence, Tuple
 
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
 from dbt_semantic_interfaces.naming.keywords import METRIC_TIME_ELEMENT_NAME
 from dbt_semantic_interfaces.protocols import WhereFilterIntersection
-from dbt_semantic_interfaces.references import MetricReference
+from dbt_semantic_interfaces.references import EntityReference, MetricReference, TimeDimensionReference
 from dbt_semantic_interfaces.type_enums import MetricType, TimeGranularity
 from dbt_semantic_interfaces.type_enums.date_part import DatePart
 from typing_extensions import override
@@ -34,29 +34,36 @@ class MetricTimeQueryValidationRule(PostResolutionQueryValidationRule):
     def __init__(self, manifest_lookup: SemanticManifestLookup) -> None:  # noqa: D
         super().__init__(manifest_lookup=manifest_lookup)
 
-        metric_time_specs: List[TimeDimensionSpec] = []
+        self._metric_time_specs = tuple(
+            self._generate_valid_specs_for_time_dimension(
+                time_dimension_reference=TimeDimensionReference(element_name=METRIC_TIME_ELEMENT_NAME), entity_links=()
+            )
+        )
 
+    def _generate_valid_specs_for_time_dimension(
+        self, time_dimension_reference: TimeDimensionReference, entity_links: Tuple[EntityReference, ...]
+    ) -> List[TimeDimensionSpec]:
+        time_dimension_specs: List[TimeDimensionSpec] = []
         for time_granularity in TimeGranularity:
-            metric_time_specs.append(
+            time_dimension_specs.append(
                 TimeDimensionSpec(
-                    element_name=METRIC_TIME_ELEMENT_NAME,
-                    entity_links=(),
+                    element_name=time_dimension_reference.element_name,
+                    entity_links=entity_links,
                     time_granularity=time_granularity,
                     date_part=None,
                 )
             )
         for date_part in DatePart:
             for time_granularity in date_part.compatible_granularities:
-                metric_time_specs.append(
+                time_dimension_specs.append(
                     TimeDimensionSpec(
-                        element_name=METRIC_TIME_ELEMENT_NAME,
-                        entity_links=(),
+                        element_name=time_dimension_reference.element_name,
+                        entity_links=entity_links,
                         time_granularity=time_granularity,
                         date_part=date_part,
                     )
                 )
-
-        self._metric_time_specs = tuple(metric_time_specs)
+        return time_dimension_specs
 
     def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInputForQuery) -> bool:
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
@@ -65,6 +72,38 @@ def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInpu
 
         return False
 
+    def _group_by_items_include_agg_time_dimension(
+        self, query_resolver_input: ResolverInputForQuery, metric_reference: MetricReference
+    ) -> bool:
+        metric = self._manifest_lookup.metric_lookup.get_metric(metric_reference=metric_reference)
+        semantic_model_lookup = self._manifest_lookup.semantic_model_lookup
+
+        valid_agg_time_dimension_specs: List[TimeDimensionSpec] = []
+        for measure_reference in metric.measure_references:
+            agg_time_dimension_reference = semantic_model_lookup.get_agg_time_dimension_for_measure(measure_reference)
+            semantic_model = semantic_model_lookup.get_semantic_model_for_measure(measure_reference)
+            assert semantic_model, f"No semantic model found for measure {measure_reference}."
+
+            # is this too broad? need to narrow entity links?
+            possible_entity_links = semantic_model_lookup.entity_links_for_local_elements(semantic_model)
+            for entity_link in possible_entity_links:
+                valid_agg_time_dimension_specs.extend(
+                    self._generate_valid_specs_for_time_dimension(
+                        time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
+                    )
+                )
+        print("valid:::")
+        for x in valid_agg_time_dimension_specs:
+            print(f"\n{x}")
+
+        print("requested:::")
+        for group_by_item_input in query_resolver_input.group_by_item_inputs:
+            print(print(f"\n{group_by_item_input}"))
+            if group_by_item_input.spec_pattern.matches_any(valid_agg_time_dimension_specs):
+                return True
+
+        return False
+
     @override
     def validate_metric_in_resolution_dag(
         self,
@@ -73,7 +112,11 @@ def validate_metric_in_resolution_dag(
         resolution_path: MetricFlowQueryResolutionPath,
     ) -> MetricFlowQueryResolutionIssueSet:
         metric = self._get_metric(metric_reference)
-        query_includes_metric_time = self._group_by_items_include_metric_time(resolver_input_for_query)
+        query_includes_metric_time_or_agg_time_dimension = self._group_by_items_include_metric_time(
+            resolver_input_for_query
+        ) or self._group_by_items_include_agg_time_dimension(
+            query_resolver_input=resolver_input_for_query, metric_reference=metric_reference
+        )
 
         if metric.type is MetricType.SIMPLE or metric.type is MetricType.CONVERSION:
             return MetricFlowQueryResolutionIssueSet.empty_instance()
@@ -81,7 +124,7 @@ def validate_metric_in_resolution_dag(
             if (
                 metric.type_params is not None
                 and (metric.type_params.window is not None or metric.type_params.grain_to_date is not None)
-                and not query_includes_metric_time
+                and not query_includes_metric_time_or_agg_time_dimension
             ):
                 return MetricFlowQueryResolutionIssueSet.from_issue(
                     CumulativeMetricRequiresMetricTimeIssue.from_parameters(
@@ -97,7 +140,7 @@ def validate_metric_in_resolution_dag(
                 for input_metric in metric.input_metrics
             )
 
-            if has_time_offset and not query_includes_metric_time:
+            if has_time_offset and not query_includes_metric_time_or_agg_time_dimension:
                 return MetricFlowQueryResolutionIssueSet.from_issue(
                     OffsetMetricRequiresMetricTimeIssue.from_parameters(
                         metric_reference=metric_reference,
diff --git a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
index a86a9ea838..1f5d8b0eb9 100644
--- a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
+++ b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
@@ -347,3 +347,31 @@ integration_test:
       OR {{ render_time_constraint("a.ds", "2020-01-04", "2020-01-04") }}
     GROUP BY a.ds
     ORDER BY a.ds
+---
+integration_test:
+  name: cumulative_metric_with_agg_time_dimension
+  description: Query a cumulative metric with its agg_time_dimension.
+  model: SIMPLE_MODEL
+  metrics: ["trailing_2_months_revenue"]
+  group_bys: ["company__ds__day"]
+  order_bys: ["company__ds__day"]
+  time_constraint: ["2020-03-05", "2021-01-04"]
+  check_query: |
+    SELECT
+      SUM(b.txn_revenue) as trailing_2_months_revenue
+      , a.ds AS company__ds__day
+    FROM (
+      SELECT ds
+      FROM {{ mf_time_spine_source }}
+      WHERE {{ render_time_constraint("ds", "2020-01-05", "2021-01-04") }}
+    ) a
+    INNER JOIN (
+      SELECT
+        revenue as txn_revenue
+        , created_at AS ds
+      FROM {{ source_schema }}.fct_revenue
+    ) b
+    ON b.ds <= a.ds AND b.ds > {{ render_date_sub("a", "ds", 2, TimeGranularity.MONTH) }}
+    WHERE {{ render_time_constraint("a.ds", "2020-03-05", "2021-01-04") }}
+    GROUP BY a.ds
+    ORDER BY a.ds
diff --git a/metricflow/test/integration/test_configured_cases.py b/metricflow/test/integration/test_configured_cases.py
index 92462b515f..6b6e080470 100644
--- a/metricflow/test/integration/test_configured_cases.py
+++ b/metricflow/test/integration/test_configured_cases.py
@@ -230,7 +230,8 @@ def filter_not_supported_features(
 
 @pytest.mark.parametrize(
     "name",
-    CONFIGURED_INTEGRATION_TESTS_REPOSITORY.all_test_case_names,
+    # CONFIGURED_INTEGRATION_TESTS_REPOSITORY.all_test_case_names,
+    ["itest_cumulative_metric.yaml/cumulative_metric_with_agg_time_dimension"],
     ids=lambda name: f"name={name}",
 )
 def test_case(
diff --git a/metricflow/test/model/test_semantic_model_container.py b/metricflow/test/model/test_semantic_model_container.py
index 80ec27d5c7..1623eae3cb 100644
--- a/metricflow/test/model/test_semantic_model_container.py
+++ b/metricflow/test/model/test_semantic_model_container.py
@@ -58,18 +58,18 @@ def test_get_elements(semantic_model_lookup: SemanticModelLookup) -> None:  # no
         assert semantic_model_lookup.get_measure(measure_reference=measure_reference).reference == measure_reference
 
 
-def test_get_semantic_models_for_measure(semantic_model_lookup: SemanticModelLookup) -> None:  # noqa: D
-    bookings_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="bookings"))
-    assert len(bookings_sources) == 1
-    assert bookings_sources[0].name == "bookings_source"
-
-    views_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="views"))
-    assert len(views_sources) == 1
-    assert views_sources[0].name == "views_source"
-
-    listings_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="listings"))
-    assert len(listings_sources) == 1
-    assert listings_sources[0].name == "listings_latest"
+def test_get_semantic_model_for_measure(semantic_model_lookup: SemanticModelLookup) -> None:  # noqa: D
+    bookings_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="bookings"))
+    assert bookings_source
+    assert bookings_source.name == "bookings_source"
+
+    views_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="views"))
+    assert views_source
+    assert views_source.name == "views_source"
+
+    listings_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="listings"))
+    assert listings_source
+    assert listings_source.name == "listings_latest"
 
 
 def test_elements_for_metric(  # noqa: D

From 25ef666b7e48a2ac6db8aed3045063311dee391f Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Thu, 18 Jan 2024 14:49:44 -0800
Subject: [PATCH 02/22] Remove unneeded change

---
 .../dataflow/builder/dataflow_plan_builder.py | 10 ++++----
 .../model/semantics/semantic_model_lookup.py  | 17 +++++++------
 metricflow/protocols/semantics.py             |  2 +-
 .../model/test_semantic_model_container.py    | 24 +++++++++----------
 4 files changed, 29 insertions(+), 24 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 8d1e1fbc33..6604dca8bc 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -711,10 +711,12 @@ def _get_semantic_model_names_for_measures(self, measures: Sequence[MeasureSpec]
         """
         semantic_model_names: Set[str] = set()
         for measure in measures:
-            semantic_model = self._semantic_model_lookup.get_semantic_model_for_measure(measure.reference)
-            if not semantic_model:
-                raise ValueError(f"Could not find measure with name {measure.reference} in configured semantic models.")
-            semantic_model_names.add(semantic_model.name)
+            semantic_model_names.update(
+                {
+                    semantic_model.name
+                    for semantic_model in self._semantic_model_lookup.get_semantic_models_for_measure(measure.reference)
+                }
+            )
 
         return semantic_model_names
 
diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 3d68d460a8..9aceec4582 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -52,13 +52,12 @@ def __init__(  # noqa: D
         model: SemanticManifest,
     ) -> None:
         self._model = model
-        self._measure_index: Dict[MeasureReference, SemanticModel] = {}
+        self._measure_index: Dict[MeasureReference, List[SemanticModel]] = defaultdict(list)
         self._measure_aggs: Dict[
             MeasureReference, AggregationType
         ] = {}  # maps measures to their one consistent aggregation
         self._measure_agg_time_dimension: Dict[MeasureReference, TimeDimensionReference] = {}
         self._measure_non_additive_dimension_specs: Dict[MeasureReference, NonAdditiveDimensionSpec] = {}
-        # TODO: remove defaultdicts. Will add fake elements to the dict that might get referenced.
         self._dimension_index: Dict[DimensionReference, List[SemanticModel]] = defaultdict(list)
         self._linkable_reference_index: Dict[LinkableElementReference, List[SemanticModel]] = defaultdict(list)
         self._entity_index: Dict[Optional[str], List[SemanticModel]] = defaultdict(list)
@@ -142,10 +141,12 @@ def get_measure_from_semantic_model(semantic_model: SemanticModel, measure_refer
         )
 
     def get_measure(self, measure_reference: MeasureReference) -> Measure:  # noqa: D
-        semantic_model = self._measure_index.get(measure_reference)
-        if not semantic_model:
+        if measure_reference not in self._measure_index:
             raise ValueError(f"Could not find measure with name ({measure_reference}) in configured semantic models")
 
+        assert len(self._measure_index[measure_reference]) >= 1
+        # Measures should be consistent across semantic models, so just use the first one.
+        semantic_model = list(self._measure_index[measure_reference])[0]
         return SemanticModelLookup.get_measure_from_semantic_model(
             semantic_model=semantic_model, measure_reference=measure_reference
         )
@@ -154,8 +155,10 @@ def get_entity_references(self) -> Sequence[EntityReference]:  # noqa: D
         return list(self._entity_ref_to_entity.keys())
 
     # DSC interface
-    def get_semantic_model_for_measure(self, measure_reference: MeasureReference) -> Optional[SemanticModel]:  # noqa: D
-        return self._measure_index.get(measure_reference)
+    def get_semantic_models_for_measure(  # noqa: D
+        self, measure_reference: MeasureReference
+    ) -> Sequence[SemanticModel]:
+        return self._measure_index[measure_reference]
 
     def get_agg_time_dimension_for_measure(  # noqa: D
         self, measure_reference: MeasureReference
@@ -199,7 +202,7 @@ def _add_semantic_model(self, semantic_model: SemanticModel) -> None:
 
         for measure in semantic_model.measures:
             self._measure_aggs[measure.reference] = measure.agg
-            self._measure_index[measure.reference] = semantic_model
+            self._measure_index[measure.reference].append(semantic_model)
             agg_time_dimension_reference = semantic_model.checked_agg_time_dimension_for_measure(measure.reference)
 
             matching_dimensions = tuple(
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index 291eb1d25a..cdaeeaa9a6 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -85,7 +85,7 @@ def get_entity_references(self) -> Sequence[EntityReference]:
         raise NotImplementedError
 
     @abstractmethod
-    def get_semantic_model_for_measure(self, measure_reference: MeasureReference) -> Optional[SemanticModel]:
+    def get_semantic_models_for_measure(self, measure_reference: MeasureReference) -> Sequence[SemanticModel]:
         """Retrieve a list of all semantic model model objects associated with the measure reference."""
         raise NotImplementedError
 
diff --git a/metricflow/test/model/test_semantic_model_container.py b/metricflow/test/model/test_semantic_model_container.py
index 1623eae3cb..80ec27d5c7 100644
--- a/metricflow/test/model/test_semantic_model_container.py
+++ b/metricflow/test/model/test_semantic_model_container.py
@@ -58,18 +58,18 @@ def test_get_elements(semantic_model_lookup: SemanticModelLookup) -> None:  # no
         assert semantic_model_lookup.get_measure(measure_reference=measure_reference).reference == measure_reference
 
 
-def test_get_semantic_model_for_measure(semantic_model_lookup: SemanticModelLookup) -> None:  # noqa: D
-    bookings_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="bookings"))
-    assert bookings_source
-    assert bookings_source.name == "bookings_source"
-
-    views_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="views"))
-    assert views_source
-    assert views_source.name == "views_source"
-
-    listings_source = semantic_model_lookup.get_semantic_model_for_measure(MeasureReference(element_name="listings"))
-    assert listings_source
-    assert listings_source.name == "listings_latest"
+def test_get_semantic_models_for_measure(semantic_model_lookup: SemanticModelLookup) -> None:  # noqa: D
+    bookings_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="bookings"))
+    assert len(bookings_sources) == 1
+    assert bookings_sources[0].name == "bookings_source"
+
+    views_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="views"))
+    assert len(views_sources) == 1
+    assert views_sources[0].name == "views_source"
+
+    listings_sources = semantic_model_lookup.get_semantic_models_for_measure(MeasureReference(element_name="listings"))
+    assert len(listings_sources) == 1
+    assert listings_sources[0].name == "listings_latest"
 
 
 def test_elements_for_metric(  # noqa: D

From 1a471995840224dd61dbfc3eefb499fe94984370 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Thu, 18 Jan 2024 15:43:36 -0800
Subject: [PATCH 03/22] Get correct primary entity

---
 .../model/semantics/semantic_model_lookup.py  |  8 ++---
 metricflow/protocols/semantics.py             |  5 +++
 .../metric_time_requirements.py               | 33 ++++++++++---------
 .../test_cases/itest_cumulative_metric.yaml   |  6 ++--
 metricflow/test/query/test_query_parser.py    |  8 ++---
 5 files changed, 33 insertions(+), 27 deletions(-)

diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 9aceec4582..33cb099c48 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -224,7 +224,7 @@ def _add_semantic_model(self, semantic_model: SemanticModel) -> None:
                     f"Aggregation time dimension does not have a time granularity set: {agg_time_dimension}"
                 )
 
-            primary_entity = SemanticModelLookup._resolved_primary_entity(semantic_model)
+            primary_entity = SemanticModelLookup.resolved_primary_entity(semantic_model)
 
             if primary_entity is None:
                 raise RuntimeError(
@@ -299,7 +299,7 @@ def get_entity_from_semantic_model(
         )
 
     @staticmethod
-    def _resolved_primary_entity(semantic_model: SemanticModel) -> Optional[EntityReference]:
+    def resolved_primary_entity(semantic_model: SemanticModel) -> Optional[EntityReference]:
         """Return the primary entity for dimensions in the model."""
         primary_entity_reference = semantic_model.primary_entity_reference
 
@@ -308,14 +308,12 @@ def _resolved_primary_entity(semantic_model: SemanticModel) -> Optional[EntityRe
         )
 
         # This should be caught by the validation, but adding a sanity check.
-        assert len(entities_with_type_primary) <= 1, f"Found >1 primary entity in {semantic_model}"
+        assert len(entities_with_type_primary) <= 1, f"Found > 1 primary entity in {semantic_model}"
         if primary_entity_reference is not None:
             assert len(entities_with_type_primary) == 0, (
                 f"The primary_entity field was set to {primary_entity_reference}, but there are non-zero entities with "
                 f"type {EntityType.PRIMARY} in {semantic_model}"
             )
-
-        if primary_entity_reference is not None:
             return primary_entity_reference
 
         if len(entities_with_type_primary) > 0:
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index cdaeeaa9a6..3266e5fd05 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -98,6 +98,11 @@ def get_entity_in_semantic_model(self, ref: SemanticModelElementReference) -> Op
         """Retrieve the entity matching the element -> semantic model mapping, if any."""
         raise NotImplementedError
 
+    @staticmethod
+    def resolved_primary_entity(semantic_model: SemanticModel) -> Optional[EntityReference]:
+        """Return the primary entity for dimensions in the model."""
+        raise NotImplementedError
+
     @abstractmethod
     def get_by_reference(self, semantic_model_reference: SemanticModelReference) -> Optional[SemanticModel]:
         """Retrieve the semantic model object matching the input semantic model reference, if any."""
diff --git a/metricflow/query/validation_rules/metric_time_requirements.py b/metricflow/query/validation_rules/metric_time_requirements.py
index 61c8e506aa..8f16508949 100644
--- a/metricflow/query/validation_rules/metric_time_requirements.py
+++ b/metricflow/query/validation_rules/metric_time_requirements.py
@@ -81,24 +81,27 @@ def _group_by_items_include_agg_time_dimension(
         valid_agg_time_dimension_specs: List[TimeDimensionSpec] = []
         for measure_reference in metric.measure_references:
             agg_time_dimension_reference = semantic_model_lookup.get_agg_time_dimension_for_measure(measure_reference)
-            semantic_model = semantic_model_lookup.get_semantic_model_for_measure(measure_reference)
-            assert semantic_model, f"No semantic model found for measure {measure_reference}."
-
-            # is this too broad? need to narrow entity links?
-            possible_entity_links = semantic_model_lookup.entity_links_for_local_elements(semantic_model)
-            for entity_link in possible_entity_links:
-                valid_agg_time_dimension_specs.extend(
-                    self._generate_valid_specs_for_time_dimension(
-                        time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
-                    )
+
+            # A measure's gg_time_dimension is required to be in the same semantic model as the measure,
+            # so we can assume the same semantic model for both measure and dimension.
+            semantic_models = semantic_model_lookup.get_semantic_models_for_measure(measure_reference)
+            assert (
+                len(semantic_models) == 1
+            ), f"Expected exactly one semantic model for measure {measure_reference}, but found semantic models {semantic_models}."
+            semantic_model = semantic_models[0]
+
+            entity_link = semantic_model_lookup.resolved_primary_entity(semantic_model)
+            assert (
+                entity_link is not None
+            ), f"Expected semantic model {semantic_model} to have a primary entity since is contains dimensions, but found none."
+
+            valid_agg_time_dimension_specs.extend(
+                self._generate_valid_specs_for_time_dimension(
+                    time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
                 )
-        print("valid:::")
-        for x in valid_agg_time_dimension_specs:
-            print(f"\n{x}")
+            )
 
-        print("requested:::")
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
-            print(print(f"\n{group_by_item_input}"))
             if group_by_item_input.spec_pattern.matches_any(valid_agg_time_dimension_specs):
                 return True
 
diff --git a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
index 1f5d8b0eb9..7ace7d118c 100644
--- a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
+++ b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
@@ -353,13 +353,13 @@ integration_test:
   description: Query a cumulative metric with its agg_time_dimension.
   model: SIMPLE_MODEL
   metrics: ["trailing_2_months_revenue"]
-  group_bys: ["company__ds__day"]
-  order_bys: ["company__ds__day"]
+  group_bys: ["revenue_instance__ds__day"]
+  order_bys: ["revenue_instance__ds__day"]
   time_constraint: ["2020-03-05", "2021-01-04"]
   check_query: |
     SELECT
       SUM(b.txn_revenue) as trailing_2_months_revenue
-      , a.ds AS company__ds__day
+      , a.ds AS revenue_instance__ds__day
     FROM (
       SELECT ds
       FROM {{ mf_time_spine_source }}
diff --git a/metricflow/test/query/test_query_parser.py b/metricflow/test/query/test_query_parser.py
index 7860d2a66d..ee927e1b85 100644
--- a/metricflow/test/query/test_query_parser.py
+++ b/metricflow/test/query/test_query_parser.py
@@ -103,7 +103,7 @@
           type: categorical
           expr: country
 
-      primary_entity: company
+      primary_entity: revenue_instance
 
       entities:
         - name: user
@@ -455,7 +455,7 @@ def test_cumulative_metric_wrong_time_dimension_validation() -> None:
     with pytest.raises(InvalidQueryException, match="do not include 'metric_time'"):
         query_parser.parse_and_validate_query(
             metric_names=["revenue_cumulative"],
-            group_by_names=["company__loaded_at"],
+            group_by_names=["revenue_instance__loaded_at"],
         )
 
 
@@ -480,7 +480,7 @@ def test_cumulative_metric_agg_time_dimension_name_validation() -> None:
     with pytest.raises(InvalidQueryException, match="do not include 'metric_time'"):
         query_parser.parse_and_validate_query(
             metric_names=["revenue_cumulative"],
-            group_by_names=["company__ds"],
+            group_by_names=["revenue_instance__loaded_at"],
         )
 
 
@@ -531,7 +531,7 @@ def test_derived_metric_with_offset_parsing() -> None:
     with pytest.raises(InvalidQueryException, match="do not include 'metric_time'"):
         query_parser.parse_and_validate_query(
             metric_names=["revenue_growth_2_weeks"],
-            group_by_names=["company__country"],
+            group_by_names=["revenue_instance__country"],
         )
 
     # Query with time dimension

From 08d2e0f56977f7c2eb7c254927816836ded19ce4 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Fri, 19 Jan 2024 16:01:09 -0800
Subject: [PATCH 04/22] WIP

---
 .../dataflow/builder/dataflow_plan_builder.py | 95 +++++++++++++------
 metricflow/model/semantics/metric_lookup.py   | 36 ++++++-
 .../model/semantics/semantic_model_lookup.py  | 23 ++++-
 metricflow/plan_conversion/dataflow_to_sql.py |  9 +-
 metricflow/protocols/semantics.py             |  8 ++
 .../metric_time_requirements.py               | 61 ++----------
 metricflow/specs/specs.py                     | 28 +++++-
 7 files changed, 171 insertions(+), 89 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 6604dca8bc..1eabbaad81 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -412,10 +412,10 @@ def _build_base_metric_output_node(
         metric_input_measure_spec = self._build_input_measure_spec_for_base_metric(
             filter_spec_factory=filter_spec_factory,
             metric_reference=metric_reference,
-            query_contains_metric_time=queried_linkable_specs.contains_metric_time,
+            queried_linkable_specs=queried_linkable_specs,
             child_metric_offset_window=metric_spec.offset_window,
             child_metric_offset_to_grain=metric_spec.offset_to_grain,
-            culmination_description=CumulativeMeasureDescription(
+            cumulation_description=CumulativeMeasureDescription(
                 cumulative_window=metric.type_params.window,
                 cumulative_grain_to_date=metric.type_params.grain_to_date,
             )
@@ -504,9 +504,14 @@ def _build_derived_metric_output_node(
 
         # For nested ratio / derived metrics with time offset, apply offset & where constraint after metric computation.
         if metric_spec.has_time_offset:
+            # TODO: if you only query with the agg_time_dimension for the offset metric, should that work? (assuming another input metric uses a diff agg_time_dim)
+            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
+            if not query_contains_metric_time_or_agg_time_dimension:
+                pass  # check for agg_time_dimension and update accordingly
+                # Write a test case for this scenario
             assert (
-                queried_linkable_specs.contains_metric_time
-            ), "Joining to time spine requires querying with metric_time."
+                query_contains_metric_time_or_agg_time_dimension
+            ), "Joining to time spine requires querying with metric_time or the appropriate agg_time_dimension."
             output_node = JoinToTimeSpineNode(
                 parent_node=output_node,
                 requested_metric_time_dimension_specs=list(queried_linkable_specs.metric_time_specs),
@@ -1045,8 +1050,8 @@ def _build_input_measure_spec_for_base_metric(
         child_metric_offset_window: Optional[MetricTimeWindow],
         child_metric_offset_to_grain: Optional[TimeGranularity],
         descendent_filter_specs: Sequence[WhereFilterSpec],
-        query_contains_metric_time: bool,
-        culmination_description: Optional[CumulativeMeasureDescription],
+        queried_linkable_specs: LinkableSpecSet,
+        cumulation_description: Optional[CumulativeMeasureDescription],
     ) -> MetricInputMeasureSpec:
         """Return the input measure spec required to compute the base metric.
 
