chore: import upstream snapshot with attribution

This commit is contained in:
wehub-resource-sync
2026-07-13 13:17:40 +08:00
commit f1825c8ceb
10096 changed files with 2364182 additions and 0 deletions
@@ -0,0 +1,478 @@
import logging
import re
from collections import defaultdict
from typing import AsyncIterable, Awaitable, Callable, Dict, List, Optional, Tuple
from ray import ActorID, NodeID, WorkerID
from ray._common.pydantic_compat import BaseModel
from ray.core.generated.gcs_pb2 import ActorTableData
from ray.dashboard.modules.job.common import JOB_LOGS_PATH_TEMPLATE
from ray.util.state.common import (
DEFAULT_RPC_TIMEOUT,
GetLogOptions,
protobuf_to_task_state_dict,
)
from ray.util.state.state_manager import StateDataSourceClient
if BaseModel is None:
raise ModuleNotFoundError("Please install pydantic via `pip install pydantic`.")
logger = logging.getLogger(__name__)
WORKER_LOG_PATTERN = re.compile(r".*worker-([0-9a-f]+)-([0-9a-f]+)-(\d+).(out|err)")
class ResolvedStreamFileInfo(BaseModel):
# The node id where the log file is located.
node_id: str
# The log file path name. Could be a relative path relative to ray's logging folder,
# or an absolute path.
filename: str
# Start offset in the log file to stream from. None to indicate beginning of
# the file, or determined by last tail lines.
start_offset: Optional[int] = None
# End offset in the log file to stream from. None to indicate the end of the file.
end_offset: Optional[int] = None
class LogsManager:
def __init__(self, data_source_client: StateDataSourceClient):
self.client = data_source_client
@property
def data_source_client(self) -> StateDataSourceClient:
return self.client
async def ip_to_node_id(self, node_ip: Optional[str]) -> Optional[str]:
"""Resolve the node id in hex from a given node ip.
Args:
node_ip: The node ip.
Returns:
node_id if there's a node id that matches the given node ip and is alive.
None otherwise.
"""
return await self.client.ip_to_node_id(node_ip)
async def list_logs(
self, node_id: str, timeout: int, glob_filter: str = "*"
) -> Dict[str, List[str]]:
"""Return a list of log files on a given node id filtered by the glob.
Args:
node_id: The node id where log files present.
timeout: The timeout of the API.
glob_filter: The glob filter to filter out log files.
Returns:
Dictionary of {component_name -> list of log files}
Raises:
ValueError: If a source is unresponsive.
"""
reply = await self.client.list_logs(node_id, glob_filter, timeout=timeout)
return self._categorize_log_files(reply.log_files)
async def stream_logs(
self,
options: GetLogOptions,
get_actor_fn: Callable[[ActorID], Awaitable[Optional[ActorTableData]]],
) -> AsyncIterable[bytes]:
"""Generate a stream of logs in bytes.
Args:
options: The option for streaming logs.
get_actor_fn: Callable used to resolve actor metadata when the
request targets an actor's logs.
Yields:
bytes: Successive chunks of log content streamed from the agent.
"""
node_id = options.node_id
if node_id is None:
node_id = await self.ip_to_node_id(options.node_ip)
res = await self.resolve_filename(
node_id=node_id,
log_filename=options.filename,
actor_id=options.actor_id,
task_id=options.task_id,
attempt_number=options.attempt_number,
pid=options.pid,
get_actor_fn=get_actor_fn,
timeout=options.timeout,
suffix=options.suffix,
submission_id=options.submission_id,
)
keep_alive = options.media_type == "stream"
stream = await self.client.stream_log(
node_id=res.node_id,
log_file_name=res.filename,
keep_alive=keep_alive,
lines=options.lines,
interval=options.interval,
# If we keepalive logs connection, we shouldn't have timeout
# otherwise the stream will be terminated forcefully
# after the deadline is expired.
timeout=options.timeout if not keep_alive else None,
start_offset=res.start_offset,
end_offset=res.end_offset,
)
async for streamed_log in stream:
yield streamed_log.data
async def _resolve_job_filename(self, sub_job_id: str) -> Tuple[str, str]:
"""Return the log file name and node id for a given job submission id.
Args:
sub_job_id: The job submission id.
Returns:
The log file name and node id.
"""
job_infos = await self.client.get_job_info(timeout=DEFAULT_RPC_TIMEOUT)
target_job = None
for job_info in job_infos:
if job_info.submission_id == sub_job_id:
target_job = job_info
break
if target_job is None:
logger.info(f"Submission job ID {sub_job_id} not found.")
return None, None
node_id = job_info.driver_node_id
if node_id is None:
raise ValueError(
f"Job {sub_job_id} has no driver node id info. "
"This is likely a bug. Please file an issue."
