def add_node(self, **override_kwargs):
"""Adds a node to the local Ray Cluster.
All nodes are by default started with the following settings:
cleanup=True,
num_cpus=1,
object_store_memory=100 * (2**20) # 100 MB
Args:
override_kwargs: Keyword arguments used in `start_ray_head`
and `start_ray_node`. Overrides defaults.
Returns:
Node object of the added Ray node.
"""
node_kwargs = {
"num_cpus": 1,
"object_store_memory": 100 * (2**20) # 100 MB
}
node_kwargs.update(override_kwargs)
ray_params = RayParams(
node_ip_address=services.get_node_ip_address(), **node_kwargs)
if self.head_node is None:
ray_params.update(include_webui=False)
address_info = services.start_ray_head(ray_params, cleanup=True)
self.redis_address = address_info["redis_address"]
# TODO(rliaw): Find a more stable way than modifying global state.
process_dict_copy = services.all_processes.copy()
for key in services.all_processes:
services.all_processes[key] = []
node = Node(address_info, process_dict_copy)
self.head_node = node
else:
ray_params.update(redis_address=self.redis_address)
address_info = services.start_ray_node(ray_params, cleanup=True)
# TODO(rliaw): Find a more stable way than modifying global state.
process_dict_copy = services.all_processes.copy()
for key in services.all_processes:
services.all_processes[key] = []
node = Node(address_info, process_dict_copy)
self.worker_nodes[node] = address_info
logger.info("Starting Node with raylet socket {}".format(
address_info["raylet_socket_name"]))
return node
def ray_start_workers_separate():
# Start the Ray processes.
ray_params = RayParams(num_cpus=1,
start_ray_local=True,
redirect_output=True)
ray.worker._init(ray_params)
yield None
# The code after the yield will run as teardown code.
ray.shutdown()
def _test_component_failed(component_type):
"""Kill a component on all worker nodes and check workload succeeds."""
# Start with 4 workers and 4 cores.
num_local_schedulers = 4
num_workers_per_scheduler = 8
ray_params = RayParams(num_local_schedulers=num_local_schedulers,
start_ray_local=True,
num_cpus=[num_workers_per_scheduler] *
num_local_schedulers,
redirect_output=True,
_internal_config=json.dumps({
"initial_reconstruction_timeout_milliseconds":
1000,
"num_heartbeats_timeout":
10,
}))
ray.worker._init(ray_params)
# Submit many tasks with many dependencies.
@ray.remote
def f(x):
return x
@ray.remote
def g(*xs):
return 1
# Kill the component on all nodes except the head node as the tasks
# execute. Do this in a loop while submitting tasks between each
# component failure.
time.sleep(0.1)
components = ray.services.all_processes[component_type]
for process in components[1:]:
# Submit a round of tasks with many dependencies.
x = 1
for _ in range(1000):
x = f.remote(x)
xs = [g.remote(1)]
for _ in range(100):
xs.append(g.remote(*xs))
xs.append(g.remote(1))
# Kill a component on one of the nodes.
process.terminate()
time.sleep(1)
process.kill()
process.wait()
assert not process.poll() is None
# Make sure that we can still get the objects after the
# executing tasks died.
ray.get(x)
ray.get(xs)
def ray_start_combination(request):
num_local_schedulers = request.param[0]
num_workers_per_scheduler = request.param[1]
# Start the Ray processes.
ray_params = RayParams(start_ray_local=True,
num_local_schedulers=num_local_schedulers,
num_cpus=10)
ray.worker._init(ray_params)
yield num_local_schedulers, num_workers_per_scheduler
# The code after the yield will run as teardown code.
ray.shutdown()
def ray_start_two_nodes():
# Start the Ray processes.
ray_params = RayParams(start_ray_local=True,
num_local_schedulers=2,
num_cpus=0,
_internal_config=json.dumps(
{"num_heartbeats_timeout": 40}))
ray.worker._init(ray_params)
yield None
# The code after the yield will run as teardown code.
ray.shutdown()
def ray_start_workers_separate_multinode(request):
num_local_schedulers = request.param[0]
num_initial_workers = request.param[1]
# Start the Ray processes.
ray_params = RayParams(num_local_schedulers=num_local_schedulers,
start_ray_local=True,
num_cpus=[num_initial_workers] *
num_local_schedulers,
redirect_output=True)
ray.worker._init(ray_params)
yield num_local_schedulers, num_initial_workers
# The code after the yield will run as teardown code.
ray.shutdown()
def add_node(self, **override_kwargs):
"""Adds a node to the local Ray Cluster.
