def test_failed_job_status(ray_start_with_dashboard, disable_aiohttp_cache,
enable_test_module):
address = ray_start_with_dashboard.address_info["webui_url"]
assert wait_until_server_available(address)
address = format_web_url(address)
job_sleep_time_s = 5
entrypoint_cmd = ('python -c"'
"import ray;"
"ray.init();"
"import time;"
f"time.sleep({job_sleep_time_s});"
"import sys;"
"sys.exit(1);"
'"')
start_time_s = int(time.time())
client = JobSubmissionClient(address)
runtime_env = {"env_vars": {"RAY_TEST_456": "456"}}
metadata = {"ray_test_789": "789"}
job_id = client.submit_job(entrypoint=entrypoint_cmd,
metadata=metadata,
runtime_env=runtime_env)
def wait_for_job_to_fail():
data = _get_snapshot(address)
legacy_job_failed = False
job_failed = False
# Test legacy job snapshot (one driver per job).
for job_entry in data["data"]["snapshot"]["jobs"].values():
if job_entry["status"] is not None:
assert job_entry["config"]["metadata"][
"jobSubmissionId"] == job_id
assert job_entry["status"] in {"PENDING", "RUNNING", "FAILED"}
assert job_entry["statusMessage"] is not None
legacy_job_failed = job_entry["status"] == "FAILED"
# Test new jobs snapshot (0 to N drivers per job).
for job_submission_id, entry in data["data"]["snapshot"][
"jobSubmission"].items():
if entry["status"] is not None:
assert entry["status"] in {"PENDING", "RUNNING", "FAILED"}
assert entry["message"] is not None
# TODO(architkulkarni): Disable automatic camelcase.
assert entry["runtimeEnv"] == {
"envVars": {
"RAYTest456": "456"
}
}
assert entry["metadata"] == {"rayTest789": "789"}
assert entry["errorType"] is None
assert abs(entry["startTime"] - start_time_s) <= 2
if entry["status"] == "FAILED":
job_failed = True
assert entry[
"endTime"] >= entry["startTime"] + job_sleep_time_s
return legacy_job_failed and job_failed
wait_for_condition(wait_for_job_to_fail, timeout=10)
def test_ray_tune_basic(job_sdk_client: JobSubmissionClient):
run_cmd = "python ray_tune_basic.py"
job_id = job_sdk_client.submit_job(
entrypoint=run_cmd,
runtime_env={"working_dir": DRIVER_SCRIPT_DIR},
)
wait_for_condition(_check_job_succeeded,
timeout=30,
client=job_sdk_client,
job_id=job_id)
def test_per_task_runtime_env(job_sdk_client: JobSubmissionClient):
run_cmd = "python per_task_runtime_env.py"
job_id = job_sdk_client.submit_job(
entrypoint=run_cmd,
runtime_env={"working_dir": DRIVER_SCRIPT_DIR},
)
wait_for_condition(_check_job_succeeded,
client=job_sdk_client,
job_id=job_id)
def test_cli_apis_sanity_check(ray_start_cluster):
"""Test all of CLI APIs work as expected."""
cluster = ray_start_cluster
cluster.add_node(num_cpus=2)
ray.init(address=cluster.address)
for _ in range(3):
cluster.add_node(num_cpus=2)
runner = CliRunner()
client = JobSubmissionClient(
f"http://{ray._private.worker.global_worker.node.address_info['webui_url']}"
)
@ray.remote
def f():
import time
time.sleep(30)
@ray.remote
class Actor:
pass
obj = ray.put(3) # noqa
task = f.remote() # noqa
actor = Actor.remote() # noqa
actor_runtime_env = Actor.options( # noqa
runtime_env={
"pip": ["requests"]
}).remote()
job_id = client.submit_job( # noqa
# Entrypoint shell command to execute
entrypoint="ls", )
pg = ray.util.placement_group(bundles=[{"CPU": 1}]) # noqa
def verify_output(resource_name, necessary_substrings: List[str]):
result = runner.invoke(cli_list, [resource_name])
exit_code_correct = result.exit_code == 0
substring_matched = all(substr in result.output
for substr in necessary_substrings)
print(result.output)
return exit_code_correct and substring_matched
wait_for_condition(lambda: verify_output("actors", ["actor_id"]))
wait_for_condition(lambda: verify_output("workers", ["worker_id"]))
wait_for_condition(lambda: verify_output("nodes", ["node_id"]))
wait_for_condition(
lambda: verify_output("placement-groups", ["placement_group_id"]))
wait_for_condition(lambda: verify_output("jobs", ["raysubmit"]))
wait_for_condition(lambda: verify_output("tasks", ["task_id"]))
wait_for_condition(lambda: verify_output("objects", ["object_id"]))
wait_for_condition(lambda: verify_output("runtime-envs", ["runtime_env"]))
def test_list_jobs(shutdown_only):
ray.init()
client = JobSubmissionClient(
f"http://{ray.worker.global_worker.node.address_info['webui_url']}")
job_id = client.submit_job( # noqa
# Entrypoint shell command to execute
entrypoint="ls", )
def verify():
job_data = list(list_jobs().values())[0]
job_id_from_api = list(list_jobs().keys())[0]
correct_state = job_data["status"] == "SUCCEEDED"
correct_id = job_id == job_id_from_api
return correct_state and correct_id
wait_for_condition(verify)
print(list_jobs())
def ray_job_submit(
script_name: str,
head_service: str,
k8s_namespace: str = "default",
ray_dashboard_port: int = 8265,
) -> str:
"""Submits a Python script via the Ray Job Submission API, using the Python SDK.
