def test_db_all_in_one_quotas_2(monkeypatch):
"""
quotas[queue, project, job_type, user] = [int, int, float];
| | |
maximum used resources ----------+ | |
maximum number of running jobs -------+ |
maximum resources times (hours) ------------+
"""
create_quotas_rules_file('{"quotas": {"*,*,*,/": [-1, 1, -1]}}')
# Submit and allocate an Advance Reservation
t0 = get_date()
insert_and_sched_ar(t0 + 100)
# Submit other jobs
insert_job(res=[(100, [('resource_id=1', "")])], properties="", user="******")
insert_job(res=[(200, [('resource_id=1', "")])], properties="", user="******")
# pdb.set_trace()
t1 = get_date()
meta_schedule('internal')
res = []
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time - t1)
res.append(i.start_time - t1)
assert (res[1] - res[0]) == 120
assert (res[2] - res[0]) == 280
def test_db_all_in_one_BE_to_kill(monkeypatch):
os.environ['USER'] = '******' # to allow fragging
db['Queue'].create(name='besteffort', priority=3, scheduler_policy='kamelot', state='Active')
insert_job(res=[(100, [('resource_id=2', "")])], queue_name='besteffort', types=['besteffort'])
meta_schedule('internal')
job = db['Job'].query.one()
assert (job.state == 'toLaunch')
insert_job(res=[(100, [('resource_id=5', "")])])
meta_schedule('internal')
jobs = db['Job'].query.all()
print(jobs[0].state, jobs[1].state)
print("frag...", db['FragJob'].query.one())
frag_job = db['FragJob'].query.one()
assert jobs[0].state == 'toLaunch'
assert jobs[1].state == 'Waiting'
assert frag_job.job_id == jobs[0].id
def minimal_db_initialization(request):
with db.session(ephemeral=True):
for i in range(5):
db['Resource'].create(network_address="localhost")
for i in range(5):
insert_job(res=[(60, [('resource_id=2', "")])], properties="")
yield
def insert_and_sched_ar(start_time, walltime=60):
insert_job(res=[(walltime, [('resource_id=4', "")])],
reservation='toSchedule', start_time=start_time,
info_type='localhost:4242')
meta_schedule('internal')
return (db['Job'].query.one())
def test_db_all_in_one_BE(monkeypatch):
db['Queue'].create(name='besteffort', priority=3, scheduler_policy='kamelot', state='Active')
insert_job(res=[(100, [('resource_id=1', "")])], queue_name='besteffort', types=['besteffort'])
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
assert (job.state == 'toLaunch')
def test_suspend_resume_1(monkeypatch):
# now = get_date()
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
set_job_state(job.id, 'Resuming')
job = db['Job'].query.one()
print(job.state)
meta_schedule('internal')
assert(job.state == 'Resuming')
def test_db_all_in_one_AR_7(monkeypatch):
now = get_date()
insert_job(res=[(60, [('resource_id=4', "")])],
reservation='toSchedule', start_time=now+10,
info_type='localhost:4242', types=["timesharing=*,*"])
meta_schedule('internal')
job = db['Job'].query.one()
assert ((job.state == 'Waiting') and (job.reservation == 'Scheduled'))
def test_suspend_resume_2(monkeypatch):
config['JUST_BEFORE_RESUME_EXEC_FILE'] = 'sleep 2'
# now = get_date()
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
set_job_state(job.id, 'Resuming')
job = db['Job'].query.one()
print(job.state)
meta_schedule('internal')
assert(job.state == 'Resuming')
def test_db_all_in_one_simple_interactive_waiting_1(monkeypatch):
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
insert_job(res=[(60, [('resource_id=4', "")])], properties="", job_type='INTERACTIVE',
info_type="0.0.0.0:1234")
meta_schedule('internal')
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time)
jobs = db['Job'].query.order_by(db['Job'].id).all()
assert (jobs[0].state == 'toLaunch')
assert (jobs[1].state == 'Waiting')
def test_db_all_in_one_simple_1(monkeypatch):
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
job = db['Job'].query.one()
print('job state:', job.state)
# pdb.set_trace()
meta_schedule('internal')
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time)
job = db['Job'].query.one()
print(job.state)
assert (job.state == 'toLaunch')
def test_treematch(monkeypatch):
insert_job(res=[(60, [('resource_id=4', "")])], properties="",