@@ -1090,12 +1095,17 @@ def _build_input_measure_spec_for_base_metric(
         # Even if the measure is configured to join to time spine, if there's no metric_time in the query,
         # there's no need to join to the time spine since all metric_time will be aggregated.
         after_aggregation_time_spine_join_description = None
-        if input_measure.join_to_timespine and query_contains_metric_time:
-            after_aggregation_time_spine_join_description = JoinToTimeSpineDescription(
-                join_type=SqlJoinType.LEFT_OUTER,
-                offset_window=None,
-                offset_to_grain=None,
-            )
+        if input_measure.join_to_timespine:
+            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
+            if not query_contains_metric_time_or_agg_time_dimension:
+                pass  # check for agg_time_dimension and update accordingly
+                # Write a test case for this scenario
+            if query_contains_metric_time_or_agg_time_dimension:
+                after_aggregation_time_spine_join_description = JoinToTimeSpineDescription(
+                    join_type=SqlJoinType.LEFT_OUTER,
+                    offset_window=None,
+                    offset_to_grain=None,
+                )
 
         filter_specs: List[WhereFilterSpec] = []
         filter_specs.extend(
@@ -1116,7 +1126,7 @@ def _build_input_measure_spec_for_base_metric(
             fill_nulls_with=input_measure.fill_nulls_with,
             offset_window=child_metric_offset_window,
             offset_to_grain=child_metric_offset_to_grain,
-            culmination_description=culmination_description,
+            cumulation_description=cumulation_description,
             filter_specs=tuple(filter_specs),
             alias=input_measure.alias,
             before_aggregation_time_spine_join_description=before_aggregation_time_spine_join_description,
@@ -1211,15 +1221,15 @@ def _build_aggregated_measure_from_measure_source_node(
         measure_recipe: Optional[DataflowRecipe] = None,
     ) -> BaseOutput:
         measure_spec = metric_input_measure_spec.measure_spec
-        cumulative = metric_input_measure_spec.culmination_description is not None
+        cumulative = metric_input_measure_spec.cumulation_description is not None
         cumulative_window = (
-            metric_input_measure_spec.culmination_description.cumulative_window
-            if metric_input_measure_spec.culmination_description is not None
+            metric_input_measure_spec.cumulation_description.cumulative_window
+            if metric_input_measure_spec.cumulation_description is not None
             else None
         )
         cumulative_grain_to_date = (
-            metric_input_measure_spec.culmination_description.cumulative_grain_to_date
-            if metric_input_measure_spec.culmination_description
+            metric_input_measure_spec.cumulation_description.cumulative_grain_to_date
+            if metric_input_measure_spec.cumulation_description
             else None
         )
         measure_properties = self._build_measure_spec_properties([measure_spec])
@@ -1278,25 +1288,43 @@ def _build_aggregated_measure_from_measure_source_node(
                 f"Recipe not found for measure spec: {measure_spec} and linkable specs: {required_linkable_specs}"
             )
 
-        # If a cumulative metric is queried with metric_time, join over time range.
+        # If a cumulative metric is queried with metric_time or agg_time_dimension, join over time range.
         # Otherwise, the measure will be aggregated over all time.
         time_range_node: Optional[JoinOverTimeRangeNode] = None
-        if cumulative and queried_linkable_specs.contains_metric_time:
-            time_range_node = JoinOverTimeRangeNode(
-                parent_node=measure_recipe.source_node,
-                window=cumulative_window,
-                grain_to_date=cumulative_grain_to_date,
-                time_range_constraint=time_range_constraint
-                if not before_aggregation_time_spine_join_description
-                else None,
-            )
+        if cumulative:
+            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
+            if not query_contains_metric_time_or_agg_time_dimension:
+                # TODO: Write a test case for this scenario
+                agg_time_dimension_element_path_key = (
+                    self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(measure_spec.reference)
+                )
+                for time_dimension_spec in queried_linkable_specs.time_dimension_specs:
+                    if (
+                        time_dimension_spec.element_name == agg_time_dimension_element_path_key.element_name
+                        and time_dimension_spec.entity_links == agg_time_dimension_element_path_key.entity_links
+                    ):
+                        query_contains_metric_time_or_agg_time_dimension = True
+            if query_contains_metric_time_or_agg_time_dimension:
+                time_range_node = JoinOverTimeRangeNode(
+                    parent_node=measure_recipe.source_node,
+                    window=cumulative_window,
+                    grain_to_date=cumulative_grain_to_date,
+                    time_range_constraint=time_range_constraint
+                    if not before_aggregation_time_spine_join_description
+                    else None,
+                )
 
         # If querying an offset metric, join to time spine before aggregation.
         join_to_time_spine_node: Optional[JoinToTimeSpineNode] = None
         if before_aggregation_time_spine_join_description is not None:
+            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
+            if not query_contains_metric_time_or_agg_time_dimension:
+                pass  # check for agg_time_dimension and update accordingly
+                # Write a test case for this scenario
             assert (
-                queried_linkable_specs.contains_metric_time
-            ), "Joining to time spine requires querying with metric time."
+                query_contains_metric_time_or_agg_time_dimension
+            ), "Joining to time spine requires querying with metric time or the appropriate agg_time_dimension."
+            # Can you use agg_time_dimension if it's a ratio metric? Only if both metrics use same agg time dim?
             assert before_aggregation_time_spine_join_description.join_type is SqlJoinType.INNER, (
                 f"Expected {SqlJoinType.INNER} for joining to time spine before aggregation. Remove this if there's a "
                 f"new use case."
@@ -1337,11 +1365,16 @@ def _build_aggregated_measure_from_measure_source_node(
         else:
             unaggregated_measure_node = filtered_measure_source_node
 
+        query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
+        if not query_contains_metric_time_or_agg_time_dimension:
+            pass  # check for agg_time_dimension and update accordingly
+            # Write a test case for this scenario
+
         cumulative_metric_constrained_node: Optional[ConstrainTimeRangeNode] = None
         if (
             cumulative_metric_adjusted_time_constraint is not None
             and time_range_constraint is not None
-            and queried_linkable_specs.contains_metric_time
+            and query_contains_metric_time_or_agg_time_dimension
         ):
             cumulative_metric_constrained_node = ConstrainTimeRangeNode(
                 unaggregated_measure_node, time_range_constraint
diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index 4f9df240d7..200e821eab 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -1,16 +1,25 @@
 from __future__ import annotations
 
 import logging
-from typing import Dict, FrozenSet, Optional, Sequence, Set
+from typing import Dict, FrozenSet, Optional, Sequence, Set, Tuple
 
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
 from dbt_semantic_interfaces.protocols.metric import Metric, MetricInputMeasure, MetricType
 from dbt_semantic_interfaces.protocols.semantic_manifest import SemanticManifest
-from dbt_semantic_interfaces.references import MeasureReference, MetricReference
+from dbt_semantic_interfaces.references import (
+    EntityReference,
+    MeasureReference,
+    MetricReference,
+    TimeDimensionReference,
+)
 
 from metricflow.errors.errors import DuplicateMetricError, MetricNotFoundError, NonExistentMeasureError
 from metricflow.model.semantics.linkable_element_properties import LinkableElementProperties
-from metricflow.model.semantics.linkable_spec_resolver import LinkableElementSet, ValidLinkableSpecResolver
+from metricflow.model.semantics.linkable_spec_resolver import (
+    LinkableElementSet,
+    ValidLinkableSpecResolver,
+    ElementPathKey,
+)
 from metricflow.model.semantics.semantic_model_join_evaluator import MAX_JOIN_HOPS
 from metricflow.model.semantics.semantic_model_lookup import SemanticModelLookup
 from metricflow.protocols.semantics import MetricAccessor
@@ -159,3 +168,24 @@ def contains_cumulative_or_time_offset_metric(self, metric_references: Sequence[
                     if input_metric.offset_window or input_metric.offset_to_grain:
                         return True
         return False
+
+    def _get_agg_time_dimension_path_keys_for_metric(self, metric_reference: MetricReference) -> Set[ElementPathKey]:
+        """Retrieves the aggregate time dimensions associated with the metric's measures."""
+        metric = self.get_metric(metric_reference)
+        assert metric.input_measures, f"No input measures found for metric {metric_reference}"
+        return {
+            self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(
+                measure_reference=input_measure.measure_reference
+            )
+            for input_measure in metric.input_measures
+        }
+
+    def get_agg_time_dimension_to_replace_metric_time(
+        self, metric_reference: MetricReference
+    ) -> Optional[ElementPathKey]:
+        agg_time_dimension_element_path_keys = self._get_agg_time_dimension_path_keys_for_metric(metric_reference)
+        if len(agg_time_dimension_element_path_keys) == 1:
+            return agg_time_dimension_element_path_keys[0]
+
+        # If the metric's input measures have different agg_time_dimensions, user must use metric_time.
+        return None
diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 33cb099c48..bbb26c8a56 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -3,8 +3,10 @@
 import logging
 from collections import defaultdict
 from copy import deepcopy
-from typing import Dict, List, Optional, Sequence, Set
+from typing import Dict, List, Optional, Sequence, Set, Tuple
 
+from dbt_semantic_interfaces.type_enums import TimeGranularity
+from dbt_semantic_interfaces.type_enums.date_part import DatePart
 from dbt_semantic_interfaces.pretty_print import pformat_big_objects
 from dbt_semantic_interfaces.protocols.dimension import Dimension
 from dbt_semantic_interfaces.protocols.entity import Entity
@@ -20,6 +22,7 @@
     SemanticModelReference,
     TimeDimensionReference,
 )
+from metricflow.model.semantics.linkable_spec_resolver import ElementPathKey
 from dbt_semantic_interfaces.type_enums import DimensionType, EntityType
 from dbt_semantic_interfaces.type_enums.aggregation_type import AggregationType
 from typing_extensions import override
@@ -345,3 +348,21 @@ def get_element_spec_for_name(self, element_name: str) -> LinkableInstanceSpec:
             return self._entity_ref_to_spec[EntityReference(element_name=element_name)]
         else:
             raise ValueError(f"Unable to find linkable element {element_name} in manifest")
+
+    def get_agg_time_dimension_path_key_for_measure(self, measure_reference: MeasureReference) -> ElementPathKey:
+        agg_time_dimension = self.get_agg_time_dimension_for_measure(measure_reference)
+
+        # A measure's agg_time_dimension is required to be in the same semantic model as the measure,
+        # so we can assume the same semantic model for both measure and dimension.
+        semantic_models = self.get_semantic_models_for_measure(measure_reference)
+        assert (
+            len(semantic_models) == 1
+        ), f"Expected exactly one semantic model for measure {measure_reference}, but found semantic models {semantic_models}."
+        semantic_model = semantic_models[0]
+
+        entity_link = self.resolved_primary_entity(semantic_model)
+        assert (
+            entity_link is not None
+        ), f"Expected semantic model {semantic_model} to have a primary entity since is contains dimensions, but found none."
+
+        return ElementPathKey(element_name=agg_time_dimension.element_name, entity_links=(entity_link,))
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 407cc01056..8b13b865cd 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -293,8 +293,13 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
                 metric_time_dimension_instance = instance
                 metric_time_dimension_spec = instance.spec
                 break
+        # User might refer to the agg_time_dimension by its dimension name instead of 'metric_time'.
+        if not metric_time_dimension_spec:
+            pass  # finish this
 
-        assert metric_time_dimension_spec
+        assert (
+            metric_time_dimension_spec and metric_time_dimension_instance
+        ), "No metric time dimension or agg_time_dimension found in join over time range query. This should have been caught by validations."
         time_spine_data_set_alias = self._next_unique_table_alias()
 
         metric_time_dimension_column_name = self.column_association_resolver.resolve_spec(
@@ -303,7 +308,6 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
 
         # Assemble time_spine dataset with metric_time_dimension to join.
         # Granularity of time_spine column should match granularity of metric_time column from parent dataset.
-        assert metric_time_dimension_instance
         time_spine_data_set = self._make_time_spine_data_set(
             metric_time_dimension_instance=metric_time_dimension_instance,
             metric_time_dimension_column_name=metric_time_dimension_column_name,
@@ -1249,6 +1253,7 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         parent_alias = self._next_unique_table_alias()
 
         # Build time spine dataset
+        # Here: if no metric time instance, replace this var with agg_time_dim
         metric_time_dimension_instance: Optional[TimeDimensionInstance] = None
         for instance in parent_data_set.metric_time_dimension_instances:
             if len(instance.spec.entity_links) == 0:
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index 3266e5fd05..dc2e1498ed 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -26,6 +26,8 @@
     TimeDimensionReference,
 )
 
+from metricflow.model.semantics.linkable_spec_resolver import ElementPathKey
+
 from metricflow.model.semantics.element_group import ElementGrouper
 from metricflow.model.semantics.linkable_element_properties import LinkableElementProperties
 from metricflow.specs.specs import (
@@ -92,6 +94,7 @@ def get_semantic_models_for_measure(self, measure_reference: MeasureReference) -
     @abstractmethod
     def get_agg_time_dimension_for_measure(self, measure_reference: MeasureReference) -> TimeDimensionReference:
         """Retrieves the aggregate time dimension that is associated with the measure reference."""
+        raise NotImplementedError
 
     @abstractmethod
     def get_entity_in_semantic_model(self, ref: SemanticModelElementReference) -> Optional[Entity]:
@@ -99,6 +102,7 @@ def get_entity_in_semantic_model(self, ref: SemanticModelElementReference) -> Op
         raise NotImplementedError
 
     @staticmethod
+    @abstractmethod
     def resolved_primary_entity(semantic_model: SemanticModel) -> Optional[EntityReference]:
         """Return the primary entity for dimensions in the model."""
         raise NotImplementedError
@@ -137,6 +141,10 @@ def get_element_spec_for_name(self, element_name: str) -> LinkableInstanceSpec:
         """Returns the spec for the given name of a linkable element (dimension or entity)."""
         raise NotImplementedError
 
+    @abstractmethod
+    def get_agg_time_dimension_path_key_for_measure(self, measure_reference: MeasureReference) -> ElementPathKey:
+        raise NotImplementedError
+
 
 class MetricAccessor(ABC):
     """Interface for accessing semantic information about a set of metric objects.
diff --git a/metricflow/query/validation_rules/metric_time_requirements.py b/metricflow/query/validation_rules/metric_time_requirements.py
index 8f16508949..b2f18de814 100644
--- a/metricflow/query/validation_rules/metric_time_requirements.py
+++ b/metricflow/query/validation_rules/metric_time_requirements.py
@@ -35,36 +35,11 @@ def __init__(self, manifest_lookup: SemanticManifestLookup) -> None:  # noqa: D
         super().__init__(manifest_lookup=manifest_lookup)
 
         self._metric_time_specs = tuple(
-            self._generate_valid_specs_for_time_dimension(
+            TimeDimensionSpec.generate_possible_specs_for_time_dimension(
                 time_dimension_reference=TimeDimensionReference(element_name=METRIC_TIME_ELEMENT_NAME), entity_links=()
             )
         )
 
-    def _generate_valid_specs_for_time_dimension(
-        self, time_dimension_reference: TimeDimensionReference, entity_links: Tuple[EntityReference, ...]
-    ) -> List[TimeDimensionSpec]:
-        time_dimension_specs: List[TimeDimensionSpec] = []
-        for time_granularity in TimeGranularity:
-            time_dimension_specs.append(
-                TimeDimensionSpec(
-                    element_name=time_dimension_reference.element_name,
-                    entity_links=entity_links,
-                    time_granularity=time_granularity,
-                    date_part=None,
-                )
-            )
-        for date_part in DatePart:
-            for time_granularity in date_part.compatible_granularities:
-                time_dimension_specs.append(
-                    TimeDimensionSpec(
-                        element_name=time_dimension_reference.element_name,
-                        entity_links=entity_links,
-                        time_granularity=time_granularity,
-                        date_part=date_part,
-                    )
-                )
-        return time_dimension_specs
-
     def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInputForQuery) -> bool:
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
             if group_by_item_input.spec_pattern.matches_any(self._metric_time_specs):
@@ -75,32 +50,16 @@ def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInpu
     def _group_by_items_include_agg_time_dimension(
         self, query_resolver_input: ResolverInputForQuery, metric_reference: MetricReference
     ) -> bool:
-        metric = self._manifest_lookup.metric_lookup.get_metric(metric_reference=metric_reference)
-        semantic_model_lookup = self._manifest_lookup.semantic_model_lookup
-
-        valid_agg_time_dimension_specs: List[TimeDimensionSpec] = []
-        for measure_reference in metric.measure_references:
-            agg_time_dimension_reference = semantic_model_lookup.get_agg_time_dimension_for_measure(measure_reference)
-
-            # A measure's gg_time_dimension is required to be in the same semantic model as the measure,
-            # so we can assume the same semantic model for both measure and dimension.
-            semantic_models = semantic_model_lookup.get_semantic_models_for_measure(measure_reference)
-            assert (
-                len(semantic_models) == 1
-            ), f"Expected exactly one semantic model for measure {measure_reference}, but found semantic models {semantic_models}."
-            semantic_model = semantic_models[0]
-
-            entity_link = semantic_model_lookup.resolved_primary_entity(semantic_model)
-            assert (
-                entity_link is not None
-            ), f"Expected semantic model {semantic_model} to have a primary entity since is contains dimensions, but found none."
-
-            valid_agg_time_dimension_specs.extend(
-                self._generate_valid_specs_for_time_dimension(
-                    time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
-                )
-            )
+        agg_time_dimension_and_entity_link = (
+            self._manifest_lookup.metric_lookup.get_agg_time_dimension_to_replace_metric_time(metric_reference)
+        )
+        if agg_time_dimension_and_entity_link is None:
+            return False
 
+        agg_time_dimension_reference, entity_link = agg_time_dimension_and_entity_link
+        valid_agg_time_dimension_specs = TimeDimensionSpec.generate_possible_specs_for_time_dimension(
+            time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
+        )
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
             if group_by_item_input.spec_pattern.matches_any(valid_agg_time_dimension_specs):
                 return True
diff --git a/metricflow/specs/specs.py b/metricflow/specs/specs.py
index d7e74ac01d..ae6668f4e7 100644
--- a/metricflow/specs/specs.py
+++ b/metricflow/specs/specs.py
@@ -449,6 +449,32 @@ def comparison_key(self, exclude_fields: Sequence[TimeDimensionSpecField] = ())
             exclude_fields=exclude_fields,
         )
 
+    @staticmethod
+    def generate_possible_specs_for_time_dimension(
+        time_dimension_reference: TimeDimensionReference, entity_links: Tuple[EntityReference, ...]
+    ) -> List[TimeDimensionSpec]:
+        time_dimension_specs: List[TimeDimensionSpec] = []
+        for time_granularity in TimeGranularity:
+            time_dimension_specs.append(
+                TimeDimensionSpec(
+                    element_name=time_dimension_reference.element_name,
+                    entity_links=entity_links,
+                    time_granularity=time_granularity,
+                    date_part=None,
+                )
+            )
+        for date_part in DatePart:
+            for time_granularity in date_part.compatible_granularities:
+                time_dimension_specs.append(
+                    TimeDimensionSpec(
+                        element_name=time_dimension_reference.element_name,
+                        entity_links=entity_links,
+                        time_granularity=time_granularity,
+                        date_part=date_part,
+                    )
+                )
+        return time_dimension_specs
+
 
 @dataclass(frozen=True)
 class NonAdditiveDimensionSpec(SerializableDataclass):
@@ -585,7 +611,7 @@ class MetricInputMeasureSpec(SerializableDataclass):
     fill_nulls_with: Optional[int] = None
     offset_window: Optional[MetricTimeWindow] = None
     offset_to_grain: Optional[TimeGranularity] = None
-    culmination_description: Optional[CumulativeMeasureDescription] = None
+    cumulation_description: Optional[CumulativeMeasureDescription] = None
     filter_specs: Tuple[WhereFilterSpec, ...] = ()
     alias: Optional[str] = None
     before_aggregation_time_spine_join_description: Optional[JoinToTimeSpineDescription] = None

From 1563c185f0fdb6937c277ab89ad70e7f54337682 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Tue, 23 Jan 2024 16:47:21 -0800
Subject: [PATCH 05/22] WIP

---
 .../dataflow/builder/dataflow_plan_builder.py | 28 +++++++------
 metricflow/dataflow/dataflow_plan.py          |  4 ++
 .../model/semantics/linkable_spec_resolver.py | 12 ++----
 metricflow/model/semantics/metric_lookup.py   | 41 +++++++++++--------
 .../model/semantics/semantic_model_lookup.py  | 18 +++++++-
 metricflow/plan_conversion/dataflow_to_sql.py | 22 ++++------
 metricflow/protocols/semantics.py             | 27 ++++++++----
 .../metric_time_requirements.py               | 20 ++++-----
 metricflow/specs/specs.py                     |  8 ++++
 .../test/integration/test_configured_cases.py |  3 +-
 .../test_cumulative_metric_rendering.py       |  1 +
 11 files changed, 110 insertions(+), 74 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 123e662e1d..bcecb01675 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -1315,21 +1315,25 @@ def _build_aggregated_measure_from_measure_source_node(
         # Otherwise, the measure will be aggregated over all time.
         time_range_node: Optional[JoinOverTimeRangeNode] = None
         if cumulative:
-            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
-            if not query_contains_metric_time_or_agg_time_dimension:
-                # TODO: Write a test case for this scenario
-                agg_time_dimension_element_path_key = (
-                    self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(measure_spec.reference)
+            queried_metric_time_spec = queried_linkable_specs.metric_time_spec_with_smallest_granularity
+            if not queried_metric_time_spec:
+                valid_agg_time_dimensions = (
+                    self._semantic_model_lookup.get_agg_time_dimensions_to_replace_metric_time_for_measure(
+                        measure_spec.reference
+                    )
                 )
-                for time_dimension_spec in queried_linkable_specs.time_dimension_specs:
-                    if (
-                        time_dimension_spec.element_name == agg_time_dimension_element_path_key.element_name
-                        and time_dimension_spec.entity_links == agg_time_dimension_element_path_key.entity_links
-                    ):
-                        query_contains_metric_time_or_agg_time_dimension = True
-            if query_contains_metric_time_or_agg_time_dimension:
+                # is there actually only one we allow?? no other granularity/date part?
+                queried_agg_time_dims = sorted(
+                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions)),
+                    key=lambda x: x.time_granularity.to_int(),
+                )
+                if queried_agg_time_dims:
+                    queried_metric_time_spec = queried_agg_time_dims[0]
+
+            if queried_metric_time_spec:
                 time_range_node = JoinOverTimeRangeNode(
                     parent_node=measure_recipe.source_node,
+                    metric_time_dimension_spec=queried_metric_time_spec,
                     window=cumulative_window,
                     grain_to_date=cumulative_grain_to_date,
                     time_range_constraint=time_range_constraint
diff --git a/metricflow/dataflow/dataflow_plan.py b/metricflow/dataflow/dataflow_plan.py
index ccc55c874d..db506b5bad 100644
--- a/metricflow/dataflow/dataflow_plan.py
+++ b/metricflow/dataflow/dataflow_plan.py
@@ -376,6 +376,7 @@ class JoinOverTimeRangeNode(BaseOutput):
     def __init__(
         self,
         parent_node: BaseOutput,
+        metric_time_dimension_spec: TimeDimensionSpec,
         window: Optional[MetricTimeWindow],
         grain_to_date: Optional[TimeGranularity],
         node_id: Optional[NodeId] = None,
@@ -390,6 +391,7 @@ def __init__(
             (eg month to day)
             node_id: Override the node ID with this value
             time_range_constraint: time range to aggregate over
+            metric_time_dimension_spec: time dimension spec to use when joining to time spine
         """
         if window and grain_to_date:
             raise RuntimeError(
@@ -400,6 +402,7 @@ def __init__(
         self._grain_to_date = grain_to_date
         self._window = window
         self.time_range_constraint = time_range_constraint
+        self.metric_time_dimension_spec = metric_time_dimension_spec
 
         # Doing a list comprehension throws a type error, so doing it this way.
         parent_nodes: List[DataflowPlanNode] = [self._parent_node]
@@ -447,6 +450,7 @@ def with_new_parents(self, new_parent_nodes: Sequence[BaseOutput]) -> JoinOverTi
             window=self.window,
             grain_to_date=self.grain_to_date,
             time_range_constraint=self.time_range_constraint,
+            metric_time_dimension_spec=self.metric_time_dimension_spec,
         )
 
 
diff --git a/metricflow/model/semantics/linkable_spec_resolver.py b/metricflow/model/semantics/linkable_spec_resolver.py
index bc9ccd43a3..739a947458 100644
--- a/metricflow/model/semantics/linkable_spec_resolver.py
+++ b/metricflow/model/semantics/linkable_spec_resolver.py
@@ -26,7 +26,6 @@
 from metricflow.mf_logging.pretty_print import mf_pformat
 from metricflow.model.semantics.linkable_element_properties import LinkableElementProperties
 from metricflow.model.semantics.semantic_model_join_evaluator import SemanticModelJoinEvaluator
-from metricflow.model.semantics.semantic_model_lookup import SemanticModelLookup
 from metricflow.protocols.semantics import SemanticModelAccessor
 from metricflow.specs.specs import (
     DEFAULT_TIME_GRANULARITY,
@@ -524,9 +523,7 @@ def __init__(
         linkable_element_sets_to_merge: List[LinkableElementSet] = []
 
         for semantic_model in semantic_manifest.semantic_models:
-            linkable_element_sets_to_merge.append(
-                ValidLinkableSpecResolver._get_elements_in_semantic_model(semantic_model)
-            )
+            linkable_element_sets_to_merge.append(self._get_elements_in_semantic_model(semantic_model))
 
         metric_time_elements_for_no_metrics = self._get_metric_time_elements(measure_reference=None)
         self._no_metric_linkable_element_set = LinkableElementSet.merge_by_path_key(
@@ -550,8 +547,7 @@ def _get_semantic_model_for_measure(self, measure_reference: MeasureReference) -
             )
         return semantic_models_where_measure_was_found[0]
 
-    @staticmethod
-    def _get_elements_in_semantic_model(semantic_model: SemanticModel) -> LinkableElementSet:
+    def _get_elements_in_semantic_model(self, semantic_model: SemanticModel) -> LinkableElementSet:
         """Gets the elements in the semantic model, without requiring any joins.
 
         Elements related to metric_time are handled separately in _get_metric_time_elements().
@@ -568,7 +564,7 @@ def _get_elements_in_semantic_model(semantic_model: SemanticModel) -> LinkableEl
                     properties=frozenset({LinkableElementProperties.LOCAL, LinkableElementProperties.ENTITY}),
                 )
             )
-            for entity_link in SemanticModelLookup.entity_links_for_local_elements(semantic_model):
+            for entity_link in self._semantic_model_lookup.entity_links_for_local_elements(semantic_model):
                 linkable_entities.append(
                     LinkableEntity(
                         semantic_model_origin=semantic_model.reference,
@@ -579,7 +575,7 @@ def _get_elements_in_semantic_model(semantic_model: SemanticModel) -> LinkableEl
                     )
                 )
 
-        for entity_link in SemanticModelLookup.entity_links_for_local_elements(semantic_model):
+        for entity_link in self._semantic_model_lookup.entity_links_for_local_elements(semantic_model):
             dimension_properties = frozenset({LinkableElementProperties.LOCAL})
             for dimension in semantic_model.dimensions:
                 dimension_type = dimension.type
diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index 5fae09f372..e881cff910 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -6,10 +6,7 @@
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
 from dbt_semantic_interfaces.protocols.metric import Metric, MetricInputMeasure, MetricType
 from dbt_semantic_interfaces.protocols.semantic_manifest import SemanticManifest
-from dbt_semantic_interfaces.references import (
-    MeasureReference,
-    MetricReference,
-)
+from dbt_semantic_interfaces.references import MeasureReference, MetricReference, TimeDimensionReference
 
 from metricflow.errors.errors import DuplicateMetricError, MetricNotFoundError, NonExistentMeasureError
 from metricflow.model.semantics.linkable_element_properties import LinkableElementProperties
@@ -21,7 +18,7 @@
 from metricflow.model.semantics.semantic_model_join_evaluator import MAX_JOIN_HOPS
 from metricflow.model.semantics.semantic_model_lookup import SemanticModelLookup
 from metricflow.protocols.semantics import MetricAccessor
-from metricflow.specs.specs import LinkableInstanceSpec
+from metricflow.specs.specs import LinkableInstanceSpec, TimeDimensionSpec
 
 logger = logging.getLogger(__name__)
 
@@ -165,23 +162,33 @@ def contains_cumulative_or_time_offset_metric(self, metric_references: Sequence[
                         return True
         return False
 
-    def _get_agg_time_dimension_path_keys_for_metric(self, metric_reference: MetricReference) -> Set[ElementPathKey]:
+    def _get_agg_time_dimension_path_keys_for_metric(
+        self, metric_reference: MetricReference
+    ) -> Sequence[ElementPathKey]:
         """Retrieves the aggregate time dimensions associated with the metric's measures."""
         metric = self.get_metric(metric_reference)
         assert metric.input_measures, f"No input measures found for metric {metric_reference}"
-        return {
-            self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(
+
+        path_keys = set()
+        for input_measure in metric.input_measures:
+            path_key = self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(
                 measure_reference=input_measure.measure_reference
             )
-            for input_measure in metric.input_measures
-        }
+            path_keys.add(path_key)
+        return list(path_keys)
 
-    def get_agg_time_dimension_to_replace_metric_time(
+    def get_agg_time_dimensions_to_replace_metric_time_for_metric(
         self, metric_reference: MetricReference
-    ) -> Optional[ElementPathKey]:
+    ) -> Sequence[TimeDimensionSpec]:
+        """Get the agg time dimension specs that can be used in place of metric time for this metric, if applicable."""
         agg_time_dimension_element_path_keys = self._get_agg_time_dimension_path_keys_for_metric(metric_reference)
-        if len(agg_time_dimension_element_path_keys) == 1:
-            return agg_time_dimension_element_path_keys[0]
-
-        # If the metric's input measures have different agg_time_dimensions, user must use metric_time.
-        return None
+        if len(agg_time_dimension_element_path_keys) != 1:
+            # If the metric's input measures have different agg_time_dimensions, user must use metric_time.
+            return []
+
+        path_key = agg_time_dimension_element_path_keys[0]
+        valid_agg_time_dimension_specs = TimeDimensionSpec.generate_possible_specs_for_time_dimension(
+            time_dimension_reference=TimeDimensionReference(element_name=path_key.element_name),
+            entity_links=path_key.entity_links,
+        )
+        return valid_agg_time_dimension_specs
diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 2e80b5b204..3079eabbd9 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -340,6 +340,7 @@ def get_element_spec_for_name(self, element_name: str) -> LinkableInstanceSpec:
             raise ValueError(f"Unable to find linkable element {element_name} in manifest")
 
     def get_agg_time_dimension_path_key_for_measure(self, measure_reference: MeasureReference) -> ElementPathKey:
+        """Get the agg time dimension associated with the measure."""
         agg_time_dimension = self.get_agg_time_dimension_for_measure(measure_reference)
 
         # A measure's agg_time_dimension is required to be in the same semantic model as the measure,
@@ -355,4 +356,19 @@ def get_agg_time_dimension_path_key_for_measure(self, measure_reference: Measure
             entity_link is not None
         ), f"Expected semantic model {semantic_model} to have a primary entity since is contains dimensions, but found none."
 