Waits for successful completion of the job and returns the job logs as a string.
Uses `kubectl port-forward` to access the Ray head's dashboard port.
Scripts live in `tests/kuberay/scripts`. This directory is used as the working
dir for the job.
Args:
script_name: The name of the script to submit.
head_service: The name of the Ray head K8s service.
k8s_namespace: K8s namespace the Ray cluster belongs to.
ray_dashboard_port: The port on which the Ray head is running the Ray dashboard.
"""
with _kubectl_port_forward(service=head_service,
namespace=k8s_namespace,
target_port=ray_dashboard_port) as local_port:
# It takes a bit of time to establish the connection.
# Try a few times to instantiate the JobSubmissionClient, as the client's
# instantiation does not retry on connection errors.
for trie in range(1, 7):
time.sleep(5)
try:
client = JobSubmissionClient(f"http://127.0.0.1:{local_port}")
except ConnectionError as e:
if trie < 6:
logger.info(
"Job client connection failed. Retrying in 5 seconds.")
else:
raise e from None
job_id = client.submit_job(
entrypoint=f"python {script_name}",
runtime_env={
"working_dir": SCRIPTS_DIR,
# Throw in some extra data for fun, to validate runtime envs.
"pip": ["pytest==6.0.0"],
"env_vars": {
"key_foo": "value_bar"
},
},
)
# Wait for the job to complete successfully.
# This logic is copied from the Job Submission docs.
start = time.time()
timeout = 60
while time.time() - start <= timeout:
status = client.get_job_status(job_id)
print(f"status: {status}")
if status in {
JobStatus.SUCCEEDED, JobStatus.STOPPED, JobStatus.FAILED
}:
break
time.sleep(5)
assert status == JobStatus.SUCCEEDED
return client.get_job_logs(job_id)
async def test_state_data_source_client(ray_start_cluster):
cluster = ray_start_cluster
# head
cluster.add_node(num_cpus=2)
ray.init(address=cluster.address)
# worker
worker = cluster.add_node(num_cpus=2)
GRPC_CHANNEL_OPTIONS = (
("grpc.enable_http_proxy", 0),
("grpc.max_send_message_length",
ray_constants.GRPC_CPP_MAX_MESSAGE_SIZE),
("grpc.max_receive_message_length",
ray_constants.GRPC_CPP_MAX_MESSAGE_SIZE),
)
gcs_channel = ray._private.utils.init_grpc_channel(cluster.address,
GRPC_CHANNEL_OPTIONS,
asynchronous=True)
client = StateDataSourceClient(gcs_channel)
"""
Test actor
"""
result = await client.get_all_actor_info()
assert isinstance(result, GetAllActorInfoReply)
"""
Test placement group
"""
result = await client.get_all_placement_group_info()
assert isinstance(result, GetAllPlacementGroupReply)
"""
Test node
"""
result = await client.get_all_node_info()
assert isinstance(result, GetAllNodeInfoReply)
"""
Test worker info
"""
result = await client.get_all_worker_info()
assert isinstance(result, GetAllWorkerInfoReply)
"""
Test job
"""
job_client = JobSubmissionClient(
f"http://{ray.worker.global_worker.node.address_info['webui_url']}")
job_id = job_client.submit_job( # noqa
# Entrypoint shell command to execute
entrypoint="ls", )
result = client.get_job_info()
assert list(result.keys())[0] == job_id
assert isinstance(result, dict)
"""
Test tasks
"""
with pytest.raises(ValueError):
