tao.chenandClaude
9fc886a55e
schedule:
- New _execution_loop runs alongside _database_event_loop. It claims
job.node.execute rows, sets a 30-min lease on available_at, then
dispatches each as asyncio.create_task under a Semaphore(N).
Polling loop is back to sub-millisecond turnaround for
schedule.run.requested and job.node.finished. Long notebook
execution no longer blocks DAG advance events.
- _process_pending_events filters by event_type IN
('schedule.run.requested', 'job.node.finished'); the executor
loop owns job.node.execute exclusively.
- _process_outbox_event builds a plain dict envelope before
handler dispatch; the previous ORM-row handoff risked
DetachedInstanceError once the outer session closed.
- _sync_once uses get_job + reschedule_job for existing job ids
instead of add_job(replace_existing=True). Each cron schedule
no longer removed-and-readded every 5s.
- service.py threads settings.schedule_execution_concurrency into
the orchestrator (default 4).
common:
- create_async_engine gets explicit pool_size=10, max_overflow=20,
pool_recycle=1800. No more relying on SQLAlchemy defaults.
- New schedule_execution_concurrency setting.
runtime:
- scan_workspaces: add missing 'import os' (NameError on startup)
and switch to asyncio.gather bounded by Semaphore(4) so N
workspaces start in parallel instead of sequentially.
Co-Authored-By: Claude <noreply@anthropic.com>
Runtime
独立 Runtime/Jupyter 管理服务：
- 使用共享 Jupyter Server；
- 在 MySQL 中维护 Runtime 实例和编辑会话租约；
- 创建、心跳和释放文件编辑锁；
- 创建短期 Jupyter 访问票据；
- 为 Nginx
auth_request校验票据并注入内部 Jupyter Token。
当前简化部署要求 Runtime 单副本运行。