-        return ElementPathKey(element_name=agg_time_dimension.element_name, entity_links=(entity_link,))
+        return ElementPathKey(
+            element_name=agg_time_dimension.element_name,
+            entity_links=(entity_link,),
+            time_granularity=None,
+            date_part=None,
+        )
+
+    def get_agg_time_dimensions_to_replace_metric_time_for_measure(
+        self, measure_reference: MeasureReference
+    ) -> Sequence[TimeDimensionSpec]:
+        """Get the agg time dimension specs that can be used in place of metric time for this measure."""
+        path_key = self.get_agg_time_dimension_path_key_for_measure(measure_reference)
+        return TimeDimensionSpec.generate_possible_specs_for_time_dimension(
+            time_dimension_reference=TimeDimensionReference(element_name=path_key.element_name),
+            entity_links=path_key.entity_links,
+        )
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 9d1f32007d..8a31c604c0 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -281,24 +281,19 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
         input_data_set = node.parent_node.accept(self)
         input_data_set_alias = self._next_unique_table_alias()
 
-        metric_time_dimension_spec: Optional[TimeDimensionSpec] = None
         metric_time_dimension_instance: Optional[TimeDimensionInstance] = None
-        for instance in input_data_set.metric_time_dimension_instances:
-            if len(instance.spec.entity_links) == 0:
+        for instance in input_data_set.instance_set.time_dimension_instances:
+            if instance.spec == node.metric_time_dimension_spec:
                 metric_time_dimension_instance = instance
-                metric_time_dimension_spec = instance.spec
                 break
-        # User might refer to the agg_time_dimension by its dimension name instead of 'metric_time'.
-        if not metric_time_dimension_spec:
-            pass  # finish this
 
         assert (
-            metric_time_dimension_spec and metric_time_dimension_instance
-        ), "No metric time dimension or agg_time_dimension found in join over time range query. This should have been caught by validations."
+            metric_time_dimension_instance
+        ), "Specified metric time spec not found in join over time range query. This should have been caught by validations."
         time_spine_data_set_alias = self._next_unique_table_alias()
 
         metric_time_dimension_column_name = self.column_association_resolver.resolve_spec(
-            metric_time_dimension_spec
+            metric_time_dimension_instance.spec
         ).column_name
 
         # Assemble time_spine dataset with metric_time_dimension to join.
@@ -313,12 +308,12 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
 
         # Figure out which columns correspond to the time dimension that we want to join on.
         input_data_set_metric_time_column_association = input_data_set.column_association_for_time_dimension(
-            metric_time_dimension_spec
+            metric_time_dimension_instance.spec
         )
         input_data_set_metric_time_col = input_data_set_metric_time_column_association.column_name
 
         time_spine_data_set_column_associations = time_spine_data_set.column_association_for_time_dimension(
-            metric_time_dimension_spec
+            metric_time_dimension_instance.spec
         )
         time_spine_data_set_time_dimension_col = time_spine_data_set_column_associations.column_name
 
@@ -346,13 +341,14 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
                 [
                     time_dimension_instance
                     for time_dimension_instance in input_data_set.instance_set.time_dimension_instances
-                    if time_dimension_instance.spec != metric_time_dimension_spec
+                    if time_dimension_instance != metric_time_dimension_instance
                 ]
             ),
         )
         table_alias_to_instance_set[input_data_set_alias] = modified_input_instance_set
 
         # The output instances are the same as the input instances.
+        # Shouldn't this just be the selected ones? maybe it is (un-optimized)
         output_instance_set = ChangeAssociatedColumns(self._column_association_resolver).transform(
             input_data_set.instance_set
         )
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index dc2e1498ed..c9b4b0f049 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -9,7 +9,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import Dict, FrozenSet, Optional, Sequence, Set
+from typing import TYPE_CHECKING, Dict, FrozenSet, Optional, Sequence, Set
 
 from dbt_semantic_interfaces.protocols.dimension import Dimension
 from dbt_semantic_interfaces.protocols.entity import Entity
@@ -26,15 +26,12 @@
     TimeDimensionReference,
 )
 
-from metricflow.model.semantics.linkable_spec_resolver import ElementPathKey
-
 from metricflow.model.semantics.element_group import ElementGrouper
 from metricflow.model.semantics.linkable_element_properties import LinkableElementProperties
-from metricflow.specs.specs import (
-    LinkableInstanceSpec,
-    MeasureSpec,
-    NonAdditiveDimensionSpec,
-)
+from metricflow.specs.specs import LinkableInstanceSpec, MeasureSpec, NonAdditiveDimensionSpec, TimeDimensionSpec
+
+if TYPE_CHECKING:
+    from metricflow.model.semantics.linkable_spec_resolver import ElementPathKey
 
 
 class SemanticModelAccessor(ABC):
@@ -143,6 +140,13 @@ def get_element_spec_for_name(self, element_name: str) -> LinkableInstanceSpec:
 
     @abstractmethod
     def get_agg_time_dimension_path_key_for_measure(self, measure_reference: MeasureReference) -> ElementPathKey:
+        """Get the agg time dimension associated with the measure."""
+        raise NotImplementedError
+
+    def get_agg_time_dimensions_to_replace_metric_time_for_measure(
+        self, measure_reference: MeasureReference
+    ) -> Sequence[TimeDimensionSpec]:
+        """Get the agg time dimension specs that can be used in place of metric time for this measure."""
         raise NotImplementedError
 
 
@@ -214,3 +218,10 @@ def group_by_item_specs_for_no_metrics_query(
     ) -> Sequence[LinkableInstanceSpec]:
         """Return the possible group-by-items for a dimension values query with no metrics."""
         raise NotImplementedError
+
+    @abstractmethod
+    def get_agg_time_dimensions_to_replace_metric_time_for_metric(
+        self, metric_reference: MetricReference
+    ) -> Sequence[TimeDimensionSpec]:
+        """Get the agg time dimension specs that can be used in place of metric time for this metric, if applicable."""
+        raise NotImplementedError
diff --git a/metricflow/query/validation_rules/metric_time_requirements.py b/metricflow/query/validation_rules/metric_time_requirements.py
index b2f18de814..569b9c5a41 100644
--- a/metricflow/query/validation_rules/metric_time_requirements.py
+++ b/metricflow/query/validation_rules/metric_time_requirements.py
@@ -1,13 +1,12 @@
 from __future__ import annotations
 
-from typing import List, Sequence, Tuple
+from typing import Sequence
 
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
 from dbt_semantic_interfaces.naming.keywords import METRIC_TIME_ELEMENT_NAME
 from dbt_semantic_interfaces.protocols import WhereFilterIntersection
-from dbt_semantic_interfaces.references import EntityReference, MetricReference, TimeDimensionReference
-from dbt_semantic_interfaces.type_enums import MetricType, TimeGranularity
-from dbt_semantic_interfaces.type_enums.date_part import DatePart
+from dbt_semantic_interfaces.references import MetricReference, TimeDimensionReference
+from dbt_semantic_interfaces.type_enums import MetricType
 from typing_extensions import override
 
 from metricflow.model.semantic_manifest_lookup import SemanticManifestLookup
@@ -50,15 +49,10 @@ def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInpu
     def _group_by_items_include_agg_time_dimension(
         self, query_resolver_input: ResolverInputForQuery, metric_reference: MetricReference
     ) -> bool:
-        agg_time_dimension_and_entity_link = (
-            self._manifest_lookup.metric_lookup.get_agg_time_dimension_to_replace_metric_time(metric_reference)
-        )
-        if agg_time_dimension_and_entity_link is None:
-            return False
-
-        agg_time_dimension_reference, entity_link = agg_time_dimension_and_entity_link
-        valid_agg_time_dimension_specs = TimeDimensionSpec.generate_possible_specs_for_time_dimension(
-            time_dimension_reference=agg_time_dimension_reference, entity_links=(entity_link,)
+        valid_agg_time_dimension_specs = (
+            self._manifest_lookup.metric_lookup.get_agg_time_dimensions_to_replace_metric_time_for_metric(
+                metric_reference
+            )
         )
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
             if group_by_item_input.spec_pattern.matches_any(valid_agg_time_dimension_specs):
diff --git a/metricflow/specs/specs.py b/metricflow/specs/specs.py
index ae6668f4e7..bcfc71289e 100644
--- a/metricflow/specs/specs.py
+++ b/metricflow/specs/specs.py
@@ -453,6 +453,7 @@ def comparison_key(self, exclude_fields: Sequence[TimeDimensionSpecField] = ())
     def generate_possible_specs_for_time_dimension(
         time_dimension_reference: TimeDimensionReference, entity_links: Tuple[EntityReference, ...]
     ) -> List[TimeDimensionSpec]:
+        """Generate a list of time dimension specs with all combinations of granularity & date part."""
         time_dimension_specs: List[TimeDimensionSpec] = []
         for time_granularity in TimeGranularity:
             time_dimension_specs.append(
@@ -664,6 +665,13 @@ def metric_time_specs(self) -> Sequence[TimeDimensionSpec]:
             if time_dimension_spec.element_name == METRIC_TIME_ELEMENT_NAME
         )
 
+    # TODO: what about date part? not allowed for cumulative, right?
+    @property
+    def metric_time_spec_with_smallest_granularity(self) -> Optional[TimeDimensionSpec]:
+        """Get the metric time spec with the smallest granularity, if there are any metric time specs."""
+        sorted_specs = sorted(self.metric_time_specs, key=lambda x: x.time_granularity)
+        return sorted_specs[0] if sorted_specs else None
+
     @property
     def as_tuple(self) -> Tuple[LinkableInstanceSpec, ...]:  # noqa: D
         return tuple(itertools.chain(self.dimension_specs, self.time_dimension_specs, self.entity_specs))
diff --git a/metricflow/test/integration/test_configured_cases.py b/metricflow/test/integration/test_configured_cases.py
index 6b6e080470..92462b515f 100644
--- a/metricflow/test/integration/test_configured_cases.py
+++ b/metricflow/test/integration/test_configured_cases.py
@@ -230,8 +230,7 @@ def filter_not_supported_features(
 
 @pytest.mark.parametrize(
     "name",
-    # CONFIGURED_INTEGRATION_TESTS_REPOSITORY.all_test_case_names,
-    ["itest_cumulative_metric.yaml/cumulative_metric_with_agg_time_dimension"],
+    CONFIGURED_INTEGRATION_TESTS_REPOSITORY.all_test_case_names,
     ids=lambda name: f"name={name}",
 )
 def test_case(
diff --git a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
index d3e887078b..7d80301f7e 100644
--- a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
@@ -81,6 +81,7 @@ def test_cumulative_metric_with_time_constraint(
                 TimeDimensionSpec(
                     element_name="metric_time",
                     entity_links=(),
+                    # TODO: figure out this case. Do we allow querying by month here?
                     time_granularity=TimeGranularity.MONTH,
                 ),
             ),

From fde7f07e162013dcb5dff102ba3cd3b5038ba77e Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Tue, 23 Jan 2024 18:02:43 -0800
Subject: [PATCH 06/22] Cleanup

---
 .../test/query_rendering/test_cumulative_metric_rendering.py     | 1 -
 1 file changed, 1 deletion(-)

diff --git a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
index 7d80301f7e..d3e887078b 100644
--- a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
@@ -81,7 +81,6 @@ def test_cumulative_metric_with_time_constraint(
                 TimeDimensionSpec(
                     element_name="metric_time",
                     entity_links=(),
-                    # TODO: figure out this case. Do we allow querying by month here?
                     time_granularity=TimeGranularity.MONTH,
                 ),
             ),

From cd8a1367c234926e4f07b2f665e68dbb1d97725c Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Tue, 23 Jan 2024 18:11:21 -0800
Subject: [PATCH 07/22] Cleanup

---
 metricflow/model/semantics/metric_lookup.py                     | 1 +
 metricflow/plan_conversion/dataflow_to_sql.py                   | 2 +-
 .../issues/parsing/cumulative_metric_requires_metric_time.py    | 1 -
 3 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index e881cff910..caea42cbe9 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -187,6 +187,7 @@ def get_agg_time_dimensions_to_replace_metric_time_for_metric(
             return []
 
         path_key = agg_time_dimension_element_path_keys[0]
+        # TODO: do we need all these? Or just the one valid granularity? Depends what's allowed for time_offset
         valid_agg_time_dimension_specs = TimeDimensionSpec.generate_possible_specs_for_time_dimension(
             time_dimension_reference=TimeDimensionReference(element_name=path_key.element_name),
             entity_links=path_key.entity_links,
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 8a31c604c0..983ae2293a 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -289,7 +289,7 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
 
         assert (
             metric_time_dimension_instance
-        ), "Specified metric time spec not found in join over time range query. This should have been caught by validations."
+        ), "Specified metric time spec not found in parent data set. This should have been caught by validations."
         time_spine_data_set_alias = self._next_unique_table_alias()
 
         metric_time_dimension_column_name = self.column_association_resolver.resolve_spec(
diff --git a/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py b/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
index 60893c6b98..e135cd7f2c 100644
--- a/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
+++ b/metricflow/query/issues/parsing/cumulative_metric_requires_metric_time.py
@@ -26,7 +26,6 @@ def ui_description(self, associated_input: MetricFlowQueryResolverInput) -> str:
             f"The query includes a cumulative metric {repr(self.metric_reference.element_name)} that does not "
             f"accumulate over all-time, but the group-by items do not include {repr(METRIC_TIME_ELEMENT_NAME)} "
             "or the metric's agg_time_dimension."
-            # TODO: add name of agg_time_dim?
         )
 
     @override

From a30b4e33c3e24582805dd6cbaf2b41627e4a615a Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 10:52:48 -0800
Subject: [PATCH 08/22] Get time offset working

---
 .../dataflow/builder/dataflow_plan_builder.py |  34 +-
 metricflow/model/semantics/metric_lookup.py   |   3 +-
 .../model/semantics/semantic_model_lookup.py  |   2 +-
 metricflow/plan_conversion/dataflow_to_sql.py |  68 ++-
 metricflow/protocols/semantics.py             |   4 +-
 .../metric_time_requirements.py               |   6 +-
 metricflow/specs/specs.py                     |   6 +-
 .../integration/test_cases/itest_metrics.yaml |  71 +++
 .../test_derived_metric_rendering.py          |  52 ++
 ...ive_metric_with_time_constraint__plan0.sql |  12 +-
 ..._with_time_constraint__plan0_optimized.sql |  17 +-
 ...fset_to_grain_with_agg_time_dim__plan0.sql | 534 ++++++++++++++++++
 ...ain_with_agg_time_dim__plan0_optimized.sql |  55 ++
 ...offset_window_with_agg_time_dim__plan0.sql | 534 ++++++++++++++++++
 ...dow_with_agg_time_dim__plan0_optimized.sql |  55 ++
 15 files changed, 1393 insertions(+), 60 deletions(-)
 create mode 100644 metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
 create mode 100644 metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0_optimized.sql
 create mode 100644 metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
 create mode 100644 metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0_optimized.sql

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index bcecb01675..ad1a1fa4d8 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -1317,12 +1317,11 @@ def _build_aggregated_measure_from_measure_source_node(
         if cumulative:
             queried_metric_time_spec = queried_linkable_specs.metric_time_spec_with_smallest_granularity
             if not queried_metric_time_spec:
-                valid_agg_time_dimensions = (
-                    self._semantic_model_lookup.get_agg_time_dimensions_to_replace_metric_time_for_measure(
-                        measure_spec.reference
-                    )
+                valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
+                    measure_spec.reference
                 )
-                # is there actually only one we allow?? no other granularity/date part?
+                # TODO: we only actually allow one granularity for cumulative. Should that be reflected here?
+                # Definitely shouldn't have date part in here
                 queried_agg_time_dims = sorted(
                     set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions)),
                     key=lambda x: x.time_granularity.to_int(),
@@ -1344,21 +1343,28 @@ def _build_aggregated_measure_from_measure_source_node(
         # If querying an offset metric, join to time spine before aggregation.
         join_to_time_spine_node: Optional[JoinToTimeSpineNode] = None
         if before_aggregation_time_spine_join_description is not None:
-            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
-            if not query_contains_metric_time_or_agg_time_dimension:
-                pass  # check for agg_time_dimension and update accordingly
-                # Write a test case for this scenario
-            assert (
-                query_contains_metric_time_or_agg_time_dimension
-            ), "Joining to time spine requires querying with metric time or the appropriate agg_time_dimension."
-            # Can you use agg_time_dimension if it's a ratio metric? Only if both metrics use same agg time dim?
+            # TODO: below logic is somewhat duplicated
+            queried_metric_time_specs = list(queried_linkable_specs.metric_time_specs)
+            if not queried_metric_time_specs:
+                valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
+                    measure_spec.reference
+                )
+                queried_metric_time_specs = list(
+                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
+                )
+
+            assert queried_metric_time_specs, (
+                "Joining to time spine requires querying with metric time or the appropriate agg_time_dimension."
+                "This should have been caught by validations."
+            )
+
             assert before_aggregation_time_spine_join_description.join_type is SqlJoinType.INNER, (
                 f"Expected {SqlJoinType.INNER} for joining to time spine before aggregation. Remove this if there's a "
                 f"new use case."
             )
             join_to_time_spine_node = JoinToTimeSpineNode(
                 parent_node=time_range_node or measure_recipe.source_node,
-                requested_metric_time_dimension_specs=list(queried_linkable_specs.metric_time_specs),
+                requested_metric_time_dimension_specs=queried_metric_time_specs,
                 time_range_constraint=time_range_constraint,
                 offset_window=before_aggregation_time_spine_join_description.offset_window,
                 offset_to_grain=before_aggregation_time_spine_join_description.offset_to_grain,
diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index caea42cbe9..4a57090197 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -167,6 +167,7 @@ def _get_agg_time_dimension_path_keys_for_metric(
     ) -> Sequence[ElementPathKey]:
         """Retrieves the aggregate time dimensions associated with the metric's measures."""
         metric = self.get_metric(metric_reference)
+        # This should get hit on offset metric, right?
         assert metric.input_measures, f"No input measures found for metric {metric_reference}"
 
         path_keys = set()
@@ -177,7 +178,7 @@ def _get_agg_time_dimension_path_keys_for_metric(
             path_keys.add(path_key)
         return list(path_keys)
 
-    def get_agg_time_dimensions_to_replace_metric_time_for_metric(
+    def get_valid_agg_time_dimensions_for_metric(
         self, metric_reference: MetricReference
     ) -> Sequence[TimeDimensionSpec]:
         """Get the agg time dimension specs that can be used in place of metric time for this metric, if applicable."""
diff --git a/metricflow/model/semantics/semantic_model_lookup.py b/metricflow/model/semantics/semantic_model_lookup.py
index 3079eabbd9..edf9f18066 100644
--- a/metricflow/model/semantics/semantic_model_lookup.py
+++ b/metricflow/model/semantics/semantic_model_lookup.py
@@ -363,7 +363,7 @@ def get_agg_time_dimension_path_key_for_measure(self, measure_reference: Measure
             date_part=None,
         )
 
-    def get_agg_time_dimensions_to_replace_metric_time_for_measure(
+    def get_agg_time_dimension_specs_for_measure(
         self, measure_reference: MeasureReference
     ) -> Sequence[TimeDimensionSpec]:
         """Get the agg time dimension specs that can be used in place of metric time for this measure."""
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 983ae2293a..be222e1e98 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -5,6 +5,7 @@
 from typing import List, Optional, Sequence, Tuple, Union
 
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
+from dbt_semantic_interfaces.naming.keywords import METRIC_TIME_ELEMENT_NAME
 from dbt_semantic_interfaces.protocols.metric import MetricInputMeasure, MetricType
 from dbt_semantic_interfaces.references import MetricModelReference
 from dbt_semantic_interfaces.type_enums.aggregation_type import AggregationType
@@ -1239,57 +1240,76 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         parent_data_set = node.parent_node.accept(self)
         parent_alias = self._next_unique_table_alias()
 
-        # Build time spine dataset
-        # Here: if no metric time instance, replace this var with agg_time_dim
-        metric_time_dimension_instance: Optional[TimeDimensionInstance] = None
-        for instance in parent_data_set.metric_time_dimension_instances:
-            if len(instance.spec.entity_links) == 0:
-                # Use the instance with the lowest granularity
-                if not metric_time_dimension_instance or (
-                    instance.spec.time_granularity < metric_time_dimension_instance.spec.time_granularity
-                ):
-                    metric_time_dimension_instance = instance
+        # TODO: rename requested_metric_time_dimension_specs -> requested_agg_time_dimension_specs
         assert (
-            metric_time_dimension_instance
-        ), "Can't join to time spine without metric time. Validations should have prevented this."
-        metric_time_dimension_column_name = self.column_association_resolver.resolve_spec(
-            metric_time_dimension_instance.spec
+            len(node.requested_metric_time_dimension_specs) > 0
+        ), "Must have at least one  value in requested_metric_time_dimension_specs for JoinToTimeSpineNode."
+
+        # Determine if the time spine join should use metric_time or the agg_time_dimension (metric_time takes priority).
+        agg_time_dimension_for_join = node.requested_metric_time_dimension_specs[0]
+        for spec in node.requested_metric_time_dimension_specs[1:]:
+            if spec.element_name == METRIC_TIME_ELEMENT_NAME:
+                agg_time_dimension_for_join = spec
+                break
+
+        # Find the time dimension instances in the parent data set that match the one we want to join with.
+        agg_time_dimension_instances: List[TimeDimensionInstance] = []
+        for instance in parent_data_set.instance_set.time_dimension_instances:
+            if (
+                instance.spec.date_part is None  # Ensure we don't join using an instance with date part
+                and instance.spec.element_name == agg_time_dimension_for_join.element_name
+                and instance.spec.entity_links == agg_time_dimension_for_join.entity_links
+            ):
+                agg_time_dimension_instances.append(instance)
+
+        # Choose the instance with the smallest granularity available.
+        agg_time_dimension_instances.sort(key=lambda instance: instance.spec.time_granularity.to_int())
+        assert (
+            len(agg_time_dimension_instances) > 0
+        ), "Couldn't find requested agg_time_dimension in parent data set. The dataflow plan may have been configured incorrectly."
+        agg_time_dimension_instance_for_join = agg_time_dimension_instances[0]
+
+        # Build time spine data set using the requested agg_time_dimension name.
+        agg_time_dimension_column_name = self.column_association_resolver.resolve_spec(
+            agg_time_dimension_instance_for_join.spec
         ).column_name
         time_spine_alias = self._next_unique_table_alias()
         time_spine_dataset = self._make_time_spine_data_set(
-            metric_time_dimension_instance=metric_time_dimension_instance,
-            metric_time_dimension_column_name=metric_time_dimension_column_name,
+            metric_time_dimension_instance=agg_time_dimension_instance_for_join,
+            metric_time_dimension_column_name=agg_time_dimension_column_name,
             time_spine_source=self._time_spine_source,
             time_range_constraint=node.time_range_constraint,
         )
 
-        # Build join expression
+        # Build join expression.
         join_description = SqlQueryPlanJoinBuilder.make_join_to_time_spine_join_description(
             node=node,
             time_spine_alias=time_spine_alias,
-            metric_time_dimension_column_name=metric_time_dimension_column_name,
+            metric_time_dimension_column_name=agg_time_dimension_column_name,
             parent_sql_select_node=parent_data_set.sql_select_node,
             parent_alias=parent_alias,
         )
 
-        # Use all instances EXCEPT metric_time from parent data set.
-        non_metric_time_parent_instance_set = InstanceSet(
+        # Select all instances from the parent data set, EXCEPT the requested agg_time_dimension.
+        # The agg_time_dimension will be selected from the time spine data set.
+        parent_instance_set = InstanceSet(
             measure_instances=parent_data_set.instance_set.measure_instances,
             dimension_instances=parent_data_set.instance_set.dimension_instances,
             time_dimension_instances=tuple(
                 time_dimension_instance
                 for time_dimension_instance in parent_data_set.instance_set.time_dimension_instances
-                if time_dimension_instance.spec.element_name != DataSet.metric_time_dimension_reference().element_name
+                if time_dimension_instance.spec.element_name != agg_time_dimension_for_join.element_name
+                # and time_dimension_instance.spec.entity_links != agg_time_dimension_for_join.entity_links
             ),
             entity_instances=parent_data_set.instance_set.entity_instances,
             metric_instances=parent_data_set.instance_set.metric_instances,
             metadata_instances=parent_data_set.instance_set.metadata_instances,
         )
         parent_select_columns = create_select_columns_for_instance_sets(
-            self._column_association_resolver, OrderedDict({parent_alias: non_metric_time_parent_instance_set})
+            self._column_association_resolver, OrderedDict({parent_alias: parent_instance_set})
         )
 
-        # Use time instance from time spine to replace metric_time instances.
+        # Select agg_time_dimension instance from time spine data set.
         assert (
             len(time_spine_dataset.instance_set.time_dimension_instances) == 1
             and len(time_spine_dataset.sql_select_node.select_columns) == 1
@@ -1344,7 +1364,7 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         time_spine_instance_set = InstanceSet(time_dimension_instances=tuple(time_spine_dim_instances))
 
         return SqlDataSet(
-            instance_set=InstanceSet.merge([time_spine_instance_set, non_metric_time_parent_instance_set]),
+            instance_set=InstanceSet.merge([time_spine_instance_set, parent_instance_set]),
             sql_select_node=SqlSelectStatementNode(
                 description=node.description,
                 select_columns=tuple(time_spine_select_columns) + parent_select_columns,
diff --git a/metricflow/protocols/semantics.py b/metricflow/protocols/semantics.py
index c9b4b0f049..f9afb82548 100644
--- a/metricflow/protocols/semantics.py
+++ b/metricflow/protocols/semantics.py
@@ -143,7 +143,7 @@ def get_agg_time_dimension_path_key_for_measure(self, measure_reference: Measure
         """Get the agg time dimension associated with the measure."""
         raise NotImplementedError
 
-    def get_agg_time_dimensions_to_replace_metric_time_for_measure(
+    def get_agg_time_dimension_specs_for_measure(
         self, measure_reference: MeasureReference
     ) -> Sequence[TimeDimensionSpec]:
         """Get the agg time dimension specs that can be used in place of metric time for this measure."""
@@ -220,7 +220,7 @@ def group_by_item_specs_for_no_metrics_query(
         raise NotImplementedError
 
     @abstractmethod
-    def get_agg_time_dimensions_to_replace_metric_time_for_metric(
+    def get_valid_agg_time_dimensions_for_metric(
         self, metric_reference: MetricReference
     ) -> Sequence[TimeDimensionSpec]:
         """Get the agg time dimension specs that can be used in place of metric time for this metric, if applicable."""
diff --git a/metricflow/query/validation_rules/metric_time_requirements.py b/metricflow/query/validation_rules/metric_time_requirements.py
index 569b9c5a41..aeb4693f01 100644
--- a/metricflow/query/validation_rules/metric_time_requirements.py
+++ b/metricflow/query/validation_rules/metric_time_requirements.py
@@ -49,10 +49,8 @@ def _group_by_items_include_metric_time(self, query_resolver_input: ResolverInpu
     def _group_by_items_include_agg_time_dimension(
         self, query_resolver_input: ResolverInputForQuery, metric_reference: MetricReference
     ) -> bool:
-        valid_agg_time_dimension_specs = (
-            self._manifest_lookup.metric_lookup.get_agg_time_dimensions_to_replace_metric_time_for_metric(
-                metric_reference
-            )
+        valid_agg_time_dimension_specs = self._manifest_lookup.metric_lookup.get_valid_agg_time_dimensions_for_metric(
+            metric_reference
         )
         for group_by_item_input in query_resolver_input.group_by_item_inputs:
             if group_by_item_input.spec_pattern.matches_any(valid_agg_time_dimension_specs):
diff --git a/metricflow/specs/specs.py b/metricflow/specs/specs.py
index bcfc71289e..0c24e97010 100644
--- a/metricflow/specs/specs.py
+++ b/metricflow/specs/specs.py
@@ -476,6 +476,10 @@ def generate_possible_specs_for_time_dimension(
                 )
         return time_dimension_specs
 
+    @property
+    def is_metric_time(self) -> bool:  # noqa: D
+        return self.element_name == METRIC_TIME_ELEMENT_NAME
+
 
 @dataclass(frozen=True)
 class NonAdditiveDimensionSpec(SerializableDataclass):
@@ -662,7 +666,7 @@ def metric_time_specs(self) -> Sequence[TimeDimensionSpec]:
         return tuple(
             time_dimension_spec
             for time_dimension_spec in self.time_dimension_specs
-            if time_dimension_spec.element_name == METRIC_TIME_ELEMENT_NAME
+            if time_dimension_spec.is_metric_time
         )
 
