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Refactor ORM DAG insertion logic #42358

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200 changes: 104 additions & 96 deletions airflow/dag_processing/collection.py
Original file line number Diff line number Diff line change
Expand Up @@ -61,46 +61,28 @@
log = logging.getLogger(__name__)


def collect_orm_dags(dags: dict[str, DAG], *, session: Session) -> dict[str, DagModel]:
"""
Collect DagModel objects from DAG objects.

An existing DagModel is fetched if there's a matching ID in the database.
Otherwise, a new DagModel is created and added to the session.
"""
def _find_orm_dags(dag_ids: Iterable[str], *, session: Session) -> dict[str, DagModel]:
"""Find existing DagModel objects from DAG objects."""
stmt = (
select(DagModel)
.options(joinedload(DagModel.tags, innerjoin=False))
.where(DagModel.dag_id.in_(dags))
.where(DagModel.dag_id.in_(dag_ids))
.options(joinedload(DagModel.schedule_dataset_references))
.options(joinedload(DagModel.schedule_dataset_alias_references))
.options(joinedload(DagModel.task_outlet_dataset_references))
)
stmt = with_row_locks(stmt, of=DagModel, session=session)
existing_orm_dags = {dm.dag_id: dm for dm in session.scalars(stmt).unique()}
return {dm.dag_id: dm for dm in session.scalars(stmt).unique()}


for dag_id, dag in dags.items():
if dag_id in existing_orm_dags:
continue
orm_dag = DagModel(dag_id=dag_id)
def _create_orm_dags(dags: Iterable[DAG], *, session: Session) -> Iterator[DagModel]:
for dag in dags:
orm_dag = DagModel(dag_id=dag.dag_id)
if dag.is_paused_upon_creation is not None:
orm_dag.is_paused = dag.is_paused_upon_creation
orm_dag.tags = []
log.info("Creating ORM DAG for %s", dag_id)
log.info("Creating ORM DAG for %s", dag.dag_id)
session.add(orm_dag)
existing_orm_dags[dag_id] = orm_dag

return existing_orm_dags


def create_orm_dag(dag: DAG, session: Session) -> DagModel:
orm_dag = DagModel(dag_id=dag.dag_id)
if dag.is_paused_upon_creation is not None:
orm_dag.is_paused = dag.is_paused_upon_creation
orm_dag.tags = []
log.info("Creating ORM DAG for %s", dag.dag_id)
session.add(orm_dag)
return orm_dag
yield orm_dag


def _get_latest_runs_stmt(dag_ids: Collection[str]) -> Select:
Expand Down Expand Up @@ -158,75 +140,101 @@ def calculate(cls, dags: dict[str, DAG], *, session: Session) -> Self:
)


def update_orm_dags(
source_dags: dict[str, DAG],
target_dags: dict[str, DagModel],
*,
processor_subdir: str | None = None,
session: Session,
) -> None:
"""
Apply DAG attributes to DagModel objects.

Objects in ``target_dags`` are modified in-place.
"""
run_info = _RunInfo.calculate(source_dags, session=session)

for dag_id, dm in sorted(target_dags.items()):
dag = source_dags[dag_id]
dm.fileloc = dag.fileloc
dm.owners = dag.owner
dm.is_active = True
dm.has_import_errors = False
dm.last_parsed_time = utcnow()
dm.default_view = dag.default_view
dm._dag_display_property_value = dag._dag_display_property_value
dm.description = dag.description
dm.max_active_tasks = dag.max_active_tasks
dm.max_active_runs = dag.max_active_runs
dm.max_consecutive_failed_dag_runs = dag.max_consecutive_failed_dag_runs
dm.has_task_concurrency_limits = any(
t.max_active_tis_per_dag is not None or t.max_active_tis_per_dagrun is not None for t in dag.tasks
)
dm.timetable_summary = dag.timetable.summary
dm.timetable_description = dag.timetable.description
dm.dataset_expression = dag.timetable.dataset_condition.as_expression()
dm.processor_subdir = processor_subdir

last_automated_run: DagRun | None = run_info.latest_runs.get(dag.dag_id)
if last_automated_run is None:
last_automated_data_interval = None
else:
last_automated_data_interval = dag.get_run_data_interval(last_automated_run)
if run_info.num_active_runs.get(dag.dag_id, 0) >= dm.max_active_runs:
dm.next_dagrun_create_after = None
def _update_dag_tags(tag_names: set[str], dm: DagModel, *, session: Session) -> None:
orm_tags = {t.name: t for t in dm.tags}
for name, orm_tag in orm_tags.items():
if name not in tag_names:
session.delete(orm_tag)
dm.tags.extend(DagTag(name=name, dag_id=dm.dag_id) for name in tag_names if name not in orm_tags)
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def _update_dag_owner_links(dag_owner_links: dict[str, str], dm: DagModel, *, session: Session) -> None:
orm_dag_owner_attributes = {obj.owner: obj for obj in dm.dag_owner_links}
for owner, obj in orm_dag_owner_attributes.items():
try:
link = dag_owner_links[owner]
except KeyError:
session.delete(obj)
else:
dm.calculate_dagrun_date_fields(dag, last_automated_data_interval)

if not dag.timetable.dataset_condition:
dm.schedule_dataset_references = []
dm.schedule_dataset_alias_references = []
# FIXME: STORE NEW REFERENCES.