All nodes are by default started with the following settings:
cleanup=True,
resources={"CPU": 1},
object_store_memory=100 * (2**20) # 100 MB
Args:
override_kwargs: Keyword arguments used in `start_ray_head`
and `start_ray_node`. Overrides defaults.
Returns:
Node object of the added Ray node.
"""
node_kwargs = {
"resources": {
"CPU": 1
},
"object_store_memory": 100 * (2**20) # 100 MB
}
node_kwargs.update(override_kwargs)
ray_params = RayParams(node_ip_address=services.get_node_ip_address(),
**node_kwargs)
if self.head_node is None:
ray_params.update(include_webui=False)
address_info = services.start_ray_head(ray_params, cleanup=True)
self.redis_address = address_info["redis_address"]
# TODO(rliaw): Find a more stable way than modifying global state.
process_dict_copy = services.all_processes.copy()
for key in services.all_processes:
services.all_processes[key] = []
node = Node(address_info, process_dict_copy)
self.head_node = node
else:
ray_params.update(redis_address=self.redis_address)
address_info = services.start_ray_node(ray_params, cleanup=True)
# TODO(rliaw): Find a more stable way than modifying global state.
process_dict_copy = services.all_processes.copy()
for key in services.all_processes:
services.all_processes[key] = []
node = Node(address_info, process_dict_copy)
self.worker_nodes[node] = address_info
logger.info("Starting Node with raylet socket {}".format(
address_info["raylet_socket_names"]))
return node
def start(node_ip_address, redis_address, redis_port, num_redis_shards,
redis_max_clients, redis_password, redis_shard_ports,
object_manager_port, node_manager_port, object_store_memory,
redis_max_memory, num_workers, num_cpus, num_gpus, resources, head,
no_ui, block, plasma_directory, huge_pages, autoscaling_config,
no_redirect_worker_output, no_redirect_output,
plasma_store_socket_name, raylet_socket_name, temp_dir,
internal_config):
# Convert hostnames to numerical IP address.
if node_ip_address is not None:
node_ip_address = services.address_to_ip(node_ip_address)
if redis_address is not None:
redis_address = services.address_to_ip(redis_address)
try:
resources = json.loads(resources)
except Exception:
raise Exception("Unable to parse the --resources argument using "
"json.loads. Try using a format like\n\n"
" --resources='{\"CustomResource1\": 3, "
"\"CustomReseource2\": 2}'")
ray_params = RayParams(
node_ip_address=node_ip_address,
object_manager_port=object_manager_port,
node_manager_port=node_manager_port,
num_workers=num_workers,
object_store_memory=object_store_memory,
redis_password=redis_password,
redirect_worker_output=not no_redirect_worker_output,
redirect_output=not no_redirect_output,
num_cpus=num_cpus,
num_gpus=num_gpus,
resources=resources,
plasma_directory=plasma_directory,
huge_pages=huge_pages,
plasma_store_socket_name=plasma_store_socket_name,
raylet_socket_name=raylet_socket_name,
temp_dir=temp_dir,
_internal_config=internal_config)
if head:
# Start Ray on the head node.
if redis_shard_ports is not None:
redis_shard_ports = redis_shard_ports.split(",")
# Infer the number of Redis shards from the ports if the number is
# not provided.
if num_redis_shards is None:
num_redis_shards = len(redis_shard_ports)
# Check that the arguments match.
if len(redis_shard_ports) != num_redis_shards:
raise Exception("If --redis-shard-ports is provided, it must "
"have the form '6380,6381,6382', and the "
"number of ports provided must equal "
"--num-redis-shards (which is 1 if not "
"provided)")
if redis_address is not None:
raise Exception("If --head is passed in, a Redis server will be "
"started, so a Redis address should not be "
"provided.")