     # TODO: what about date part? not allowed for cumulative, right?
diff --git a/metricflow/test/integration/test_cases/itest_metrics.yaml b/metricflow/test/integration/test_cases/itest_metrics.yaml
index 26ae81116f..7110f22109 100644
--- a/metricflow/test/integration/test_cases/itest_metrics.yaml
+++ b/metricflow/test/integration/test_cases/itest_metrics.yaml
@@ -1743,3 +1743,74 @@ integration_test:
       ) subq_11
       WHERE booking__is_instant
     )
+---
+integration_test:
+  name: offset_window_with_agg_time_dim
+  description: Tests a derived metric query with an offset_window queried with agg_time_dimension
+  model: SIMPLE_MODEL
+  metrics: ["bookings_growth_2_weeks"]
+  group_bys: ["booking__ds__day"]
+  check_query: |
+    SELECT
+      COALESCE(a.booking__ds__day, b.booking__ds__day) AS booking__ds__day
+      , bookings - bookings_2_weeks_ago AS bookings_growth_2_weeks
+    FROM (
+      SELECT
+        ds AS booking__ds__day
+        , SUM(1) AS bookings
+      FROM {{ source_schema }}.fct_bookings
+      GROUP BY
+        ds
+    ) a
+    FULL OUTER JOIN (
+      SELECT
+        c.ds AS booking__ds__day
+        , d.bookings_2_weeks_ago AS bookings_2_weeks_ago
+      FROM {{ mf_time_spine_source }} c
+      INNER JOIN (
+        SELECT
+          ds AS booking__ds__day
+          , SUM(1) AS bookings_2_weeks_ago
+        FROM {{ source_schema }}.fct_bookings
+        GROUP BY
+          ds
+      ) d
+      ON {{ render_date_sub("C", "ds", 14, TimeGranularity.DAY) }} = d.booking__ds__day
+    ) b
+    ON a.booking__ds__day = b.booking__ds__day
+---
+integration_test:
+  name: offset_to_grain_with_agg_time_dim
+  description: Tests a derived metric query with an offset_to_grain and agg_time_dimension.
+  model: SIMPLE_MODEL
+  metrics: ["bookings_growth_since_start_of_month"]
+  group_bys: ["booking__ds__day"]
+  check_query: |
+    SELECT
+      COALESCE(a.booking__ds__day, b.booking__ds__day) AS booking__ds__day
+      , bookings - bookings_at_start_of_month AS bookings_growth_since_start_of_month
+    FROM (
+      SELECT
+        ds AS booking__ds__day
+        , SUM(1) AS bookings
+      FROM {{ source_schema }}.fct_bookings
+      GROUP BY
+        ds
+    ) a
+    FULL OUTER JOIN (
+      SELECT
+        c.ds AS booking__ds__day
+        , d.bookings_at_start_of_month AS bookings_at_start_of_month
+      FROM {{ mf_time_spine_source }} c
+      INNER JOIN (
+        SELECT
+          ds AS booking__ds__day
+          , SUM(1) AS bookings_at_start_of_month
+        FROM {{ source_schema }}.fct_bookings
+        GROUP BY
+          ds
+      ) d
+      ON {{ render_date_trunc("c.ds", TimeGranularity.MONTH) }} = d.booking__ds__day
+    ) b
+    ON a.booking__ds__day = b.booking__ds__day
+# TODO: tests with granularity, date part, multiple metric time / agg time options
diff --git a/metricflow/test/query_rendering/test_derived_metric_rendering.py b/metricflow/test/query_rendering/test_derived_metric_rendering.py
index 1bf6204a9d..00f9e79974 100644
--- a/metricflow/test/query_rendering/test_derived_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_derived_metric_rendering.py
@@ -520,3 +520,55 @@ def test_nested_derived_metric_offset_with_joined_where_constraint_not_selected(
         sql_client=sql_client,
         node=dataflow_plan.sink_output_nodes[0].parent_node,
     )
+
+
+@pytest.mark.sql_engine_snapshot
+def test_offset_window_with_agg_time_dim(  # noqa: D
+    request: FixtureRequest,
+    mf_test_session_state: MetricFlowTestSessionState,
+    query_parser: MetricFlowQueryParser,
+    dataflow_plan_builder: DataflowPlanBuilder,
+    dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter,
+    sql_client: SqlClient,
+    create_source_tables: bool,
+    column_association_resolver: ColumnAssociationResolver,
+) -> None:
+    query_spec = query_parser.parse_and_validate_query(
+        metric_names=("bookings_growth_2_weeks",),
+        group_by_names=("booking__ds__day",),
+    )
+
+    dataflow_plan = dataflow_plan_builder.build_plan(query_spec)
+    convert_and_check(
+        request=request,
+        mf_test_session_state=mf_test_session_state,
+        dataflow_to_sql_converter=dataflow_to_sql_converter,
+        sql_client=sql_client,
+        node=dataflow_plan.sink_output_nodes[0].parent_node,
+    )
+
+
+@pytest.mark.sql_engine_snapshot
+def test_offset_to_grain_with_agg_time_dim(  # noqa: D
+    request: FixtureRequest,
+    mf_test_session_state: MetricFlowTestSessionState,
+    query_parser: MetricFlowQueryParser,
+    dataflow_plan_builder: DataflowPlanBuilder,
+    dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter,
+    sql_client: SqlClient,
+    create_source_tables: bool,
+    column_association_resolver: ColumnAssociationResolver,
+) -> None:
+    query_spec = query_parser.parse_and_validate_query(
+        metric_names=("bookings_growth_since_start_of_month",),
+        group_by_names=("booking__ds__day",),
+    )
+
+    dataflow_plan = dataflow_plan_builder.build_plan(query_spec)
+    convert_and_check(
+        request=request,
+        mf_test_session_state=mf_test_session_state,
+        dataflow_to_sql_converter=dataflow_to_sql_converter,
+        sql_client=sql_client,
+        node=dataflow_plan.sink_output_nodes[0].parent_node,
+    )
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
index 38870197e4..2927feac1d 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
@@ -20,7 +20,7 @@ FROM (
       FROM (
         -- Join Self Over Time Range
         SELECT
-          subq_3.metric_time__day AS metric_time__day
+          subq_3.metric_time__month AS metric_time__month
           , subq_2.ds__day AS ds__day
           , subq_2.ds__week AS ds__week
           , subq_2.ds__month AS ds__month
@@ -43,8 +43,8 @@ FROM (
           , subq_2.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day
           , subq_2.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow
           , subq_2.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy
+          , subq_2.metric_time__day AS metric_time__day
           , subq_2.metric_time__week AS metric_time__week
-          , subq_2.metric_time__month AS metric_time__month
           , subq_2.metric_time__quarter AS metric_time__quarter
           , subq_2.metric_time__year AS metric_time__year
           , subq_2.metric_time__extract_year AS metric_time__extract_year
@@ -59,9 +59,11 @@ FROM (
         FROM (
           -- Time Spine
           SELECT
-            subq_4.ds AS metric_time__day
+            DATE_TRUNC('month', subq_4.ds) AS metric_time__month
           FROM ***************************.mf_time_spine subq_4
           WHERE subq_4.ds BETWEEN '2020-01-01' AND '2020-01-01'
+          GROUP BY
+            DATE_TRUNC('month', subq_4.ds)
         ) subq_3
         INNER JOIN (
           -- Constrain Time Range to [2019-11-01T00:00:00, 2020-01-01T00:00:00]
@@ -176,9 +178,9 @@ FROM (
         ) subq_2
         ON
           (
-            subq_2.metric_time__day <= subq_3.metric_time__day
+            subq_2.metric_time__month <= subq_3.metric_time__month
           ) AND (
-            subq_2.metric_time__day > subq_3.metric_time__day - INTERVAL 2 month
+            subq_2.metric_time__month > subq_3.metric_time__month - INTERVAL 2 month
           )
       ) subq_5
     ) subq_6
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
index 933797f685..db55011cab 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
@@ -4,32 +4,33 @@
 -- Aggregate Measures
 -- Compute Metrics via Expressions
 SELECT
-  subq_11.metric_time__month AS metric_time__month
+  subq_12.metric_time__month AS metric_time__month
   , SUM(subq_11.txn_revenue) AS trailing_2_months_revenue
 FROM (
   -- Time Spine
   SELECT
-    ds AS metric_time__day
+    DATE_TRUNC('month', ds) AS metric_time__month
   FROM ***************************.mf_time_spine subq_13
   WHERE ds BETWEEN '2020-01-01' AND '2020-01-01'
+  GROUP BY
+    DATE_TRUNC('month', ds)
 ) subq_12
 INNER JOIN (
   -- Read Elements From Semantic Model 'revenue'
   -- Metric Time Dimension 'ds'
   -- Constrain Time Range to [2019-11-01T00:00:00, 2020-01-01T00:00:00]
   SELECT
-    DATE_TRUNC('day', created_at) AS metric_time__day
-    , DATE_TRUNC('month', created_at) AS metric_time__month
+    DATE_TRUNC('month', created_at) AS metric_time__month
     , revenue AS txn_revenue
   FROM ***************************.fct_revenue revenue_src_10007
   WHERE DATE_TRUNC('day', created_at) BETWEEN '2019-11-01' AND '2020-01-01'
 ) subq_11
 ON
   (
-    subq_11.metric_time__day <= subq_12.metric_time__day
+    subq_11.metric_time__month <= subq_12.metric_time__month
   ) AND (
-    subq_11.metric_time__day > subq_12.metric_time__day - INTERVAL 2 month
+    subq_11.metric_time__month > subq_12.metric_time__month - INTERVAL 2 month
   )
-WHERE subq_11.metric_time__month BETWEEN '2020-01-01' AND '2020-01-01'
+WHERE subq_12.metric_time__month BETWEEN '2020-01-01' AND '2020-01-01'
 GROUP BY
-  subq_11.metric_time__month
+  subq_12.metric_time__month
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
new file mode 100644
index 0000000000..2c317b7ee1
--- /dev/null
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
@@ -0,0 +1,534 @@
+-- Compute Metrics via Expressions
+SELECT
+  subq_13.booking__ds__day
+  , bookings - bookings_at_start_of_month AS bookings_growth_since_start_of_month
+FROM (
+  -- Combine Aggregated Outputs
+  SELECT
+    COALESCE(subq_4.booking__ds__day, subq_12.booking__ds__day) AS booking__ds__day
+    , MAX(subq_4.bookings) AS bookings
+    , MAX(subq_12.bookings_at_start_of_month) AS bookings_at_start_of_month
+  FROM (
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_3.booking__ds__day
+      , subq_3.bookings
+    FROM (
+      -- Aggregate Measures
+      SELECT
+        subq_2.booking__ds__day
+        , SUM(subq_2.bookings) AS bookings
+      FROM (
+        -- Pass Only Elements: ['bookings', 'booking__ds__day']
+        SELECT
+          subq_1.booking__ds__day
+          , subq_1.bookings
+        FROM (
+          -- Metric Time Dimension 'ds'
+          SELECT
+            subq_0.ds__day
+            , subq_0.ds__week
+            , subq_0.ds__month
+            , subq_0.ds__quarter
+            , subq_0.ds__year
+            , subq_0.ds__extract_year
+            , subq_0.ds__extract_quarter
+            , subq_0.ds__extract_month
+            , subq_0.ds__extract_day
+            , subq_0.ds__extract_dow
+            , subq_0.ds__extract_doy
+            , subq_0.ds_partitioned__day
+            , subq_0.ds_partitioned__week
+            , subq_0.ds_partitioned__month
+            , subq_0.ds_partitioned__quarter
+            , subq_0.ds_partitioned__year
+            , subq_0.ds_partitioned__extract_year
+            , subq_0.ds_partitioned__extract_quarter
+            , subq_0.ds_partitioned__extract_month
+            , subq_0.ds_partitioned__extract_day
+            , subq_0.ds_partitioned__extract_dow
+            , subq_0.ds_partitioned__extract_doy
+            , subq_0.paid_at__day
+            , subq_0.paid_at__week
+            , subq_0.paid_at__month
+            , subq_0.paid_at__quarter
+            , subq_0.paid_at__year
+            , subq_0.paid_at__extract_year
+            , subq_0.paid_at__extract_quarter
+            , subq_0.paid_at__extract_month
+            , subq_0.paid_at__extract_day
+            , subq_0.paid_at__extract_dow
+            , subq_0.paid_at__extract_doy
+            , subq_0.booking__ds__day
+            , subq_0.booking__ds__week
+            , subq_0.booking__ds__month
+            , subq_0.booking__ds__quarter
+            , subq_0.booking__ds__year
+            , subq_0.booking__ds__extract_year
+            , subq_0.booking__ds__extract_quarter
+            , subq_0.booking__ds__extract_month
+            , subq_0.booking__ds__extract_day
+            , subq_0.booking__ds__extract_dow
+            , subq_0.booking__ds__extract_doy
+            , subq_0.booking__ds_partitioned__day
+            , subq_0.booking__ds_partitioned__week
+            , subq_0.booking__ds_partitioned__month
+            , subq_0.booking__ds_partitioned__quarter
+            , subq_0.booking__ds_partitioned__year
+            , subq_0.booking__ds_partitioned__extract_year
+            , subq_0.booking__ds_partitioned__extract_quarter
+            , subq_0.booking__ds_partitioned__extract_month
+            , subq_0.booking__ds_partitioned__extract_day
+            , subq_0.booking__ds_partitioned__extract_dow
+            , subq_0.booking__ds_partitioned__extract_doy
+            , subq_0.booking__paid_at__day
+            , subq_0.booking__paid_at__week
+            , subq_0.booking__paid_at__month
+            , subq_0.booking__paid_at__quarter
+            , subq_0.booking__paid_at__year
+            , subq_0.booking__paid_at__extract_year
+            , subq_0.booking__paid_at__extract_quarter
+            , subq_0.booking__paid_at__extract_month
+            , subq_0.booking__paid_at__extract_day
+            , subq_0.booking__paid_at__extract_dow
+            , subq_0.booking__paid_at__extract_doy
+            , subq_0.ds__day AS metric_time__day
+            , subq_0.ds__week AS metric_time__week
+            , subq_0.ds__month AS metric_time__month
+            , subq_0.ds__quarter AS metric_time__quarter
+            , subq_0.ds__year AS metric_time__year
+            , subq_0.ds__extract_year AS metric_time__extract_year
+            , subq_0.ds__extract_quarter AS metric_time__extract_quarter
+            , subq_0.ds__extract_month AS metric_time__extract_month
+            , subq_0.ds__extract_day AS metric_time__extract_day
+            , subq_0.ds__extract_dow AS metric_time__extract_dow
+            , subq_0.ds__extract_doy AS metric_time__extract_doy
+            , subq_0.listing
+            , subq_0.guest
+            , subq_0.host
+            , subq_0.booking__listing
+            , subq_0.booking__guest
+            , subq_0.booking__host
+            , subq_0.is_instant
+            , subq_0.booking__is_instant
+            , subq_0.bookings
+            , subq_0.instant_bookings
+            , subq_0.booking_value
+            , subq_0.max_booking_value
+            , subq_0.min_booking_value
+            , subq_0.bookers
+            , subq_0.average_booking_value
+            , subq_0.referred_bookings
+            , subq_0.median_booking_value
+            , subq_0.booking_value_p99
+            , subq_0.discrete_booking_value_p99
+            , subq_0.approximate_continuous_booking_value_p99
+            , subq_0.approximate_discrete_booking_value_p99
+          FROM (
+            -- Read Elements From Semantic Model 'bookings_source'
+            SELECT
+              1 AS bookings
+              , CASE WHEN is_instant THEN 1 ELSE 0 END AS instant_bookings
+              , bookings_source_src_10001.booking_value
+              , bookings_source_src_10001.booking_value AS max_booking_value
+              , bookings_source_src_10001.booking_value AS min_booking_value
+              , bookings_source_src_10001.guest_id AS bookers
+              , bookings_source_src_10001.booking_value AS average_booking_value
+              , bookings_source_src_10001.booking_value AS booking_payments
+              , CASE WHEN referrer_id IS NOT NULL THEN 1 ELSE 0 END AS referred_bookings
+              , bookings_source_src_10001.booking_value AS median_booking_value
+              , bookings_source_src_10001.booking_value AS booking_value_p99
+              , bookings_source_src_10001.booking_value AS discrete_booking_value_p99
+              , bookings_source_src_10001.booking_value AS approximate_continuous_booking_value_p99
+              , bookings_source_src_10001.booking_value AS approximate_discrete_booking_value_p99
+              , bookings_source_src_10001.is_instant
+              , DATE_TRUNC('day', bookings_source_src_10001.ds) AS ds__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds) AS ds__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds) AS ds__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS ds__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds) AS ds__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds) AS ds__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS ds__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds) AS ds__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds) AS ds__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS ds__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds) AS ds__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS paid_at__day
+              , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS paid_at__week
+              , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS paid_at__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS paid_at__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS paid_at__year
+              , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS paid_at__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS paid_at__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS paid_at__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS paid_at__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS paid_at__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS paid_at__extract_doy
+              , bookings_source_src_10001.is_instant AS booking__is_instant
+              , DATE_TRUNC('day', bookings_source_src_10001.ds) AS booking__ds__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds) AS booking__ds__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds) AS booking__ds__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS booking__ds__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds) AS booking__ds__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds) AS booking__ds__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS booking__ds__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds) AS booking__ds__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds) AS booking__ds__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS booking__ds__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds) AS booking__ds__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS booking__paid_at__day
+              , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS booking__paid_at__week
+              , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS booking__paid_at__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS booking__paid_at__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS booking__paid_at__year
+              , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_doy
+              , bookings_source_src_10001.listing_id AS listing
+              , bookings_source_src_10001.guest_id AS guest
+              , bookings_source_src_10001.host_id AS host
+              , bookings_source_src_10001.listing_id AS booking__listing
+              , bookings_source_src_10001.guest_id AS booking__guest
+              , bookings_source_src_10001.host_id AS booking__host
+            FROM ***************************.fct_bookings bookings_source_src_10001
+          ) subq_0
+        ) subq_1
+      ) subq_2
+      GROUP BY
+        subq_2.booking__ds__day
+    ) subq_3
+  ) subq_4
+  FULL OUTER JOIN (
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_11.booking__ds__day
+      , subq_11.bookings AS bookings_at_start_of_month
+    FROM (
+      -- Aggregate Measures
+      SELECT
+        subq_10.booking__ds__day
+        , SUM(subq_10.bookings) AS bookings
+      FROM (
+        -- Pass Only Elements: ['bookings', 'booking__ds__day']
+        SELECT
+          subq_9.booking__ds__day
+          , subq_9.bookings
+        FROM (
+          -- Join to Time Spine Dataset
+          SELECT
+            subq_7.booking__ds__day AS booking__ds__day
+            , subq_6.ds_partitioned__day AS ds_partitioned__day
+            , subq_6.ds_partitioned__week AS ds_partitioned__week
+            , subq_6.ds_partitioned__month AS ds_partitioned__month
+            , subq_6.ds_partitioned__quarter AS ds_partitioned__quarter
+            , subq_6.ds_partitioned__year AS ds_partitioned__year
+            , subq_6.ds_partitioned__extract_year AS ds_partitioned__extract_year
+            , subq_6.ds_partitioned__extract_quarter AS ds_partitioned__extract_quarter
+            , subq_6.ds_partitioned__extract_month AS ds_partitioned__extract_month
+            , subq_6.ds_partitioned__extract_day AS ds_partitioned__extract_day
+            , subq_6.ds_partitioned__extract_dow AS ds_partitioned__extract_dow
+            , subq_6.ds_partitioned__extract_doy AS ds_partitioned__extract_doy
+            , subq_6.paid_at__day AS paid_at__day
+            , subq_6.paid_at__week AS paid_at__week
+            , subq_6.paid_at__month AS paid_at__month
+            , subq_6.paid_at__quarter AS paid_at__quarter
+            , subq_6.paid_at__year AS paid_at__year
+            , subq_6.paid_at__extract_year AS paid_at__extract_year
+            , subq_6.paid_at__extract_quarter AS paid_at__extract_quarter
+            , subq_6.paid_at__extract_month AS paid_at__extract_month
+            , subq_6.paid_at__extract_day AS paid_at__extract_day
+            , subq_6.paid_at__extract_dow AS paid_at__extract_dow
+            , subq_6.paid_at__extract_doy AS paid_at__extract_doy
+            , subq_6.booking__ds_partitioned__day AS booking__ds_partitioned__day
+            , subq_6.booking__ds_partitioned__week AS booking__ds_partitioned__week
+            , subq_6.booking__ds_partitioned__month AS booking__ds_partitioned__month
+            , subq_6.booking__ds_partitioned__quarter AS booking__ds_partitioned__quarter
+            , subq_6.booking__ds_partitioned__year AS booking__ds_partitioned__year
+            , subq_6.booking__ds_partitioned__extract_year AS booking__ds_partitioned__extract_year
+            , subq_6.booking__ds_partitioned__extract_quarter AS booking__ds_partitioned__extract_quarter
+            , subq_6.booking__ds_partitioned__extract_month AS booking__ds_partitioned__extract_month
+            , subq_6.booking__ds_partitioned__extract_day AS booking__ds_partitioned__extract_day
+            , subq_6.booking__ds_partitioned__extract_dow AS booking__ds_partitioned__extract_dow
+            , subq_6.booking__ds_partitioned__extract_doy AS booking__ds_partitioned__extract_doy
+            , subq_6.booking__paid_at__day AS booking__paid_at__day
+            , subq_6.booking__paid_at__week AS booking__paid_at__week
+            , subq_6.booking__paid_at__month AS booking__paid_at__month
+            , subq_6.booking__paid_at__quarter AS booking__paid_at__quarter
+            , subq_6.booking__paid_at__year AS booking__paid_at__year
+            , subq_6.booking__paid_at__extract_year AS booking__paid_at__extract_year
+            , subq_6.booking__paid_at__extract_quarter AS booking__paid_at__extract_quarter
+            , subq_6.booking__paid_at__extract_month AS booking__paid_at__extract_month
+            , subq_6.booking__paid_at__extract_day AS booking__paid_at__extract_day
+            , subq_6.booking__paid_at__extract_dow AS booking__paid_at__extract_dow
+            , subq_6.booking__paid_at__extract_doy AS booking__paid_at__extract_doy
+            , subq_6.metric_time__day AS metric_time__day
+            , subq_6.metric_time__week AS metric_time__week
+            , subq_6.metric_time__month AS metric_time__month
+            , subq_6.metric_time__quarter AS metric_time__quarter
+            , subq_6.metric_time__year AS metric_time__year
+            , subq_6.metric_time__extract_year AS metric_time__extract_year
+            , subq_6.metric_time__extract_quarter AS metric_time__extract_quarter
+            , subq_6.metric_time__extract_month AS metric_time__extract_month
+            , subq_6.metric_time__extract_day AS metric_time__extract_day
+            , subq_6.metric_time__extract_dow AS metric_time__extract_dow
+            , subq_6.metric_time__extract_doy AS metric_time__extract_doy
+            , subq_6.listing AS listing
+            , subq_6.guest AS guest
+            , subq_6.host AS host
+            , subq_6.booking__listing AS booking__listing
+            , subq_6.booking__guest AS booking__guest
+            , subq_6.booking__host AS booking__host
+            , subq_6.is_instant AS is_instant
+            , subq_6.booking__is_instant AS booking__is_instant
+            , subq_6.bookings AS bookings
+            , subq_6.instant_bookings AS instant_bookings
+            , subq_6.booking_value AS booking_value
+            , subq_6.max_booking_value AS max_booking_value
+            , subq_6.min_booking_value AS min_booking_value
+            , subq_6.bookers AS bookers
+            , subq_6.average_booking_value AS average_booking_value
+            , subq_6.referred_bookings AS referred_bookings
+            , subq_6.median_booking_value AS median_booking_value
+            , subq_6.booking_value_p99 AS booking_value_p99
+            , subq_6.discrete_booking_value_p99 AS discrete_booking_value_p99
+            , subq_6.approximate_continuous_booking_value_p99 AS approximate_continuous_booking_value_p99
+            , subq_6.approximate_discrete_booking_value_p99 AS approximate_discrete_booking_value_p99
+          FROM (
+            -- Time Spine
+            SELECT
+              subq_8.ds AS booking__ds__day
+            FROM ***************************.mf_time_spine subq_8
+          ) subq_7
+          INNER JOIN (
+            -- Metric Time Dimension 'ds'
+            SELECT
+              subq_5.ds__day
+              , subq_5.ds__week
+              , subq_5.ds__month
+              , subq_5.ds__quarter
+              , subq_5.ds__year
+              , subq_5.ds__extract_year
+              , subq_5.ds__extract_quarter
+              , subq_5.ds__extract_month
+              , subq_5.ds__extract_day
+              , subq_5.ds__extract_dow
+              , subq_5.ds__extract_doy
+              , subq_5.ds_partitioned__day
+              , subq_5.ds_partitioned__week
+              , subq_5.ds_partitioned__month
+              , subq_5.ds_partitioned__quarter
+              , subq_5.ds_partitioned__year
+              , subq_5.ds_partitioned__extract_year
+              , subq_5.ds_partitioned__extract_quarter
+              , subq_5.ds_partitioned__extract_month
+              , subq_5.ds_partitioned__extract_day
+              , subq_5.ds_partitioned__extract_dow
+              , subq_5.ds_partitioned__extract_doy
+              , subq_5.paid_at__day
+              , subq_5.paid_at__week
+              , subq_5.paid_at__month
+              , subq_5.paid_at__quarter
+              , subq_5.paid_at__year
+              , subq_5.paid_at__extract_year
+              , subq_5.paid_at__extract_quarter
+              , subq_5.paid_at__extract_month
+              , subq_5.paid_at__extract_day
+              , subq_5.paid_at__extract_dow
+              , subq_5.paid_at__extract_doy
+              , subq_5.booking__ds__day
+              , subq_5.booking__ds__week
+              , subq_5.booking__ds__month
+              , subq_5.booking__ds__quarter
+              , subq_5.booking__ds__year
+              , subq_5.booking__ds__extract_year
+              , subq_5.booking__ds__extract_quarter
+              , subq_5.booking__ds__extract_month
+              , subq_5.booking__ds__extract_day
+              , subq_5.booking__ds__extract_dow
+              , subq_5.booking__ds__extract_doy
+              , subq_5.booking__ds_partitioned__day
+              , subq_5.booking__ds_partitioned__week
+              , subq_5.booking__ds_partitioned__month
+              , subq_5.booking__ds_partitioned__quarter
+              , subq_5.booking__ds_partitioned__year
+              , subq_5.booking__ds_partitioned__extract_year
+              , subq_5.booking__ds_partitioned__extract_quarter
+              , subq_5.booking__ds_partitioned__extract_month
+              , subq_5.booking__ds_partitioned__extract_day
+              , subq_5.booking__ds_partitioned__extract_dow
+              , subq_5.booking__ds_partitioned__extract_doy
+              , subq_5.booking__paid_at__day
+              , subq_5.booking__paid_at__week
+              , subq_5.booking__paid_at__month
+              , subq_5.booking__paid_at__quarter
+              , subq_5.booking__paid_at__year
+              , subq_5.booking__paid_at__extract_year
+              , subq_5.booking__paid_at__extract_quarter
+              , subq_5.booking__paid_at__extract_month
+              , subq_5.booking__paid_at__extract_day
+              , subq_5.booking__paid_at__extract_dow
+              , subq_5.booking__paid_at__extract_doy
+              , subq_5.ds__day AS metric_time__day
+              , subq_5.ds__week AS metric_time__week
+              , subq_5.ds__month AS metric_time__month
+              , subq_5.ds__quarter AS metric_time__quarter
+              , subq_5.ds__year AS metric_time__year
+              , subq_5.ds__extract_year AS metric_time__extract_year
+              , subq_5.ds__extract_quarter AS metric_time__extract_quarter
+              , subq_5.ds__extract_month AS metric_time__extract_month
+              , subq_5.ds__extract_day AS metric_time__extract_day
+              , subq_5.ds__extract_dow AS metric_time__extract_dow
+              , subq_5.ds__extract_doy AS metric_time__extract_doy
+              , subq_5.listing
+              , subq_5.guest
+              , subq_5.host
+              , subq_5.booking__listing
+              , subq_5.booking__guest
+              , subq_5.booking__host
+              , subq_5.is_instant
+              , subq_5.booking__is_instant
+              , subq_5.bookings
+              , subq_5.instant_bookings
+              , subq_5.booking_value
+              , subq_5.max_booking_value
+              , subq_5.min_booking_value
+              , subq_5.bookers
+              , subq_5.average_booking_value
+              , subq_5.referred_bookings
+              , subq_5.median_booking_value
+              , subq_5.booking_value_p99
+              , subq_5.discrete_booking_value_p99
+              , subq_5.approximate_continuous_booking_value_p99
+              , subq_5.approximate_discrete_booking_value_p99
+            FROM (
+              -- Read Elements From Semantic Model 'bookings_source'
+              SELECT
+                1 AS bookings
+                , CASE WHEN is_instant THEN 1 ELSE 0 END AS instant_bookings
+                , bookings_source_src_10001.booking_value
+                , bookings_source_src_10001.booking_value AS max_booking_value
+                , bookings_source_src_10001.booking_value AS min_booking_value
+                , bookings_source_src_10001.guest_id AS bookers
+                , bookings_source_src_10001.booking_value AS average_booking_value
+                , bookings_source_src_10001.booking_value AS booking_payments
+                , CASE WHEN referrer_id IS NOT NULL THEN 1 ELSE 0 END AS referred_bookings
+                , bookings_source_src_10001.booking_value AS median_booking_value
+                , bookings_source_src_10001.booking_value AS booking_value_p99
+                , bookings_source_src_10001.booking_value AS discrete_booking_value_p99
+                , bookings_source_src_10001.booking_value AS approximate_continuous_booking_value_p99
+                , bookings_source_src_10001.booking_value AS approximate_discrete_booking_value_p99
+                , bookings_source_src_10001.is_instant
+                , DATE_TRUNC('day', bookings_source_src_10001.ds) AS ds__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds) AS ds__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds) AS ds__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS ds__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds) AS ds__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds) AS ds__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS ds__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds) AS ds__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds) AS ds__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS ds__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds) AS ds__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS paid_at__day
+                , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS paid_at__week
+                , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS paid_at__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS paid_at__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS paid_at__year
+                , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS paid_at__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS paid_at__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS paid_at__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS paid_at__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS paid_at__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS paid_at__extract_doy
+                , bookings_source_src_10001.is_instant AS booking__is_instant
+                , DATE_TRUNC('day', bookings_source_src_10001.ds) AS booking__ds__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds) AS booking__ds__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds) AS booking__ds__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS booking__ds__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds) AS booking__ds__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds) AS booking__ds__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS booking__ds__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds) AS booking__ds__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds) AS booking__ds__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS booking__ds__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds) AS booking__ds__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS booking__paid_at__day
+                , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS booking__paid_at__week
+                , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS booking__paid_at__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS booking__paid_at__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS booking__paid_at__year
+                , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_doy
+                , bookings_source_src_10001.listing_id AS listing
+                , bookings_source_src_10001.guest_id AS guest
+                , bookings_source_src_10001.host_id AS host
+                , bookings_source_src_10001.listing_id AS booking__listing
+                , bookings_source_src_10001.guest_id AS booking__guest
+                , bookings_source_src_10001.host_id AS booking__host
+              FROM ***************************.fct_bookings bookings_source_src_10001
+            ) subq_5
+          ) subq_6
+          ON
+            DATE_TRUNC('month', subq_7.booking__ds__day) = subq_6.booking__ds__day
+        ) subq_9
+      ) subq_10
+      GROUP BY
+        subq_10.booking__ds__day
+    ) subq_11
+  ) subq_12
+  ON
+    subq_4.booking__ds__day = subq_12.booking__ds__day
+  GROUP BY
+    COALESCE(subq_4.booking__ds__day, subq_12.booking__ds__day)
+) subq_13
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0_optimized.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0_optimized.sql
new file mode 100644
index 0000000000..c75e71d99a
--- /dev/null
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0_optimized.sql
@@ -0,0 +1,55 @@
+-- Compute Metrics via Expressions
+SELECT
+  booking__ds__day
+  , bookings - bookings_at_start_of_month AS bookings_growth_since_start_of_month
+FROM (
+  -- Combine Aggregated Outputs
+  SELECT
+    COALESCE(subq_18.booking__ds__day, subq_26.booking__ds__day) AS booking__ds__day
+    , MAX(subq_18.bookings) AS bookings
+    , MAX(subq_26.bookings_at_start_of_month) AS bookings_at_start_of_month
+  FROM (
+    -- Aggregate Measures
+    -- Compute Metrics via Expressions
+    SELECT
+      booking__ds__day
+      , SUM(bookings) AS bookings
+    FROM (
+      -- Read Elements From Semantic Model 'bookings_source'
+      -- Metric Time Dimension 'ds'
+      -- Pass Only Elements: ['bookings', 'booking__ds__day']
+      SELECT
+        DATE_TRUNC('day', ds) AS booking__ds__day
+        , 1 AS bookings
+      FROM ***************************.fct_bookings bookings_source_src_10001
+    ) subq_16
+    GROUP BY
+      booking__ds__day
+  ) subq_18
+  FULL OUTER JOIN (
+    -- Join to Time Spine Dataset
+    -- Pass Only Elements: ['bookings', 'booking__ds__day']
+    -- Aggregate Measures
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_22.ds AS booking__ds__day
+      , SUM(subq_20.bookings) AS bookings_at_start_of_month
+    FROM ***************************.mf_time_spine subq_22
+    INNER JOIN (
+      -- Read Elements From Semantic Model 'bookings_source'
+      -- Metric Time Dimension 'ds'
+      SELECT
+        DATE_TRUNC('day', ds) AS booking__ds__day
+        , 1 AS bookings
+      FROM ***************************.fct_bookings bookings_source_src_10001
+    ) subq_20
+    ON
+      DATE_TRUNC('month', subq_22.ds) = subq_20.booking__ds__day
+    GROUP BY
+      subq_22.ds
+  ) subq_26
+  ON
+    subq_18.booking__ds__day = subq_26.booking__ds__day
+  GROUP BY
+    COALESCE(subq_18.booking__ds__day, subq_26.booking__ds__day)
+) subq_27
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
new file mode 100644
index 0000000000..6cdb31c5d2
--- /dev/null
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
@@ -0,0 +1,534 @@
+-- Compute Metrics via Expressions
+SELECT
+  subq_13.booking__ds__day
+  , bookings - bookings_2_weeks_ago AS bookings_growth_2_weeks
+FROM (
+  -- Combine Aggregated Outputs
+  SELECT
+    COALESCE(subq_4.booking__ds__day, subq_12.booking__ds__day) AS booking__ds__day
+    , MAX(subq_4.bookings) AS bookings
+    , MAX(subq_12.bookings_2_weeks_ago) AS bookings_2_weeks_ago
+  FROM (
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_3.booking__ds__day
+      , subq_3.bookings
+    FROM (
+      -- Aggregate Measures
+      SELECT
+        subq_2.booking__ds__day
+        , SUM(subq_2.bookings) AS bookings
+      FROM (
+        -- Pass Only Elements: ['bookings', 'booking__ds__day']
+        SELECT
+          subq_1.booking__ds__day
+          , subq_1.bookings
+        FROM (
+          -- Metric Time Dimension 'ds'
+          SELECT
+            subq_0.ds__day
+            , subq_0.ds__week
+            , subq_0.ds__month
+            , subq_0.ds__quarter
+            , subq_0.ds__year
+            , subq_0.ds__extract_year
+            , subq_0.ds__extract_quarter
+            , subq_0.ds__extract_month
+            , subq_0.ds__extract_day
+            , subq_0.ds__extract_dow
+            , subq_0.ds__extract_doy
+            , subq_0.ds_partitioned__day
+            , subq_0.ds_partitioned__week
+            , subq_0.ds_partitioned__month
+            , subq_0.ds_partitioned__quarter
+            , subq_0.ds_partitioned__year
+            , subq_0.ds_partitioned__extract_year
+            , subq_0.ds_partitioned__extract_quarter
+            , subq_0.ds_partitioned__extract_month
+            , subq_0.ds_partitioned__extract_day
+            , subq_0.ds_partitioned__extract_dow
+            , subq_0.ds_partitioned__extract_doy
+            , subq_0.paid_at__day
+            , subq_0.paid_at__week
+            , subq_0.paid_at__month
+            , subq_0.paid_at__quarter
+            , subq_0.paid_at__year
+            , subq_0.paid_at__extract_year
+            , subq_0.paid_at__extract_quarter
+            , subq_0.paid_at__extract_month
+            , subq_0.paid_at__extract_day
+            , subq_0.paid_at__extract_dow
+            , subq_0.paid_at__extract_doy
+            , subq_0.booking__ds__day
+            , subq_0.booking__ds__week
+            , subq_0.booking__ds__month
+            , subq_0.booking__ds__quarter
+            , subq_0.booking__ds__year
+            , subq_0.booking__ds__extract_year
+            , subq_0.booking__ds__extract_quarter
+            , subq_0.booking__ds__extract_month
+            , subq_0.booking__ds__extract_day
+            , subq_0.booking__ds__extract_dow
+            , subq_0.booking__ds__extract_doy
+            , subq_0.booking__ds_partitioned__day
+            , subq_0.booking__ds_partitioned__week
+            , subq_0.booking__ds_partitioned__month
+            , subq_0.booking__ds_partitioned__quarter
+            , subq_0.booking__ds_partitioned__year
+            , subq_0.booking__ds_partitioned__extract_year
+            , subq_0.booking__ds_partitioned__extract_quarter
+            , subq_0.booking__ds_partitioned__extract_month
+            , subq_0.booking__ds_partitioned__extract_day
+            , subq_0.booking__ds_partitioned__extract_dow
+            , subq_0.booking__ds_partitioned__extract_doy
+            , subq_0.booking__paid_at__day
+            , subq_0.booking__paid_at__week
+            , subq_0.booking__paid_at__month
+            , subq_0.booking__paid_at__quarter
+            , subq_0.booking__paid_at__year
+            , subq_0.booking__paid_at__extract_year
+            , subq_0.booking__paid_at__extract_quarter
+            , subq_0.booking__paid_at__extract_month
+            , subq_0.booking__paid_at__extract_day
+            , subq_0.booking__paid_at__extract_dow
+            , subq_0.booking__paid_at__extract_doy
+            , subq_0.ds__day AS metric_time__day
+            , subq_0.ds__week AS metric_time__week
+            , subq_0.ds__month AS metric_time__month
+            , subq_0.ds__quarter AS metric_time__quarter
+            , subq_0.ds__year AS metric_time__year
+            , subq_0.ds__extract_year AS metric_time__extract_year
+            , subq_0.ds__extract_quarter AS metric_time__extract_quarter
+            , subq_0.ds__extract_month AS metric_time__extract_month
+            , subq_0.ds__extract_day AS metric_time__extract_day
+            , subq_0.ds__extract_dow AS metric_time__extract_dow
+            , subq_0.ds__extract_doy AS metric_time__extract_doy
+            , subq_0.listing
+            , subq_0.guest
+            , subq_0.host
+            , subq_0.booking__listing
+            , subq_0.booking__guest
+            , subq_0.booking__host
+            , subq_0.is_instant
+            , subq_0.booking__is_instant
+            , subq_0.bookings
+            , subq_0.instant_bookings
+            , subq_0.booking_value
+            , subq_0.max_booking_value
+            , subq_0.min_booking_value
+            , subq_0.bookers
+            , subq_0.average_booking_value
+            , subq_0.referred_bookings
+            , subq_0.median_booking_value
+            , subq_0.booking_value_p99
+            , subq_0.discrete_booking_value_p99
+            , subq_0.approximate_continuous_booking_value_p99
+            , subq_0.approximate_discrete_booking_value_p99
+          FROM (
+            -- Read Elements From Semantic Model 'bookings_source'
+            SELECT
+              1 AS bookings
+              , CASE WHEN is_instant THEN 1 ELSE 0 END AS instant_bookings
+              , bookings_source_src_10001.booking_value
+              , bookings_source_src_10001.booking_value AS max_booking_value
+              , bookings_source_src_10001.booking_value AS min_booking_value
+              , bookings_source_src_10001.guest_id AS bookers
+              , bookings_source_src_10001.booking_value AS average_booking_value
+              , bookings_source_src_10001.booking_value AS booking_payments
+              , CASE WHEN referrer_id IS NOT NULL THEN 1 ELSE 0 END AS referred_bookings
+              , bookings_source_src_10001.booking_value AS median_booking_value
+              , bookings_source_src_10001.booking_value AS booking_value_p99
+              , bookings_source_src_10001.booking_value AS discrete_booking_value_p99
+              , bookings_source_src_10001.booking_value AS approximate_continuous_booking_value_p99
+              , bookings_source_src_10001.booking_value AS approximate_discrete_booking_value_p99
+              , bookings_source_src_10001.is_instant
+              , DATE_TRUNC('day', bookings_source_src_10001.ds) AS ds__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds) AS ds__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds) AS ds__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS ds__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds) AS ds__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds) AS ds__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS ds__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds) AS ds__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds) AS ds__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS ds__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds) AS ds__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS paid_at__day
+              , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS paid_at__week
+              , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS paid_at__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS paid_at__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS paid_at__year
+              , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS paid_at__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS paid_at__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS paid_at__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS paid_at__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS paid_at__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS paid_at__extract_doy
+              , bookings_source_src_10001.is_instant AS booking__is_instant
+              , DATE_TRUNC('day', bookings_source_src_10001.ds) AS booking__ds__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds) AS booking__ds__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds) AS booking__ds__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS booking__ds__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds) AS booking__ds__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds) AS booking__ds__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS booking__ds__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds) AS booking__ds__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds) AS booking__ds__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS booking__ds__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds) AS booking__ds__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__day
+              , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__week
+              , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__year
+              , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_doy
+              , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS booking__paid_at__day
+              , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS booking__paid_at__week
+              , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS booking__paid_at__month
+              , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS booking__paid_at__quarter
+              , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS booking__paid_at__year
+              , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_year
+              , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_quarter
+              , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_month
+              , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_day
+              , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_dow
+              , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_doy
+              , bookings_source_src_10001.listing_id AS listing
+              , bookings_source_src_10001.guest_id AS guest
+              , bookings_source_src_10001.host_id AS host
+              , bookings_source_src_10001.listing_id AS booking__listing
+              , bookings_source_src_10001.guest_id AS booking__guest
+              , bookings_source_src_10001.host_id AS booking__host
+            FROM ***************************.fct_bookings bookings_source_src_10001
+          ) subq_0
+        ) subq_1
+      ) subq_2
+      GROUP BY
+        subq_2.booking__ds__day
+    ) subq_3
+  ) subq_4
+  FULL OUTER JOIN (
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_11.booking__ds__day
+      , subq_11.bookings AS bookings_2_weeks_ago
+    FROM (
+      -- Aggregate Measures
+      SELECT
+        subq_10.booking__ds__day
+        , SUM(subq_10.bookings) AS bookings
+      FROM (
+        -- Pass Only Elements: ['bookings', 'booking__ds__day']
+        SELECT
+          subq_9.booking__ds__day
+          , subq_9.bookings
+        FROM (
+          -- Join to Time Spine Dataset
+          SELECT
+            subq_7.booking__ds__day AS booking__ds__day
+            , subq_6.ds_partitioned__day AS ds_partitioned__day
+            , subq_6.ds_partitioned__week AS ds_partitioned__week
+            , subq_6.ds_partitioned__month AS ds_partitioned__month
+            , subq_6.ds_partitioned__quarter AS ds_partitioned__quarter
+            , subq_6.ds_partitioned__year AS ds_partitioned__year
+            , subq_6.ds_partitioned__extract_year AS ds_partitioned__extract_year
+            , subq_6.ds_partitioned__extract_quarter AS ds_partitioned__extract_quarter
+            , subq_6.ds_partitioned__extract_month AS ds_partitioned__extract_month
+            , subq_6.ds_partitioned__extract_day AS ds_partitioned__extract_day
+            , subq_6.ds_partitioned__extract_dow AS ds_partitioned__extract_dow
+            , subq_6.ds_partitioned__extract_doy AS ds_partitioned__extract_doy
+            , subq_6.paid_at__day AS paid_at__day
+            , subq_6.paid_at__week AS paid_at__week
+            , subq_6.paid_at__month AS paid_at__month
+            , subq_6.paid_at__quarter AS paid_at__quarter
+            , subq_6.paid_at__year AS paid_at__year
+            , subq_6.paid_at__extract_year AS paid_at__extract_year
+            , subq_6.paid_at__extract_quarter AS paid_at__extract_quarter
+            , subq_6.paid_at__extract_month AS paid_at__extract_month
+            , subq_6.paid_at__extract_day AS paid_at__extract_day
+            , subq_6.paid_at__extract_dow AS paid_at__extract_dow
+            , subq_6.paid_at__extract_doy AS paid_at__extract_doy
+            , subq_6.booking__ds_partitioned__day AS booking__ds_partitioned__day
+            , subq_6.booking__ds_partitioned__week AS booking__ds_partitioned__week
+            , subq_6.booking__ds_partitioned__month AS booking__ds_partitioned__month
+            , subq_6.booking__ds_partitioned__quarter AS booking__ds_partitioned__quarter
+            , subq_6.booking__ds_partitioned__year AS booking__ds_partitioned__year
+            , subq_6.booking__ds_partitioned__extract_year AS booking__ds_partitioned__extract_year
+            , subq_6.booking__ds_partitioned__extract_quarter AS booking__ds_partitioned__extract_quarter
+            , subq_6.booking__ds_partitioned__extract_month AS booking__ds_partitioned__extract_month
+            , subq_6.booking__ds_partitioned__extract_day AS booking__ds_partitioned__extract_day
+            , subq_6.booking__ds_partitioned__extract_dow AS booking__ds_partitioned__extract_dow
+            , subq_6.booking__ds_partitioned__extract_doy AS booking__ds_partitioned__extract_doy
+            , subq_6.booking__paid_at__day AS booking__paid_at__day
+            , subq_6.booking__paid_at__week AS booking__paid_at__week
+            , subq_6.booking__paid_at__month AS booking__paid_at__month
+            , subq_6.booking__paid_at__quarter AS booking__paid_at__quarter
+            , subq_6.booking__paid_at__year AS booking__paid_at__year
+            , subq_6.booking__paid_at__extract_year AS booking__paid_at__extract_year
+            , subq_6.booking__paid_at__extract_quarter AS booking__paid_at__extract_quarter
+            , subq_6.booking__paid_at__extract_month AS booking__paid_at__extract_month
+            , subq_6.booking__paid_at__extract_day AS booking__paid_at__extract_day
+            , subq_6.booking__paid_at__extract_dow AS booking__paid_at__extract_dow
+            , subq_6.booking__paid_at__extract_doy AS booking__paid_at__extract_doy
+            , subq_6.metric_time__day AS metric_time__day
+            , subq_6.metric_time__week AS metric_time__week
+            , subq_6.metric_time__month AS metric_time__month
+            , subq_6.metric_time__quarter AS metric_time__quarter
+            , subq_6.metric_time__year AS metric_time__year
+            , subq_6.metric_time__extract_year AS metric_time__extract_year
+            , subq_6.metric_time__extract_quarter AS metric_time__extract_quarter
+            , subq_6.metric_time__extract_month AS metric_time__extract_month
+            , subq_6.metric_time__extract_day AS metric_time__extract_day
+            , subq_6.metric_time__extract_dow AS metric_time__extract_dow
+            , subq_6.metric_time__extract_doy AS metric_time__extract_doy
+            , subq_6.listing AS listing
+            , subq_6.guest AS guest
+            , subq_6.host AS host
+            , subq_6.booking__listing AS booking__listing
+            , subq_6.booking__guest AS booking__guest
+            , subq_6.booking__host AS booking__host
+            , subq_6.is_instant AS is_instant
+            , subq_6.booking__is_instant AS booking__is_instant
+            , subq_6.bookings AS bookings
+            , subq_6.instant_bookings AS instant_bookings
+            , subq_6.booking_value AS booking_value
+            , subq_6.max_booking_value AS max_booking_value
+            , subq_6.min_booking_value AS min_booking_value
+            , subq_6.bookers AS bookers
+            , subq_6.average_booking_value AS average_booking_value
+            , subq_6.referred_bookings AS referred_bookings
+            , subq_6.median_booking_value AS median_booking_value
+            , subq_6.booking_value_p99 AS booking_value_p99
+            , subq_6.discrete_booking_value_p99 AS discrete_booking_value_p99
+            , subq_6.approximate_continuous_booking_value_p99 AS approximate_continuous_booking_value_p99
+            , subq_6.approximate_discrete_booking_value_p99 AS approximate_discrete_booking_value_p99
+          FROM (
+            -- Time Spine
+            SELECT
+              subq_8.ds AS booking__ds__day
+            FROM ***************************.mf_time_spine subq_8
+          ) subq_7
+          INNER JOIN (
+            -- Metric Time Dimension 'ds'
+            SELECT
+              subq_5.ds__day
+              , subq_5.ds__week
+              , subq_5.ds__month
+              , subq_5.ds__quarter
+              , subq_5.ds__year
+              , subq_5.ds__extract_year
+              , subq_5.ds__extract_quarter
+              , subq_5.ds__extract_month
+              , subq_5.ds__extract_day
+              , subq_5.ds__extract_dow
+              , subq_5.ds__extract_doy
+              , subq_5.ds_partitioned__day
+              , subq_5.ds_partitioned__week
+              , subq_5.ds_partitioned__month
+              , subq_5.ds_partitioned__quarter
+              , subq_5.ds_partitioned__year
+              , subq_5.ds_partitioned__extract_year
+              , subq_5.ds_partitioned__extract_quarter
+              , subq_5.ds_partitioned__extract_month
+              , subq_5.ds_partitioned__extract_day
+              , subq_5.ds_partitioned__extract_dow
+              , subq_5.ds_partitioned__extract_doy
+              , subq_5.paid_at__day
+              , subq_5.paid_at__week
+              , subq_5.paid_at__month
+              , subq_5.paid_at__quarter
+              , subq_5.paid_at__year
+              , subq_5.paid_at__extract_year
+              , subq_5.paid_at__extract_quarter
+              , subq_5.paid_at__extract_month
+              , subq_5.paid_at__extract_day
+              , subq_5.paid_at__extract_dow
+              , subq_5.paid_at__extract_doy
+              , subq_5.booking__ds__day
+              , subq_5.booking__ds__week
+              , subq_5.booking__ds__month
+              , subq_5.booking__ds__quarter
+              , subq_5.booking__ds__year
+              , subq_5.booking__ds__extract_year
+              , subq_5.booking__ds__extract_quarter
+              , subq_5.booking__ds__extract_month
+              , subq_5.booking__ds__extract_day
+              , subq_5.booking__ds__extract_dow
+              , subq_5.booking__ds__extract_doy
+              , subq_5.booking__ds_partitioned__day
+              , subq_5.booking__ds_partitioned__week
+              , subq_5.booking__ds_partitioned__month
+              , subq_5.booking__ds_partitioned__quarter
+              , subq_5.booking__ds_partitioned__year
+              , subq_5.booking__ds_partitioned__extract_year
+              , subq_5.booking__ds_partitioned__extract_quarter
+              , subq_5.booking__ds_partitioned__extract_month
+              , subq_5.booking__ds_partitioned__extract_day
+              , subq_5.booking__ds_partitioned__extract_dow
+              , subq_5.booking__ds_partitioned__extract_doy
+              , subq_5.booking__paid_at__day
+              , subq_5.booking__paid_at__week
+              , subq_5.booking__paid_at__month
+              , subq_5.booking__paid_at__quarter
+              , subq_5.booking__paid_at__year
+              , subq_5.booking__paid_at__extract_year
+              , subq_5.booking__paid_at__extract_quarter
+              , subq_5.booking__paid_at__extract_month
+              , subq_5.booking__paid_at__extract_day
+              , subq_5.booking__paid_at__extract_dow
+              , subq_5.booking__paid_at__extract_doy
+              , subq_5.ds__day AS metric_time__day
+              , subq_5.ds__week AS metric_time__week
+              , subq_5.ds__month AS metric_time__month
+              , subq_5.ds__quarter AS metric_time__quarter
+              , subq_5.ds__year AS metric_time__year
+              , subq_5.ds__extract_year AS metric_time__extract_year
+              , subq_5.ds__extract_quarter AS metric_time__extract_quarter
+              , subq_5.ds__extract_month AS metric_time__extract_month
+              , subq_5.ds__extract_day AS metric_time__extract_day
+              , subq_5.ds__extract_dow AS metric_time__extract_dow
+              , subq_5.ds__extract_doy AS metric_time__extract_doy
+              , subq_5.listing
+              , subq_5.guest
+              , subq_5.host
+              , subq_5.booking__listing
+              , subq_5.booking__guest
+              , subq_5.booking__host
+              , subq_5.is_instant
+              , subq_5.booking__is_instant
+              , subq_5.bookings
+              , subq_5.instant_bookings
+              , subq_5.booking_value
+              , subq_5.max_booking_value
+              , subq_5.min_booking_value
+              , subq_5.bookers
+              , subq_5.average_booking_value
+              , subq_5.referred_bookings
+              , subq_5.median_booking_value
+              , subq_5.booking_value_p99
+              , subq_5.discrete_booking_value_p99
+              , subq_5.approximate_continuous_booking_value_p99
+              , subq_5.approximate_discrete_booking_value_p99
+            FROM (
+              -- Read Elements From Semantic Model 'bookings_source'
+              SELECT
+                1 AS bookings
+                , CASE WHEN is_instant THEN 1 ELSE 0 END AS instant_bookings
+                , bookings_source_src_10001.booking_value
+                , bookings_source_src_10001.booking_value AS max_booking_value
+                , bookings_source_src_10001.booking_value AS min_booking_value
+                , bookings_source_src_10001.guest_id AS bookers
+                , bookings_source_src_10001.booking_value AS average_booking_value
+                , bookings_source_src_10001.booking_value AS booking_payments
+                , CASE WHEN referrer_id IS NOT NULL THEN 1 ELSE 0 END AS referred_bookings
+                , bookings_source_src_10001.booking_value AS median_booking_value
+                , bookings_source_src_10001.booking_value AS booking_value_p99
+                , bookings_source_src_10001.booking_value AS discrete_booking_value_p99
+                , bookings_source_src_10001.booking_value AS approximate_continuous_booking_value_p99
+                , bookings_source_src_10001.booking_value AS approximate_discrete_booking_value_p99
+                , bookings_source_src_10001.is_instant
+                , DATE_TRUNC('day', bookings_source_src_10001.ds) AS ds__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds) AS ds__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds) AS ds__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS ds__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds) AS ds__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds) AS ds__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS ds__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds) AS ds__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds) AS ds__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS ds__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds) AS ds__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS ds_partitioned__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS ds_partitioned__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS paid_at__day
+                , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS paid_at__week
+                , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS paid_at__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS paid_at__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS paid_at__year
+                , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS paid_at__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS paid_at__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS paid_at__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS paid_at__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS paid_at__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS paid_at__extract_doy
+                , bookings_source_src_10001.is_instant AS booking__is_instant
+                , DATE_TRUNC('day', bookings_source_src_10001.ds) AS booking__ds__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds) AS booking__ds__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds) AS booking__ds__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds) AS booking__ds__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds) AS booking__ds__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds) AS booking__ds__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds) AS booking__ds__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds) AS booking__ds__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds) AS booking__ds__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds) AS booking__ds__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds) AS booking__ds__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__day
+                , DATE_TRUNC('week', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__week
+                , DATE_TRUNC('month', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__year
+                , EXTRACT(year FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.ds_partitioned) AS booking__ds_partitioned__extract_doy
+                , DATE_TRUNC('day', bookings_source_src_10001.paid_at) AS booking__paid_at__day
+                , DATE_TRUNC('week', bookings_source_src_10001.paid_at) AS booking__paid_at__week
+                , DATE_TRUNC('month', bookings_source_src_10001.paid_at) AS booking__paid_at__month
+                , DATE_TRUNC('quarter', bookings_source_src_10001.paid_at) AS booking__paid_at__quarter
+                , DATE_TRUNC('year', bookings_source_src_10001.paid_at) AS booking__paid_at__year
+                , EXTRACT(year FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_year
+                , EXTRACT(quarter FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_quarter
+                , EXTRACT(month FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_month
+                , EXTRACT(day FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_day
+                , EXTRACT(isodow FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_dow
+                , EXTRACT(doy FROM bookings_source_src_10001.paid_at) AS booking__paid_at__extract_doy
+                , bookings_source_src_10001.listing_id AS listing
+                , bookings_source_src_10001.guest_id AS guest
+                , bookings_source_src_10001.host_id AS host
+                , bookings_source_src_10001.listing_id AS booking__listing
+                , bookings_source_src_10001.guest_id AS booking__guest
+                , bookings_source_src_10001.host_id AS booking__host
+              FROM ***************************.fct_bookings bookings_source_src_10001
+            ) subq_5
+          ) subq_6
+          ON
+            subq_7.booking__ds__day - INTERVAL 14 day = subq_6.booking__ds__day
+        ) subq_9
+      ) subq_10
+      GROUP BY
+        subq_10.booking__ds__day
+    ) subq_11
+  ) subq_12
+  ON
+    subq_4.booking__ds__day = subq_12.booking__ds__day
+  GROUP BY
+    COALESCE(subq_4.booking__ds__day, subq_12.booking__ds__day)
+) subq_13
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0_optimized.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0_optimized.sql
new file mode 100644
index 0000000000..d972aa60d9
--- /dev/null
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0_optimized.sql
@@ -0,0 +1,55 @@
+-- Compute Metrics via Expressions
+SELECT
+  booking__ds__day
+  , bookings - bookings_2_weeks_ago AS bookings_growth_2_weeks
+FROM (
+  -- Combine Aggregated Outputs
+  SELECT
+    COALESCE(subq_18.booking__ds__day, subq_26.booking__ds__day) AS booking__ds__day
+    , MAX(subq_18.bookings) AS bookings
+    , MAX(subq_26.bookings_2_weeks_ago) AS bookings_2_weeks_ago
+  FROM (
+    -- Aggregate Measures
+    -- Compute Metrics via Expressions
+    SELECT
+      booking__ds__day
+      , SUM(bookings) AS bookings
+    FROM (
+      -- Read Elements From Semantic Model 'bookings_source'
+      -- Metric Time Dimension 'ds'
+      -- Pass Only Elements: ['bookings', 'booking__ds__day']
+      SELECT
+        DATE_TRUNC('day', ds) AS booking__ds__day
+        , 1 AS bookings
+      FROM ***************************.fct_bookings bookings_source_src_10001
+    ) subq_16
+    GROUP BY
+      booking__ds__day
+  ) subq_18
+  FULL OUTER JOIN (
+    -- Join to Time Spine Dataset
+    -- Pass Only Elements: ['bookings', 'booking__ds__day']
+    -- Aggregate Measures
+    -- Compute Metrics via Expressions
+    SELECT
+      subq_22.ds AS booking__ds__day
+      , SUM(subq_20.bookings) AS bookings_2_weeks_ago
+    FROM ***************************.mf_time_spine subq_22
+    INNER JOIN (
+      -- Read Elements From Semantic Model 'bookings_source'
+      -- Metric Time Dimension 'ds'
+      SELECT
+        DATE_TRUNC('day', ds) AS booking__ds__day
+        , 1 AS bookings
+      FROM ***************************.fct_bookings bookings_source_src_10001
+    ) subq_20
+    ON
+      subq_22.ds - INTERVAL 14 day = subq_20.booking__ds__day
+    GROUP BY
+      subq_22.ds
+  ) subq_26
+  ON
+    subq_18.booking__ds__day = subq_26.booking__ds__day
+  GROUP BY
+    COALESCE(subq_18.booking__ds__day, subq_26.booking__ds__day)
+) subq_27