types=["find=treematch:matrix_file"])
job = db['Job'].query.one()
print('job state:', job.state)
meta_schedule('internal')
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ',
i.start_time)
job = db['Job'].query.one()
print(job.state)
assert (job.state == 'toLaunch')
def test_db_moldable_2(monkeypatch):
now = get_date()
insert_job(res=[(60, [('resource_id=3', "")])], properties="")
insert_job(res=[(60, [('resource_id=4', "")]), (70, [('resource_id=2', "")])], properties="")
meta_schedule('internal')
for j in db['Job'].query.all():
print(j.state)
res = []
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time - now)
res.append(i.start_time - now)
assert res[0] == res[1]
def test_db_koa_simple_1(monkeypatch):
insert_job(res=[(60, [("resource_id=4", "")])], properties="")
job = db["Job"].query.one()
print("job state:", job.state)
# pdb.set_trace()
main()
for i in db["GanttJobsPrediction"].query.all():
print("moldable_id: ", i.moldable_id, " start_time: ", i.start_time)
job = db["Job"].query.one()
print(job.state)
assert job.state == "toLaunch"
def test_db_placeholder_2(monkeypatch):
now = get_date()
insert_job(res=[(60, [('resource_id=4', "")])], properties="", types=["placeholder=yop"])
insert_job(res=[(60, [('resource_id=4', "")])], properties="", types=["allow=poy"])
meta_schedule('internal')
for j in db['Job'].query.all():
print(j.state)
res = []
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time - now)
res.append(i.start_time - now)
assert res[0] != res[1]
def test_db_metasched_simple_1(monkeypatch):
print("DB_BASE_FILE: ", config["DB_BASE_FILE"])
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
job = db['Job'].query.one()
print('job state:', job.state)
meta_schedule()
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time)
job = db['Job'].query.one()
print(job.state)
assert (job.state == 'toLaunch')
def test_db_all_in_one_wakeup_node_energy_saving_internal_1(monkeypatch):
config['ENERGY_SAVING_INTERNAL'] = 'yes'
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
now = get_date()
# Suspend nodes
db.query(Resource).update({Resource.state: 'Absent', Resource.available_upto: now + 1000},
synchronize_session=False)
db.commit()
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
print(node_list)
assert (job.state == 'Waiting')
def test_db_metasched_ar_1(monkeypatch):
# add one job
now = get_date()
# sql_now = local_to_sql(now)
insert_job(res=[(60, [('resource_id=4', "")])], properties="",
reservation='toSchedule', start_time=(now + 10),
info_type='localhost:4242')
meta_schedule()
job = db['Job'].query.one()
print(job.state, ' ', job.reservation)
assert ((job.state == 'Waiting') and (job.reservation == 'Scheduled'))
def test_db_kamelot_fifo_no_hierarchy():
# add some resources
for i in range(5):
db['Resource'].create(network_address="localhost")
for i in range(5):
insert_job(res=[(60, [('resource_id=2', "")])], properties="")
main()
req = db['GanttJobsPrediction'].query.all()
# for i, r in enumerate(req):
# print "req:", r.moldable_id, r.start_time
assert len(req) == 2
def test_db_all_in_one_wakeup_node_1(monkeypatch):
insert_job(res=[(60, [('resource_id=4', "")])], properties="")
now = get_date()
# Suspend nodes
db.query(Resource).update({Resource.state: 'Absent', Resource.available_upto: now + 1000},
synchronize_session=False)
db.commit()
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
print(node_list)
assert (job.state == 'Waiting')
assert (node_list == [u'localhost0', u'localhost1'])
def test_db_timesharing_2(monkeypatch):
now = get_date()
insert_job(res=[(60, [('resource_id=4', "")])], properties="",
types=["timesharing=user,*"], user='******')
insert_job(res=[(60, [('resource_id=4', "")])], properties="",
types=["timesharing=user,*"], user='******')
meta_schedule('internal')
for j in db['Job'].query.all():
print(j.state)
res = []
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time - now)
res.append(i.start_time - now)
assert res[0] != res[1]
def test_db_all_in_one_sleep_node_1(monkeypatch):
now = get_date()
