Rename internal batch_info variable to previous_batch_results

core/dbt/contracts/graph/nodes.py

@@ -444,13 +444,15 @@ def resource_class(cls) -> Type[HookNodeResource]:
 
 @dataclass
 class ModelNode(ModelResource, CompiledNode):
-    batch_info: Optional[BatchResults] = None
+    previous_batch_results: Optional[BatchResults] = None
     _has_this: Optional[bool] = None
 
     def __post_serialize__(self, dct: Dict, context: Optional[Dict] = None):
         dct = super().__post_serialize__(dct, context)
         if "_has_this" in dct:
             del dct["_has_this"]
+        if "previous_batch_results" in dct:
+            del dct["previous_batch_results"]
         return dct
 
     @classmethod

core/dbt/task/retry.py

@@ -136,7 +136,7 @@ def run(self):
         # batch info if there were _no_ successful batches previously. This is
         # because passing the batch info _forces_ the microbatch process into
         # _incremental_ model, and it may be that we need to be in full refresh
-        # mode which is only handled if batch_info _isn't_ passed for a node
+        # mode which is only handled if previous_batch_results _isn't_ passed for a node
         batch_map = {
             result.unique_id: result.batch_results
             for result in self.previous_results.results

core/dbt/task/run.py

@@ -445,8 +445,8 @@
         result.batch_results.failed = sorted(result.batch_results.failed)
 
         # # If retrying, propagate previously successful batches into final result, even thoguh they were not run in this invocation
-        if self.node.batch_info is not None:
-            result.batch_results.successful += self.node.batch_info.successful
+        if self.node.previous_batch_results is not None:
+            result.batch_results.successful += self.node.previous_batch_results.successful
 
     def _build_succesful_run_batch_result(
         self,
@@ -508,15 +508,15 @@
         )
 
         if self.batch_idx is None:
-            # Note currently (9/30/2024) model.batch_info is only ever _not_ `None`
+            # Note currently (9/30/2024) model.previous_batch_results is only ever _not_ `None`
             # IFF `dbt retry` is being run and the microbatch model had batches which
             # failed on the run of the model (which is being retried)
-            if model.batch_info is None:
+            if model.previous_batch_results is None:
                 end = microbatch_builder.build_end_time()
                 start = microbatch_builder.build_start_time(end)
                 batches = microbatch_builder.build_batches(start, end)
             else:
-                batches = model.batch_info.failed
+                batches = model.previous_batch_results.failed
                 # If there is batch info, then don't run as full_refresh and do force is_incremental
                 # not doing this risks blowing away the work that has already been done
                 if self._has_relation(model=model):
@@ -885,7 +885,7 @@
                 if uid in self.batch_map:
                     node = self.manifest.ref_lookup.perform_lookup(uid, self.manifest)
                     if isinstance(node, ModelNode):
-                        node.batch_info = self.batch_map[uid]
+                        node.previous_batch_results = self.batch_map[uid]
 
     def before_run(self, adapter: BaseAdapter, selected_uids: AbstractSet[str]) -> RunStatus:
         with adapter.connection_named("master"):

tests/unit/contracts/graph/test_manifest.py

@@ -96,7 +96,6 @@
         "deprecation_date",
         "defer_relation",
         "time_spine",
-        "batch_info",
     }
 )