# Get the node IP address if one is not provided.
ray_params.update_if_absent(
node_ip_address=services.get_node_ip_address())
logger.info("Using IP address {} for this node.".format(
ray_params.node_ip_address))
ray_params.update_if_absent(redis_port=redis_port,
redis_shard_ports=redis_shard_ports,
redis_max_memory=redis_max_memory,
num_redis_shards=num_redis_shards,
redis_max_clients=redis_max_clients,
include_webui=(not no_ui),
autoscaling_config=autoscaling_config)
address_info = services.start_ray_head(ray_params, cleanup=False)
logger.info(address_info)
logger.info(
"\nStarted Ray on this node. You can add additional nodes to "
"the cluster by calling\n\n"
" ray start --redis-address {}{}{}\n\n"
"from the node you wish to add. You can connect a driver to the "
"cluster from Python by running\n\n"
" import ray\n"
" ray.init(redis_address=\"{}{}{}\")\n\n"
"If you have trouble connecting from a different machine, check "
"that your firewall is configured properly. If you wish to "
"terminate the processes that have been started, run\n\n"
" ray stop".format(
address_info["redis_address"],
" --redis-password " if redis_password else "",
redis_password if redis_password else "",
address_info["redis_address"],
"\", redis_password=\"" if redis_password else "",
redis_password if redis_password else ""))
else:
# Start Ray on a non-head node.
if redis_port is not None:
raise Exception("If --head is not passed in, --redis-port is not "
"allowed")
if redis_shard_ports is not None:
raise Exception("If --head is not passed in, --redis-shard-ports "
"is not allowed")
if redis_address is None:
raise Exception("If --head is not passed in, --redis-address must "
"be provided.")
if num_redis_shards is not None:
raise Exception("If --head is not passed in, --num-redis-shards "
"must not be provided.")
if redis_max_clients is not None:
raise Exception("If --head is not passed in, --redis-max-clients "
"must not be provided.")
if no_ui:
raise Exception("If --head is not passed in, the --no-ui flag is "
"not relevant.")
redis_ip_address, redis_port = redis_address.split(":")
# Wait for the Redis server to be started. And throw an exception if we
# can't connect to it.
services.wait_for_redis_to_start(redis_ip_address,
int(redis_port),
password=redis_password)
# Create a Redis client.
redis_client = services.create_redis_client(redis_address,
password=redis_password)
# Check that the verion information on this node matches the version
# information that the cluster was started with.
services.check_version_info(redis_client)
# Get the node IP address if one is not provided.
ray_params.update_if_absent(
node_ip_address=services.get_node_ip_address(redis_address))
logger.info("Using IP address {} for this node.".format(
ray_params.node_ip_address))
# Check that there aren't already Redis clients with the same IP
# address connected with this Redis instance. This raises an exception
# if the Redis server already has clients on this node.
check_no_existing_redis_clients(ray_params.node_ip_address,
redis_client)
ray_params.redis_address = redis_address
address_info = services.start_ray_node(ray_params, cleanup=False)
logger.info(address_info)
logger.info("\nStarted Ray on this node. If you wish to terminate the "
"processes that have been started, run\n\n"
" ray stop")
if block:
import time
while True:
time.sleep(30)
args = parser.parse_args()
info = {
"node_ip_address": args.node_ip_address,
"redis_address": args.redis_address,
"redis_password": args.redis_password,
"store_socket_name": args.object_store_name,
"raylet_socket_name": args.raylet_name,
}
ray.utils.setup_logger(args.logging_level, args.logging_format)
ray_params = RayParams(node_ip_address=args.node_ip_address,
redis_address=args.redis_address,
redis_password=args.redis_password,
plasma_store_socket_name=args.object_store_name,
raylet_socket_name=args.raylet_name,
temp_dir=args.temp_dir,
load_code_from_local=args.load_code_from_local)
node = ray.node.Node(ray_params,
head=False,
shutdown_at_exit=False,
connect_only=True)
