Encode JSON responses on a thread in C, mk2 (#10905)

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).
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Erik Johnston 2021-09-28 10:37:58 +01:00 committed by GitHub
parent d37841787a
commit 707d5e4e48
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4 changed files with 76 additions and 18 deletions

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@ -21,13 +21,28 @@ from typing import (
Iterable,
Iterator,
Mapping,
Sequence,
Set,
Sized,
Tuple,
TypeVar,
)
from typing_extensions import Protocol
T = TypeVar("T")
S = TypeVar("S", bound="_SelfSlice")
class _SelfSlice(Sized, Protocol):
"""A helper protocol that matches types where taking a slice results in the
same type being returned.
This is more specific than `Sequence`, which allows another `Sequence` to be
returned.
"""
def __getitem__(self: S, i: slice) -> S:
...
def batch_iter(iterable: Iterable[T], size: int) -> Iterator[Tuple[T, ...]]:
@ -46,7 +61,7 @@ def batch_iter(iterable: Iterable[T], size: int) -> Iterator[Tuple[T, ...]]:
return iter(lambda: tuple(islice(sourceiter, size)), ())
def chunk_seq(iseq: Sequence[T], maxlen: int) -> Iterable[Sequence[T]]:
def chunk_seq(iseq: S, maxlen: int) -> Iterator[S]:
"""Split the given sequence into chunks of the given size
The last chunk may be shorter than the given size.