Add a Resolver for Saved-Query Dependencies

.changes/unreleased/Features-20240426-144119.yaml

@@ -0,0 +1,6 @@
+kind: Features
+body: Add a Dependency Resolver for Saved Queries
+time: 2024-04-26T14:41:19.27946-07:00
+custom:
+  Author: plypaul
+  Issue: "1155"

metricflow-semantics/metricflow_semantics/api/v0_1/saved_query_dependency_resolver.py

@@ -0,0 +1,75 @@
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from typing import Tuple
+
+from dbt_semantic_interfaces.protocols import SemanticManifest
+from dbt_semantic_interfaces.references import (
+    SemanticModelReference,
+)
+
+from metricflow_semantics.model.semantic_manifest_lookup import SemanticManifestLookup
+from metricflow_semantics.query.query_parser import MetricFlowQueryParser
+from metricflow_semantics.specs.query_param_implementations import SavedQueryParameter
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True)
+class SavedQueryDependencySet:
+    """The dependencies of a saved query.
+
+    The primary use case is to handle creation of the cache item associated with the saved query. The dependencies
+    listed in this class must be up-to-date before the cache associated with the saved query can be created. Otherwise,
+    running the export / creating the cache may create a cache item that is out-of-date / unusable.
+    """
+
+    # The semantic models that the saved query depends on.
+    semantic_model_references: Tuple[SemanticModelReference, ...]
+
+
+class SavedQueryDependencyResolver:
+    """Resolves the dependencies of a saved query. Also see `SavedQueryDependencySet`."""
+
+    def __init__(self, semantic_manifest: SemanticManifest) -> None:  # noqa: D107
+        self._semantic_manifest = semantic_manifest
+        self._query_parser = MetricFlowQueryParser(SemanticManifestLookup(semantic_manifest))
+
+    def _resolve_dependencies(self, saved_query_name: str) -> SavedQueryDependencySet:
+        parse_result = self._query_parser.parse_and_validate_saved_query(
+            saved_query_parameter=SavedQueryParameter(saved_query_name),
+            where_filter=None,
+            limit=None,
+            time_constraint_start=None,
+            time_constraint_end=None,
+            order_by_names=None,
+            order_by_parameters=None,
+        )
+
+        return SavedQueryDependencySet(
+            semantic_model_references=tuple(
+                sorted(
+                    parse_result.queried_semantic_models,
+                    key=lambda reference: reference.semantic_model_name,
+                )
+            ),
+        )
+
+    def resolve_dependencies(self, saved_query_name: str) -> SavedQueryDependencySet:
+        """Return the dependencies of the given saved query in the manifest."""
+        try:
+            return self._resolve_dependencies(saved_query_name)
+        except Exception:
+            logger.exception(
+                f"Got an exception while getting the dependencies of saved-query {repr(saved_query_name)}. "
+                f"All semantic models will be returned instead for safety."
+            )
+            return SavedQueryDependencySet(
+                semantic_model_references=tuple(
+                    sorted(
+                        (semantic_model.reference for semantic_model in self._semantic_manifest.semantic_models),
+                        key=lambda reference: reference.semantic_model_name,
+                    )
+                ),
+            )

metricflow-semantics/metricflow_semantics/collection_helpers/dedupe.py

@@ -0,0 +1,15 @@
+from __future__ import annotations
+
+from typing import Dict, Iterable, Tuple, TypeVar
+
+IterableT = TypeVar("IterableT")
+
+
+def ordered_dedupe(*iterables: Iterable[IterableT]) -> Tuple[IterableT, ...]:
+    """De-duplicates the items in the iterables while preserving the order."""
+    ordered_results: Dict[IterableT, None] = {}
+    for iterable in iterables:
+        for item in iterable:
+            ordered_results[item] = None
+
+    return tuple(ordered_results.keys())

metricflow-semantics/metricflow_semantics/instances.py

@@ -16,12 +16,12 @@
     EntitySpec,
     GroupByMetricSpec,
     InstanceSpec,
-    InstanceSpecSet,
     MeasureSpec,
     MetadataSpec,
     MetricSpec,
     TimeDimensionSpec,
 )
+from metricflow_semantics.specs.spec_set import InstanceSpecSet
 