insert_job(res=[(60, [('resource_id=1', "")])], properties="")
# Suspend nodes
# pdb.set_trace()
db.query(Resource).update({Resource.available_upto: now + 50000},
synchronize_session=False)
db.commit()
meta_schedule('internal')
job = db['Job'].query.one()
print(job.state)
print(node_list)
assert (job.state == 'toLaunch')
assert (node_list == [u'localhost2', u'localhost1'] or
node_list == [u'localhost1', u'localhost2'])
def test_db_all_in_one_BE_2(monkeypatch):
# TODO TOFINISH
db['Queue'].create(name='besteffort', priority=3, scheduler_policy='kamelot', state='Active')
insert_job(res=[(100, [('resource_id=1', "")])], queue_name='besteffort',
types=['besteffort', "timesharing=*,*"])
meta_schedule('internal')
job = db['Job'].query.one()
set_job_state(job.id, 'Running')
insert_job(res=[(50, [('resource_id=1', "")])], types=["timesharing=*,*"])
meta_schedule('internal')
jobs = db['Job'].query.all()
print(jobs[1].id, jobs[1].state)
# assert (jobs[1].state == 'toLaunch')
assert (jobs[1].state == 'Waiting')
def test_db_all_in_one_quotas_1(monkeypatch):
"""
quotas[queue, project, job_type, user] = [int, int, float];
| | |
maximum used resources ----------+ | |
maximum number of running jobs -------+ |
maximum resources times (hours) ------------+
"""
create_quotas_rules_file('{"quotas": {"*,*,*,/": [-1, 1, -1], "/,*,*,*": [-1, -1, 0.55]}}')
insert_job(res=[(100, [('resource_id=1', "")])], properties="", user="******")
insert_job(res=[(200, [('resource_id=1', "")])], properties="", user="******")
insert_job(res=[(200, [('resource_id=1', "")])], properties="", user="******")
# pdb.set_trace()
now = get_date()
meta_schedule('internal')
res = []
for i in db['GanttJobsPrediction'].query.order_by(GanttJobsPrediction.moldable_id).all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time - now)
res.append(i.start_time - now)
assert res == [0, 160, 420]
def test_db_kamelot_fifo_w_hierarchy():
# add some resources
for i in range(5):
db['Resource'].create(network_address="localhost" + str(int(i / 2)))
for res in db['Resource'].query.all():
print(res.id, res.network_address)
for i in range(5):
insert_job(res=[(60, [('network_address=1', "")])],
properties="")
plt = Platform()
schedule_fifo_cycle(plt, "default", True)
req = db['GanttJobsPrediction'].query.all()
# for i, r in enumerate(req):
# print("req:", r.moldable_id, r.start_time)
assert len(req) == 3
def test_db_job_sorting_simple_priority_no_waiting_time():
config['JOB_SORTING'] = "simple_priority"
plt = Platform()
now = plt.get_time()
# add some resources
for i in range(4):
db['Resource'].create(network_address="localhost")
# add some job with priority
for i in range(10):
priority = str(float(i)/10.0)
insert_job(res=[(60, [('resource_id=4', "")])],
submission_time=now,
types=['priority='+priority])
schedule_cycle(plt, plt.get_time())
req = db['GanttJobsPrediction'].query\
.order_by(db['GanttJobsPrediction'].start_time)\
.all()
flag = True
print(req)
for r in req:
print(r.moldable_id, r.start_time)
for i, r in enumerate(req):
if i != 0:
print(r.moldable_id, prev_id)
if r.moldable_id > prev_id:
flag = False
break
prev_id = r.moldable_id
assert flag
def test_db_extra_metasched_1():
config['EXTRA_METASCHED'] = 'foo'
insert_job(res=[(60, [('resource_id=1', "")])], properties="deploy='YES'")
insert_job(res=[(60, [('resource_id=1', "")])], properties="deploy='FOO'")
insert_job(res=[(60, [('resource_id=1', "")])], properties="")
for job in db['Job'].query.all():
print('job state:', job.state, job.id)
meta_schedule()
for i in db['GanttJobsPrediction'].query.all():
print("moldable_id: ", i.moldable_id, ' start_time: ', i.start_time)
states = [job.state for job in db['Job'].query.order_by(Job.id).all()]
print(states)
assert states == ['toLaunch', 'Waiting', 'toLaunch']
def test_db_suspended_duration_1(monkeypatch):
insert_job(res=[(60, [('resource_id=3', "")])], properties="", suspended='YES')
meta_schedule('internal')
job = db['Job'].query.one()
assert (job.state == 'toLaunch')
def bataar(wkp_filename, database_mode, socket, node_size, scheduler_policy, types, scheduler_delay):