From fa28dc96f901611a96e7da3bd1d75de493b491a5 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 10:55:18 -0800
Subject: [PATCH 09/22] Quick fix

---
 metricflow/plan_conversion/dataflow_to_sql.py         |  6 ++++--
 .../test_offset_to_grain_with_agg_time_dim__plan0.sql | 11 +++++++++++
 .../test_offset_window_with_agg_time_dim__plan0.sql   | 11 +++++++++++
 3 files changed, 26 insertions(+), 2 deletions(-)

diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index be222e1e98..dca49699a9 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -1298,8 +1298,10 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
             time_dimension_instances=tuple(
                 time_dimension_instance
                 for time_dimension_instance in parent_data_set.instance_set.time_dimension_instances
-                if time_dimension_instance.spec.element_name != agg_time_dimension_for_join.element_name
-                # and time_dimension_instance.spec.entity_links != agg_time_dimension_for_join.entity_links
+                if not (
+                    time_dimension_instance.spec.element_name == agg_time_dimension_for_join.element_name
+                    and time_dimension_instance.spec.entity_links == agg_time_dimension_for_join.entity_links
+                )
             ),
             entity_instances=parent_data_set.instance_set.entity_instances,
             metric_instances=parent_data_set.instance_set.metric_instances,
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
index 2c317b7ee1..1f55db2271 100644
--- a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_to_grain_with_agg_time_dim__plan0.sql
@@ -242,6 +242,17 @@ FROM (
           -- Join to Time Spine Dataset
           SELECT
             subq_7.booking__ds__day AS booking__ds__day
+            , subq_6.ds__day AS ds__day
+            , subq_6.ds__week AS ds__week
+            , subq_6.ds__month AS ds__month
+            , subq_6.ds__quarter AS ds__quarter
+            , subq_6.ds__year AS ds__year
+            , subq_6.ds__extract_year AS ds__extract_year
+            , subq_6.ds__extract_quarter AS ds__extract_quarter
+            , subq_6.ds__extract_month AS ds__extract_month
+            , subq_6.ds__extract_day AS ds__extract_day
+            , subq_6.ds__extract_dow AS ds__extract_dow
+            , subq_6.ds__extract_doy AS ds__extract_doy
             , subq_6.ds_partitioned__day AS ds_partitioned__day
             , subq_6.ds_partitioned__week AS ds_partitioned__week
             , subq_6.ds_partitioned__month AS ds_partitioned__month
diff --git a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
index 6cdb31c5d2..10afa5e97a 100644
--- a/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
+++ b/metricflow/test/snapshots/test_derived_metric_rendering.py/SqlQueryPlan/DuckDB/test_offset_window_with_agg_time_dim__plan0.sql
@@ -242,6 +242,17 @@ FROM (
           -- Join to Time Spine Dataset
           SELECT
             subq_7.booking__ds__day AS booking__ds__day
+            , subq_6.ds__day AS ds__day
+            , subq_6.ds__week AS ds__week
+            , subq_6.ds__month AS ds__month
+            , subq_6.ds__quarter AS ds__quarter
+            , subq_6.ds__year AS ds__year
+            , subq_6.ds__extract_year AS ds__extract_year
+            , subq_6.ds__extract_quarter AS ds__extract_quarter
+            , subq_6.ds__extract_month AS ds__extract_month
+            , subq_6.ds__extract_day AS ds__extract_day
+            , subq_6.ds__extract_dow AS ds__extract_dow
+            , subq_6.ds__extract_doy AS ds__extract_doy
             , subq_6.ds_partitioned__day AS ds_partitioned__day
             , subq_6.ds_partitioned__week AS ds_partitioned__week
             , subq_6.ds_partitioned__month AS ds_partitioned__month