 # Type for the specification used in the instance.
 SpecT = TypeVar("SpecT", bound=InstanceSpec)

metricflow-semantics/metricflow_semantics/model/linkable_element_property.py

@@ -0,0 +1,43 @@
+from __future__ import annotations
+
+from enum import Enum
+from typing import FrozenSet
+
+
+class LinkableElementProperty(Enum):
+    """The properties associated with a valid linkable element.
+
+    Local means an element that is defined within the same semantic model as the measure. This definition is used
+    throughout the related classes.
+    """
+
+    # A local element as per above definition.
+    LOCAL = "local"
+    # A local dimension that is prefixed with a local primary entity.
+    LOCAL_LINKED = "local_linked"
+    # An element that was joined to the measure semantic model by an entity.
+    JOINED = "joined"
+    # An element that was joined to the measure semantic model by joining multiple semantic models.
+    MULTI_HOP = "multi_hop"
+    # A time dimension that is a version of a time dimension in a semantic model, but at a different granularity.
+    DERIVED_TIME_GRANULARITY = "derived_time_granularity"
+    # Refers to an entity, not a dimension.
+    ENTITY = "entity"
+    # See metric_time in DataSet
+    METRIC_TIME = "metric_time"
+    # Refers to a metric, not a dimension.
+    METRIC = "metric"
+
+    @staticmethod
+    def all_properties() -> FrozenSet[LinkableElementProperty]:  # noqa: D102
+        return frozenset(
+            {
+                LinkableElementProperty.LOCAL,
+                LinkableElementProperty.LOCAL_LINKED,
+                LinkableElementProperty.JOINED,
+                LinkableElementProperty.MULTI_HOP,
+                LinkableElementProperty.DERIVED_TIME_GRANULARITY,
+                LinkableElementProperty.METRIC_TIME,
+                LinkableElementProperty.METRIC,
+            }
+        )

metricflow-semantics/metricflow_semantics/model/semantic_model_derivation.py

@@ -0,0 +1,19 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Sequence
+
+from dbt_semantic_interfaces.references import SemanticModelReference
+
+
+class SemanticModelDerivation(ABC):
+    """Interface for an object that can be described as derived from a semantic model."""
+
+    @property
+    @abstractmethod
+    def derived_from_semantic_models(self) -> Sequence[SemanticModelReference]:
+        """The semantic models that this was derived from.
+
+        The returned sequence should be ordered and not contain duplicates.
+        """
+        raise NotImplementedError

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

@@ -1,16 +1,27 @@
 from __future__ import annotations
 
+import logging
+from abc import ABC
 from dataclasses import dataclass
 from enum import Enum
-from typing import FrozenSet, Optional, Tuple
+from typing import FrozenSet, Optional, Sequence, Tuple
 
 from dbt_semantic_interfaces.enum_extension import assert_values_exhausted
 from dbt_semantic_interfaces.protocols.dimension import DimensionType
-from dbt_semantic_interfaces.references import DimensionReference, MetricReference, SemanticModelReference
+from dbt_semantic_interfaces.references import (
+    DimensionReference,
+    EntityReference,
+    MetricReference,
+    SemanticModelReference,
+)
 from dbt_semantic_interfaces.type_enums.date_part import DatePart
 from dbt_semantic_interfaces.type_enums.time_granularity import TimeGranularity
+from typing_extensions import override
 
-from metricflow_semantics.specs.spec_classes import EntityReference
+from metricflow_semantics.model.linkable_element_property import LinkableElementProperty
+from metricflow_semantics.model.semantic_model_derivation import SemanticModelDerivation
+
+logger = logging.getLogger(__name__)
 
 
 class LinkableElementType(Enum):
@@ -40,45 +51,6 @@ def is_dimension_type(self) -> bool:
             return assert_values_exhausted(element_type)
 
