class TestClusterBatchScheduling(unittest.TestCase):
def setUp(self) -> None:
"""
Batch scheduling setup
"""
self.env = simpy.Environment()
config = Config(CONFIG)
self.cluster = Cluster(env=self.env, config=config)
self.telescope = Telescope(self.env,
config,
planner=None,
scheduler=None)
self.observation = self.telescope.observations[0]
def test_provision_resources(self):
"""
Test that resource provisioning occurs and the right number of
resources exist in the right place
Returns
-------
"""
provision_size = 5
self.cluster.provision_batch_resources(provision_size,
self.observation)
self.assertEqual(5, len(self.cluster.get_available_resources()))
self.assertEqual(
5, len(self.cluster.get_idle_resources(self.observation)))
self.assertListEqual(self.cluster._get_batch_observations(),
[self.observation])
def test_batch_removal(self):
provision_size = 5
self.cluster.provision_batch_resources(provision_size,
self.observation)
self.cluster.release_batch_resources(self.observation)
self.assertListEqual([],
self.cluster.get_idle_resources(self.observation))
self.assertEqual(10, len(self.cluster.get_available_resources()))
def tearDown(self) -> None:
"""
TODO
Batch scheduling tear down
"""
pass
class TestBatchSchedulerAllocation(unittest.TestCase):
def setUp(self):
self.algorithm = BatchProcessing
self.env = simpy.Environment()
config = Config(CONFIG)
self.cluster = Cluster(self.env, config=config)
self.buffer = Buffer(self.env, self.cluster, config)
self.scheduler = Scheduler(self.env, self.buffer, self.cluster,
DynamicAlgorithmFromPlan())
self.algorithm = BatchProcessing()
self.model = BatchPlanning('batch')
self.planner = Planner(
self.env,
'heft',
self.cluster,
self.model,
)
self.telescope = Telescope(self.env, config, self.planner,
self.scheduler)
def test_resource_provision(self):
"""
Given a max_resource_split of 2, and total machines of 10, we should
provision a maximum of 5 machines within the cluster (
max_resource_split being the number of parallel provision ings we can
make).
Returns
-------
"""
self.assertEqual(10, len(self.cluster.get_available_resources()))
def test_max_resource_provision(self):
obs = self.telescope.observations[0]
self.env.process(self.cluster.provision_ingest_resources(5, obs))
self.env.run(until=1)
self.assertEqual(5, len(self.cluster.get_available_resources()))
self.assertEqual(5,
self.algorithm._max_resource_provision(self.cluster))
# TODO The algorithm must provision resources if they are not already
# provisioned.
plan = self.planner.run(obs, self.buffer, self.telescope.max_ingest)
self.algorithm._provision_resources(self.cluster, plan)
self.assertEqual(5, len(self.cluster.get_idle_resources(obs.name)))
self.assertEqual(0,
self.algorithm._max_resource_provision(self.cluster))
# self.planner.run(obs, )
def test_algorithm_allocation(self):
obs = self.telescope.observations[0]
obs.plan = self.planner.run(obs, self.buffer,
self.telescope.max_ingest)
# Replicate the Scheduler allocate_task() methods
existing_schedule = {}
existing_schedule, status = self.algorithm.run(self.cluster,
self.env.now, obs.plan,
existing_schedule)
self.assertTrue(obs.plan.tasks[0] in existing_schedule)
def test_observation_queue(self):
"""
