mik-laj commented on a change in pull request #6792: [AIRFLOW-5930] Use
cached-SQL query building for hot-path queries
URL: https://github.com/apache/airflow/pull/6792#discussion_r356991452
##########
File path: airflow/jobs/scheduler_job.py
##########
@@ -1057,30 +1027,34 @@ def _find_executable_task_instances(self,
simple_dag_bag, states, session=None):
TI = models.TaskInstance
DR = models.DagRun
DM = models.DagModel
- ti_query = (
- session
- .query(TI)
- .filter(TI.dag_id.in_(simple_dag_bag.dag_ids))
+ ti_query = BAKED_QUERIES(
+ lambda session: session.query(TI).filter(
+ TI.dag_id.in_(simple_dag_bag.dag_ids)
+ )
.outerjoin(
DR,
and_(DR.dag_id == TI.dag_id, DR.execution_date ==
TI.execution_date)
)
- .filter(or_(DR.run_id == None, # noqa: E711 pylint:
disable=singleton-comparison
- not_(DR.run_id.like(BackfillJob.ID_PREFIX + '%'))))
+ .filter(or_(DR.run_id.is_(None),
+ not_(DR.run_id.like(BackfillJob.ID_PREFIX + '%'))))
Review comment:
I really don't like filtering with the like expression. This makes the query
very difficult to optimize. It is not possible to store it in a simple data
structure. We have to have a very complex binary tree, but which takes more
memory than a simple structure with 3 values. Which causes other problems, e.g.
unbalanced tree, and thus performance degradation.
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