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date = "2022-10-18"
draft = true
path = "/blog/speedy-ifd"
tags = ["haskell", "nix"]
title = "Speedy import-from-derivation in Nix?"
+++
Nix has a feature called "import from derivation", which is sometimes called
"such a nice foot gun" (grahamc, 2022). I can't argue with its
usefulness; it lets Nix do amazing things that can't be accomplished any other
way, and avoid pointlessly checking build products into git. However, it has a
dirty secret: it can *atrociously* slow down your builds.
The essence of this feature is that Nix can do operations such as build
derivations whose result is used in the *evaluation stage*.
## Nix build staging?
Nix, in its current implementation (there are efforts [such as tvix][tvix] to
change this), can do one of two things at a given time.
* Evaluate: run Nix expressions to create some derivations to build. This stage
outputs `.drv` files, which can then be instantiated. Nix evaluation happens
in serial (single threaded), and in a lazy fashion.
* Build: given some `.drv` files, fetch the result from a binary cache or build
from scratch.
[tvix]: https://code.tvl.fyi/about/tvix
### How does import-from-derivation fit in?
Import-from-derivation (IFD for short) lets you do magical things: since Nix
derivations can do arbitrary computation in any language, Nix expressions or
other data can be generated by external programs that need to do pesky things
such as parse cursed file formats such as cabal files.
N.B. I've heard that someone wrote a PureScript compiler targeting the Nix
language, which was then targeted at [parsing a Cabal file to do cabal2nix's job][evil-cabal2nix]
entirely within Nix. Nothing is sacred.
[evil-cabal2nix]: https://github.com/cdepillabout/cabal2nixWithoutIFD
In order to achieve this, however, the evaluation stage can demand builds be
run. In fact, such builds need to be run before proceeding with evaluation! So
IFD serializes builds.
### What constitutes IFD?
The following is a nonexhaustive list of things constituting IFD:
* `builtins.readFile someDerivation`
* `import someDerivation`
* *Any use* of builtin fetchers:
* `builtins.fetchGit`
* `builtins.fetchTree`
* `builtins.fetchTarball`
* `builtins.fetchurl`
* etc
#### Builtin fetchers
Use of builtin fetchers is a surprisingly common IFD problem. Sometimes it is
done by mistake, but other times it is done for good reason, with unfortunate
tradeoffs. I think it's reasonable to use IFD to import libraries such as
nixpkgs, since fundamentally the thing needs to be fetched for evaluation to
proceed, but other cases are more dubious.
One reason one might use the builtin fetchers is that there is no way
(excepting calculated use of impure builders) to use a derivation to download a
URL without knowing the hash ahead of time.
An example I've seen of this being done on purpose is wanting to avoid
requiring contributors to have Nix installed to update the hash of some
tarball, since Nix has its own bespoke algorithm for hashing tarball contents
that nobody has yet implemented outside Nix. So the maintainers used an impure
network fetch (only feasible with a builtin) and instituted a curse on the
build times of Nix users.
The reason that impure fetching needs to be a builtin is because Nix has an
important purity rule for derivations: either input is fixed and network access
is disallowed, or output is fixed and network access is allowed. In the Nix
model as designed ([content-addressed store] aside), derivations are identified
only by what goes into them, but not the output.
Let's see why that is. Assume that network access is allowed in normal
builders. If the URL but no hash goes in *and* network access is available,
anything can come out without changing the store path. Such an impurity would
completely break the fantastic property that Nix has no such thing as a clean
build since the builds don't get dirtied to begin with.
Thus, if one is doing an impure network fetch, the resulting store path has to
depend on the content without knowing the hash ahead of time. Therefore the
fetch *has* to serialize all evaluation after it, since it affects the store
paths of anything downstream of it during evaluation.
That said, it is, in my opinion, a significant design flaw in the Nix evaluator
that it cannot queue all the derivations that are reachable, rather than
stopping and building each in order.
[content-addressed store]: https://github.com/NixOS/rfcs/blob/master/rfcs/0062-content-addressed-paths.md
## Stories
I work at a Haskell shop which makes extensive use of Nix. We had a bug where
Nix would go and serially build "`all-cabal-hashes-component-*`". For several
minutes.
This was what I would call a "very frustrating and expensive developer UX bug".
I fixed it in a couple of afternoons by refactoring the use of
import-from-derivation to result in fewer switches between building and
evaluating, which I will expand on in a bit.
## Background on nixpkgs Haskell
The way that the nixpkgs Haskell infrastructure works is that it has a
[Stackage]-based package set based on some Stackage Long-Term Support release,
comprising package versions that are all known to work together. The set is
generated via a program called [`hackage2nix`][hackage2nix], which runs
`cabal2nix` against the entirety of Hackage.
`cabal2nix` is a program that generates metadata, input hashes, and hooks up
dependencies declared in the `.cabal` files to Nix build inputs.
