MagicStack / MagicStack/asyncpg
backpressure on LISTEN?
- Dominant language
- Python
- Stars
- 8.1k
- Forks
- 468
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Description
* **asyncpg version**: 0.18.3
* **PostgreSQL version**: 9.5
* **Do you use a PostgreSQL SaaS? If so, which? Can you reproduce
the issue with a local PostgreSQL install?**:
* **Python version**: 3.6
* **Platform**:
* **Do you use pgbouncer?**:
* **Did you install asyncpg with pip?**:
* **If you built asyncpg locally, which version of Cython did you use?**:
* **Can the issue be reproduced under both asyncio and
[uvloop](https://github.com/magicstack/uvloop)?**:
My application subscribes to postgres notifications and fans them out to subscribers using streaming http.
I see that notifications emerge in connection._process_notification, where they are dispatched via call_soon(), each time calling _call_listener(), which will synchronously call the callback that I specify in conn.add_listener(). In the callback, I insert a task into the queue for asynchronous processing...
I see a lot of tasks inserted this way, e.g. ~5000 before my application has a chance to process them. Therefore application memory has big unpredictable spikes, like +300k
Question: how do you apply back-pressure in this setup? is there a way to limit the number of postgres notifications that are being converted to tasks, to control overall number of in-flight tasks? Thanks!
Contributor guide
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Research direction
Read connection._process_notification, call_soon(), _call_listener(), and conn.add_listener() first, then trace how the application’s queue creates tasks. The issue does not name a target file, test, or acceptance behavior; define whether the outcome should be an API-level limit on in-flight notifications and add coverage for that behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- postgresql, python
- Domain
- databases
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100