The spread iterator can panic when processing an evaluation, resulting
in an unrecoverable state in the cluster. Whenever a panicked server
restarts and quorum is restored, the next server to dequeue the
evaluation will panic.
To trigger this state:
* The job must have `max_parallel = 0` and a `canary >= 1`.
* The job must not have a `spread` block.
* The job must have a previous version.
* The previous version must have a `spread` block and at least one
failed allocation.
In this scenario, the desired changes include `(place 1+) (stop
1+), (ignore n) (canary 1)`. Before the scheduler can place the canary
allocation, it tries to find out which allocations can be
stopped. This passes back through the stack so that we can determine
previous-node penalties, etc. We call `SetJob` on the stack with the
previous version of the job, which will include assessing the `spread`
block (even though the results are unused). The task group spread info
state from that pass through the spread iterator is not reset when we
call `SetJob` again. When the new job version iterates over the
`groupPropertySets`, it will get an empty `spreadAttributeMap`,
resulting in an unexpected nil pointer dereference.
This changeset resets the spread iterator internal state when setting
the job, logging with a bypass around the bug in case we hit similar
cases, and a test that panics the scheduler without the patch.
When the scheduler picks a node for each evaluation, the
`LimitIterator` provides at most 2 eligible nodes for the
`MaxScoreIterator` to choose from. This keeps scheduling fast while
producing acceptable results because the results are binpacked.
Jobs with a `spread` block (or node affinity) remove this limit in
order to produce correct spread scoring. This means that every
allocation within a job with a `spread` block is evaluated against
_all_ eligible nodes. Operators of large clusters have reported that
jobs with `spread` blocks that are eligible on a large number of nodes
can take longer than the nack timeout to evaluate (60s). Typical
evaluations are processed in milliseconds.
In practice, it's not necessary to evaluate every eligible node for
every allocation on large clusters, because the `RandomIterator` at
the base of the scheduler stack produces enough variation in each pass
that the likelihood of an uneven spread is negligible. Note that
feasibility is checked before the limit, so this only impacts the
number of _eligible_ nodes available for scoring, not the total number
of nodes.
This changeset sets the iterator limit for "large" `spread` block and
node affinity jobs to be equal to the number of desired
allocations. This brings an example problematic job evaluation down
from ~3min to ~10s. The included tests ensure that we have acceptable
spread results across a variety of large cluster topologies.
* use msgtype in upsert node
adds message type to signature for upsert node, update tests, remove placeholder method
* UpsertAllocs msg type test setup
* use upsertallocs with msg type in signature
update test usage of delete node
delete placeholder msgtype method
* add msgtype to upsert evals signature, update test call sites with test setup msg type
handle snapshot upsert eval outside of FSM and ignore eval event
remove placeholder upsertevalsmsgtype
handle job plan rpc and prevent event creation for plan
msgtype cleanup upsertnodeevents
updatenodedrain msgtype
msg type 0 is a node registration event, so set the default to the ignore type
* fix named import
* fix signature ordering on upsertnode to match