 
-class LinkableElementProperty(Enum):
-    """The properties associated with a valid linkable element.
-
-    Local means an element that is defined within the same semantic model as the measure. This definition is used
-    throughout the related classes.
-    """
-
-    # A local element as per above definition.
-    LOCAL = "local"
-    # A local dimension that is prefixed with a local primary entity.
-    LOCAL_LINKED = "local_linked"
-    # An element that was joined to the measure semantic model by an entity.
-    JOINED = "joined"
-    # An element that was joined to the measure semantic model by joining multiple semantic models.
-    MULTI_HOP = "multi_hop"
-    # A time dimension that is a version of a time dimension in a semantic model, but at a different granularity.
-    DERIVED_TIME_GRANULARITY = "derived_time_granularity"
-    # Refers to an entity, not a dimension.
-    ENTITY = "entity"
-    # See metric_time in DataSet
-    METRIC_TIME = "metric_time"
-    # Refers to a metric, not a dimension.
-    METRIC = "metric"
-
-    @staticmethod
-    def all_properties() -> FrozenSet[LinkableElementProperty]:  # noqa: D102
-        return frozenset(
-            {
-                LinkableElementProperty.LOCAL,
-                LinkableElementProperty.LOCAL_LINKED,
-                LinkableElementProperty.JOINED,
-                LinkableElementProperty.MULTI_HOP,
-                LinkableElementProperty.DERIVED_TIME_GRANULARITY,
-                LinkableElementProperty.METRIC_TIME,
-                LinkableElementProperty.METRIC,
-            }
-        )
-
-
 @dataclass(frozen=True)
 class ElementPathKey:
     """A key that can uniquely identify an element and the joins used to realize the element."""
@@ -110,8 +82,14 @@ class SemanticModelJoinPathElement:
     join_on_entity: EntityReference
 
 
+class LinkableElement(SemanticModelDerivation, ABC):
+    """An entity / dimension that may have been joined by entities."""
+
+    pass
+
+
 @dataclass(frozen=True)
-class LinkableDimension:
+class LinkableDimension(LinkableElement):
     """Describes how a dimension can be realized by joining based on entity links."""
 
     # The semantic model where this dimension was defined.
@@ -143,9 +121,20 @@ def path_key(self) -> ElementPathKey:  # noqa: D102
     def reference(self) -> DimensionReference:  # noqa: D102
         return DimensionReference(element_name=self.element_name)
 
+    @property
+    @override
+    def derived_from_semantic_models(self) -> Sequence[SemanticModelReference]:
+        semantic_model_references = set()
+        if self.semantic_model_origin:
+            semantic_model_references.add(self.semantic_model_origin)
+        for join_path_item in self.join_path:
+            semantic_model_references.add(join_path_item.semantic_model_reference)
+
+        return sorted(semantic_model_references, key=lambda reference: reference.semantic_model_name)
+
 
 @dataclass(frozen=True)
-class LinkableEntity:
+class LinkableEntity(LinkableElement, SemanticModelDerivation):
     """Describes how an entity can be realized by joining based on entity links."""
 
     # The semantic model where this entity was defined.
@@ -165,9 +154,18 @@ def path_key(self) -> ElementPathKey:  # noqa: D102
     def reference(self) -> EntityReference:  # noqa: D102
         return EntityReference(element_name=self.element_name)
 
+    @property
+    @override
+    def derived_from_semantic_models(self) -> Sequence[SemanticModelReference]:
+        semantic_model_references = {self.semantic_model_origin}
+        for join_path_item in self.join_path:
+            semantic_model_references.add(join_path_item.semantic_model_reference)
+
+        return sorted(semantic_model_references, key=lambda reference: reference.semantic_model_name)
+
 
 @dataclass(frozen=True)
-class LinkableMetric:
+class LinkableMetric(LinkableElement, SemanticModelDerivation):
     """Describes how a metric can be realized by joining based on entity links."""
 
     element_name: str
@@ -187,6 +185,15 @@ def path_key(self) -> ElementPathKey:  # noqa: D102
     def reference(self) -> MetricReference:  # noqa: D102
         return MetricReference(element_name=self.element_name)
 
+    @property
+    @override
+    def derived_from_semantic_models(self) -> Sequence[SemanticModelReference]:
+        semantic_model_references = {self.join_by_semantic_model}
+        for join_path_item in self.join_path:
+            semantic_model_references.add(join_path_item.semantic_model_reference)
+
+        return sorted(semantic_model_references, key=lambda reference: reference.semantic_model_name)
+
 
 @dataclass(frozen=True)
 class SemanticModelJoinPath: