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Asset-triggered Dag runs cause scheduler memory spikes
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### Under which category would you file this issue?
Ariflow Core
### Apache Airflow version
`main`
### What happened and how to reproduce it?
When the scheduler creates an asset-triggered Dag run, it selects every `AssetEvent` in the event window as a full ORM object. This materializes each event's JSON metadata and relationship state in the scheduler process before writing rows to `dagrun_asset_event`.
The scheduler's peak memory therefore grows linearly with the number of events. A production-path benchmark using a 512-byte JSON payload per event produced the following baseline results:
| Database | Events | Duration | Python peak | RSS increase |
|---|---:|---:|---:|---:|
| SQLite | 1,000 | 0.537 s | 6.23 MB | 0.17 MB |
| SQLite | 10,000 | 1.785 s | 54.24 MB | 79.98 MB |
| SQLite | 50,000 | 12.545 s | 274.21 MB | 465.98 MB |
| PostgreSQL | 1,000 | 0.339 s | 7.39 MB | 1.88 MB |
| PostgreSQL | 10,000 | 2.510 s | 62.34 MB | 108.78 MB |
| PostgreSQL | 50,000 | 10.046 s | 289.72 MB | 483.77 MB |
| MySQL | 1,000 | 2.622 s | 6.76 MB | 0.75 MB |
| MySQL | 10,000 | 4.478 s | 54.54 MB | 98.21 MB |
| MySQL | 50,000 | 21.502 s | 272.63 MB | 475.28 MB |
Reproduction outline:
1. Create an asset-scheduled Dag with `catchup=False`.
2. Insert 1,000, 10,000, or 50,000 matching `AssetEvent` rows containing a 512-byte JSON value.
3. Add the corresponding `AssetDagRunQueue` row.
4. Invoke `SchedulerJobRunner._create_dag_runs_asset_triggered`.
5. Measure elapsed time, Python allocations, and scheduler RSS during Dag run creation.
Fixture creation is outside the measured interval. Every run creates the expected number of
`dagrun_asset_event` associations.
### What you think should happen instead?
Dag run creation should preserve exact consumed-event membership without materializing complete `AssetEvent` objects in scheduler memory. The association can be written as a set-based `INSERT ... SELECT` in the existing transaction, using the same direct-asset, alias, and event-window predicat…
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