def test_spread_scheduling_strategy(ray_start_cluster, connect_to_client):
cluster = ray_start_cluster
# Create a head node
cluster.add_node(
num_cpus=0,
_system_config={
"scheduler_spread_threshold": 1,
},
)
ray.init(address=cluster.address)
for i in range(2):
cluster.add_node(num_cpus=8, resources={f"foo:{i}": 1})
cluster.wait_for_nodes()
with connect_to_client_or_not(connect_to_client):
@ray.remote
def get_node_id():
return ray.worker.global_worker.current_node_id
worker_node_ids = {
ray.get(get_node_id.options(resources={
f"foo:{i}": 1
}).remote())
for i in range(2)
}
# Wait for updating driver raylet's resource view.
time.sleep(5)
@ray.remote(scheduling_strategy=SPREAD_SCHEDULING_STRATEGY)
def task1():
internal_kv._internal_kv_put("test_task1", "task1")
while internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
return ray.worker.global_worker.current_node_id
@ray.remote
def task2():
internal_kv._internal_kv_put("test_task2", "task2")
return ray.worker.global_worker.current_node_id
locations = []
locations.append(task1.remote())
while not internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
# Wait for updating driver raylet's resource view.
time.sleep(5)
locations.append(
task2.options(
scheduling_strategy=SPREAD_SCHEDULING_STRATEGY).remote())
while not internal_kv._internal_kv_exists("test_task2"):
time.sleep(0.1)
internal_kv._internal_kv_del("test_task1")
internal_kv._internal_kv_del("test_task2")
assert set(ray.get(locations)) == worker_node_ids
def test_create_upload_once(self, tmp_path, random_dir, ray_start_regular):
uri = get_uri_for_directory(random_dir)
uploaded = upload_package_if_needed(uri, tmp_path, random_dir)
assert uploaded
assert _internal_kv_exists(uri, namespace=KV_NAMESPACE_PACKAGE)
uploaded = upload_package_if_needed(uri, tmp_path, random_dir)
assert not uploaded
assert _internal_kv_exists(uri, namespace=KV_NAMESPACE_PACKAGE)
# Delete the URI from the internal_kv. This should trigger re-upload.
_internal_kv_del(uri, namespace=KV_NAMESPACE_PACKAGE)
assert not _internal_kv_exists(uri, namespace=KV_NAMESPACE_PACKAGE)
uploaded = upload_package_if_needed(uri, tmp_path, random_dir)
assert uploaded
def test_create_upload_once(self, empty_dir, random_dir,
ray_start_regular):
uri = get_uri_for_directory(random_dir)
uploaded = upload_package_if_needed(uri, empty_dir, random_dir)
assert uploaded
assert _internal_kv_exists(uri)
uploaded = upload_package_if_needed(uri, empty_dir, random_dir)
assert not uploaded
assert _internal_kv_exists(uri)
# Delete the URI from the internal_kv. This should trigger re-upload.
_internal_kv_del(uri)
assert not _internal_kv_exists(uri)
uploaded = upload_package_if_needed(uri, empty_dir, random_dir)
assert uploaded
def test_upload_succeeds(self, ray_start_regular):
"""Check function behavior when upload succeeds."""
uri = "gcs://test.zip"
bytes = b"test"
assert len(bytes) < GCS_STORAGE_MAX_SIZE
assert not _internal_kv_exists(uri, namespace=KV_NAMESPACE_PACKAGE)
assert _store_package_in_gcs(uri, bytes) == len(bytes)
assert bytes == _internal_kv_get(uri, namespace=KV_NAMESPACE_PACKAGE)
def wait(self, keys: list):
while (True):
all_exist = True
for key in keys:
result = internal_kv._internal_kv_exists(key)
if not result:
all_exist = False
break
if all_exist:
return True
time.sleep(1)
def wait(self, keys: list):
while True:
all_exist = True
for key in keys:
key = self.__concat_key_with_prefixes(key)
result = internal_kv._internal_kv_exists(key)
if not result:
all_exist = False
break
if all_exist:
return True
time.sleep(1)
def package_exists(pkg_uri: str) -> bool:
"""Check whether the package with given uri exists or not.
