def test_listRunnable(self):
arr = [("ready", Job.READY), ("running", Job.RUNNING), ("finished", Job.FINISHED),
("running", Job.RUNNING), ("delayed", Job.DELAYED)]
for name, status in arr:
job = Job.create(db.session, **self.opts)
job.name = name
job.status = status
if status is Job.DELAYED:
job.submittime = job.submittime - 10000
job.priority = job.submittime / 1000L
db.session.commit()
jobs = Job.listRunnable(db.session, 5, utils.currentTimeMillis())
self.assertEqual(len(jobs), 2)
self.assertEqual([x.name for x in jobs], ["delayed", "ready"])
self.assertEqual([x.status for x in jobs], [Job.DELAYED, Job.READY])
def action(sampler):
if not sampler:
scheduler.logger.error("Sampler is undefined, exiting")
return
session = SignallingSession(db)
try:
sampler.logger.info("Start refreshing application state")
sampler.incrementNumRuns()
lock.acquire()
for uid, pid in sampler.pool.items():
if updateProcessStatus(pid) >= 0:
job = Job.get(session, uid)
if not job:
sampler.logger.warn("Job '%s' does not exist in database, updated skipped", uid)
else:
Job.finish(session, job)
sampler.removeFromPool(uid)
else:
sampler.logger.info("Process '%s' is still running, job uid: '%s'", pid, uid)
# Check how many pids are left. Compare against NUM_SLOTS, if comparison yields false,
# skip execution, otherwise it yields true, and we proceed with number of free slots
freeSlots = NUM_SLOTS - len(sampler.pool)
if freeSlots <= 0:
sampler.logger.info("All %s slots are taken, cannot launch job, skipped", NUM_SLOTS)
sampler.logger.debug("Free slots: %s, pool size: %s, numSlots: %s", freeSlots,
len(sampler.pool), NUM_SLOTS)
else:
# Check how many jobs are running at the moment by checking status of the cluster and
# requesting number of running applications, if number of applications is equal or more
# than NUM_SLOTS, skip execution, otherwise compute number of jobs to launch and proceed.
sparkStatus = sparkContext.clusterStatus()
if sparkStatus == DOWN:
sampler.logger.info("Cluster %s[%s] is down, will try again later",
sparkContext.getMasterAddress(), sparkContext.getUiAddress())
else:
apps = sparkContext.clusterRunningApps()
freeSlots = NUM_SLOTS - len(apps)
if freeSlots <= 0:
sampler.logger.info("There are %s applications running already, cannot " + \
"launch job, skipped", len(apps))
sampler.logger.debug("Free slots: %s, apps: %s, numSlots: %s", freeSlots,
len(apps), NUM_SLOTS)
else:
# Fetch jobs active (runnable) jobs using Job API based on number of free slots,
# acquired earlier. Start jobs in the list, if any. Report when no jobs found.
currentTime = utils.currentTimeMillis()
sampler.logger.debug("Fetch jobs with session %s, free slots %s, time %s",
session, freeSlots, currentTime)
runnableJobs = Job.listRunnable(session, freeSlots, currentTime)
sampler.logger.info("Registering %s jobs", len(runnableJobs))
for job in runnableJobs:
pid = launchSparkJob(job)
Job.run(session, job)
sampler.addToPool(job.uid, pid)
session.commit()
except Exception as e:
sampler.logger.error("Sampler encountered error, execution skipped")
sampler.logger.exception(e.message)
finally:
lock.release()
session.close()
if sampler.enabled:
sampler.logger.debug("Prepared to be invoked in %s seconds", sampler.interval)
timer = Timer(sampler.interval, action, [sampler])
timer.daemon = True
timer.start()
else:
sampler.logger.info("Sampler stopped")