ray.worker._global_node = node
# TODO(suquark): Use "node" as the input of "connect".
ray.worker.connect(info,
redis_password=args.redis_password,
mode=ray.WORKER_MODE,
load_code_from_local=args.load_code_from_local)
if len(config_list) > 1:
i = 0
while i < len(config_list):
internal_config[config_list[i]] = config_list[i + 1]
i += 2
raylet_ip_address = args.raylet_ip_address
if raylet_ip_address is None:
raylet_ip_address = args.node_ip_address
ray_params = RayParams(
node_ip_address=args.node_ip_address,
raylet_ip_address=raylet_ip_address,
node_manager_port=args.node_manager_port,
redis_address=args.redis_address,
redis_password=args.redis_password,
plasma_store_socket_name=args.object_store_name,
raylet_socket_name=args.raylet_name,
temp_dir=args.temp_dir,
load_code_from_local=args.load_code_from_local,
_internal_config=json.dumps(internal_config),
)
node = ray.node.Node(ray_params,
head=False,
shutdown_at_exit=False,
spawn_reaper=False,
connect_only=True)
ray.worker._global_node = node
ray.worker.connect(node,
mode=ray.WORKER_MODE,
internal_config=internal_config)
if raylet_ip_address is None:
raylet_ip_address = args.node_ip_address
code_search_path = args.code_search_path
if code_search_path is not None:
for p in code_search_path.split(":"):
if os.path.isfile(p):
p = os.path.dirname(p)
sys.path.append(p)
ray_params = RayParams(
node_ip_address=args.node_ip_address,
raylet_ip_address=raylet_ip_address,
node_manager_port=args.node_manager_port,
redis_address=args.redis_address,
redis_password=args.redis_password,
plasma_store_socket_name=args.object_store_name,
raylet_socket_name=args.raylet_name,
temp_dir=args.temp_dir,
load_code_from_local=args.load_code_from_local,
metrics_agent_port=args.metrics_agent_port,
)
node = ray.node.Node(ray_params,
head=False,
shutdown_at_exit=False,
spawn_reaper=False,
connect_only=True)
ray.worker._global_node = node
ray.worker.connect(node, mode=mode)
# Setup log file.
def main(args):
ray.ray_logging.setup_logger(args.logging_level, args.logging_format)
if args.worker_type == "WORKER":
mode = ray.WORKER_MODE
elif args.worker_type == "SPILL_WORKER":
mode = ray.SPILL_WORKER_MODE
elif args.worker_type == "RESTORE_WORKER":
mode = ray.RESTORE_WORKER_MODE
else:
raise ValueError("Unknown worker type: " + args.worker_type)
# NOTE(suquark): We must initialize the external storage before we
# connect to raylet. Otherwise we may receive requests before the
# external storage is intialized.
if mode == ray.RESTORE_WORKER_MODE or mode == ray.SPILL_WORKER_MODE:
from ray import external_storage
if args.object_spilling_config:
object_spilling_config = base64.b64decode(
args.object_spilling_config)
object_spilling_config = json.loads(object_spilling_config)
else:
object_spilling_config = {}
external_storage.setup_external_storage(object_spilling_config)
raylet_ip_address = args.raylet_ip_address
if raylet_ip_address is None:
raylet_ip_address = args.node_ip_address
code_search_path = args.code_search_path
if code_search_path is not None:
for p in code_search_path.split(":"):
if os.path.isfile(p):
p = os.path.dirname(p)
sys.path.append(p)
ray_params = RayParams(
node_ip_address=args.node_ip_address,
raylet_ip_address=raylet_ip_address,
node_manager_port=args.node_manager_port,
redis_address=args.redis_address,
redis_password=args.redis_password,
plasma_store_socket_name=args.object_store_name,
raylet_socket_name=args.raylet_name,
temp_dir=args.temp_dir,
load_code_from_local=args.load_code_from_local,
metrics_agent_port=args.metrics_agent_port,
)
node = ray.node.Node(ray_params,
head=False,
shutdown_at_exit=False,
spawn_reaper=False,
connect_only=True)
ray.worker._global_node = node
ray.worker.connect(node, mode=mode)
# Redirect stdout and stderr to the default worker interceptor logger.
# NOTE: We deprecated redirect_worker_output arg,
# so we don't need to handle here.
stdout_interceptor = StandardStreamInterceptor(
setup_and_get_worker_interceptor_logger(is_for_stdout=True),
intercept_stdout=True)
stderr_interceptor = StandardStreamInterceptor(
setup_and_get_worker_interceptor_logger(is_for_stdout=False),
intercept_stdout=False)
with redirect_stdout(stdout_interceptor):
with redirect_stderr(stderr_interceptor):
if mode == ray.WORKER_MODE:
ray.worker.global_worker.main_loop()
elif (mode == ray.RESTORE_WORKER_MODE
or mode == ray.SPILL_WORKER_MODE):
