This is required on systemd, which mounts filesystems as "shared"
subtrees. Changes to shared trees in a private mount namespace are
propagated to the outside world, which is bad.
This is a problem because one process may set the immutable bit before
the second process has created its link.
Addressed random Hydra failures such as:
error: cannot rename `/nix/store/.tmp-link-17397-1804289383' to
`/nix/store/rsvzm574rlfip3830ac7kmaa028bzl6h-nixos-0.1pre-git/upstart-interface-version':
Operation not permitted
Since SubstitutionGoal::finished() in build.cc computes the hash
anyway, we can prevent the inefficiency of computing the hash twice by
letting the substituter tell Nix about the expected hash, which can
then verify it.
Incremental optimisation requires creating links in /nix/store/.links
to all files in the store. However, this means that if we delete a
store path, no files are actually deleted because links in
/nix/store/.links still exists. So we need to check /nix/store/.links
for files with a link count of 1 and delete them.
optimiseStore() now creates persistent, content-addressed hard links
in /nix/store/.links. For instance, if it encounters a file P with
hash H, it will create a hard link
P' = /nix/store/.link/<H>
to P if P' doesn't already exist; if P' exist, then P is replaced by a
hard link to P'. This is better than the previous in-memory map,
because it had the tendency to unnecessarily replace hard links with a
hard link to whatever happened to be the first file with a given hash
it encountered. It also allows on-the-fly, incremental optimisation.
To implement binary caches efficiently, Hydra needs to be able to map
the hash part of a store path (e.g. "gbg...zr7") to the full store
path (e.g. "/nix/store/gbg...kzr7-subversion-1.7.5"). (The binary
cache mechanism uses hash parts as a key for looking up store paths to
ensure privacy.) However, doing a search in the Nix store for
/nix/store/<hash>* is expensive since it requires reading the entire
directory. queryPathFromHashPart() prevents this by doing a cheap
database lookup.
queryValidPaths() combines multiple calls to isValidPath() in one.
This matters when using the Nix daemon because it reduces latency.
For instance, on "nix-env -qas \*" it reduces execution time from 5.7s
to 4.7s (which is indistinguishable from the non-daemon case).
Instead make a single call to querySubstitutablePathInfo() per
derivation output. This is faster and prevents having to implement
the "have" function in the binary cache substituter.
Getting substitute information using the binary cache substituter has
non-trivial latency overhead. A package or NixOS system configuration
can have hundreds of dependencies, and in the worst case (when the
local info cache is empty) we have to do a separate HTTP request for
each of these. If the ping time to the server is t, getting N info
files will take tN seconds; e.g., with a ping time of 0.1s to
nixos.org, sequentially downloading 1000 info files (a typical NixOS
config) will take at least 100 seconds.
To fix this problem, the binary cache substituter can now perform
requests in parallel. This required changing the substituter
interface to support a function querySubstitutablePathInfos() that
queries multiple paths at the same time, and rewriting queryMissing()
to take advantage of parallelism. (Due to local caching,
parallelising queryMissing() is sufficient for most use cases, since
it's almost always called before building a derivation and thus fills
the local info cache.)
For example, parallelism speeds up querying all 1056 paths in a
particular NixOS system configuration from 116s to 2.6s. It works so
well because the eccentricity of the top-level derivation in the
dependency graph is only 9. So we only need 10 round-trips (when
using an unlimited number of parallel connections) to get everything.
Currently we do a maximum of 150 parallel connections to the server.
Thus it's important that the binary cache server (e.g. nixos.org) has
a high connection limit. Alternatively we could use HTTP pipelining,
but WWW::Curl doesn't support it and libcurl has a hard-coded limit of
5 requests per pipeline.
