This allows fully declarative project specifications. This is best
illustrated by example:
* I create a new project, setting the declarative spec file to
"spec.json" and the declarative input to a git repo pointing
at git://github.com/shlevy/declarative-hydra-example.git
* hydra creates a special ".jobsets" jobset alongside the project
* Just before evaluating the ".jobsets" jobset, hydra fetches
declarative-hydra-example.git, reads spec.json as a jobset spec,
and updates the jobset's configuration accordingly:
{
"enabled": 1,
"hidden": false,
"description": "Jobsets",
"nixexprinput": "src",
"nixexprpath": "default.nix",
"checkinterval": 300,
"schedulingshares": 100,
"enableemail": false,
"emailoverride": "",
"keepnr": 3,
"inputs": {
"src": { "type": "git", "value": "git://github.com/shlevy/declarative-hydra-example.git", "emailresponsible": false },
"nixpkgs": { "type": "git", "value": "git://github.com/NixOS/nixpkgs.git release-16.03", "emailresponsible": false }
}
}
* When the "jobsets" job of the ".jobsets" jobset completes, hydra
reads its output as a JSON representation of a dictionary of
jobset specs and creates a jobset named "master" configured
accordingly (In this example, this is the same configuration as
.jobsets itself, except using release.nix instead of default.nix):
{
"enabled": 1,
"hidden": false,
"description": "js",
"nixexprinput": "src",
"nixexprpath": "release.nix",
"checkinterval": 300,
"schedulingshares": 100,
"enableemail": false,
"emailoverride": "",
"keepnr": 3,
"inputs": {
"src": { "type": "git", "value": "git://github.com/shlevy/declarative-hydra-example.git", "emailresponsible": false },
"nixpkgs": { "type": "git", "value": "git://github.com/NixOS/nixpkgs.git release-16.03", "emailresponsible": false }
}
}
Currently, the hydra.nixos.org queue contains 1000s of Darwin builds
that all depend on a stdenv-darwin that previously failed. However,
before, first createStep() would construct a dependency graph for each
build, then getQueuedBuilds() would discover that one of the steps had
failed previously and discard all those steps. Since the graph
construction involves a lot of uncached calls to isValidPath(), this
took several seconds per build.
Now createStep() detects the previous failure right away and bails
out.
These are build steps that remain "busy" in the database even though
they have finished, because they couldn't be updated (e.g. due to a
PostgreSQL connection problem). To prevent them from showing up as
busy in the "Machine status" page, we now periodically purge them.
Previously, if the queue monitor thread encounters a build that Hydra
has previously built, it downloaded the output paths from the binary
cache, just to determine the build products and metrics. This is very
inefficient. In particular, when doing something like merging
nixpkgs:staging into nixpkgs:master, the queue monitor thread will be
locked up for a long time fetching files from S3, causing the build
farm to be mostly idle.
Of course this is entirely unnecessary, since the build
products/metrics are already in the Hydra database. So now we just
look up a previous build with the same output path, and copy the
products/metrics.
Mutliple <githubstatus> sections are possible:
* jobs: regexp for jobs to match
* inputs: the input which corresponds to the github repo/rev whose
status we want to report. Can be repeated
* authorization: Verbatim contents of the Authorization header. See
https://developer.github.com/v3/#authentication.
Otherwise, the browser may mix up HTML and JSON responses if it has
requested both. For example, hitting the back button to return to a
job metric page will show a JSON response, because that was the last
thing the browser fetched for that URL.
This requires Catalyst::Action::Rest >= 1.20.
The previous query
select count(*) from builds b left join buildsteps s on s.build = b.id where busy = 1 and finished = 0
is suddenly taking several minutes. Probably PostgreSQL decided to use
a suboptimal query plan.
The maximum output size per build step (as the sum of the NARs of each
output) can be set via hydra.conf, e.g.
max-output-size = 1000000000
The default is 2 GiB.
Also refactored the build error / status handling a bit.
When using a binary cache store, the queue runner receives NARs from
the build machines, compresses them, and uploads them to the
cache. However, keeping multiple large NARs in memory can cause the
queue runner to run out of memory. This can happen for instance when
it's processing multiple ISO images concurrently.
The fix is to use a TokenServer to prevent the builder threads to
store more than a certain total size of NARs concurrently (at the
moment, this is hard-coded at 4 GiB). Builder threads that cause the
limit to be exceeded will block until other threads have finished.
The 4 GiB limit does not include certain other allocations, such as
for xz compression or for FSAccessor::readFile(). But since these are
unlikely to be more than the size of the NARs and hydra.nixos.org has
32 GiB RAM, it should be fine.
The old page didn't scale very well if you have 150K builds in the
queue, in fact it tended to make browsers hang. The new one just
shows, for each jobset, the number of queued builds. The actual builds
can be seen by going to the corresponding jobset page and looking at
the evals.
Same problem as d744362e4a.
at /nix/store/ksvsbr7pg4z69bv6fbbc8h7x7rm2104m-gcc-4.9.3/include/c++/4.9.3/bits/predefined_ops.h:166
__last@entry=..., __comp=...) at /nix/store/ksvsbr7pg4z69bv6fbbc8h7x7rm2104m-gcc-4.9.3/include/c++/4.9.3/bits/stl_algo.h:1827
__comp=...) at /nix/store/ksvsbr7pg4z69bv6fbbc8h7x7rm2104m-gcc-4.9.3/include/c++/4.9.3/bits/stl_algo.h:4717
Respects <slack> blocks in the hydra config, with attributes:
* jobs: a regexp matching the job name (in the format project:jobset:job)
* url: The URL to a slack incoming webhook
* force: If true, always send messages. Otherwise, only when the build status changes
Multiple <slack> blocks are allowed
To use the local Nix store (default):
store_mode = direct
To use a local binary cache:
store_mode = local-binary-cache
binary_cache_dir = /var/lib/hydra/binary-cache
To use an S3 bucket:
store_mode = s3-binary-cache
binary_cache_s3_bucket = my-nix-bucket
Also, respect binary_cache_{secret,public}_key_file for signing the
binary cache.