Args:
pkg_uri (str): The uri of the package
Return:
True for package existing and False for not.
"""
(protocol, pkg_name) = _parse_uri(pkg_uri)
if protocol in (Protocol.GCS, Protocol.PIN_GCS):
return internal_kv._internal_kv_exists(pkg_uri)
else:
raise NotImplementedError(f"Protocol {protocol} is not supported")
def package_exists(pkg_uri: str) -> bool:
"""Check whether the package with given URI exists or not.
Args:
pkg_uri: The uri of the package
Return:
True for package existing and False for not.
"""
protocol, pkg_name = parse_uri(pkg_uri)
if protocol == Protocol.GCS:
return _internal_kv_exists(pkg_uri)
else:
raise NotImplementedError(f"Protocol {protocol} is not supported")
def test_task_failure_when_driver_local_raylet_dies(ray_start_cluster):
cluster = ray_start_cluster
head = cluster.add_node(num_cpus=4, resources={"foo": 1})
cluster.wait_for_nodes()
ray.init(address=cluster.address)
@ray.remote(resources={"foo": 1})
def func():
internal_kv._internal_kv_put("test_func", "func")
while True:
time.sleep(1)
func.remote()
while not internal_kv._internal_kv_exists("test_func"):
time.sleep(0.1)
# The lease request should wait inside raylet
# since there is no available resources.
ret = func.remote()
# Waiting for the lease request to reach raylet.
time.sleep(1)
head.kill_raylet()
with pytest.raises(LocalRayletDiedError):
ray.get(ret)
def task1():
internal_kv._internal_kv_put("test_task1", "task1")
while internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
return ray.worker.global_worker.current_node_id
def task1():
internal_kv._internal_kv_put("test_task1", "task1")
while internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
return ray.get_runtime_context().node_id.hex()
def test_spread_scheduling_strategy(ray_start_cluster, connect_to_client):
cluster = ray_start_cluster
# Create a head node
cluster.add_node(
num_cpus=0,
_system_config={
"scheduler_spread_threshold": 1,
},
)
ray.init(address=cluster.address)
for i in range(2):
cluster.add_node(num_cpus=8, resources={f"foo:{i}": 1})
cluster.wait_for_nodes()
with connect_to_client_or_not(connect_to_client):
@ray.remote
def get_node_id():
return ray.get_runtime_context().node_id.hex()
worker_node_ids = {
ray.get(get_node_id.options(resources={
f"foo:{i}": 1
}).remote())
for i in range(2)
}
# Wait for updating driver raylet's resource view.
time.sleep(5)
@ray.remote(scheduling_strategy="SPREAD")
def task1():
internal_kv._internal_kv_put("test_task1", "task1")
while internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
return ray.get_runtime_context().node_id.hex()
@ray.remote
def task2():
internal_kv._internal_kv_put("test_task2", "task2")
return ray.get_runtime_context().node_id.hex()
locations = []
locations.append(task1.remote())
while not internal_kv._internal_kv_exists("test_task1"):
time.sleep(0.1)
# Wait for updating driver raylet's resource view.
time.sleep(5)
locations.append(task2.options(scheduling_strategy="SPREAD").remote())
while not internal_kv._internal_kv_exists("test_task2"):
time.sleep(0.1)
internal_kv._internal_kv_del("test_task1")
internal_kv._internal_kv_del("test_task2")
assert set(ray.get(locations)) == worker_node_ids
# Wait for updating driver raylet's resource view.
time.sleep(5)
