* 'eval_started' has the format '<tmpId>\t<project>\t<jobset>'.
* 'eval_failed' has the format '<tmpId>'. (The cause of the error can
be found in the database.)
* 'eval_added' has the format '<tmpId>:<evalId>'.
It now receives notifications about started/finished builds/steps via
PostgreSQL. This gets rid of the (substantial) overhead of starting
hydra-notify for every event. It also allows other programs (even on
other machines) to listen to Hydra notifications.
When using the "build" or "sysbuild" jobset input types in conjunction
with a binary cache store, the evaluator needs to be able to fetch
store paths from the binary cache. Typical usage:
store_uri = s3://nix-test-cache?secret-key=...
eval_substituter = s3://nix-test-cache
Also, the public key of the binary cache must be added to
binary-cache-public-keys in nix.conf, otherwise the local nix-daemon
won't allow the store paths to be copied over.
Also, remove support in hydra-eval-jobs for multiple jobset input
alternatives. The web interface hasn't supported this in a long
time. Thus we can use the regular "--arg" handler.
When creating a Hydra user with the `hydra-create-user` command, you can now
provide a SHA1 password hash with the `--password-hash` flag. This is useful for
the upcoming work on Fully Declarative Hydra, since the end user should not have
to specify plaintext passwords in their `configuration.nix` file.
As @dtzWill discovered, with the concurrent hydra-evaluator, there can
be multiple active transactions adding builds to the database. As a
result, builds can become visible in a non-monotonically increasing
order, breaking the queue monitor's assumption that build IDs only go
up.
The fix is to have hydra-eval-jobset provide the lowest build ID it
just added in the builds_added notification, and have the queue
monitor check from there.
Fixes#496.
This can take an excessive amount of time. For example, on
hydra.nixos.org, a call to hydra-notify takes 0.7s even if there are
no plugins. So for an eval with ~45K new builds, the calls to
hydra-notify add up to about 9 hours.
The proper fix would be to pass a list of build IDs, or an eval ID.
* The "Jobset" page now shows when evaluations are in progress (rather
than just pending).
* Restored the ability to do a single evaluation from the command line
by doing "hydra-evaluator <project> <jobset>".
* Fix some consistency issues between jobset status in PostgreSQL and
in hydra-evaluator. In particular, "lastCheckedTime" was never
updated internally.
Without this, if (failed or aborted) derivations have been
garbage-collected, there is no way to restart them, which is very
annoying. Now we set a forceEval flag in the jobset to cause it to be
re-evaluated even if none of the inputs have changed.
This rewrites the top-level loop of hydra-evaluator in C++. The Perl
stuff is moved into hydra-eval-jobset. (Rewriting the entire evaluator
would be nice but is a bit too much work.) The new version has some
advantages:
* It can run multiple jobset evaluations in parallel.
* It uses PostgreSQL notifications so it doesn't have to poll the
database. So if a jobset is triggered via the web interface or from
a GitHub / Bitbucket webhook, evaluation of the jobset will start
almost instantaneously (assuming the evaluator is not at its
concurrency limit).
* It imposes a timeout on evaluations. So if e.g. hydra-eval-jobset
hangs connecting to a Mercurial server, it will eventually be
killed.
This prevents the server from gradually filling up due to store paths
fetched by hydra-server that then get turned into a GC root by
hydra-update-gc-roots.
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 }
}
}
This is currently done by a separate program that periodically
calls "hydra-queue-runner --status". Eventually, I'll do this
in the queue runner directly.
Fixes#220.
Hydra-queue-runner now no longer polls the queue periodically, but
instead sleeps until it receives a notification from PostgreSQL about
a change to the queue (build added, build cancelled or build
restarted).
Also, for the "build added" case, we now only check for builds with an
ID greater than the previous greatest ID. This is much more efficient
if the queue is large.
These give warnings in Perl >= 5.18:
given is experimental at /home/hydra/src/hydra/src/lib/Hydra/Helper/CatalystUtils.pm line 241.
when is experimental at /home/hydra/src/hydra/src/lib/Hydra/Helper/CatalystUtils.pm line 242.
...
This incorporates the following two commits from <nixpkgs>:
NixOS/nixpkgs@f83af95f8aNixOS/nixpkgs@5e7a1cf955
Hydra was the original reason why I was fixing tempdir creation in the
first place. Seeing that Hydra ships its own versions of these scripts,
we need to patch them here as well.
Signed-off-by: aszlig <aszlig@redmoonstudios.org>
If hydra-eval-jobs creates a new root, and hydra-update-gc-roots runs
before hydra-evaluator has had a chance to add the corresponding build
to the database, then hydra-update-gc-roots will remove the root. If
subsequently the Nix garbage collector kicks in, it may remove the
build's .drv file before the build is performed. Since evaluation of
the Nixpkgs and NixOS jobsets nowadays takes a lot of time (e.g. an
hour), the probability of this happening is fairly high.
The quick fix is not to delete roots that are less than a day old. So
long as evaluation doesn't take longer than a day, this should be fine
;-)
Fixes#166.
