rajat315315 opened a new pull request, #70019:
URL: https://github.com/apache/airflow/pull/70019
Closes: #70018
### Description
### Motivation
Improves the performance of the scheduler loop by optimizing
[ConcurrencyMap.load](file:///home/rajat/airflow/airflow-core/src/airflow/jobs/scheduler_job_runner.py#L239-L247).
By introducing a composite index on `(state, dag_id, task_id, run_id)` inside
[taskinstance.py](file:///home/rajat/airflow/airflow-core/src/airflow/models/taskinstance.py),
we enable a **Covering Index Scan** (Index Only Scan) and eliminate the
temporary B-Tree sorting/grouping step when aggregating active task instances.
### Proposed Changes
1. **Model Update**: Added index definition to `TaskInstance.__table_args__`
in
[taskinstance.py](file:///home/rajat/airflow/airflow-core/src/airflow/models/taskinstance.py):
```python
Index("ti_state_active_composite", state, dag_id, task_id, run_id)
```
2. **Database Migration**: Added an Alembic migration script to create
`ti_state_active_composite`.
### Verification
Ran query plan analysis and benchmarks on SQLite:
* **Before Plan**:
```text
SEARCH task_instance USING INDEX ti_state (state=?)
USE TEMP B-TREE FOR GROUP BY
```
* **After Plan**:
```text
SEARCH task_instance USING COVERING INDEX ti_state_active_composite
(state=?)
```
* **Performance Gain**: ~10% latency reduction on local SQLite; expected to
be higher under high PostgreSQL/MySQL heap-read and buffer pool pressure.
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