# import pdb; pdb.set_trace()
if database_mode == 'memory':
config.clear()
config.update(BATSIM_DEFAULT_CONFIG)
assign = False
assign_func = None
find = False
find_func = None
add_1h = False # control addition of one level of hierarchy in resources' request
add_mld = False # control addition of one modldable instance in resources' request
sp = scheduler_policy
if sp == 'BASIC' or sp == '0':
print("BASIC scheduler_policy selected")
# default
pass
elif sp == 'BEST_EFFORT_CONTIGUOUS' or sp == '1':
print("BEST_EFFORT_CONTIGUOUS scheduler_policy selected")
find = True
find_func = getattr(oar.kao.advanced_scheduling, 'find_contiguous_1h')
assign = True
assign_func = getattr(oar.kao.advanced_scheduling, 'assign_one_time_find')
elif sp == 'CONTIGUOUS' or sp == '2':
print("CONTIGUOUS scheduler_policy selected")
find = True
find_func = getattr(oar.kao.advanced_scheduling, 'find_contiguous_1h')
elif sp == 'BEST_EFFORT_LOCAL' or sp == '3':
print("BEST_EFFORT_LOCAL scheduler_policy selected")
add_1h = True
add_mld = True
elif sp == 'LOCAL' or sp == '4':
print("LOCAL scheduler_policy selected")
add_1h = True
#
# Load workload
#
json_jobs, nb_res = load_json_workload_profile(wkp_filename)
print("nb_res:", nb_res)
if types and types != '':
types_array = types.split(',')
for type_value in types_array:
t, v = type_value.split('=')
if t == "assign":
print("type assign with function: ", v)
assign = True
assign_func = getattr(oar.kao.advanced_scheduling, 'assign_' + v)
if t == "find":
print("type find with function: ", v)
find = True
find_func = getattr(oar.kao.advanced_scheduling, 'find_' + v)
if database_mode == 'no-db':
#
# generate ResourceSet
#
hy_resource_id = [[(i, i)] for i in range(1,nb_res+1)]
hierarchy = {'resource_id': hy_resource_id}
if node_size > 0:
node_id = [[(node_size*i, node_size*(i+1)-1)] for i in range(int(nb_res/node_size))]
hierarchy['node'] = node_id
print('hierarchy: ', hierarchy)
res_set = ResourceSetSimu(
rid_i2o=range(nb_res+1),
rid_o2i=range(nb_res+1),
roid_itvs=[(1, nb_res)],
hierarchy=hierarchy,
available_upto={2147483600: [(1, nb_res)]}
)
#
# prepare jobs
#
mld_id = 1
print("Genererate jobs")
for j in json_jobs:
jid = int(j['id'])
walltime = int(math.ceil(float(j["walltime"])))
rqb = [([('resource_id', j['res'])], [(1, nb_res)])]
rqbh = [([('node', 1), ('resource_id', j['res'])], [(1, nb_res)])]
if add_1h:
if add_mld:
mld_res_rqts = [(mld_id, walltime, rqbh), (mld_id+1, walltime, rqb)]
mld_id += 2
else:
mld_res_rqts = [(mld_id, walltime, rqbh)]
mld_id += 1
else:
if add_mld:
mld_res_rqts = [(mld_id, walltime, rqb), (mld_id+1, walltime, rqb)]
mld_id += 2
else:
mld_res_rqts = [(mld_id, walltime, rqb)]
mld_id += 1
jobs[jid] = JobSimu(id=jid,
state="Waiting",
queue="test",
start_time=0,
walltime=0,
types={},
res_set=[],
moldable_id=0,
mld_res_rqts=mld_res_rqts,
run_time=0,
deps=[],
key_cache={},
ts=False, ph=0,
assign=assign, assign_func=assign_func,
find=find, find_func=find_func)
# print("jobs: ", jid, " mld_res_rqts: ", mld_res_rqts)
# import pdb; pdb.set_trace()
BatSched(res_set, jobs, 'simu', {}, scheduler_delay, socket).run()
elif database_mode == 'memory':
global offset_idx
offset_idx = 1
monkeypatch_oar_lib_tools()
db_initialization(nb_res)
#
# prepare jobs
#
db_jid2s_jid = {}
print("Prepare jobs")
for i, j in enumerate(json_jobs):
jid = int(j["id"])
walltime = int(math.ceil(float(j["walltime"])))
jobs[jid] = JobSimu(id=jid,
state="Waiting",
queue="test",
start_time=0,
walltime=0,
moldable_id=0,
mld_res_rqts=[(jid, walltime,
[([("resource_id", j["res"])],
[(1, nb_res - 0)])])],
run_time=0,
db_jid=i + 1,
assign=False,
find=False)
insert_job(res=[(walltime, [('resource_id=' + str(j["res"]), "")])],
state='Hold', properties='', user='')
db_jid2s_jid[i + 1] = jid
db.flush() # TO REMOVE ???
# import pdb; pdb.set_trace()
BatSched([], jobs, 'batsim-db', db_jid2s_jid, scheduler_delay, socket).run()
if __name__ != '__main__':
# If used oar.lib.tools' functions are used after we need to undo monkeypatching.
# Main use case is suite testing evaluation
restore_oar_lib_tools()