This set can then be overridden by [overlays] which can apply patches, override
sources, introduce new packages, and do basically any other arbitrary
modification.
At build time, the builder will be provisioned with a GHC package database with
everything in the build inputs of the package, and it will build and test the
package.
In this way, each dependency is turned into a Nix derivation so caching
of dependencies for development shells, parallelism across package builds, and
other useful properties simply fall out for free.
[Stackage]: https://www.stackage.org/
[hackage2nix]: https://github.com/NixOS/cabal2nix/tree/master/cabal2nix/hackage2nix
[overlays]: https://nixos.org/manual/nixpkgs/stable/#chap-overlays
## Where's the IFD?
nixpkgs Haskell provides a wonderfully useful function called `callCabal2nix`,
which executes `cabal2nix` to generate the Nix expression for some Haskell
source code at Nix evaluation time. Uh oh.
It also provides another wonderfully useful function called `callHackage`. This
is a very sweet function: it will grab a package of the specified version off
of Hackage, and call `cabal2nix` on it.
Wait, how does that work, since you can't just download stuff for fun without
knowing its hash? Well, there's your problem.
"Figuring out hashes of stuff on Hackage" was solved by someone publishing a
comically large GitHub repo called `all-cabal-hashes` with hashes of all of the
tarballs on Hackage and CI to keep it up to date. Using this repo, you only
have to deal with keeping one hash up to date: the hash of the version of
`all-cabal-hashes` you're using, and the rest are just fetched from there.
### Oh no
This repository has an obscene number of files in it, such that it takes dozens
of seconds to unpack it. So it's simply not unpacked. Fetching a file out of it
involves invoking tar to selectively extract the relevant file from the giant
tarball of this repo.
That, in turn, takes around 7 seconds on the fastest MacBook available, for
each and every package, in serial. Also, Nix checks the binary caches for each
and every one, further compounding the fail.
I optimized it to take about 7 seconds, *total*. Although I *am* a witch, I
think that there is some generally applicable intuition derived from this that
can be used to make IFD go fast.
# Making IFD go fast
Nix is great at building big graphs of dependencies in parallel and caching
them. So what if we ask Nix to do that?
How can this be achieved?
What if you only demand one big derivation be built with IFD then reuse it
across all the usage sites?
## Details of `some-cabal2nix`
My observation was that hot-cache builds with a bunch of IFD are fine; it's
refilling it that's horribly painful since Nix spends a lot of time doing
pointless things in serial. What if we warmed up the cache by asking it to
build all that stuff in one shot? Then, the rest of the IFD would hit a hot
cache.
*The* major innovation in the fix, which I called `some-cabal-hashes`, is that
it builds *one* derivation with IFD that contains everything that will be
needed for further evaluation, then all the following imports will hit that
already-built derivation.
Specifically, my build dependency graph now looks like:
```
/- cabal2nix-pkg1 -\
some-cabal2nix -+- cabal2nix-pkg2 -+- some-cabal-hashes -> all-cabal-hashes
\- cabal2nix-pkg3 -/
```
There are two notable things about this graph:
1. It is (approximately) the natural graph of the dependencies of the build
assuming that the Nix evaluator could keep going when it encounters IFD.
2. It allows Nix to naturally parallelize all the `cabal2nix-*` derivations.
Then, all of the usage sites are `import "${some-cabal2nix}/pkg1` or similar.
In this way, one derivation is built, letting Nix do what it's good at. I did
something clever also: I made `some-cabal2nix` have no runtime dependencies by
*copying* all the resulting cabal files into the output directory. Thus, the
whole thing can be fetched from a cache server and not built at all.
Acquiring the data to know what will be demanded by any IFD is the other piece
of the puzzle, of course. I extracted the data from the overlays by calling the
overlays with stubs first (to avoid a cyclic dependency), then evaluating for
real with a `callHackage` function using the `some-cabal2nix` created using
that information.
The last and very important optimization I did was to fix the `tar` invocation.
`tar` files have a linear structure that is perfect for making `t`ape
`ar`chives (hence the name of the tool) which can be streamed to a tape: one
file after the other, without any index. Thus, finding a file in the tarball
takes an amount of time proportional to `O(n)` where `n` is the number of files
in the archive.
If you call tar `m` times for the number of files you need, then you do
`O(n*m)` work. However, if you call `tar` *once* with a set of files that you
want such that it can do one parse through the file and an `O(1)` membership
check of that set, then the overall time complexity is `O(n)`. I can assume
that is what `tar` actually does, since it does the entire extraction in
basically the same time with a long file list as with one file.
Enough making myself sound like I am in an ivory tower with big O notation;
regardless, extracting with a file list yielded a major performance win.
I also found that if you use the `--wildcards` option, `tar` is extremely slow
and it seems worse with more files to extract. Use exact file paths instead.
FIXME: get permission to release the sources of that file