From 23e5c0b90ce7784ba7ccf697af58be7ebeb74679 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 10:56:55 -0800
Subject: [PATCH 10/22] Comment

---
 metricflow/test/integration/test_cases/itest_metrics.yaml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/metricflow/test/integration/test_cases/itest_metrics.yaml b/metricflow/test/integration/test_cases/itest_metrics.yaml
index 7110f22109..b874fc104c 100644
--- a/metricflow/test/integration/test_cases/itest_metrics.yaml
+++ b/metricflow/test/integration/test_cases/itest_metrics.yaml
@@ -1813,4 +1813,5 @@ integration_test:
       ON {{ render_date_trunc("c.ds", TimeGranularity.MONTH) }} = d.booking__ds__day
     ) b
     ON a.booking__ds__day = b.booking__ds__day
-# TODO: tests with granularity, date part, multiple metric time / agg time options
+# TODO: offset tests with granularity, date part, multiple metric time / agg time options
+# TODO: cumulative tests with multiple metric_time / agg time options

From a8018d9dc7b64fdb366ce15c02ceeae8aeeb3ec6 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 11:16:34 -0800
Subject: [PATCH 11/22] WIP

---
 .../dataflow/builder/dataflow_plan_builder.py | 54 +++++++++++--------
 1 file changed, 32 insertions(+), 22 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index ad1a1fa4d8..f2af2e2c60 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -499,19 +499,23 @@ def _build_derived_metric_output_node(
         )
         output_node: BaseOutput = ComputeMetricsNode(parent_node=parent_node, metric_specs=[metric_spec])
 
+        # TODO: Write a test case for this scenario
         # For nested ratio / derived metrics with time offset, apply offset & where constraint after metric computation.
         if metric_spec.has_time_offset:
-            # TODO: if you only query with the agg_time_dimension for the offset metric, should that work? (assuming another input metric uses a diff agg_time_dim)
-            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
-            if not query_contains_metric_time_or_agg_time_dimension:
-                pass  # check for agg_time_dimension and update accordingly
-                # Write a test case for this scenario
+            queried_agg_time_dimension_specs = list(queried_linkable_specs.metric_time_specs)
+            if not queried_agg_time_dimension_specs:
+                valid_agg_time_dimensions = self._metric_lookup.get_valid_agg_time_dimensions_for_metric(
+                    metric_spec.reference
+                )
+                queried_agg_time_dimension_specs = list(
+                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
+                )
             assert (
-                query_contains_metric_time_or_agg_time_dimension
+                queried_agg_time_dimension_specs
             ), "Joining to time spine requires querying with metric_time or the appropriate agg_time_dimension."
             output_node = JoinToTimeSpineNode(
                 parent_node=output_node,
-                requested_metric_time_dimension_specs=list(queried_linkable_specs.metric_time_specs),
+                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
                 time_range_constraint=time_range_constraint,
                 offset_window=metric_spec.offset_window,
                 offset_to_grain=metric_spec.offset_to_grain,
@@ -1110,15 +1114,22 @@ def _build_input_measure_spec_for_base_metric(
                 offset_to_grain=child_metric_offset_to_grain,
             )
 
-        # Even if the measure is configured to join to time spine, if there's no metric_time in the query,
-        # there's no need to join to the time spine since all metric_time will be aggregated.
+        # Even if the measure is configured to join to time spine, if there's no agg_time_dimension in the query,
+        # there's no need to join to the time spine since all time will be aggregated.
         after_aggregation_time_spine_join_description = None
         if input_measure.join_to_timespine:
-            query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
-            if not query_contains_metric_time_or_agg_time_dimension:
-                pass  # check for agg_time_dimension and update accordingly
-                # Write a test case for this scenario
-            if query_contains_metric_time_or_agg_time_dimension:
+            # TODO: Write a test case for this scenario
+            query_contains_agg_time_dimension = queried_linkable_specs.contains_metric_time
+            if not query_contains_agg_time_dimension:
+                # TODO: should this be checking valid agg time dims for measure or metric?
+                valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
+                    measure_spec.reference
+                )
+                query_contains_agg_time_dimension = bool(
+                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
+                )
+
+            if query_contains_agg_time_dimension:
                 after_aggregation_time_spine_join_description = JoinToTimeSpineDescription(
                     join_type=SqlJoinType.LEFT_OUTER,
                     offset_window=None,
@@ -1311,7 +1322,7 @@ def _build_aggregated_measure_from_measure_source_node(
                 f"Recipe not found for measure spec: {measure_spec} and linkable specs: {required_linkable_specs}"
             )
 
-        # If a cumulative metric is queried with metric_time or agg_time_dimension, join over time range.
+        # If a cumulative metric is queried with agg_time_dimension, join over time range.
         # Otherwise, the measure will be aggregated over all time.
         time_range_node: Optional[JoinOverTimeRangeNode] = None
         if cumulative:
@@ -1320,8 +1331,7 @@ def _build_aggregated_measure_from_measure_source_node(
                 valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
                     measure_spec.reference
                 )
-                # TODO: we only actually allow one granularity for cumulative. Should that be reflected here?
-                # Definitely shouldn't have date part in here
+                # TODO: will it be a problem if we get one with date part or diff granularity?
                 queried_agg_time_dims = sorted(
                     set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions)),
                     key=lambda x: x.time_granularity.to_int(),
@@ -1344,16 +1354,16 @@ def _build_aggregated_measure_from_measure_source_node(
         join_to_time_spine_node: Optional[JoinToTimeSpineNode] = None
         if before_aggregation_time_spine_join_description is not None:
             # TODO: below logic is somewhat duplicated
-            queried_metric_time_specs = list(queried_linkable_specs.metric_time_specs)
-            if not queried_metric_time_specs:
+            queried_agg_time_dimension_specs = list(queried_linkable_specs.metric_time_specs)
+            if not queried_agg_time_dimension_specs:
                 valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
                     measure_spec.reference
                 )
-                queried_metric_time_specs = list(
+                queried_agg_time_dimension_specs = list(
                     set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
                 )
 
-            assert queried_metric_time_specs, (
+            assert queried_agg_time_dimension_specs, (
                 "Joining to time spine requires querying with metric time or the appropriate agg_time_dimension."
                 "This should have been caught by validations."
             )
@@ -1364,7 +1374,7 @@ def _build_aggregated_measure_from_measure_source_node(
             )
             join_to_time_spine_node = JoinToTimeSpineNode(
                 parent_node=time_range_node or measure_recipe.source_node,
-                requested_metric_time_dimension_specs=queried_metric_time_specs,
+                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
                 time_range_constraint=time_range_constraint,
                 offset_window=before_aggregation_time_spine_join_description.offset_window,
                 offset_to_grain=before_aggregation_time_spine_join_description.offset_to_grain,

From 3f58e882a649803982955784ddcbf5ae67ba5a05 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 11:58:00 -0800
Subject: [PATCH 12/22] Update snapshots

---
 ...cumulative_metric_with_time_constraint__plan0.sql | 12 +++++-------
 ..._metric_with_time_constraint__plan0_optimized.sql |  8 +++-----
 2 files changed, 8 insertions(+), 12 deletions(-)

diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
index 63ee35aaad..4faccf1d37 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0.sql
@@ -20,7 +20,7 @@ FROM (
       FROM (
         -- Join Self Over Time Range
         SELECT
-          subq_3.metric_time__month AS metric_time__month
+          subq_3.metric_time__day AS metric_time__day
           , subq_2.ds__day AS ds__day
           , subq_2.ds__week AS ds__week
           , subq_2.ds__month AS ds__month
@@ -43,8 +43,8 @@ FROM (
           , subq_2.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day
           , subq_2.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow
           , subq_2.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy
-          , subq_2.metric_time__day AS metric_time__day
           , subq_2.metric_time__week AS metric_time__week
+          , subq_2.metric_time__month AS metric_time__month
           , subq_2.metric_time__quarter AS metric_time__quarter
           , subq_2.metric_time__year AS metric_time__year
           , subq_2.metric_time__extract_year AS metric_time__extract_year
@@ -59,11 +59,9 @@ FROM (
         FROM (
           -- Time Spine
           SELECT
-            DATE_TRUNC('month', subq_4.ds) AS metric_time__month
+            subq_4.ds AS metric_time__day
           FROM ***************************.mf_time_spine subq_4
           WHERE subq_4.ds BETWEEN '2020-01-01' AND '2020-01-01'
-          GROUP BY
-            DATE_TRUNC('month', subq_4.ds)
         ) subq_3
         INNER JOIN (
           -- Constrain Time Range to [2019-11-01T00:00:00, 2020-01-01T00:00:00]
@@ -178,9 +176,9 @@ FROM (
         ) subq_2
         ON
           (
-            subq_2.metric_time__month <= subq_3.metric_time__month
+            subq_2.metric_time__day <= subq_3.metric_time__day
           ) AND (
-            subq_2.metric_time__month > subq_3.metric_time__month - INTERVAL 2 month
+            subq_2.metric_time__day > subq_3.metric_time__day - INTERVAL 2 month
           )
       ) subq_5
     ) subq_6
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
index 1fa1babb3d..ddcc18a49f 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_time_constraint__plan0_optimized.sql
@@ -9,11 +9,9 @@ SELECT
 FROM (
   -- Time Spine
   SELECT
-    DATE_TRUNC('month', ds) AS metric_time__month
+    ds AS metric_time__day
   FROM ***************************.mf_time_spine subq_13
   WHERE ds BETWEEN '2020-01-01' AND '2020-01-01'
-  GROUP BY
-    DATE_TRUNC('month', ds)
 ) subq_12
 INNER JOIN (
   -- Read Elements From Semantic Model 'revenue'
@@ -27,9 +25,9 @@ INNER JOIN (
 ) subq_11
 ON
   (
-    subq_11.metric_time__month <= subq_12.metric_time__month
+    subq_11.metric_time__day <= subq_12.metric_time__day
   ) AND (
-    subq_11.metric_time__month > subq_12.metric_time__month - INTERVAL 2 month
+    subq_11.metric_time__day > subq_12.metric_time__day - INTERVAL 2 month
   )
 WHERE subq_12.metric_time__day BETWEEN '2020-01-01' AND '2020-01-01'
 GROUP BY

From f0039d2b17e7a80317d6a063f7b9834e6dd1b862 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 13:17:23 -0800
Subject: [PATCH 13/22] Comment

---
 metricflow/dataflow/builder/dataflow_plan_builder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 8d1f2f1738..de2458cd6a 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -1331,7 +1331,7 @@ def _build_aggregated_measure_from_measure_source_node(
                 valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
                     measure_spec.reference
                 )
-                # TODO: will it be a problem if we get one with date part or diff granularity?
+                # TODO: will it be a problem if we get one with date part or diff granularity? Write test case
                 queried_agg_time_dims = sorted(
                     set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions)),
                     key=lambda x: x.time_granularity.to_int(),

From 3fc26652614fc383eec852a5ed2e68b3ab7322ff Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 16:03:24 -0800
Subject: [PATCH 14/22] WIP

---
 .../test_cases/itest_cumulative_metric.yaml   |   2 +-
 .../test_cumulative_metric_rendering.py       |  46 +++--
 ..._metric_with_agg_time_dimension__plan0.sql | 189 ++++++++++++++++++
 ...th_agg_time_dimension__plan0_optimized.sql |  34 ++++
 4 files changed, 258 insertions(+), 13 deletions(-)
 create mode 100644 metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
 create mode 100644 metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql

diff --git a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
index 974296656f..17b9927073 100644
--- a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
+++ b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
@@ -387,7 +387,7 @@ integration_test:
 ---
 integration_test:
   name: cumulative_metric_with_agg_time_dimension
-  description: Query a cumulative metric with its agg_time_dimension.
+  description: Query a cumulative metric with its agg_time_dimension and a time constraint.
   model: SIMPLE_MODEL
   metrics: ["trailing_2_months_revenue"]
   group_bys: ["revenue_instance__ds__day"]
diff --git a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
index 38a59242fe..873cf79ea8 100644
--- a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
@@ -15,11 +15,7 @@
 from metricflow.protocols.sql_client import SqlClient
 from metricflow.query.query_parser import MetricFlowQueryParser
 from metricflow.specs.column_assoc import ColumnAssociationResolver
-from metricflow.specs.specs import (
-    MetricFlowQuerySpec,
-    MetricSpec,
-    TimeDimensionSpec,
-)
+from metricflow.specs.specs import EntityReference, MetricFlowQuerySpec, MetricSpec, TimeDimensionSpec
 from metricflow.test.fixtures.model_fixtures import ConsistentIdObjectRepository
 from metricflow.test.fixtures.setup_fixtures import MetricFlowTestSessionState
 from metricflow.test.query_rendering.compare_rendered_query import convert_and_check
@@ -212,13 +208,7 @@ def test_cumulative_metric_no_window_with_time_constraint(
         MetricFlowQuerySpec(
             metric_specs=(MetricSpec(element_name="revenue_all_time"),),
             dimension_specs=(),
-            time_dimension_specs=(
-                TimeDimensionSpec(
-                    element_name="ds",
-                    entity_links=(),
-                    time_granularity=TimeGranularity.MONTH,
-                ),
-            ),
+            time_dimension_specs=(MTD_SPEC_MONTH,),
             time_range_constraint=TimeRangeConstraint(
                 start_time=as_datetime("2020-01-01"), end_time=as_datetime("2020-01-01")
             ),
@@ -295,3 +285,35 @@ def test_cumulative_metric_month(
         sql_client=sql_client,
         node=dataflow_plan.sink_output_nodes[0].parent_node,
     )
+
+
+@pytest.mark.sql_engine_snapshot
+def test_cumulative_metric_with_agg_time_dimension(
+    request: FixtureRequest,
+    mf_test_session_state: MetricFlowTestSessionState,
+    dataflow_plan_builder: DataflowPlanBuilder,
+    dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter,
+    consistent_id_object_repository: ConsistentIdObjectRepository,
+    sql_client: SqlClient,
+) -> None:
+    """Tests rendering a query for a cumulative metric queried with agg time dimension."""
+    dataflow_plan = dataflow_plan_builder.build_plan(
+        MetricFlowQuerySpec(
+            metric_specs=(MetricSpec(element_name="trailing_2_months_revenue"),),
+            dimension_specs=(),
+            time_dimension_specs=(
+                TimeDimensionSpec(element_name="ds", entity_links=(EntityReference("revenue_instance"),)),
+            ),
+            time_range_constraint=TimeRangeConstraint(
+                start_time=as_datetime("2020-03-05"), end_time=as_datetime("2021-01-04")
+            ),
+        )
+    )
+
+    convert_and_check(
+        request=request,
+        mf_test_session_state=mf_test_session_state,
+        dataflow_to_sql_converter=dataflow_to_sql_converter,
+        sql_client=sql_client,
+        node=dataflow_plan.sink_output_nodes[0].parent_node,
+    )
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
new file mode 100644
index 0000000000..24daa015d5
--- /dev/null
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
@@ -0,0 +1,189 @@
+-- Compute Metrics via Expressions
+SELECT
+  subq_8.revenue_instance__ds__day
+  , subq_8.txn_revenue AS trailing_2_months_revenue
+FROM (
+  -- Aggregate Measures
+  SELECT
+    subq_7.revenue_instance__ds__day
+    , SUM(subq_7.txn_revenue) AS txn_revenue
+  FROM (
+    -- Constrain Time Range to [2020-03-05T00:00:00, 2021-01-04T00:00:00]
+    SELECT
+      subq_6.revenue_instance__ds__day
+      , subq_6.txn_revenue
+    FROM (
+      -- Pass Only Elements: ['txn_revenue', 'revenue_instance__ds__day']
+      SELECT
+        subq_5.revenue_instance__ds__day
+        , subq_5.txn_revenue
+      FROM (
+        -- Join Self Over Time Range
+        SELECT
+          subq_3.revenue_instance__ds__day AS revenue_instance__ds__day
+          , subq_2.ds__day AS ds__day
+          , subq_2.ds__week AS ds__week
+          , subq_2.ds__month AS ds__month
+          , subq_2.ds__quarter AS ds__quarter
+          , subq_2.ds__year AS ds__year
+          , subq_2.ds__extract_year AS ds__extract_year
+          , subq_2.ds__extract_quarter AS ds__extract_quarter
+          , subq_2.ds__extract_month AS ds__extract_month
+          , subq_2.ds__extract_day AS ds__extract_day
+          , subq_2.ds__extract_dow AS ds__extract_dow
+          , subq_2.ds__extract_doy AS ds__extract_doy
+          , subq_2.revenue_instance__ds__week AS revenue_instance__ds__week
+          , subq_2.revenue_instance__ds__month AS revenue_instance__ds__month
+          , subq_2.revenue_instance__ds__quarter AS revenue_instance__ds__quarter
+          , subq_2.revenue_instance__ds__year AS revenue_instance__ds__year
+          , subq_2.revenue_instance__ds__extract_year AS revenue_instance__ds__extract_year
+          , subq_2.revenue_instance__ds__extract_quarter AS revenue_instance__ds__extract_quarter
+          , subq_2.revenue_instance__ds__extract_month AS revenue_instance__ds__extract_month
+          , subq_2.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day
+          , subq_2.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow
+          , subq_2.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy
+          , subq_2.metric_time__day AS metric_time__day
+          , subq_2.metric_time__week AS metric_time__week
+          , subq_2.metric_time__month AS metric_time__month
+          , subq_2.metric_time__quarter AS metric_time__quarter
+          , subq_2.metric_time__year AS metric_time__year
+          , subq_2.metric_time__extract_year AS metric_time__extract_year
+          , subq_2.metric_time__extract_quarter AS metric_time__extract_quarter
+          , subq_2.metric_time__extract_month AS metric_time__extract_month
+          , subq_2.metric_time__extract_day AS metric_time__extract_day
+          , subq_2.metric_time__extract_dow AS metric_time__extract_dow
+          , subq_2.metric_time__extract_doy AS metric_time__extract_doy
+          , subq_2.user AS user
+          , subq_2.revenue_instance__user AS revenue_instance__user
+          , subq_2.txn_revenue AS txn_revenue
+        FROM (
+          -- Time Spine
+          SELECT
+            subq_4.ds AS revenue_instance__ds__day
+          FROM ***************************.mf_time_spine subq_4
+          WHERE subq_4.ds BETWEEN '2020-03-05' AND '2021-01-04'
+        ) subq_3
+        INNER JOIN (
+          -- Constrain Time Range to [2020-01-05T00:00:00, 2021-01-04T00:00:00]
+          SELECT
+            subq_1.ds__day
+            , subq_1.ds__week
+            , subq_1.ds__month
+            , subq_1.ds__quarter
+            , subq_1.ds__year
+            , subq_1.ds__extract_year
+            , subq_1.ds__extract_quarter
+            , subq_1.ds__extract_month
+            , subq_1.ds__extract_day
+            , subq_1.ds__extract_dow
+            , subq_1.ds__extract_doy
+            , subq_1.revenue_instance__ds__day
+            , subq_1.revenue_instance__ds__week
+            , subq_1.revenue_instance__ds__month
+            , subq_1.revenue_instance__ds__quarter
+            , subq_1.revenue_instance__ds__year
+            , subq_1.revenue_instance__ds__extract_year
+            , subq_1.revenue_instance__ds__extract_quarter
+            , subq_1.revenue_instance__ds__extract_month
+            , subq_1.revenue_instance__ds__extract_day
+            , subq_1.revenue_instance__ds__extract_dow
+            , subq_1.revenue_instance__ds__extract_doy
+            , subq_1.metric_time__day
+            , subq_1.metric_time__week
+            , subq_1.metric_time__month
+            , subq_1.metric_time__quarter
+            , subq_1.metric_time__year
+            , subq_1.metric_time__extract_year
+            , subq_1.metric_time__extract_quarter
+            , subq_1.metric_time__extract_month
+            , subq_1.metric_time__extract_day
+            , subq_1.metric_time__extract_dow
+            , subq_1.metric_time__extract_doy
+            , subq_1.user
+            , subq_1.revenue_instance__user
+            , subq_1.txn_revenue
+          FROM (
+            -- Metric Time Dimension 'ds'
+            SELECT
+              subq_0.ds__day
+              , subq_0.ds__week
+              , subq_0.ds__month
+              , subq_0.ds__quarter
+              , subq_0.ds__year
+              , subq_0.ds__extract_year
+              , subq_0.ds__extract_quarter
+              , subq_0.ds__extract_month
+              , subq_0.ds__extract_day
+              , subq_0.ds__extract_dow
+              , subq_0.ds__extract_doy
+              , subq_0.revenue_instance__ds__day
+              , subq_0.revenue_instance__ds__week
+              , subq_0.revenue_instance__ds__month
+              , subq_0.revenue_instance__ds__quarter
+              , subq_0.revenue_instance__ds__year
+              , subq_0.revenue_instance__ds__extract_year
+              , subq_0.revenue_instance__ds__extract_quarter
+              , subq_0.revenue_instance__ds__extract_month
+              , subq_0.revenue_instance__ds__extract_day
+              , subq_0.revenue_instance__ds__extract_dow
+              , subq_0.revenue_instance__ds__extract_doy
+              , subq_0.ds__day AS metric_time__day
+              , subq_0.ds__week AS metric_time__week
+              , subq_0.ds__month AS metric_time__month
+              , subq_0.ds__quarter AS metric_time__quarter
+              , subq_0.ds__year AS metric_time__year
+              , subq_0.ds__extract_year AS metric_time__extract_year
+              , subq_0.ds__extract_quarter AS metric_time__extract_quarter
+              , subq_0.ds__extract_month AS metric_time__extract_month
+              , subq_0.ds__extract_day AS metric_time__extract_day
+              , subq_0.ds__extract_dow AS metric_time__extract_dow
+              , subq_0.ds__extract_doy AS metric_time__extract_doy
+              , subq_0.user
+              , subq_0.revenue_instance__user
+              , subq_0.txn_revenue
+            FROM (
+              -- Read Elements From Semantic Model 'revenue'
+              SELECT
+                revenue_src_10007.revenue AS txn_revenue
+                , DATE_TRUNC('day', revenue_src_10007.created_at) AS ds__day
+                , DATE_TRUNC('week', revenue_src_10007.created_at) AS ds__week
+                , DATE_TRUNC('month', revenue_src_10007.created_at) AS ds__month
+                , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS ds__quarter
+                , DATE_TRUNC('year', revenue_src_10007.created_at) AS ds__year
+                , EXTRACT(year FROM revenue_src_10007.created_at) AS ds__extract_year
+                , EXTRACT(quarter FROM revenue_src_10007.created_at) AS ds__extract_quarter
+                , EXTRACT(month FROM revenue_src_10007.created_at) AS ds__extract_month
+                , EXTRACT(day FROM revenue_src_10007.created_at) AS ds__extract_day
+                , EXTRACT(isodow FROM revenue_src_10007.created_at) AS ds__extract_dow
+                , EXTRACT(doy FROM revenue_src_10007.created_at) AS ds__extract_doy
+                , DATE_TRUNC('day', revenue_src_10007.created_at) AS revenue_instance__ds__day
+                , DATE_TRUNC('week', revenue_src_10007.created_at) AS revenue_instance__ds__week
+                , DATE_TRUNC('month', revenue_src_10007.created_at) AS revenue_instance__ds__month
+                , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS revenue_instance__ds__quarter
+                , DATE_TRUNC('year', revenue_src_10007.created_at) AS revenue_instance__ds__year
+                , EXTRACT(year FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_year
+                , EXTRACT(quarter FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_quarter
+                , EXTRACT(month FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_month
+                , EXTRACT(day FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_day
+                , EXTRACT(isodow FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_dow
+                , EXTRACT(doy FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_doy
+                , revenue_src_10007.user_id AS user
+                , revenue_src_10007.user_id AS revenue_instance__user
+              FROM ***************************.fct_revenue revenue_src_10007
+            ) subq_0
+          ) subq_1
+          WHERE subq_1.revenue_instance__ds__day BETWEEN '2020-01-05' AND '2021-01-04'
+        ) subq_2
+        ON
+          (
+            subq_2.revenue_instance__ds__day <= subq_3.revenue_instance__ds__day
+          ) AND (
+            subq_2.revenue_instance__ds__day > subq_3.revenue_instance__ds__day - INTERVAL 2 month
+          )
+      ) subq_5
+    ) subq_6
+    WHERE subq_6.revenue_instance__ds__day BETWEEN '2020-03-05' AND '2021-01-04'
+  ) subq_7
+  GROUP BY
+    subq_7.revenue_instance__ds__day
+) subq_8
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql
new file mode 100644
index 0000000000..09a0aa5184
--- /dev/null
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql
@@ -0,0 +1,34 @@
+-- Join Self Over Time Range
+-- Pass Only Elements: ['txn_revenue', 'revenue_instance__ds__day']
+-- Constrain Time Range to [2020-03-05T00:00:00, 2021-01-04T00:00:00]
+-- Aggregate Measures
+-- Compute Metrics via Expressions
+SELECT
+  subq_12.revenue_instance__ds__day AS revenue_instance__ds__day
+  , SUM(subq_11.txn_revenue) AS trailing_2_months_revenue
+FROM (
+  -- Time Spine
+  SELECT
+    ds AS revenue_instance__ds__day
+  FROM ***************************.mf_time_spine subq_13
+  WHERE ds BETWEEN '2020-03-05' AND '2021-01-04'
+) subq_12
+INNER JOIN (
+  -- Read Elements From Semantic Model 'revenue'
+  -- Metric Time Dimension 'ds'
+  -- Constrain Time Range to [2020-01-05T00:00:00, 2021-01-04T00:00:00]
+  SELECT
+    DATE_TRUNC('day', created_at) AS revenue_instance__ds__day
+    , revenue AS txn_revenue
+  FROM ***************************.fct_revenue revenue_src_10007
+  WHERE DATE_TRUNC('day', created_at) BETWEEN '2020-01-05' AND '2021-01-04'
+) subq_11
+ON
+  (
+    subq_11.revenue_instance__ds__day <= subq_12.revenue_instance__ds__day
+  ) AND (
+    subq_11.revenue_instance__ds__day > subq_12.revenue_instance__ds__day - INTERVAL 2 month
+  )
+WHERE subq_12.revenue_instance__ds__day BETWEEN '2020-03-05' AND '2021-01-04'
+GROUP BY
+  subq_12.revenue_instance__ds__day

From cf88ff620adbdc4a895da84a2e140639243a3328 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 16:35:39 -0800
Subject: [PATCH 15/22] Undo

---
 .../query_rendering/test_cumulative_metric_rendering.py   | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
index 873cf79ea8..d6de8292cc 100644
--- a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
@@ -208,7 +208,13 @@ def test_cumulative_metric_no_window_with_time_constraint(
         MetricFlowQuerySpec(
             metric_specs=(MetricSpec(element_name="revenue_all_time"),),
             dimension_specs=(),
-            time_dimension_specs=(MTD_SPEC_MONTH,),
+            time_dimension_specs=(
+                TimeDimensionSpec(
+                    element_name="ds",
+                    entity_links=(),
+                    time_granularity=TimeGranularity.MONTH,
+                ),
+            ),
             time_range_constraint=TimeRangeConstraint(
                 start_time=as_datetime("2020-01-01"), end_time=as_datetime("2020-01-01")
             ),

From 8ea457828ff6cde3160299b6c3d88449dcc6fad7 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 16:47:22 -0800
Subject: [PATCH 16/22] Finish

---
 .../dataflow/builder/dataflow_plan_builder.py |  77 ++---
 metricflow/plan_conversion/dataflow_to_sql.py |   2 +-
 .../test_cases/itest_cumulative_metric.yaml   |   2 +-
 .../test_cumulative_metric_rendering.py       |   3 -
 ..._metric_with_agg_time_dimension__plan0.sql | 301 ++++++++----------
 ...th_agg_time_dimension__plan0_optimized.sql |  32 +-
 6 files changed, 168 insertions(+), 249 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index de2458cd6a..e7d7e41bbe 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -796,9 +796,7 @@ def _build_measure_spec_properties(self, measure_specs: Sequence[MeasureSpec]) -
                 f"semantic models: {semantic_models}. This suggests the measure_specs were not correctly filtered."
             )
 
-        agg_time_dimension = agg_time_dimension = self._semantic_model_lookup.get_agg_time_dimension_for_measure(
-            measure_specs[0].reference
-        )
+        agg_time_dimension = self._semantic_model_lookup.get_agg_time_dimension_for_measure(measure_specs[0].reference)
         non_additive_dimension_spec = measure_specs[0].non_additive_dimension_spec
         for measure_spec in measure_specs:
             if non_additive_dimension_spec != measure_spec.non_additive_dimension_spec:
@@ -1322,47 +1320,38 @@ def _build_aggregated_measure_from_measure_source_node(
                 f"Recipe not found for measure spec: {measure_spec} and linkable specs: {required_linkable_specs}"
             )
 