Include information about who changed the build status in notification
emails, and enable optional per-input notification of said committers.
Conflicts due to two branches modifying the database schema.
Signed-off-by: Shea Levy <shea@shealevy.com>
Conflicts:
src/lib/Hydra/Schema/Jobsets.pm
src/sql/upgrade-23.sql
There are jobsets that are evaluated only once, that is, after they've
been evaluated, they're disabled automatically. This is primarily
useful for doing releases: for instance, doing an evaluation with
"officialRelease" set to "true" should be done only once.
If there are builds in the queue that depend on another scheduled
build, then hydra-queue-runner will start the dependency first and
block the dependent builds. This is implemented in
findBuildDependencyInQueue. However, if there are tens of thousands
of such dependent builds, since each call to
findBuildDependencyInQueue may take a second or so, hydra-queue-runner
will spend hours just deciding which builds *not* to do. Thus very
little progress is made.
So now, when a build is started, we immediately check which builds are
"blocked" by it (i.e. depend on it), and remove such builds from
consideration.
Pick the jobset that has used the smallest fraction of its share,
rather than the jobset furthest below its share in absolute terms.
This gives jobsets with a small share a quicker start (but they
will also run out of their share quicker).
Each jobset now has a "scheduling share" that determines how much of
the build farm's time it is entitled to. For instance, if a jobset
has 100 shares and the total number of shares of all jobsets is 1000,
it's entitled to 10% of the build farm's time. When there is a free
build slot for a given system type, the queue runner will select the
jobset that is furthest below its scheduling share over a certain time
window (currently, the last day). Withing that jobset, it will pick
the build with the highest priority.
So meta.schedulingPriority now only determines the order of builds
within a jobset, not between jobsets. This makes it much easier to
prioritise one jobset over another (e.g. nixpkgs:trunk over
nixpkgs:stdenv).
In your hydra config, you can add an arbitrary number of <s3config>
sections, with the following options:
* name (required): Bucket name
* jobs (required): A regex to match job names (in project:jobset:job
format) that should be backed up to this bucket
* compression_type: bzip2 (default), xz, or none
* prefix: String to prepend to all hydra-created s3 keys (if this is
meant to represent a directory, you should include the trailing slash,
e.g. "cache/"). Default "".
After each build with an output (i.e. successful or failed-with-output
builds), the output path and its closure are uploaded to the bucket as
.nar files, with corresponding .narinfos to enable use as a binary
cache.
This plugin requires that s3 credentials be available. It uses
Net::Amazon::S3, which as of this commit the nixpkgs version can
retrieve s3 credentials from the AWS_ACCESS_KEY_ID and
AWS_SECRET_ACCESS_KEY environment variables, or from ec2 instance
metadata when using an IAM role.
This commit also adds a hydra-s3-backup-collect-garbage program, which
uses hydra's gc roots directory to determine which paths are live, and
then deletes all files except nix-cache-info and any .nar or .narinfo
files corresponding to live paths. hydra-s3-backup-collect-garbage
respects the prefix configuration option, so it won't delete anything
outside of the hierarchy you give it, and it has the same credential
requirements as the plugin. Probably a timer unit running the garbage
collection periodically should be added to hydra-module.nix
Note that two of the added tests fail, due to a bug in the interaction
between Net::Amazon::S3 and fake-s3. Those behaviors work against real
s3 though, so I'm committing this even with the broken tests.
Signed-off-by: Shea Levy <shea@shealevy.com>
We now keep *all* unfinished evaluations of a jobset, in addition to
the <keepnr> most recent finished evaluations.
The main motivation is to ensure that mirror-{nixos,nixpkgs} work
properly: if building an evaluation takes too long, some of its builds
may already have been garbage-collected by the time the others finish.
We had Postgres barfing with this error:
DBIx::Class::Storage::DBI::_dbh_execute(): DBI Exception: DBD::Pg::st execute failed: ERROR: stack depth limit exceeded
because the ‘drvpath => [ @dependentDrvs ]’ in failDependents can
cause a query of unbounded size. (In this specific case there was a
failure of Bison, which has > 10000 dependent derivations.) So now we
just get all scheduled builds from the DB.
Aggregate constituents are derivations. However there can be multiple
builds in an evaluation that have the same derivation, i.e. they can
alias each other (e.g. "emacs", "emacs24" and "emacs24Packages.emacs"
in Nixpkgs). Previously we picked a build arbitrarily for the
AggregateConstituents table. Now we pick the one with the shortest
name (e.g. "emacs").
We now keep all builds in the N most recent evaluations of a jobset,
rather than the N most recent builds of every job. Note that this
means that typically fewer builds will be kept (since jobs may be
unchanged across evaluations).
For presentation purposes, we need to know what builds are part of an
aggregate build. So at evaluation time, look at the "members"
attribute, find the corresponding builds in the eval, and create a
mapping in the AggregateMembers table.
The NrBuilds table tracks the value of ‘select count(*) from Builds
where finished = 0’, keeping it up to date via a trigger. This is
necessary to make the /all page fast, since otherwise it needs to do a
sequential scan on the Builds table.
Samuel Dionne-Riel