# Since we didn't register this node id, it should raise an exception.
result = await client.get_task_info("1234")
wait_for_condition(lambda: len(ray.nodes()) == 2)
for node in ray.nodes():
node_id = node["NodeID"]
ip = node["NodeManagerAddress"]
port = int(node["NodeManagerPort"])
client.register_raylet_client(node_id, ip, port)
result = await client.get_task_info(node_id)
assert isinstance(result, GetTasksInfoReply)
assert len(client.get_all_registered_raylet_ids()) == 2
"""
Test objects
"""
with pytest.raises(ValueError):
# Since we didn't register this node id, it should raise an exception.
result = await client.get_object_info("1234")
wait_for_condition(lambda: len(ray.nodes()) == 2)
for node in ray.nodes():
node_id = node["NodeID"]
ip = node["NodeManagerAddress"]
port = int(node["NodeManagerPort"])
client.register_raylet_client(node_id, ip, port)
result = await client.get_object_info(node_id)
assert isinstance(result, GetNodeStatsReply)
"""
Test the exception is raised when the RPC error occurs.
"""
cluster.remove_node(worker)
# Wait until the dead node information is propagated.
wait_for_condition(lambda: len(
list(filter(lambda node: node["Alive"], ray.nodes()))) == 1)
for node in ray.nodes():
node_id = node["NodeID"]
if node["Alive"]:
continue
# Querying to the dead node raises gRPC error, which should be
# translated into `StateSourceNetworkException`
with pytest.raises(StateSourceNetworkException):
result = await client.get_object_info(node_id)
# Make sure unregister API works as expected.
client.unregister_raylet_client(node_id)
assert len(client.get_all_registered_raylet_ids()) == 1
# Since the node_id is unregistered, the API should raise ValueError.
with pytest.raises(ValueError):
result = await client.get_object_info(node_id)
async def test_state_data_source_client(ray_start_cluster):
cluster = ray_start_cluster
# head
cluster.add_node(num_cpus=2)
ray.init(address=cluster.address)
# worker
worker = cluster.add_node(num_cpus=2)
GRPC_CHANNEL_OPTIONS = (
*ray_constants.GLOBAL_GRPC_OPTIONS,
("grpc.max_send_message_length",
ray_constants.GRPC_CPP_MAX_MESSAGE_SIZE),
("grpc.max_receive_message_length",
ray_constants.GRPC_CPP_MAX_MESSAGE_SIZE),
)
gcs_channel = ray._private.utils.init_grpc_channel(cluster.address,
GRPC_CHANNEL_OPTIONS,
asynchronous=True)
client = StateDataSourceClient(gcs_channel)
"""
Test actor
"""
result = await client.get_all_actor_info()
assert isinstance(result, GetAllActorInfoReply)
"""
Test placement group
"""
result = await client.get_all_placement_group_info()
assert isinstance(result, GetAllPlacementGroupReply)
"""
Test node
"""
result = await client.get_all_node_info()
assert isinstance(result, GetAllNodeInfoReply)
"""
Test worker info
"""
result = await client.get_all_worker_info()
assert isinstance(result, GetAllWorkerInfoReply)
"""
Test job
"""
job_client = JobSubmissionClient(
f"http://{ray._private.worker.global_worker.node.address_info['webui_url']}"
)
job_id = job_client.submit_job( # noqa
# Entrypoint shell command to execute
entrypoint="ls", )
result = client.get_job_info()
assert list(result.keys())[0] == job_id
assert isinstance(result, dict)
"""
Test tasks
"""
with pytest.raises(ValueError):
# Since we didn't register this node id, it should raise an exception.
result = await client.get_task_info("1234")
wait_for_condition(lambda: len(ray.nodes()) == 2)
for node in ray.nodes():
node_id = node["NodeID"]
ip = node["NodeManagerAddress"]
port = int(node["NodeManagerPort"])
client.register_raylet_client(node_id, ip, port)
result = await client.get_task_info(node_id)
assert isinstance(result, GetTasksInfoReply)
assert len(client.get_all_registered_raylet_ids()) == 2
"""
Test objects
"""
with pytest.raises(ValueError):
# Since we didn't register this node id, it should raise an exception.
result = await client.get_object_info("1234")
wait_for_condition(lambda: len(ray.nodes()) == 2)
for node in ray.nodes():
node_id = node["NodeID"]
ip = node["NodeManagerAddress"]
port = int(node["NodeManagerPort"])
client.register_raylet_client(node_id, ip, port)
result = await client.get_object_info(node_id)
assert isinstance(result, GetNodeStatsReply)
"""
Test runtime env
"""
with pytest.raises(ValueError):