dag_tags = set(dag.tags or ())
for orm_tag in (dm_tags := list(dm.tags or [])):
if orm_tag.name not in dag_tags:
session.delete(orm_tag)
dm.tags.remove(orm_tag)
orm_tag_names = {t.name for t in dm_tags}
for dag_tag in dag_tags:
if dag_tag not in orm_tag_names:
dag_tag_orm = DagTag(name=dag_tag, dag_id=dag.dag_id)
dm.tags.append(dag_tag_orm)
session.add(dag_tag_orm)

dm_links = dm.dag_owner_links or []
for dm_link in dm_links:
if dm_link not in dag.owner_links:
session.delete(dm_link)
for owner_name, owner_link in dag.owner_links.items():
dag_owner_orm = DagOwnerAttributes(dag_id=dag.dag_id, owner=owner_name, link=owner_link)
session.add(dag_owner_orm)
if obj.link != link:
obj.link = link
dm.dag_owner_links.extend(
DagOwnerAttributes(dag_id=dm.dag_id, owner=owner, link=link)
for owner, link in dag_owner_links.items()
if owner not in orm_dag_owner_attributes
)


class DagModelOperation(NamedTuple):
"""Collect DAG objects and perform database operations for them."""

dags: dict[str, DAG]

def add_dags(self, *, session: Session) -> dict[str, DagModel]:
orm_dags = _find_orm_dags(self.dags, session=session)
orm_dags.update(
(model.dag_id, model)
for model in _create_orm_dags(
(dag for dag_id, dag in self.dags.items() if dag_id not in orm_dags),
session=session,
)
)
return orm_dags

def update_dags(
self,
orm_dags: dict[str, DagModel],
*,
processor_subdir: str | None = None,
session: Session,
) -> None:
run_info = _RunInfo.calculate(self.dags, session=session)

for dag_id, dm in sorted(orm_dags.items()):
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dag = self.dags[dag_id]
dm.fileloc = dag.fileloc
dm.owners = dag.owner
dm.is_active = True
dm.has_import_errors = False
dm.last_parsed_time = utcnow()
dm.default_view = dag.default_view
dm._dag_display_property_value = dag._dag_display_property_value
dm.description = dag.description
dm.max_active_tasks = dag.max_active_tasks
dm.max_active_runs = dag.max_active_runs
dm.max_consecutive_failed_dag_runs = dag.max_consecutive_failed_dag_runs
dm.has_task_concurrency_limits = any(
t.max_active_tis_per_dag is not None or t.max_active_tis_per_dagrun is not None
for t in dag.tasks
)
dm.timetable_summary = dag.timetable.summary
dm.timetable_description = dag.timetable.description
dm.dataset_expression = dag.timetable.dataset_condition.as_expression()
dm.processor_subdir = processor_subdir

last_automated_run: DagRun | None = run_info.latest_runs.get(dag.dag_id)
if last_automated_run is None:
last_automated_data_interval = None
else:
last_automated_data_interval = dag.get_run_data_interval(last_automated_run)
if run_info.num_active_runs.get(dag.dag_id, 0) >= dm.max_active_runs:
dm.next_dagrun_create_after = None
else:
dm.calculate_dagrun_date_fields(dag, last_automated_data_interval)

if not dag.timetable.dataset_condition:
dm.schedule_dataset_references = []
dm.schedule_dataset_alias_references = []
# FIXME: STORE NEW REFERENCES.

if dag.tags:
_update_dag_tags(set(dag.tags), dm, session=session)
else: # Optimization: no references at all, just clear everything.
dm.tags = []
if dag.owner_links:
_update_dag_owner_links(dag.owner_links, dm, session=session)
else: # Optimization: no references at all, just clear everything.
dm.dag_owner_links = []


def _find_all_datasets(dags: Iterable[DAG]) -> Iterator[Dataset]:
Expand Down
24 changes: 6 additions & 18 deletions airflow/models/dag.py
Original file line number Diff line number Diff line change
Expand Up @@ -2643,28 +2643,16 @@ def bulk_write_to_db(
if not dags:
return

from airflow.dag_processing.collection import (
DatasetModelOperation,
collect_orm_dags,
create_orm_dag,
update_orm_dags,
)
from airflow.dag_processing.collection import DagModelOperation, DatasetModelOperation

log.info("Sync %s DAGs", len(dags))
dags_by_ids = {dag.dag_id: dag for dag in dags}
del dags

orm_dags = collect_orm_dags(dags_by_ids, session=session)
orm_dags.update(
(dag_id, create_orm_dag(dag, session=session))
for dag_id, dag in dags_by_ids.items()
if dag_id not in orm_dags
)
dag_op = DagModelOperation({dag.dag_id: dag for dag in dags})

update_orm_dags(dags_by_ids, orm_dags, processor_subdir=processor_subdir, session=session)
DagCode.bulk_sync_to_db((dag.fileloc for dag in dags_by_ids.values()), session=session)
orm_dags = dag_op.add_dags(session=session)
dag_op.update_dags(orm_dags, processor_subdir=processor_subdir, session=session)
DagCode.bulk_sync_to_db((dag.fileloc for dag in dags), session=session)

dataset_op = DatasetModelOperation.collect(dags_by_ids)
dataset_op = DatasetModelOperation.collect(dag_op.dags)

orm_datasets = dataset_op.add_datasets(session=session)
orm_dataset_aliases = dataset_op.add_dataset_aliases(session=session)
Expand Down
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