def _create_job(self, job_id, data):
query = Job.query.options(load_only('id', 'job_id'))
query = query.filter_by(job_id=job_id, run=self.run)
if query.first():
error('/errors/invalid/',
"job with job_id %s already exists" % job_id)
else:
log.info("Creating job: %s/%s", data.get('name', '<no name!>'),
job_id)
self.job = Job(data, self.run)
Session.commit()
return self.job
def index_post(self):
"""
We update a job here, it should obviously exist already but most likely
the data is empty.
"""
if not self.job:
error('/errors/not_found/',
'attempted to update a non-existent job')
old_job_status = self.job.status
self.job.update(request.json)
Session.commit()
if self.job.status != old_job_status:
log.info("Job %s/%s status changed from %s to %s", self.job.name,
self.job.job_id, old_job_status, self.job.status)
return dict()
def job_stats(self, machine_type="", since_days=14):
since_days = int(since_days)
if since_days < 1:
error("/errors/invalid/", "since_days must be a positive integer")
now = datetime.utcnow()
past = now - timedelta(days=since_days)
recent_jobs = Job.query.filter(Job.posted.between(past, now)).subquery()
RecentJob = aliased(Job, recent_jobs)
query = Session.query(Node.name, RecentJob.status, func.count("*"))
if machine_type:
# Note: filtering by Job.machine_type (as below) greatly improves
# performance but could lead slightly incorrect values if many jobs
# are being scheduled using mixed machine types. We work around
# this by including the 'multi' machine type (which is the name of
# the queue Inktank uses for such jobs.
query = query.filter(RecentJob.machine_type.in_((machine_type, "multi")))
query = query.filter(Node.machine_type == machine_type)
query = query.join(RecentJob.target_nodes).group_by(Node).group_by(RecentJob.status)
all_stats = {}
results = query.all()
for (name, status, count) in results:
node_stats = all_stats.get(name, {})
node_stats[status] = count
all_stats[name] = node_stats
stats_sorter = lambda t: sum(t[1].values())
ordered_stats = OrderedDict(sorted(all_stats.items(), key=stats_sorter))
return ordered_stats
def update(self, values):
"""
:param values: a dict.
"""
self._check_for_update(values)
was_locked = self.locked
for k, v in values.items():
if k in self.allowed_update_keys:
if k == 'vm_host':
vm_host_name = v
query = self.query.filter(Node.name == vm_host_name)
v = query.one()
setattr(self, k, v)
if 'locked' in values:
if self.locked != was_locked:
self.locked_since = datetime.utcnow() if self.locked else None
if not self.locked:
self.locked_by = None
Session.flush()
def job_stats(self, machine_type='', since_days=14):
since_days = int(since_days)
if since_days < 1:
error('/errors/invalid/', "since_days must be a positive integer")
now = datetime.utcnow()
past = now - timedelta(days=since_days)
recent_jobs = Job.query.filter(Job.posted.between(past,
now)).subquery()
RecentJob = aliased(Job, recent_jobs)
query = Session.query(Node.name, RecentJob.status, func.count('*'))
if machine_type:
# Note: filtering by Job.machine_type (as below) greatly improves
# performance but could lead slightly incorrect values if many jobs
# are being scheduled using mixed machine types. We work around
# this by including the 'multi' machine type (which is the name of
# the queue Inktank uses for such jobs.
query = query.filter(
RecentJob.machine_type.in_((machine_type, 'multi')))
query = query.filter(Node.machine_type == machine_type)
query = query.join(RecentJob.target_nodes).group_by(Node)\
.group_by(RecentJob.status)
all_stats = {}
results = query.all()
for (name, status, count) in results:
node_stats = all_stats.get(name, {})
node_stats[status] = count
all_stats[name] = node_stats
stats_sorter = lambda t: sum(t[1].values())
ordered_stats = OrderedDict(sorted(all_stats.items(),
key=stats_sorter))
return ordered_stats
def index(self):
query = Session.query(Run).join(Job).filter(Job.status == 'queued')\
.group_by(Run).order_by(Run.scheduled)
return query.all()
def _create_run(cls, name):
log.info("Creating run: %s", name)
Session.flush()
return Run(name)
def index(self):
query = Session.query(Run).join(Job).filter(Job.status == 'queued')\
.group_by(Run).order_by(Run.scheduled)
return query.all()
def update(self, json_data):
self.set_or_update(json_data)
Session.flush()