+        queried_agg_time_dimension_specs = list(queried_linkable_specs.metric_time_specs)
+        if not queried_agg_time_dimension_specs:
+            valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
+                measure_spec.reference
+            )
+            queried_agg_time_dimension_specs = list(
+                set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
+            )
+
         # If a cumulative metric is queried with agg_time_dimension, join over time range.
         # Otherwise, the measure will be aggregated over all time.
         time_range_node: Optional[JoinOverTimeRangeNode] = None
-        if cumulative:
-            queried_metric_time_spec = queried_linkable_specs.metric_time_spec_with_smallest_granularity
-            if not queried_metric_time_spec:
-                valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
-                    measure_spec.reference
-                )
-                # TODO: will it be a problem if we get one with date part or diff granularity? Write test case
-                queried_agg_time_dims = sorted(
-                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions)),
-                    key=lambda x: x.time_granularity.to_int(),
-                )
-                if queried_agg_time_dims:
-                    queried_metric_time_spec = queried_agg_time_dims[0]
-
-            if queried_metric_time_spec:
-                time_range_node = JoinOverTimeRangeNode(
-                    parent_node=measure_recipe.source_node,
-                    metric_time_dimension_spec=queried_metric_time_spec,
-                    window=cumulative_window,
-                    grain_to_date=cumulative_grain_to_date,
-                    time_range_constraint=time_range_constraint
-                    if not before_aggregation_time_spine_join_description
-                    else None,
-                )
+        if cumulative and queried_agg_time_dimension_specs:
+            # TODO: will it be a problem if we get one with date part or diff granularity? Write test case to confirm
+            # Use the time dimension spec with the smallest granularity.
+            agg_time_dimension_spec_for_join = sorted(
+                queried_agg_time_dimension_specs, key=lambda spec: spec.time_granularity.to_int()
+            )[0]
+            time_range_node = JoinOverTimeRangeNode(
+                parent_node=measure_recipe.source_node,
+                # TODO: rename param
+                metric_time_dimension_spec=agg_time_dimension_spec_for_join,
+                window=cumulative_window,
+                grain_to_date=cumulative_grain_to_date,
+                time_range_constraint=time_range_constraint
+                if not before_aggregation_time_spine_join_description
+                else None,
+            )
 
         # If querying an offset metric, join to time spine before aggregation.
         join_to_time_spine_node: Optional[JoinToTimeSpineNode] = None
         if before_aggregation_time_spine_join_description is not None:
-            # TODO: below logic is somewhat duplicated
-            queried_agg_time_dimension_specs = list(queried_linkable_specs.metric_time_specs)
-            if not queried_agg_time_dimension_specs:
-                valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
-                    measure_spec.reference
-                )
-                queried_agg_time_dimension_specs = list(
-                    set(queried_linkable_specs.time_dimension_specs).intersection(set(valid_agg_time_dimensions))
-                )
-
             assert queried_agg_time_dimension_specs, (
                 "Joining to time spine requires querying with metric time or the appropriate agg_time_dimension."
                 "This should have been caught by validations."
@@ -1408,19 +1397,17 @@ def _build_aggregated_measure_from_measure_source_node(
         else:
             unaggregated_measure_node = filtered_measure_source_node
 
-        query_contains_metric_time_or_agg_time_dimension = queried_linkable_specs.contains_metric_time
-        if not query_contains_metric_time_or_agg_time_dimension:
-            pass  # check for agg_time_dimension and update accordingly
-            # Write a test case for this scenario
-
+        # If time constraint was previously adjusted for cumulative window or grain, apply original time constraint
+        # here. Can skip if metric is being aggregated over all time.
         cumulative_metric_constrained_node: Optional[ConstrainTimeRangeNode] = None
         if (
             cumulative_metric_adjusted_time_constraint is not None
             and time_range_constraint is not None
-            and query_contains_metric_time_or_agg_time_dimension
+            and queried_agg_time_dimension_specs
         ):
             cumulative_metric_constrained_node = ConstrainTimeRangeNode(
-                unaggregated_measure_node, time_range_constraint
+                parent_node=unaggregated_measure_node,
+                time_range_constraint=time_range_constraint,
             )
 
         pre_aggregate_node: BaseOutput = cumulative_metric_constrained_node or unaggregated_measure_node
@@ -1439,7 +1426,7 @@ def _build_aggregated_measure_from_measure_source_node(
             queried_time_dimension_spec: Optional[
                 TimeDimensionSpec
             ] = self._find_non_additive_dimension_in_linkable_specs(
-                agg_time_dimension=agg_time_dimension,
+                agg_time_dimension=TimeDimensionReference(agg_time_dimension.element_name),
                 linkable_specs=queried_linkable_specs.as_tuple,
                 non_additive_dimension_spec=non_additive_dimension_spec,
             )
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index dca49699a9..607a4e277d 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -958,7 +958,7 @@ def visit_constrain_time_range_node(self, node: ConstrainTimeRangeNode) -> SqlDa
 
         instead of this: DATE_TRUNC('month', ds) >= '2020-01-01' AND DATE_TRUNC('month', ds <= '2020-02-01')
         """
-        from_data_set: SqlDataSet = node.parent_node.accept(self)
+        from_data_set = node.parent_node.accept(self)
         from_data_set_alias = self._next_unique_table_alias()
 
         time_dimension_instances_for_metric_time = sorted(
diff --git a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
index 17b9927073..a854eb2846 100644
--- a/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
+++ b/metricflow/test/integration/test_cases/itest_cumulative_metric.yaml
@@ -392,7 +392,7 @@ integration_test:
   metrics: ["trailing_2_months_revenue"]
   group_bys: ["revenue_instance__ds__day"]
   order_bys: ["revenue_instance__ds__day"]
-  time_constraint: ["2020-03-05", "2021-01-04"]
+  where_filter: '{{ render_time_constraint("revenue_instance__ds__day", "2020-03-05", "2021-01-04") }}'
   check_query: |
     SELECT
       SUM(b.txn_revenue) as trailing_2_months_revenue
diff --git a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
index d6de8292cc..52dd131c20 100644
--- a/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
+++ b/metricflow/test/query_rendering/test_cumulative_metric_rendering.py
@@ -310,9 +310,6 @@ def test_cumulative_metric_with_agg_time_dimension(
             time_dimension_specs=(
                 TimeDimensionSpec(element_name="ds", entity_links=(EntityReference("revenue_instance"),)),
             ),
-            time_range_constraint=TimeRangeConstraint(
-                start_time=as_datetime("2020-03-05"), end_time=as_datetime("2021-01-04")
-            ),
         )
     )
 
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
index 24daa015d5..2d7d48e429 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0.sql
@@ -1,189 +1,140 @@
 -- Compute Metrics via Expressions
 SELECT
-  subq_8.revenue_instance__ds__day
-  , subq_8.txn_revenue AS trailing_2_months_revenue
+  subq_6.revenue_instance__ds__day
+  , subq_6.txn_revenue AS trailing_2_months_revenue
 FROM (
   -- Aggregate Measures
   SELECT
-    subq_7.revenue_instance__ds__day
-    , SUM(subq_7.txn_revenue) AS txn_revenue
+    subq_5.revenue_instance__ds__day
+    , SUM(subq_5.txn_revenue) AS txn_revenue
   FROM (
-    -- Constrain Time Range to [2020-03-05T00:00:00, 2021-01-04T00:00:00]
+    -- Pass Only Elements: ['txn_revenue', 'revenue_instance__ds__day']
     SELECT
-      subq_6.revenue_instance__ds__day
-      , subq_6.txn_revenue
+      subq_4.revenue_instance__ds__day
+      , subq_4.txn_revenue
     FROM (
-      -- Pass Only Elements: ['txn_revenue', 'revenue_instance__ds__day']
+      -- Join Self Over Time Range
       SELECT
-        subq_5.revenue_instance__ds__day
-        , subq_5.txn_revenue
+        subq_2.revenue_instance__ds__day AS revenue_instance__ds__day
+        , subq_1.ds__day AS ds__day
+        , subq_1.ds__week AS ds__week
+        , subq_1.ds__month AS ds__month
+        , subq_1.ds__quarter AS ds__quarter
+        , subq_1.ds__year AS ds__year
+        , subq_1.ds__extract_year AS ds__extract_year
+        , subq_1.ds__extract_quarter AS ds__extract_quarter
+        , subq_1.ds__extract_month AS ds__extract_month
+        , subq_1.ds__extract_day AS ds__extract_day
+        , subq_1.ds__extract_dow AS ds__extract_dow
+        , subq_1.ds__extract_doy AS ds__extract_doy
+        , subq_1.revenue_instance__ds__week AS revenue_instance__ds__week
+        , subq_1.revenue_instance__ds__month AS revenue_instance__ds__month
+        , subq_1.revenue_instance__ds__quarter AS revenue_instance__ds__quarter
+        , subq_1.revenue_instance__ds__year AS revenue_instance__ds__year
+        , subq_1.revenue_instance__ds__extract_year AS revenue_instance__ds__extract_year
+        , subq_1.revenue_instance__ds__extract_quarter AS revenue_instance__ds__extract_quarter
+        , subq_1.revenue_instance__ds__extract_month AS revenue_instance__ds__extract_month
+        , subq_1.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day
+        , subq_1.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow
+        , subq_1.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy
+        , subq_1.metric_time__day AS metric_time__day
+        , subq_1.metric_time__week AS metric_time__week
+        , subq_1.metric_time__month AS metric_time__month
+        , subq_1.metric_time__quarter AS metric_time__quarter
+        , subq_1.metric_time__year AS metric_time__year
+        , subq_1.metric_time__extract_year AS metric_time__extract_year
+        , subq_1.metric_time__extract_quarter AS metric_time__extract_quarter
+        , subq_1.metric_time__extract_month AS metric_time__extract_month
+        , subq_1.metric_time__extract_day AS metric_time__extract_day
+        , subq_1.metric_time__extract_dow AS metric_time__extract_dow
+        , subq_1.metric_time__extract_doy AS metric_time__extract_doy
+        , subq_1.user AS user
+        , subq_1.revenue_instance__user AS revenue_instance__user
+        , subq_1.txn_revenue AS txn_revenue
       FROM (
-        -- Join Self Over Time Range
+        -- Time Spine
         SELECT
-          subq_3.revenue_instance__ds__day AS revenue_instance__ds__day
-          , subq_2.ds__day AS ds__day
-          , subq_2.ds__week AS ds__week
-          , subq_2.ds__month AS ds__month
-          , subq_2.ds__quarter AS ds__quarter
-          , subq_2.ds__year AS ds__year
-          , subq_2.ds__extract_year AS ds__extract_year
-          , subq_2.ds__extract_quarter AS ds__extract_quarter
-          , subq_2.ds__extract_month AS ds__extract_month
-          , subq_2.ds__extract_day AS ds__extract_day
-          , subq_2.ds__extract_dow AS ds__extract_dow
-          , subq_2.ds__extract_doy AS ds__extract_doy
-          , subq_2.revenue_instance__ds__week AS revenue_instance__ds__week
-          , subq_2.revenue_instance__ds__month AS revenue_instance__ds__month
-          , subq_2.revenue_instance__ds__quarter AS revenue_instance__ds__quarter
-          , subq_2.revenue_instance__ds__year AS revenue_instance__ds__year
-          , subq_2.revenue_instance__ds__extract_year AS revenue_instance__ds__extract_year
-          , subq_2.revenue_instance__ds__extract_quarter AS revenue_instance__ds__extract_quarter
-          , subq_2.revenue_instance__ds__extract_month AS revenue_instance__ds__extract_month
-          , subq_2.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day
-          , subq_2.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow
-          , subq_2.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy
-          , subq_2.metric_time__day AS metric_time__day
-          , subq_2.metric_time__week AS metric_time__week
-          , subq_2.metric_time__month AS metric_time__month
-          , subq_2.metric_time__quarter AS metric_time__quarter
-          , subq_2.metric_time__year AS metric_time__year
-          , subq_2.metric_time__extract_year AS metric_time__extract_year
-          , subq_2.metric_time__extract_quarter AS metric_time__extract_quarter
-          , subq_2.metric_time__extract_month AS metric_time__extract_month
-          , subq_2.metric_time__extract_day AS metric_time__extract_day
-          , subq_2.metric_time__extract_dow AS metric_time__extract_dow
-          , subq_2.metric_time__extract_doy AS metric_time__extract_doy
-          , subq_2.user AS user
-          , subq_2.revenue_instance__user AS revenue_instance__user
-          , subq_2.txn_revenue AS txn_revenue
+          subq_3.ds AS revenue_instance__ds__day
+        FROM ***************************.mf_time_spine subq_3
+      ) subq_2
+      INNER JOIN (
+        -- Metric Time Dimension 'ds'
+        SELECT
+          subq_0.ds__day
+          , subq_0.ds__week
+          , subq_0.ds__month
+          , subq_0.ds__quarter
+          , subq_0.ds__year
+          , subq_0.ds__extract_year
+          , subq_0.ds__extract_quarter
+          , subq_0.ds__extract_month
+          , subq_0.ds__extract_day
+          , subq_0.ds__extract_dow
+          , subq_0.ds__extract_doy
+          , subq_0.revenue_instance__ds__day
+          , subq_0.revenue_instance__ds__week
+          , subq_0.revenue_instance__ds__month
+          , subq_0.revenue_instance__ds__quarter
+          , subq_0.revenue_instance__ds__year
+          , subq_0.revenue_instance__ds__extract_year
+          , subq_0.revenue_instance__ds__extract_quarter
+          , subq_0.revenue_instance__ds__extract_month
+          , subq_0.revenue_instance__ds__extract_day
+          , subq_0.revenue_instance__ds__extract_dow
+          , subq_0.revenue_instance__ds__extract_doy
+          , subq_0.ds__day AS metric_time__day
+          , subq_0.ds__week AS metric_time__week
+          , subq_0.ds__month AS metric_time__month
+          , subq_0.ds__quarter AS metric_time__quarter
+          , subq_0.ds__year AS metric_time__year
+          , subq_0.ds__extract_year AS metric_time__extract_year
+          , subq_0.ds__extract_quarter AS metric_time__extract_quarter
+          , subq_0.ds__extract_month AS metric_time__extract_month
+          , subq_0.ds__extract_day AS metric_time__extract_day
+          , subq_0.ds__extract_dow AS metric_time__extract_dow
+          , subq_0.ds__extract_doy AS metric_time__extract_doy
+          , subq_0.user
+          , subq_0.revenue_instance__user
+          , subq_0.txn_revenue
         FROM (
-          -- Time Spine
-          SELECT
-            subq_4.ds AS revenue_instance__ds__day
-          FROM ***************************.mf_time_spine subq_4
-          WHERE subq_4.ds BETWEEN '2020-03-05' AND '2021-01-04'
-        ) subq_3
-        INNER JOIN (
-          -- Constrain Time Range to [2020-01-05T00:00:00, 2021-01-04T00:00:00]
+          -- Read Elements From Semantic Model 'revenue'
           SELECT
-            subq_1.ds__day
-            , subq_1.ds__week
-            , subq_1.ds__month
-            , subq_1.ds__quarter
-            , subq_1.ds__year
-            , subq_1.ds__extract_year
-            , subq_1.ds__extract_quarter
-            , subq_1.ds__extract_month
-            , subq_1.ds__extract_day
-            , subq_1.ds__extract_dow
-            , subq_1.ds__extract_doy
-            , subq_1.revenue_instance__ds__day
-            , subq_1.revenue_instance__ds__week
-            , subq_1.revenue_instance__ds__month
-            , subq_1.revenue_instance__ds__quarter
-            , subq_1.revenue_instance__ds__year
-            , subq_1.revenue_instance__ds__extract_year
-            , subq_1.revenue_instance__ds__extract_quarter
-            , subq_1.revenue_instance__ds__extract_month
-            , subq_1.revenue_instance__ds__extract_day
-            , subq_1.revenue_instance__ds__extract_dow
-            , subq_1.revenue_instance__ds__extract_doy
-            , subq_1.metric_time__day
-            , subq_1.metric_time__week
-            , subq_1.metric_time__month
-            , subq_1.metric_time__quarter
-            , subq_1.metric_time__year
-            , subq_1.metric_time__extract_year
-            , subq_1.metric_time__extract_quarter
-            , subq_1.metric_time__extract_month
-            , subq_1.metric_time__extract_day
-            , subq_1.metric_time__extract_dow
-            , subq_1.metric_time__extract_doy
-            , subq_1.user
-            , subq_1.revenue_instance__user
-            , subq_1.txn_revenue
-          FROM (
-            -- Metric Time Dimension 'ds'
-            SELECT
-              subq_0.ds__day
-              , subq_0.ds__week
-              , subq_0.ds__month
-              , subq_0.ds__quarter
-              , subq_0.ds__year
-              , subq_0.ds__extract_year
-              , subq_0.ds__extract_quarter
-              , subq_0.ds__extract_month
-              , subq_0.ds__extract_day
-              , subq_0.ds__extract_dow
-              , subq_0.ds__extract_doy
-              , subq_0.revenue_instance__ds__day
-              , subq_0.revenue_instance__ds__week
-              , subq_0.revenue_instance__ds__month
-              , subq_0.revenue_instance__ds__quarter
-              , subq_0.revenue_instance__ds__year
-              , subq_0.revenue_instance__ds__extract_year
-              , subq_0.revenue_instance__ds__extract_quarter
-              , subq_0.revenue_instance__ds__extract_month
-              , subq_0.revenue_instance__ds__extract_day
-              , subq_0.revenue_instance__ds__extract_dow
-              , subq_0.revenue_instance__ds__extract_doy
-              , subq_0.ds__day AS metric_time__day
-              , subq_0.ds__week AS metric_time__week
-              , subq_0.ds__month AS metric_time__month
-              , subq_0.ds__quarter AS metric_time__quarter
-              , subq_0.ds__year AS metric_time__year
-              , subq_0.ds__extract_year AS metric_time__extract_year
-              , subq_0.ds__extract_quarter AS metric_time__extract_quarter
-              , subq_0.ds__extract_month AS metric_time__extract_month
-              , subq_0.ds__extract_day AS metric_time__extract_day
-              , subq_0.ds__extract_dow AS metric_time__extract_dow
-              , subq_0.ds__extract_doy AS metric_time__extract_doy
-              , subq_0.user
-              , subq_0.revenue_instance__user
-              , subq_0.txn_revenue
-            FROM (
-              -- Read Elements From Semantic Model 'revenue'
-              SELECT
-                revenue_src_10007.revenue AS txn_revenue
-                , DATE_TRUNC('day', revenue_src_10007.created_at) AS ds__day
-                , DATE_TRUNC('week', revenue_src_10007.created_at) AS ds__week
-                , DATE_TRUNC('month', revenue_src_10007.created_at) AS ds__month
-                , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS ds__quarter
-                , DATE_TRUNC('year', revenue_src_10007.created_at) AS ds__year
-                , EXTRACT(year FROM revenue_src_10007.created_at) AS ds__extract_year
-                , EXTRACT(quarter FROM revenue_src_10007.created_at) AS ds__extract_quarter
-                , EXTRACT(month FROM revenue_src_10007.created_at) AS ds__extract_month
-                , EXTRACT(day FROM revenue_src_10007.created_at) AS ds__extract_day
-                , EXTRACT(isodow FROM revenue_src_10007.created_at) AS ds__extract_dow
-                , EXTRACT(doy FROM revenue_src_10007.created_at) AS ds__extract_doy
-                , DATE_TRUNC('day', revenue_src_10007.created_at) AS revenue_instance__ds__day
-                , DATE_TRUNC('week', revenue_src_10007.created_at) AS revenue_instance__ds__week
-                , DATE_TRUNC('month', revenue_src_10007.created_at) AS revenue_instance__ds__month
-                , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS revenue_instance__ds__quarter
-                , DATE_TRUNC('year', revenue_src_10007.created_at) AS revenue_instance__ds__year
-                , EXTRACT(year FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_year
-                , EXTRACT(quarter FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_quarter
-                , EXTRACT(month FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_month
-                , EXTRACT(day FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_day
-                , EXTRACT(isodow FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_dow
-                , EXTRACT(doy FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_doy
-                , revenue_src_10007.user_id AS user
-                , revenue_src_10007.user_id AS revenue_instance__user
-              FROM ***************************.fct_revenue revenue_src_10007
-            ) subq_0
-          ) subq_1
-          WHERE subq_1.revenue_instance__ds__day BETWEEN '2020-01-05' AND '2021-01-04'
-        ) subq_2
-        ON
-          (
-            subq_2.revenue_instance__ds__day <= subq_3.revenue_instance__ds__day
-          ) AND (
-            subq_2.revenue_instance__ds__day > subq_3.revenue_instance__ds__day - INTERVAL 2 month
-          )
-      ) subq_5
-    ) subq_6
-    WHERE subq_6.revenue_instance__ds__day BETWEEN '2020-03-05' AND '2021-01-04'
-  ) subq_7
+            revenue_src_10007.revenue AS txn_revenue
+            , DATE_TRUNC('day', revenue_src_10007.created_at) AS ds__day
+            , DATE_TRUNC('week', revenue_src_10007.created_at) AS ds__week
+            , DATE_TRUNC('month', revenue_src_10007.created_at) AS ds__month
+            , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS ds__quarter
+            , DATE_TRUNC('year', revenue_src_10007.created_at) AS ds__year
+            , EXTRACT(year FROM revenue_src_10007.created_at) AS ds__extract_year
+            , EXTRACT(quarter FROM revenue_src_10007.created_at) AS ds__extract_quarter
+            , EXTRACT(month FROM revenue_src_10007.created_at) AS ds__extract_month
+            , EXTRACT(day FROM revenue_src_10007.created_at) AS ds__extract_day
+            , EXTRACT(isodow FROM revenue_src_10007.created_at) AS ds__extract_dow
+            , EXTRACT(doy FROM revenue_src_10007.created_at) AS ds__extract_doy
+            , DATE_TRUNC('day', revenue_src_10007.created_at) AS revenue_instance__ds__day
+            , DATE_TRUNC('week', revenue_src_10007.created_at) AS revenue_instance__ds__week
+            , DATE_TRUNC('month', revenue_src_10007.created_at) AS revenue_instance__ds__month
+            , DATE_TRUNC('quarter', revenue_src_10007.created_at) AS revenue_instance__ds__quarter
+            , DATE_TRUNC('year', revenue_src_10007.created_at) AS revenue_instance__ds__year
+            , EXTRACT(year FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_year
+            , EXTRACT(quarter FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_quarter
+            , EXTRACT(month FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_month
+            , EXTRACT(day FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_day
+            , EXTRACT(isodow FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_dow
+            , EXTRACT(doy FROM revenue_src_10007.created_at) AS revenue_instance__ds__extract_doy
+            , revenue_src_10007.user_id AS user
+            , revenue_src_10007.user_id AS revenue_instance__user
+          FROM ***************************.fct_revenue revenue_src_10007
+        ) subq_0
+      ) subq_1
+      ON
+        (
+          subq_1.revenue_instance__ds__day <= subq_2.revenue_instance__ds__day
+        ) AND (
+          subq_1.revenue_instance__ds__day > subq_2.revenue_instance__ds__day - INTERVAL 2 month
+        )
+    ) subq_4
+  ) subq_5
   GROUP BY
-    subq_7.revenue_instance__ds__day
-) subq_8
+    subq_5.revenue_instance__ds__day
+) subq_6
diff --git a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql
index 09a0aa5184..80e5ab0f65 100644
--- a/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql
+++ b/metricflow/test/snapshots/test_cumulative_metric_rendering.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_agg_time_dimension__plan0_optimized.sql
@@ -1,34 +1,18 @@
 -- Join Self Over Time Range
 -- Pass Only Elements: ['txn_revenue', 'revenue_instance__ds__day']
--- Constrain Time Range to [2020-03-05T00:00:00, 2021-01-04T00:00:00]
 -- Aggregate Measures
 -- Compute Metrics via Expressions
 SELECT
-  subq_12.revenue_instance__ds__day AS revenue_instance__ds__day
-  , SUM(subq_11.txn_revenue) AS trailing_2_months_revenue
-FROM (
-  -- Time Spine
-  SELECT
-    ds AS revenue_instance__ds__day
-  FROM ***************************.mf_time_spine subq_13
-  WHERE ds BETWEEN '2020-03-05' AND '2021-01-04'
-) subq_12
-INNER JOIN (
-  -- Read Elements From Semantic Model 'revenue'
-  -- Metric Time Dimension 'ds'
-  -- Constrain Time Range to [2020-01-05T00:00:00, 2021-01-04T00:00:00]
-  SELECT
-    DATE_TRUNC('day', created_at) AS revenue_instance__ds__day
-    , revenue AS txn_revenue
-  FROM ***************************.fct_revenue revenue_src_10007
-  WHERE DATE_TRUNC('day', created_at) BETWEEN '2020-01-05' AND '2021-01-04'
-) subq_11
+  subq_10.ds AS revenue_instance__ds__day
+  , SUM(revenue_src_10007.revenue) AS trailing_2_months_revenue
+FROM ***************************.mf_time_spine subq_10
+INNER JOIN
+  ***************************.fct_revenue revenue_src_10007
 ON
   (
-    subq_11.revenue_instance__ds__day <= subq_12.revenue_instance__ds__day
+    DATE_TRUNC('day', revenue_src_10007.created_at) <= subq_10.ds
   ) AND (
-    subq_11.revenue_instance__ds__day > subq_12.revenue_instance__ds__day - INTERVAL 2 month
+    DATE_TRUNC('day', revenue_src_10007.created_at) > subq_10.ds - INTERVAL 2 month
   )
-WHERE subq_12.revenue_instance__ds__day BETWEEN '2020-03-05' AND '2021-01-04'
 GROUP BY
-  subq_12.revenue_instance__ds__day
+  subq_10.ds

From a24700e432a9135916047d2dacbe9eb1bb31c6ef Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 16:51:32 -0800
Subject: [PATCH 17/22] Add nested test case

---
 .../dataflow/builder/dataflow_plan_builder.py |  1 -
 .../integration/test_cases/itest_metrics.yaml | 35 +++++++++++++++++++
 2 files changed, 35 insertions(+), 1 deletion(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index e7d7e41bbe..6a2cfe6369 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -499,7 +499,6 @@ def _build_derived_metric_output_node(
         )
         output_node: BaseOutput = ComputeMetricsNode(parent_node=parent_node, metric_specs=[metric_spec])
 
-        # TODO: Write a test case for this scenario
         # For nested ratio / derived metrics with time offset, apply offset & where constraint after metric computation.
         if metric_spec.has_time_offset:
             queried_agg_time_dimension_specs = list(queried_linkable_specs.metric_time_specs)
diff --git a/metricflow/test/integration/test_cases/itest_metrics.yaml b/metricflow/test/integration/test_cases/itest_metrics.yaml
index b874fc104c..14cd01a667 100644
--- a/metricflow/test/integration/test_cases/itest_metrics.yaml
+++ b/metricflow/test/integration/test_cases/itest_metrics.yaml
@@ -1813,5 +1813,40 @@ integration_test:
       ON {{ render_date_trunc("c.ds", TimeGranularity.MONTH) }} = d.booking__ds__day
     ) b
     ON a.booking__ds__day = b.booking__ds__day
+---
+integration_test:
+  name: nested_derived_metric_outer_offset_with_agg_time_dimension
+  description: Tests a nested derived metric where the outer metric has an input metric with offset_window, queried with agg_time_dimension.
+  model: SIMPLE_MODEL
+  metrics: ["bookings_offset_twice"]
+  group_by_objs: [{"name": "booking__ds__day"}]
+  check_query: |
+    SELECT
+      subq_9.ds AS booking__ds__day
+      , 2 * bookings_offset_once AS bookings_offset_twice
+    FROM {{ source_schema }}.mf_time_spine subq_9
+    INNER JOIN (
+      SELECT
+        booking__ds__day
+        , 2 * bookings AS bookings_offset_once
+      FROM (
+        SELECT
+          subq_3.ds AS booking__ds__day
+          , SUM(subq_1.bookings) AS bookings
+        FROM {{ source_schema }}.mf_time_spine subq_3
+        INNER JOIN (
+          SELECT
+            {{ render_date_trunc("ds", TimeGranularity.DAY) }} AS booking__ds__day
+            , 1 AS bookings
+          FROM {{ source_schema }}.fct_bookings bookings_source_src_1
+        ) subq_1
+        ON
+          {{ render_date_sub("subq_3", "ds", 5, TimeGranularity.DAY) }} = subq_1.booking__ds__day
+        GROUP BY
+          subq_3.ds
+      ) subq_7
+    ) subq_8
+    ON
+      {{ render_date_sub("subq_9", "ds", 2, TimeGranularity.DAY) }} = subq_8.booking__ds__day
 # TODO: offset tests with granularity, date part, multiple metric time / agg time options
 # TODO: cumulative tests with multiple metric_time / agg time options

From 2ff2eb1dface34183f356bc393c2ca9e3d912a06 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 17:08:16 -0800
Subject: [PATCH 18/22] Add another test case

---
 .../dataflow/builder/dataflow_plan_builder.py |  3 +--
 metricflow/plan_conversion/dataflow_to_sql.py |  2 +-
 .../integration/test_cases/itest_metrics.yaml | 20 +++++++++++++++++++
 3 files changed, 22 insertions(+), 3 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 6a2cfe6369..d5828048b5 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -1115,7 +1115,6 @@ def _build_input_measure_spec_for_base_metric(
         # there's no need to join to the time spine since all time will be aggregated.
         after_aggregation_time_spine_join_description = None
         if input_measure.join_to_timespine:
-            # TODO: Write a test case for this scenario
             query_contains_agg_time_dimension = queried_linkable_specs.contains_metric_time
             if not query_contains_agg_time_dimension:
                 # TODO: should this be checking valid agg time dims for measure or metric?
@@ -1468,7 +1467,7 @@ def _build_aggregated_measure_from_measure_source_node(
             )
             return JoinToTimeSpineNode(
                 parent_node=aggregate_measures_node,
-                requested_metric_time_dimension_specs=list(queried_linkable_specs.metric_time_specs),
+                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
                 join_type=after_aggregation_time_spine_join_description.join_type,
                 time_range_constraint=time_range_constraint,
                 offset_window=after_aggregation_time_spine_join_description.offset_window,
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 607a4e277d..83487278a1 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -1243,7 +1243,7 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         # TODO: rename requested_metric_time_dimension_specs -> requested_agg_time_dimension_specs
         assert (
             len(node.requested_metric_time_dimension_specs) > 0
-        ), "Must have at least one  value in requested_metric_time_dimension_specs for JoinToTimeSpineNode."
+        ), "Must have at least one value in requested_metric_time_dimension_specs for JoinToTimeSpineNode."
 
