jj/lib/testutils/Cargo.toml

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[package]
name = "testutils"
description = "Integration test utils for the jj-lib crate"
publish = false
version = { workspace = true }
edition = { workspace = true }
rust-version = { workspace = true }
license = { workspace = true }
homepage = { workspace = true }
repository = { workspace = true }
documentation = { workspace = true }
readme = { workspace = true }
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
backend: make read functions async The commit backend at Google is cloud-based (and so are the other backends); it reads and writes commits from/to a server, which stores them in a database. That makes latency much higher than for disk-based backends. To reduce the latency, we have a local daemon process that caches and prefetches objects. There are still many cases where latency is high, such as when diffing two uncached commits. We can improve that by changing some of our (jj's) algorithms to read many objects concurrently from the backend. In the case of tree-diffing, we can fetch one level (depth) of the tree at a time. There are several ways of doing that: * Make the backend methods `async` * Use many threads for reading from the backend * Add backend methods for batch reading I don't think we typically need CPU parallelism, so it's wasteful to have hundreds of threads running in order to fetch hundreds of objects in parallel (especially when using a synchronous backend like the Git backend). Batching would work well for the tree-diffing case, but it's not as composable as `async`. For example, if we wanted to fetch some commits at the same time as we were doing a diff, it's hard to see how to do that with batching. Using async seems like our best bet. I didn't make the backend interface's write functions async because writes are already async with the daemon we have at Google. That daemon will hash the object and immediately return, and then send the object to the server in the background. I think any cloud-based solution will need a similar daemon process. However, we may need to reconsider this if/when jj gets used on a server with a custom backend that writes directly to a database (i.e. no async daemon in between). I've tried to measure the performance impact. That's the largest difference I've been able to measure was on `jj diff --ignore-working-copy -s --from v5.0 --to v6.0` in the Linux repo, which increases from 749 ms to 773 ms (3.3%). In most cases I've tested, there's no measurable difference. I've tried diffing from the root commit, as well as `jj --ignore-working-copy log --no-graph -r '::v3.0 & author(torvalds)' -T 'commit_id ++ "\n"'` (to test a commit-heavy load).
2023-09-06 19:59:17 +00:00
async-trait = { workspace = true }
config = { workspace = true }
git2 = { workspace = true }
hex = { workspace = true }
itertools = { workspace = true }
jj-lib = { workspace = true }
rand = { workspace = true }
tempfile = { workspace = true }