# It is handled by another thread in the C++ core worker.
# We just need to keep the worker alive.
while True:
time.sleep(100000)
else:
raise ValueError(f"Unexcepted worker mode: {mode}")
def start(node_ip_address, redis_address, redis_port, num_redis_shards,
redis_max_clients, redis_password, redis_shard_ports,
object_manager_port, node_manager_port, object_store_memory,
redis_max_memory, num_workers, num_cpus, num_gpus, resources, head,
no_ui, block, plasma_directory, huge_pages, autoscaling_config,
no_redirect_worker_output, no_redirect_output,
plasma_store_socket_name, raylet_socket_name, temp_dir,
internal_config):
# Convert hostnames to numerical IP address.
if node_ip_address is not None:
node_ip_address = services.address_to_ip(node_ip_address)
if redis_address is not None:
redis_address = services.address_to_ip(redis_address)
try:
resources = json.loads(resources)
except Exception:
raise Exception("Unable to parse the --resources argument using "
"json.loads. Try using a format like\n\n"
" --resources='{\"CustomResource1\": 3, "
"\"CustomReseource2\": 2}'")
ray_params = RayParams(
node_ip_address=node_ip_address,
object_manager_port=object_manager_port,
node_manager_port=node_manager_port,
num_workers=num_workers,
object_store_memory=object_store_memory,
redis_password=redis_password,
redirect_worker_output=not no_redirect_worker_output,
redirect_output=not no_redirect_output,
num_cpus=num_cpus,
num_gpus=num_gpus,
resources=resources,
plasma_directory=plasma_directory,
huge_pages=huge_pages,
plasma_store_socket_name=plasma_store_socket_name,
raylet_socket_name=raylet_socket_name,
temp_dir=temp_dir,
_internal_config=internal_config)
if head:
# Start Ray on the head node.
if redis_shard_ports is not None:
redis_shard_ports = redis_shard_ports.split(",")
# Infer the number of Redis shards from the ports if the number is
# not provided.
if num_redis_shards is None:
num_redis_shards = len(redis_shard_ports)
# Check that the arguments match.
if len(redis_shard_ports) != num_redis_shards:
raise Exception("If --redis-shard-ports is provided, it must "
"have the form '6380,6381,6382', and the "
"number of ports provided must equal "
"--num-redis-shards (which is 1 if not "
"provided)")
if redis_address is not None:
raise Exception("If --head is passed in, a Redis server will be "
"started, so a Redis address should not be "
"provided.")
# Get the node IP address if one is not provided.
ray_params.update_if_absent(
node_ip_address=services.get_node_ip_address())
logger.info("Using IP address {} for this node.".format(
ray_params.node_ip_address))
ray_params.update_if_absent(
redis_port=redis_port,
redis_shard_ports=redis_shard_ports,
redis_max_memory=redis_max_memory,
num_redis_shards=num_redis_shards,
redis_max_clients=redis_max_clients,
include_webui=(not no_ui),
autoscaling_config=autoscaling_config)
address_info = services.start_ray_head(ray_params, cleanup=False)
logger.info(address_info)
logger.info(
"\nStarted Ray on this node. You can add additional nodes to "
"the cluster by calling\n\n"
" ray start --redis-address {}{}{}\n\n"
"from the node you wish to add. You can connect a driver to the "
"cluster from Python by running\n\n"
" import ray\n"
" ray.init(redis_address=\"{}{}{}\")\n\n"
"If you have trouble connecting from a different machine, check "
"that your firewall is configured properly. If you wish to "
"terminate the processes that have been started, run\n\n"
" ray stop".format(
address_info["redis_address"], " --redis-password "
if redis_password else "", redis_password if redis_password
else "", address_info["redis_address"], "\", redis_password=\""
if redis_password else "", redis_password
if redis_password else ""))
else:
# Start Ray on a non-head node.
if redis_port is not None:
raise Exception("If --head is not passed in, --redis-port is not "
"allowed")
if redis_shard_ports is not None:
raise Exception("If --head is not passed in, --redis-shard-ports "
"is not allowed")
if redis_address is None:
raise Exception("If --head is not passed in, --redis-address must "
"be provided.")