         # Determine if the time spine join should use metric_time or the agg_time_dimension (metric_time takes priority).
         agg_time_dimension_for_join = node.requested_metric_time_dimension_specs[0]
diff --git a/metricflow/test/integration/test_cases/itest_metrics.yaml b/metricflow/test/integration/test_cases/itest_metrics.yaml
index 14cd01a667..7424477d05 100644
--- a/metricflow/test/integration/test_cases/itest_metrics.yaml
+++ b/metricflow/test/integration/test_cases/itest_metrics.yaml
@@ -1180,6 +1180,26 @@ integration_test:
     ) subq_3
     ON subq_4.metric_time__month = subq_3.metric_time__month
 ---
+integration_test:
+  name: simple_fill_nulls_with_0_agg_time_dim
+  description: Test a simple query that joins to time spine and fills nulls, with agg_time_dimension
+  model: SIMPLE_MODEL
+  metrics: ["bookings_fill_nulls_with_0"]
+  group_by_objs: [{"name": "booking__ds__day"}]
+  check_query: |
+    SELECT
+      subq_5.ds AS booking__ds__day
+      , COALESCE(subq_3.bookings, 0) AS bookings_fill_nulls_with_0
+    FROM {{ source_schema }}.mf_time_spine subq_5
+    LEFT OUTER JOIN (
+      SELECT
+        {{ render_date_trunc("ds", TimeGranularity.DAY) }} AS booking__ds__day
+        , SUM(1) AS bookings
+      FROM {{ source_schema }}.fct_bookings bookings_source_src_1
+      GROUP BY 1
+    ) subq_3
+    ON subq_5.ds = subq_3.booking__ds__day
+---
 integration_test:
   name: simple_fill_nulls_with_0_with_non_metric_time
   description: Test simple query that fills nulls but doesn't join to time spine (non-metric time dimension)

From feae64d87d6dc4cd24f9e3391f059dd7969151ae Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 17:11:46 -0800
Subject: [PATCH 19/22] Rename param

---
 metricflow/dataflow/builder/dataflow_plan_builder.py | 4 +---
 metricflow/dataflow/dataflow_plan.py                 | 8 ++++----
 metricflow/plan_conversion/dataflow_to_sql.py        | 2 +-
 3 files changed, 6 insertions(+), 8 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index d5828048b5..1550fc5b87 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -1117,7 +1117,6 @@ def _build_input_measure_spec_for_base_metric(
         if input_measure.join_to_timespine:
             query_contains_agg_time_dimension = queried_linkable_specs.contains_metric_time
             if not query_contains_agg_time_dimension:
-                # TODO: should this be checking valid agg time dims for measure or metric?
                 valid_agg_time_dimensions = self._semantic_model_lookup.get_agg_time_dimension_specs_for_measure(
                     measure_spec.reference
                 )
@@ -1338,8 +1337,7 @@ def _build_aggregated_measure_from_measure_source_node(
             )[0]
             time_range_node = JoinOverTimeRangeNode(
                 parent_node=measure_recipe.source_node,
-                # TODO: rename param
-                metric_time_dimension_spec=agg_time_dimension_spec_for_join,
+                time_dimension_spec_for_join=agg_time_dimension_spec_for_join,
                 window=cumulative_window,
                 grain_to_date=cumulative_grain_to_date,
                 time_range_constraint=time_range_constraint
diff --git a/metricflow/dataflow/dataflow_plan.py b/metricflow/dataflow/dataflow_plan.py
index db506b5bad..1cfb79b2d8 100644
--- a/metricflow/dataflow/dataflow_plan.py
+++ b/metricflow/dataflow/dataflow_plan.py
@@ -376,7 +376,7 @@ class JoinOverTimeRangeNode(BaseOutput):
     def __init__(
         self,
         parent_node: BaseOutput,
-        metric_time_dimension_spec: TimeDimensionSpec,
+        time_dimension_spec_for_join: TimeDimensionSpec,
         window: Optional[MetricTimeWindow],
         grain_to_date: Optional[TimeGranularity],
         node_id: Optional[NodeId] = None,
@@ -391,7 +391,7 @@ def __init__(
             (eg month to day)
             node_id: Override the node ID with this value
             time_range_constraint: time range to aggregate over
-            metric_time_dimension_spec: time dimension spec to use when joining to time spine
+            time_dimension_spec_for_join: time dimension spec to use when joining to time spine
         """
         if window and grain_to_date:
             raise RuntimeError(
@@ -402,7 +402,7 @@ def __init__(
         self._grain_to_date = grain_to_date
         self._window = window
         self.time_range_constraint = time_range_constraint
-        self.metric_time_dimension_spec = metric_time_dimension_spec
+        self.time_dimension_spec_for_join = time_dimension_spec_for_join
 
         # Doing a list comprehension throws a type error, so doing it this way.
         parent_nodes: List[DataflowPlanNode] = [self._parent_node]
@@ -450,7 +450,7 @@ def with_new_parents(self, new_parent_nodes: Sequence[BaseOutput]) -> JoinOverTi
             window=self.window,
             grain_to_date=self.grain_to_date,
             time_range_constraint=self.time_range_constraint,
-            metric_time_dimension_spec=self.metric_time_dimension_spec,
+            time_dimension_spec_for_join=self.time_dimension_spec_for_join,
         )
 
 
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 83487278a1..76762e0aa6 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -284,7 +284,7 @@ def visit_join_over_time_range_node(self, node: JoinOverTimeRangeNode) -> SqlDat
 
         metric_time_dimension_instance: Optional[TimeDimensionInstance] = None
         for instance in input_data_set.instance_set.time_dimension_instances:
-            if instance.spec == node.metric_time_dimension_spec:
+            if instance.spec == node.time_dimension_spec_for_join:
                 metric_time_dimension_instance = instance
                 break
 

From 930098efecfe957f96699cc0a277e0d01d31fe90 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 17:56:39 -0800
Subject: [PATCH 20/22] Rename param

---
 .../dataflow/builder/dataflow_plan_builder.py    |  7 +++----
 metricflow/dataflow/dataflow_plan.py             | 16 ++++++++--------
 metricflow/model/semantics/metric_lookup.py      |  1 -
 metricflow/plan_conversion/dataflow_to_sql.py    | 11 +++++------
 .../plan_conversion/test_dataflow_to_sql_plan.py |  6 +++---
 5 files changed, 19 insertions(+), 22 deletions(-)

diff --git a/metricflow/dataflow/builder/dataflow_plan_builder.py b/metricflow/dataflow/builder/dataflow_plan_builder.py
index 1550fc5b87..05d9b10801 100644
--- a/metricflow/dataflow/builder/dataflow_plan_builder.py
+++ b/metricflow/dataflow/builder/dataflow_plan_builder.py
@@ -514,7 +514,7 @@ def _build_derived_metric_output_node(
             ), "Joining to time spine requires querying with metric_time or the appropriate agg_time_dimension."
             output_node = JoinToTimeSpineNode(
                 parent_node=output_node,
-                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
+                requested_agg_time_dimension_specs=queried_agg_time_dimension_specs,
                 time_range_constraint=time_range_constraint,
                 offset_window=metric_spec.offset_window,
                 offset_to_grain=metric_spec.offset_to_grain,
@@ -1330,7 +1330,6 @@ def _build_aggregated_measure_from_measure_source_node(
         # Otherwise, the measure will be aggregated over all time.
         time_range_node: Optional[JoinOverTimeRangeNode] = None
         if cumulative and queried_agg_time_dimension_specs:
-            # TODO: will it be a problem if we get one with date part or diff granularity? Write test case to confirm
             # Use the time dimension spec with the smallest granularity.
             agg_time_dimension_spec_for_join = sorted(
                 queried_agg_time_dimension_specs, key=lambda spec: spec.time_granularity.to_int()
@@ -1359,7 +1358,7 @@ def _build_aggregated_measure_from_measure_source_node(
             )
             join_to_time_spine_node = JoinToTimeSpineNode(
                 parent_node=time_range_node or measure_recipe.source_node,
-                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
+                requested_agg_time_dimension_specs=queried_agg_time_dimension_specs,
                 time_range_constraint=time_range_constraint,
                 offset_window=before_aggregation_time_spine_join_description.offset_window,
                 offset_to_grain=before_aggregation_time_spine_join_description.offset_to_grain,
@@ -1465,7 +1464,7 @@ def _build_aggregated_measure_from_measure_source_node(
             )
             return JoinToTimeSpineNode(
                 parent_node=aggregate_measures_node,
-                requested_metric_time_dimension_specs=queried_agg_time_dimension_specs,
+                requested_agg_time_dimension_specs=queried_agg_time_dimension_specs,
                 join_type=after_aggregation_time_spine_join_description.join_type,
                 time_range_constraint=time_range_constraint,
                 offset_window=after_aggregation_time_spine_join_description.offset_window,
diff --git a/metricflow/dataflow/dataflow_plan.py b/metricflow/dataflow/dataflow_plan.py
index 1cfb79b2d8..3867a1b131 100644
--- a/metricflow/dataflow/dataflow_plan.py
+++ b/metricflow/dataflow/dataflow_plan.py
@@ -672,7 +672,7 @@ class JoinToTimeSpineNode(BaseOutput, ABC):
     def __init__(
         self,
         parent_node: BaseOutput,
-        requested_metric_time_dimension_specs: List[TimeDimensionSpec],
+        requested_agg_time_dimension_specs: List[TimeDimensionSpec],
         join_type: SqlJoinType,
         time_range_constraint: Optional[TimeRangeConstraint] = None,
         offset_window: Optional[MetricTimeWindow] = None,
@@ -682,7 +682,7 @@ def __init__(
 
         Args:
             parent_node: Node that returns desired dataset to join to time spine.
-            requested_metric_time_dimension_specs: Time dimensions requested in query. Used to determine granularities.
+            requested_agg_time_dimension_specs: Time dimensions requested in query. Used to determine granularities.
             time_range_constraint: Time range to constrain the time spine to.
             offset_window: Time window to offset the parent dataset by when joining to time spine.
             offset_to_grain: Granularity period to offset the parent dataset to when joining to time spine.
@@ -693,7 +693,7 @@ def __init__(
             offset_window and offset_to_grain
         ), "Can't set both offset_window and offset_to_grain when joining to time spine. Choose one or the other."
         self._parent_node = parent_node
-        self._requested_metric_time_dimension_specs = requested_metric_time_dimension_specs
+        self._requested_agg_time_dimension_specs = requested_agg_time_dimension_specs
         self._offset_window = offset_window
         self._offset_to_grain = offset_to_grain
         self._time_range_constraint = time_range_constraint
@@ -706,9 +706,9 @@ def id_prefix(cls) -> str:  # noqa: D
         return DATAFLOW_NODE_JOIN_TO_TIME_SPINE_ID_PREFIX
 
     @property
-    def requested_metric_time_dimension_specs(self) -> List[TimeDimensionSpec]:
+    def requested_agg_time_dimension_specs(self) -> List[TimeDimensionSpec]:
         """Time dimension specs to use when creating time spine table."""
-        return self._requested_metric_time_dimension_specs
+        return self._requested_agg_time_dimension_specs
 
     @property
     def time_range_constraint(self) -> Optional[TimeRangeConstraint]:
@@ -740,7 +740,7 @@ def description(self) -> str:  # noqa: D
     @property
     def displayed_properties(self) -> List[DisplayedProperty]:  # noqa: D
         return super().displayed_properties + [
-            DisplayedProperty("requested_metric_time_dimension_specs", self._requested_metric_time_dimension_specs),
+            DisplayedProperty("requested_agg_time_dimension_specs", self._requested_agg_time_dimension_specs),
             DisplayedProperty("time_range_constraint", self._time_range_constraint),
             DisplayedProperty("offset_window", self._offset_window),
             DisplayedProperty("offset_to_grain", self._offset_to_grain),
@@ -757,7 +757,7 @@ def functionally_identical(self, other_node: DataflowPlanNode) -> bool:  # noqa:
             and other_node.time_range_constraint == self.time_range_constraint
             and other_node.offset_window == self.offset_window
             and other_node.offset_to_grain == self.offset_to_grain
-            and other_node.requested_metric_time_dimension_specs == self.requested_metric_time_dimension_specs
+            and other_node.requested_agg_time_dimension_specs == self.requested_agg_time_dimension_specs
             and other_node.join_type == self.join_type
         )
 
@@ -765,7 +765,7 @@ def with_new_parents(self, new_parent_nodes: Sequence[BaseOutput]) -> JoinToTime
         assert len(new_parent_nodes) == 1
         return JoinToTimeSpineNode(
             parent_node=new_parent_nodes[0],
-            requested_metric_time_dimension_specs=self.requested_metric_time_dimension_specs,
+            requested_agg_time_dimension_specs=self.requested_agg_time_dimension_specs,
             time_range_constraint=self.time_range_constraint,
             offset_window=self.offset_window,
             offset_to_grain=self.offset_to_grain,
diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index 4a57090197..f57b5206a1 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -188,7 +188,6 @@ def get_valid_agg_time_dimensions_for_metric(
             return []
 
         path_key = agg_time_dimension_element_path_keys[0]
-        # TODO: do we need all these? Or just the one valid granularity? Depends what's allowed for time_offset
         valid_agg_time_dimension_specs = TimeDimensionSpec.generate_possible_specs_for_time_dimension(
             time_dimension_reference=TimeDimensionReference(element_name=path_key.element_name),
             entity_links=path_key.entity_links,
diff --git a/metricflow/plan_conversion/dataflow_to_sql.py b/metricflow/plan_conversion/dataflow_to_sql.py
index 76762e0aa6..9b572a4f77 100644
--- a/metricflow/plan_conversion/dataflow_to_sql.py
+++ b/metricflow/plan_conversion/dataflow_to_sql.py
@@ -1240,14 +1240,13 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         parent_data_set = node.parent_node.accept(self)
         parent_alias = self._next_unique_table_alias()
 
-        # TODO: rename requested_metric_time_dimension_specs -> requested_agg_time_dimension_specs
         assert (
-            len(node.requested_metric_time_dimension_specs) > 0
-        ), "Must have at least one value in requested_metric_time_dimension_specs for JoinToTimeSpineNode."
+            len(node.requested_agg_time_dimension_specs) > 0
+        ), "Must have at least one value in requested_agg_time_dimension_specs for JoinToTimeSpineNode."
 
         # Determine if the time spine join should use metric_time or the agg_time_dimension (metric_time takes priority).
-        agg_time_dimension_for_join = node.requested_metric_time_dimension_specs[0]
-        for spec in node.requested_metric_time_dimension_specs[1:]:
+        agg_time_dimension_for_join = node.requested_agg_time_dimension_specs[0]
+        for spec in node.requested_agg_time_dimension_specs[1:]:
             if spec.element_name == METRIC_TIME_ELEMENT_NAME:
                 agg_time_dimension_for_join = spec
                 break
@@ -1327,7 +1326,7 @@ def visit_join_to_time_spine_node(self, node: JoinToTimeSpineNode) -> SqlDataSet
         time_spine_select_columns = []
         time_spine_dim_instances = []
         where: Optional[SqlExpressionNode] = None
-        for requested_time_dimension_spec in node.requested_metric_time_dimension_specs:
+        for requested_time_dimension_spec in node.requested_agg_time_dimension_specs:
             # Apply granularity to time spine column select expression.
             if requested_time_dimension_spec.time_granularity == time_spine_dim_instance.spec.time_granularity:
                 select_expr: SqlExpressionNode = time_spine_column_select_expr
diff --git a/metricflow/test/plan_conversion/test_dataflow_to_sql_plan.py b/metricflow/test/plan_conversion/test_dataflow_to_sql_plan.py
index 4c8d80ac6b..58c983b2c7 100644
--- a/metricflow/test/plan_conversion/test_dataflow_to_sql_plan.py
+++ b/metricflow/test/plan_conversion/test_dataflow_to_sql_plan.py
@@ -548,7 +548,7 @@ def test_join_to_time_spine_node_without_offset(  # noqa: D
     compute_metrics_node = ComputeMetricsNode(parent_node=aggregated_measures_node, metric_specs=[metric_spec])
     join_to_time_spine_node = JoinToTimeSpineNode(
         parent_node=compute_metrics_node,
-        requested_metric_time_dimension_specs=[MTD_SPEC_DAY],
+        requested_agg_time_dimension_specs=[MTD_SPEC_DAY],
         time_range_constraint=TimeRangeConstraint(
             start_time=as_datetime("2020-01-01"), end_time=as_datetime("2021-01-01")
         ),
@@ -612,7 +612,7 @@ def test_join_to_time_spine_node_with_offset_window(  # noqa: D
     compute_metrics_node = ComputeMetricsNode(parent_node=aggregated_measures_node, metric_specs=[metric_spec])
     join_to_time_spine_node = JoinToTimeSpineNode(
         parent_node=compute_metrics_node,
-        requested_metric_time_dimension_specs=[MTD_SPEC_DAY],
+        requested_agg_time_dimension_specs=[MTD_SPEC_DAY],
         time_range_constraint=TimeRangeConstraint(
             start_time=as_datetime("2020-01-01"), end_time=as_datetime("2021-01-01")
         ),
@@ -678,7 +678,7 @@ def test_join_to_time_spine_node_with_offset_to_grain(
     compute_metrics_node = ComputeMetricsNode(parent_node=aggregated_measures_node, metric_specs=[metric_spec])
     join_to_time_spine_node = JoinToTimeSpineNode(
         parent_node=compute_metrics_node,
-        requested_metric_time_dimension_specs=[MTD_SPEC_DAY],
+        requested_agg_time_dimension_specs=[MTD_SPEC_DAY],
         time_range_constraint=TimeRangeConstraint(
             start_time=as_datetime("2020-01-01"), end_time=as_datetime("2021-01-01")
         ),

From ff28ecbae34e315166ee8746fe6111b8de2482c9 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 18:18:16 -0800
Subject: [PATCH 21/22] Updates

---
 metricflow/specs/specs.py                     |  7 ------
 .../integration/test_cases/itest_metrics.yaml | 23 +++++++++++++++++--
 ..._derived_metric_offset_to_grain__dfp_0.xml |  2 +-
 ...st_derived_metric_offset_window__dfp_0.xml |  2 +-
 ..._metric_offset_with_granularity__dfp_0.xml |  2 +-
 ...erived_offset_cumulative_metric__dfp_0.xml |  2 +-
 ...in_to_time_spine_derived_metric__dfp_0.xml |  6 ++---
 ..._to_time_spine_with_metric_time__dfp_0.xml |  2 +-
 ...erived_metric_with_outer_offset__dfp_0.xml |  4 ++--
 ...spine_node_with_offset_to_grain__plan0.xml |  2 +-
 ...e_spine_node_with_offset_window__plan0.xml |  2 +-
 ..._time_spine_node_without_offset__plan0.xml |  2 +-
 12 files changed, 34 insertions(+), 22 deletions(-)

diff --git a/metricflow/specs/specs.py b/metricflow/specs/specs.py
index ec44c556cf..0705fb0a60 100644
--- a/metricflow/specs/specs.py
+++ b/metricflow/specs/specs.py
@@ -669,13 +669,6 @@ def metric_time_specs(self) -> Sequence[TimeDimensionSpec]:
             if time_dimension_spec.is_metric_time
         )
 
-    # TODO: what about date part? not allowed for cumulative, right?
-    @property
-    def metric_time_spec_with_smallest_granularity(self) -> Optional[TimeDimensionSpec]:
-        """Get the metric time spec with the smallest granularity, if there are any metric time specs."""
-        sorted_specs = sorted(self.metric_time_specs, key=lambda x: x.time_granularity)
-        return sorted_specs[0] if sorted_specs else None
-
     @property
     def as_tuple(self) -> Tuple[LinkableInstanceSpec, ...]:  # noqa: D
         return tuple(itertools.chain(self.dimension_specs, self.time_dimension_specs, self.entity_specs))
diff --git a/metricflow/test/integration/test_cases/itest_metrics.yaml b/metricflow/test/integration/test_cases/itest_metrics.yaml
index 7424477d05..29760a7fbc 100644
--- a/metricflow/test/integration/test_cases/itest_metrics.yaml
+++ b/metricflow/test/integration/test_cases/itest_metrics.yaml
@@ -1868,5 +1868,24 @@ integration_test:
     ) subq_8
     ON
       {{ render_date_sub("subq_9", "ds", 2, TimeGranularity.DAY) }} = subq_8.booking__ds__day
-# TODO: offset tests with granularity, date part, multiple metric time / agg time options
-# TODO: cumulative tests with multiple metric_time / agg time options
+---
+integration_test:
+  name: offset_metric_with_agg_time_dim_date_part
+  description: Tests a derived metric query with an offset and agg_time_dimension with date part.
+  model: SIMPLE_MODEL
+  metrics: ["bookings_5_day_lag"]
+  group_by_objs: [{"name": "booking__ds", "date_part": "doy"}]
+  check_query: |
+    SELECT
+      {{ render_extract("a.ds", DatePart.DOY) }} AS booking__ds__extract_doy
+      , b.bookings_5_day_lag
+    FROM {{ mf_time_spine_source }} a
+    INNER JOIN (
+      SELECT
+        ds
+        , SUM(1) AS bookings_5_day_lag
+      FROM {{ source_schema }}.fct_bookings
+      GROUP BY
+        ds
+    ) b
+    ON {{ render_date_sub("a", "ds", 5, TimeGranularity.DAY) }} = b.ds
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_to_grain__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_to_grain__dfp_0.xml
index 8129aca791..e86eb5a59d 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_to_grain__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_to_grain__dfp_0.xml
@@ -60,7 +60,7 @@
                             <JoinToTimeSpineNode>
                                 <!-- description = Join to Time Spine Dataset -->
                                 <!-- node_id = jts_0 -->
-                                <!-- requested_metric_time_dimension_specs =                                   -->
+                                <!-- requested_agg_time_dimension_specs =                                      -->
                                 <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                                 <!-- time_range_constraint = None -->
                                 <!-- offset_window = None -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_window__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_window__dfp_0.xml
index 3c35caec5f..b5a332709f 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_window__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_window__dfp_0.xml
@@ -30,7 +30,7 @@
                         <JoinToTimeSpineNode>
                             <!-- description = Join to Time Spine Dataset -->
                             <!-- node_id = jts_0 -->
-                            <!-- requested_metric_time_dimension_specs =                                   -->
+                            <!-- requested_agg_time_dimension_specs =                                      -->
                             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                             <!-- time_range_constraint = None -->
                             <!-- offset_window = count=5 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_with_granularity__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_with_granularity__dfp_0.xml
index ed5c63701e..841524a925 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_with_granularity__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_metric_offset_with_granularity__dfp_0.xml
@@ -30,7 +30,7 @@
                         <JoinToTimeSpineNode>
                             <!-- description = Join to Time Spine Dataset -->
                             <!-- node_id = jts_0 -->
-                            <!-- requested_metric_time_dimension_specs =                                     -->
+                            <!-- requested_agg_time_dimension_specs =                                        -->
                             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=MONTH),]  -->
                             <!-- time_range_constraint = None -->
                             <!-- offset_window = count=5 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_offset_cumulative_metric__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_offset_cumulative_metric__dfp_0.xml
index ffd5457f7a..a6d584a4d8 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_offset_cumulative_metric__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_derived_offset_cumulative_metric__dfp_0.xml
@@ -30,7 +30,7 @@
                         <JoinToTimeSpineNode>
                             <!-- description = Join to Time Spine Dataset -->
                             <!-- node_id = jts_0 -->
-                            <!-- requested_metric_time_dimension_specs =                                   -->
+                            <!-- requested_agg_time_dimension_specs =                                      -->
                             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                             <!-- time_range_constraint = None -->
                             <!-- offset_window = count=2 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_derived_metric__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_derived_metric__dfp_0.xml
index 3cf58ceada..d43e414776 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_derived_metric__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_derived_metric__dfp_0.xml
@@ -18,7 +18,7 @@
                     <JoinToTimeSpineNode>
                         <!-- description = Join to Time Spine Dataset -->
                         <!-- node_id = jts_0 -->
-                        <!-- requested_metric_time_dimension_specs =                                   -->
+                        <!-- requested_agg_time_dimension_specs =                                      -->
                         <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                         <!-- time_range_constraint = None -->
                         <!-- offset_window = None -->
@@ -63,7 +63,7 @@
                     <JoinToTimeSpineNode>
                         <!-- description = Join to Time Spine Dataset -->
                         <!-- node_id = jts_2 -->
-                        <!-- requested_metric_time_dimension_specs =                                   -->
+                        <!-- requested_agg_time_dimension_specs =                                      -->
                         <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                         <!-- time_range_constraint = None -->
                         <!-- offset_window = None -->
@@ -83,7 +83,7 @@
                                 <JoinToTimeSpineNode>
                                     <!-- description = Join to Time Spine Dataset -->
                                     <!-- node_id = jts_1 -->
-                                    <!-- requested_metric_time_dimension_specs =                                   -->
+                                    <!-- requested_agg_time_dimension_specs =                                      -->
                                     <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                                     <!-- time_range_constraint = None -->
                                     <!-- offset_window = count=14 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_with_metric_time__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_with_metric_time__dfp_0.xml
index 7edb223370..ab704033a4 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_with_metric_time__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_join_to_time_spine_with_metric_time__dfp_0.xml
@@ -10,7 +10,7 @@
             <JoinToTimeSpineNode>
                 <!-- description = Join to Time Spine Dataset -->
                 <!-- node_id = jts_0 -->
-                <!-- requested_metric_time_dimension_specs =                                   -->
+                <!-- requested_agg_time_dimension_specs =                                      -->
                 <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                 <!-- time_range_constraint = None -->
                 <!-- offset_window = None -->
diff --git a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_nested_derived_metric_with_outer_offset__dfp_0.xml b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_nested_derived_metric_with_outer_offset__dfp_0.xml
index b8a78ed26c..32fd5e1e64 100644
--- a/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_nested_derived_metric_with_outer_offset__dfp_0.xml
+++ b/metricflow/test/snapshots/test_dataflow_plan_builder.py/DataflowPlan/test_nested_derived_metric_with_outer_offset__dfp_0.xml
@@ -10,7 +10,7 @@
             <JoinToTimeSpineNode>
                 <!-- description = Join to Time Spine Dataset -->
                 <!-- node_id = jts_1 -->
-                <!-- requested_metric_time_dimension_specs =                                   -->
+                <!-- requested_agg_time_dimension_specs =                                      -->
                 <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                 <!-- time_range_constraint = None -->
                 <!-- offset_window = count=2 granularity=TimeGranularity.DAY -->
@@ -40,7 +40,7 @@
                                 <JoinToTimeSpineNode>
                                     <!-- description = Join to Time Spine Dataset -->
                                     <!-- node_id = jts_0 -->
-                                    <!-- requested_metric_time_dimension_specs =                                   -->
+                                    <!-- requested_agg_time_dimension_specs =                                      -->
                                     <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
                                     <!-- time_range_constraint = None -->
                                     <!-- offset_window = count=5 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_to_grain__plan0.xml b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_to_grain__plan0.xml
index f83b57688b..9a5d81695e 100644
--- a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_to_grain__plan0.xml
+++ b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_to_grain__plan0.xml
@@ -5,7 +5,7 @@
         <JoinToTimeSpineNode>
             <!-- description = Join to Time Spine Dataset -->
             <!-- node_id = jts_0 -->
-            <!-- requested_metric_time_dimension_specs =                                   -->
+            <!-- requested_agg_time_dimension_specs =                                      -->
             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
             <!-- time_range_constraint = [2020-01-01T00:00:00, 2021-01-01T00:00:00] -->
             <!-- offset_window = None -->
diff --git a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_window__plan0.xml b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_window__plan0.xml
index 75794f74d9..e951eebd3f 100644
--- a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_window__plan0.xml
+++ b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_with_offset_window__plan0.xml
@@ -5,7 +5,7 @@
         <JoinToTimeSpineNode>
             <!-- description = Join to Time Spine Dataset -->
             <!-- node_id = jts_0 -->
-            <!-- requested_metric_time_dimension_specs =                                   -->
+            <!-- requested_agg_time_dimension_specs =                                      -->
             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
             <!-- time_range_constraint = [2020-01-01T00:00:00, 2021-01-01T00:00:00] -->
             <!-- offset_window = count=10 granularity=TimeGranularity.DAY -->
diff --git a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_without_offset__plan0.xml b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_without_offset__plan0.xml
index 9bf1e08fa3..19602e3e91 100644
--- a/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_without_offset__plan0.xml
+++ b/metricflow/test/snapshots/test_dataflow_to_sql_plan.py/DataflowPlan/test_join_to_time_spine_node_without_offset__plan0.xml
@@ -5,7 +5,7 @@
         <JoinToTimeSpineNode>
             <!-- description = Join to Time Spine Dataset -->
             <!-- node_id = jts_0 -->
-            <!-- requested_metric_time_dimension_specs =                                   -->
+            <!-- requested_agg_time_dimension_specs =                                      -->
             <!--   [TimeDimensionSpec(element_name='metric_time', time_granularity=DAY),]  -->
             <!-- time_range_constraint = [2020-01-01T00:00:00, 2021-01-01T00:00:00] -->
             <!-- offset_window = None -->

From 86fa33ad601119a4b30f818093f3c9a09c823b69 Mon Sep 17 00:00:00 2001
From: Courtney Holcomb <courtneyeholcomb@gmail.com>
Date: Wed, 24 Jan 2024 18:20:24 -0800
Subject: [PATCH 22/22] Cleanup

---
 metricflow/model/semantics/metric_lookup.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/metricflow/model/semantics/metric_lookup.py b/metricflow/model/semantics/metric_lookup.py
index f57b5206a1..44a7bd3280 100644
--- a/metricflow/model/semantics/metric_lookup.py
+++ b/metricflow/model/semantics/metric_lookup.py
@@ -167,9 +167,6 @@ def _get_agg_time_dimension_path_keys_for_metric(
     ) -> Sequence[ElementPathKey]:
         """Retrieves the aggregate time dimensions associated with the metric's measures."""
         metric = self.get_metric(metric_reference)
-        # This should get hit on offset metric, right?
-        assert metric.input_measures, f"No input measures found for metric {metric_reference}"
-
         path_keys = set()
         for input_measure in metric.input_measures:
             path_key = self._semantic_model_lookup.get_agg_time_dimension_path_key_for_measure(