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707d5e4e48
Currently we use `JsonEncoder.iterencode` to write JSON responses, which ensures that we don't block the main reactor thread when encoding huge objects. The downside to this is that `iterencode` falls back to using a pure Python encoder that is *much* less efficient and can easily burn a lot of CPU for huge responses. To fix this, while still ensuring we don't block the reactor loop, we encode the JSON on a threadpool using the standard `JsonEncoder.encode` functions, which is backed by a C library. Doing so, however, requires `respond_with_json` to have access to the reactor, which it previously didn't. There are two ways of doing this: 1. threading through the reactor object, which is a bit fiddly as e.g. `DirectServeJsonResource` doesn't currently take a reactor, but is exposed to modules and so is a PITA to change; or 2. expose the reactor in `SynapseRequest`, which requires updating a bunch of servlet types. I went with the latter as that is just a mechanical change, and I think makes sense as a request already has a reactor associated with it (via its http channel).
2 lines
57 B
Gherkin
2 lines
57 B
Gherkin
Speed up responding with large JSON objects to requests.
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