# Make sure actors can be spreaded as well.
@ray.remote(num_cpus=1)
class Actor:
def ping(self):
return ray.get_runtime_context().node_id.hex()
actors = []
locations = []
for i in range(8):
actors.append(Actor.options(scheduling_strategy="SPREAD").remote())
locations.append(ray.get(actors[-1].ping.remote()))
locations.sort()
expected_locations = list(worker_node_ids) * 4
expected_locations.sort()
assert locations == expected_locations
def test_node_affinity_scheduling_strategy(ray_start_cluster,
connect_to_client):
cluster = ray_start_cluster
cluster.add_node(num_cpus=8, resources={"head": 1})
ray.init(address=cluster.address)
cluster.add_node(num_cpus=8, resources={"worker": 1})
cluster.wait_for_nodes()
with connect_to_client_or_not(connect_to_client):
@ray.remote
def get_node_id():
return ray.get_runtime_context().node_id
head_node_id = ray.get(
get_node_id.options(num_cpus=0, resources={
"head": 1
}).remote())
worker_node_id = ray.get(
get_node_id.options(num_cpus=0, resources={
"worker": 1
}).remote())
assert worker_node_id == ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
worker_node_id, soft=False)).remote())
assert head_node_id == ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
head_node_id, soft=False)).remote())
# Doesn't fail when the node doesn't exist since soft is true.
ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
ray.NodeID.from_random().hex(), soft=True)).remote())
# Doesn't fail when the node is infeasible since soft is true.
assert worker_node_id == ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
head_node_id, soft=True),
resources={
"worker": 1
},
).remote())
# Fail when the node doesn't exist.
with pytest.raises(ray.exceptions.TaskUnschedulableError):
ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
ray.NodeID.from_random().hex(), soft=False)).remote())
# Fail when the node is infeasible.
with pytest.raises(ray.exceptions.TaskUnschedulableError):
ray.get(
get_node_id.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
head_node_id, soft=False),
resources={
"not_exist": 1
},
).remote())
crashed_worker_node = cluster.add_node(num_cpus=8,
resources={"crashed_worker": 1})
cluster.wait_for_nodes()
crashed_worker_node_id = ray.get(
get_node_id.options(num_cpus=0, resources={
"crashed_worker": 1
}).remote())
@ray.remote(
max_retries=-1,
scheduling_strategy=NodeAffinitySchedulingStrategy(
crashed_worker_node_id, soft=True),
)
def crashed_get_node_id():
if ray.get_runtime_context().node_id == crashed_worker_node_id:
internal_kv._internal_kv_put("crashed_get_node_id",
"crashed_worker_node_id")
while True:
time.sleep(1)
else:
return ray.get_runtime_context().node_id
r = crashed_get_node_id.remote()
while not internal_kv._internal_kv_exists("crashed_get_node_id"):
time.sleep(0.1)
cluster.remove_node(crashed_worker_node, allow_graceful=False)
assert ray.get(r) in {head_node_id, worker_node_id}
@ray.remote(num_cpus=1)
class Actor:
def get_node_id(self):
return ray.get_runtime_context().node_id
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
worker_node_id, soft=False)).remote()
assert worker_node_id == ray.get(actor.get_node_id.remote())
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
head_node_id, soft=False)).remote()
assert head_node_id == ray.get(actor.get_node_id.remote())
# Wait until the target node becomes available.
worker_actor = Actor.options(resources={"worker": 1}).remote()
assert worker_node_id == ray.get(worker_actor.get_node_id.remote())
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(worker_node_id,
soft=True),
resources={
"worker": 1
},
).remote()
del worker_actor
assert worker_node_id == ray.get(actor.get_node_id.remote())
# Doesn't fail when the node doesn't exist since soft is true.
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
ray.NodeID.from_random().hex(), soft=True)).remote()
assert ray.get(actor.get_node_id.remote())
# Doesn't fail when the node is infeasible since soft is true.
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(head_node_id,
soft=True),
resources={
"worker": 1
},
).remote()
assert worker_node_id == ray.get(actor.get_node_id.remote())
# Fail when the node doesn't exist.
with pytest.raises(ray.exceptions.ActorUnschedulableError):
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
ray.NodeID.from_random().hex(), soft=False)).remote()
ray.get(actor.get_node_id.remote())
# Fail when the node is infeasible.
with pytest.raises(ray.exceptions.ActorUnschedulableError):
actor = Actor.options(
scheduling_strategy=NodeAffinitySchedulingStrategy(
worker_node_id, soft=False),
resources={
"not_exist": 1
},
).remote()
ray.get(actor.get_node_id.remote())