# Since we didn't register this node id, it should raise an exception.
result = await client.get_runtime_envs_info("1234")
wait_for_condition(lambda: len(ray.nodes()) == 2)
for node in ray.nodes():
node_id = node["NodeID"]
key = f"{dashboard_consts.DASHBOARD_AGENT_PORT_PREFIX}{node_id}"
def get_port():
return ray.experimental.internal_kv._internal_kv_get(
key, namespace=ray_constants.KV_NAMESPACE_DASHBOARD)
wait_for_condition(lambda: get_port() is not None)
# The second index is the gRPC port
port = json.loads(get_port())[1]
ip = node["NodeManagerAddress"]
client.register_agent_client(node_id, ip, port)
result = await client.get_runtime_envs_info(node_id)
assert isinstance(result, GetRuntimeEnvsInfoReply)
"""
Test logs
"""
with pytest.raises(ValueError):
result = await client.list_logs("1234", "*")
with pytest.raises(ValueError):
result = await client.stream_log("1234", "raylet.out", True, 100, 1, 5)
wait_for_condition(lambda: len(ray.nodes()) == 2)
# The node information should've been registered in the previous section.
for node in ray.nodes():
node_id = node["NodeID"]
result = await client.list_logs(node_id, timeout=30, glob_filter="*")
assert isinstance(result, ListLogsReply)
stream = await client.stream_log(node_id, "raylet.out", False, 10, 1,
5)
async for logs in stream:
log_lines = len(logs.data.decode().split("\n"))
assert isinstance(logs, StreamLogReply)
assert log_lines >= 10
assert log_lines <= 11
"""
Test the exception is raised when the RPC error occurs.
"""
cluster.remove_node(worker)
# Wait until the dead node information is propagated.
wait_for_condition(lambda: len(
list(filter(lambda node: node["Alive"], ray.nodes()))) == 1)
for node in ray.nodes():
node_id = node["NodeID"]
if node["Alive"]:
continue
# Querying to the dead node raises gRPC error, which should raise an exception.
with pytest.raises(DataSourceUnavailable):
await client.get_object_info(node_id)
# Make sure unregister API works as expected.
client.unregister_raylet_client(node_id)
assert len(client.get_all_registered_raylet_ids()) == 1
# Since the node_id is unregistered, the API should raise ValueError.
with pytest.raises(ValueError):
result = await client.get_object_info(node_id)
def test_successful_job_status(ray_start_with_dashboard, disable_aiohttp_cache,
enable_test_module, address_suffix):
address = ray_start_with_dashboard.address_info["webui_url"]
assert wait_until_server_available(address)
address = format_web_url(address)
job_sleep_time_s = 5
entrypoint = ('python -c"'
"import ray;"
"ray.init();"
"import time;"
f"time.sleep({job_sleep_time_s});"
'"')
client = JobSubmissionClient(address + address_suffix)
start_time_s = int(time.time())
runtime_env = {"env_vars": {"RAY_TEST_123": "123"}}
metadata = {"ray_test_456": "456"}
job_id = client.submit_job(entrypoint=entrypoint,
metadata=metadata,
runtime_env=runtime_env)
def wait_for_job_to_succeed():
data = _get_snapshot(address)
legacy_job_succeeded = False
job_succeeded = False
# Test legacy job snapshot (one driver per job).
for job_entry in data["data"]["snapshot"]["jobs"].values():
if job_entry["status"] is not None:
assert job_entry["config"]["metadata"][
"jobSubmissionId"] == job_id
assert job_entry["status"] in {
"PENDING", "RUNNING", "SUCCEEDED"
}
assert job_entry["statusMessage"] is not None
legacy_job_succeeded = job_entry["status"] == "SUCCEEDED"
# Test new jobs snapshot (0 to N drivers per job).
assert data["data"]["snapshot"]["jobSubmission"]
for job_submission_id, entry in data["data"]["snapshot"][
"jobSubmission"].items():
if entry["status"] is not None:
assert entry["jobSubmissionId"] == job_id
assert entry["entrypoint"] == entrypoint
assert entry["status"] in {"PENDING", "RUNNING", "SUCCEEDED"}
assert entry["message"] is not None
# TODO(architkulkarni): Disable automatic camelcase.
assert entry["runtimeEnv"] == {
"envVars": {
"RAYTest123": "123"
}
}
assert entry["metadata"] == {"rayTest456": "456"}
assert entry["errorType"] is None
assert abs(entry["startTime"] - start_time_s * 1000) <= 2000
if entry["status"] == "SUCCEEDED":
job_succeeded = True
assert (entry["endTime"] >=
entry["startTime"] + job_sleep_time_s * 1000)
print(f"Legacy job submission succeeded: {legacy_job_succeeded}")
print(f"Job submission succeeded: {job_succeeded}")
return legacy_job_succeeded and job_succeeded
wait_for_condition(wait_for_job_to_succeed, timeout=45)