The queue runner can now run up to ‘max-concurrent-notifications’ in
parallel (default is 2). This is useful when some hydra-notify
invocations can take a long time to complete (e.g. because they need
to compress a giant build log) and we don't want this to block all
other notifications.
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 plugin will post to the build status system in BitBucket. In order
to use it you need to add to ExtraConfig
<bitbucket>
username = bitbucket_username
password = bitbucket_password
</bitbucket>
You can use an application password https://blog.bitbucket.org/2016/06/06/app-passwords-bitbucket-cloud/
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.
This can be used with declarative projects to build PRs.
The github_authorization section should contain verbatim Authorization header contents keyed by repo owner for private repos
1. From the hydra configuration file.
The configuration is loaded from the "git-input" block.
Currently only the "timeout" variable is been looked up in the file.
<git-input>
# general timeout
timeout = 400
<input-name>
# specific timeout for a particular input name
timeout = 400
</input-name>
# use quotes when the input name has spaces
<"foot with spaces">
# specific timeout for a particular input name
timeout = 400
</"foo with spaces">
</git-input>
2. As an argument in the input value after the repo url and branch (and after the deepClone if is defined)
"timeout=<value>"
The preference on which value is used:
1. input value
2. Block with the name of the input in the <git-input> block
3. "timeout" inside the <git-input> block
4. Default value of 600 seconds. (original hard-coded value)
The code is generalized for more values to be configured, it might be too much
for a single value on a single plugin.
Adding a 96-core aarch64 build machine to the build farm caused the
potential number of database connections to increase a lot, so we
started hitting the Postgres connection limit.
* 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.
Setting
xxx-jobset-repeats = patchelf:master:2
will cause Hydra to perform every build step in the specified jobset 2
additional times (i.e. 3 times in total). Non-determinism is not fatal
unless the derivation has the attribute "isDeterministic = true"; we
just note the lack of determinism in the Hydra database. This will
allow us to get stats about the (lack of) reproducibility of all of
Nixpkgs.
Builds can now specify the attribute "isDeterministic = true" to tell
Hydra to build with build-repeat > 0. If there is a mismatch between
rounds, the step / build fails with a suitable status.
Maybe this should be a meta attribute, but that makes it invisible to
hydra-queue-runner, and it seems reasonable to make a claim of
mandatory determinism part of the derivation (since e.g. enabling this
flag should trigger a rebuild).
We now take into account the memory necessary for compressing the NAR
being exported to the binary cache, plus xz compression overhead.
Also, we now release the memory tokens for the NAR accessor *after*
releasing the NAR accessor. Previously the memory for the NAR accessor
might still be in use while another thread does an allocation, causing
the maximum to be exceeded temporarily.
Also, use notify_all instead of notify_one to wake up memory token
waiters. This is not very nice, but not every waiter is requesting the
same number of tokens, so some might be able to proceed.
If a step is cancelled just as its builder step is starting,
doBuildStep() will return sRetry. This causes builder() to make the
step runnable again, since the queue monitor may have added new builds
referencing it. The idea is that if the latter condition is not true,
the step's reference count will drop to zero and it will be
deleted. However, if the dispatcher thread sees and locks the step
before the reference count can drop to zero in the builder thread, the
dispatcher thread will start a new builder thread for the step. Thus
the step can be kept alive for an indefinite amount of time.
The fix is for State::builder() to use a weak pointer to the step, to
ensure that the step's reference count can drop to zero *before* it's
added to the runnable queue.
This was a bad idea because pthread_cancel() is unsalvageable broken
in C++. Destructors are not allowed to throw exceptions (especially in
C++11), but pthread_cancel() can cause a __cxxabiv1::__forced_unwind
exception inside any destructor that invokes a cancellation
point. (This exception can be caught but *must* be rethrown.) So let's
just kill the builder process instead.
It was hitting
assert(reservation.unique());
Since we do want the machine reservation to be released before calling
wakeDispatcher(), let's use a different object for keeping track of
active steps.
We now kill active build steps when there are no more referring
builds. This is useful e.g. for preventing cancelled multi-hour TPC-H
benchmark runs from hogging build machines.
If two active steps of the same build failed, then the first would be
marked as "failed", but the second would end up as "orphaned", causing
it to be marked as "aborted" later on. Now it's correctly marked as
"failed".
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.