if num_redis_shards is not None:
raise Exception("If --head is not passed in, --num-redis-shards "
"must not be provided.")
if redis_max_clients is not None:
raise Exception("If --head is not passed in, --redis-max-clients "
"must not be provided.")
if no_ui:
raise Exception("If --head is not passed in, the --no-ui flag is "
"not relevant.")
redis_ip_address, redis_port = redis_address.split(":")
# Wait for the Redis server to be started. And throw an exception if we
# can't connect to it.
services.wait_for_redis_to_start(
redis_ip_address, int(redis_port), password=redis_password)
# Create a Redis client.
redis_client = services.create_redis_client(
redis_address, password=redis_password)
# Check that the verion information on this node matches the version
# information that the cluster was started with.
services.check_version_info(redis_client)
# Get the node IP address if one is not provided.
ray_params.update_if_absent(
node_ip_address=services.get_node_ip_address(redis_address))
logger.info("Using IP address {} for this node.".format(
ray_params.node_ip_address))
# Check that there aren't already Redis clients with the same IP
# address connected with this Redis instance. This raises an exception
# if the Redis server already has clients on this node.
check_no_existing_redis_clients(ray_params.node_ip_address,
redis_client)
ray_params.redis_address = redis_address
address_info = services.start_ray_node(ray_params, cleanup=False)
logger.info(address_info)
logger.info("\nStarted Ray on this node. If you wish to terminate the "
"processes that have been started, run\n\n"
" ray stop")
if block:
import time
while True:
time.sleep(30)
def ray_start_reconstruction(request):
num_local_schedulers = request.param
# Start the Redis global state store.
node_ip_address = "127.0.0.1"
redis_address, redis_shards = ray.services.start_redis(node_ip_address)
redis_ip_address = ray.services.get_ip_address(redis_address)
redis_port = ray.services.get_port(redis_address)
time.sleep(0.1)
# Start the Plasma store instances with a total of 1GB memory.
plasma_store_memory = 10**9
plasma_addresses = []
object_store_memory = plasma_store_memory // num_local_schedulers
for i in range(num_local_schedulers):
store_stdout_file, store_stderr_file = (
ray.tempfile_services.new_plasma_store_log_file(i, True))
plasma_addresses.append(
ray.services.start_plasma_store(
node_ip_address,
redis_address,
object_store_memory=object_store_memory,
store_stdout_file=store_stdout_file,
store_stderr_file=store_stderr_file))
# Start the rest of the services in the Ray cluster.
address_info = {
"redis_address": redis_address,
"redis_shards": redis_shards,
"object_store_addresses": plasma_addresses
}
ray_params = RayParams(address_info=address_info,
start_ray_local=True,
num_local_schedulers=num_local_schedulers,
num_cpus=[1] * num_local_schedulers,
redirect_output=True,
_internal_config=json.dumps({
"initial_reconstruction_timeout_milliseconds":
200
}))
ray.worker._init(ray_params)
yield (redis_ip_address, redis_port, plasma_store_memory,
num_local_schedulers)
# The code after the yield will run as teardown code.
assert ray.services.all_processes_alive()
# Determine the IDs of all local schedulers that had a task scheduled
# or submitted.
state = ray.experimental.state.GlobalState()
state._initialize_global_state(redis_ip_address, redis_port)
if os.environ.get("RAY_USE_NEW_GCS") == "on":
tasks = state.task_table()
local_scheduler_ids = {
task["LocalSchedulerID"]
for task in tasks.values()
}
# Make sure that all nodes in the cluster were used by checking that
# the set of local scheduler IDs that had a task scheduled or submitted
# is equal to the total number of local schedulers started. We add one
# to the total number of local schedulers to account for
# NIL_LOCAL_SCHEDULER_ID. This is the local scheduler ID associated
# with the driver task, since it is not scheduled by a particular local
# scheduler.
if os.environ.get("RAY_USE_NEW_GCS") == "on":
assert len(local_scheduler_ids) == num_local_schedulers + 1
# Clean up the Ray cluster.
ray.shutdown()