)
log_filename = JOB_LOGS_PATH_TEMPLATE.format(submission_id=sub_job_id)
return node_id, log_filename
async def _resolve_worker_file(
self,
node_id_hex: str,
worker_id_hex: Optional[str],
pid: Optional[int],
suffix: str,
timeout: int,
) -> Optional[str]:
"""Resolve worker log file."""
if worker_id_hex is not None and pid is not None:
raise ValueError(
f"Only one of worker id({worker_id_hex}) or pid({pid}) should be"
"provided."
)
if worker_id_hex is not None:
log_files = await self.list_logs(
node_id_hex, timeout, glob_filter=f"*{worker_id_hex}*{suffix}"
)
else:
log_files = await self.list_logs(
node_id_hex, timeout, glob_filter=f"*{pid}*{suffix}"
)
# Find matching worker logs.
for filename in [*log_files["worker_out"], *log_files["worker_err"]]:
# Worker logs look like worker-[worker_id]-[job_id]-[pid].out
if worker_id_hex is not None:
worker_id_from_filename = WORKER_LOG_PATTERN.match(filename).group(1)
if worker_id_from_filename == worker_id_hex:
return filename
else:
worker_pid_from_filename = int(
WORKER_LOG_PATTERN.match(filename).group(3)
)
if worker_pid_from_filename == pid:
return filename
return None
async def _resolve_actor_filename(
self,
actor_id: ActorID,
get_actor_fn: Callable[[ActorID], Awaitable[Optional[ActorTableData]]],
suffix: str,
timeout: int,
):
"""Resolve actor log file.
Args:
actor_id: The actor id.
get_actor_fn: The function to get actor information.
suffix: The suffix of the log file.
timeout: Timeout in seconds.
Returns:
The log file name and node id.
Raises:
ValueError: If actor data is not found or get_actor_fn is not provided.
"""
if get_actor_fn is None:
raise ValueError("get_actor_fn needs to be specified for actor_id")
actor_data = await get_actor_fn(actor_id)
if actor_data is None:
raise ValueError(f"Actor ID {actor_id} not found.")
# TODO(sang): Only the latest worker id can be obtained from
# actor information now. That means, if actors are restarted,
# there's no way for us to get the past worker ids.
worker_id_binary = actor_data.address.worker_id
if not worker_id_binary:
raise ValueError(
f"Worker ID for Actor ID {actor_id} not found. "
"Actor is not scheduled yet."
)
worker_id = WorkerID(worker_id_binary)
node_id_binary = actor_data.address.node_id
if not node_id_binary:
raise ValueError(
f"Node ID for Actor ID {actor_id} not found. "
"Actor is not scheduled yet."
)
node_id = NodeID(node_id_binary)
log_filename = await self._resolve_worker_file(
node_id_hex=node_id.hex(),
worker_id_hex=worker_id.hex(),
pid=None,
suffix=suffix,
timeout=timeout,
)
return node_id.hex(), log_filename
async def _resolve_task_filename(
self, task_id: str, attempt_number: int, suffix: str, timeout: int
):
"""Resolve log file for a task.
Args:
task_id: The task id.
attempt_number: The attempt number.
suffix: The suffix of the log file, e.g. out or err.
timeout: Timeout in seconds.
Returns:
The log file name, node id, the start and end offsets of the
corresponding task log in the file.
Raises:
FileNotFoundError: If the log file is not found.
ValueError: If the suffix is not out or err.
"""
log_filename = None
node_id = None
start_offset = None
end_offset = None
if suffix not in ["out", "err"]:
raise ValueError(f"Suffix {suffix} is not supported.")
reply = await self.client.get_all_task_info(
filters=[("task_id", "=", task_id)], timeout=timeout
)
# Check if the task is found.
if len(reply.events_by_task) == 0:
raise FileNotFoundError(
f"Could not find log file for task: {task_id}"
f" (attempt {attempt_number}) with suffix: {suffix}"
)
task_event = None
for t in reply.events_by_task:
if t.attempt_number == attempt_number:
task_event = t
break
if task_event is None:
raise FileNotFoundError(
"Could not find log file for task attempt:"
f"{task_id}({attempt_number})"
)
# Get the worker id and node id.
task = protobuf_to_task_state_dict(task_event)
worker_id = task.get("worker_id", None)
node_id = task.get("node_id", None)
log_info = task.get("task_log_info", None)
actor_id = task.get("actor_id", None)
if node_id is None:
raise FileNotFoundError(
"Could not find log file for task attempt."
f"{task_id}({attempt_number}) due to missing node info."
)
if log_info is None and actor_id is not None:
# This is a concurrent actor task. The logs will be interleaved.
# So we return the log file of the actor instead.
raise FileNotFoundError(
f"For actor task, please query actor log for "
f"actor({actor_id}): e.g. ray logs actor --id {actor_id} . Or "
"set RAY_ENABLE_RECORD_ACTOR_TASK_LOGGING=1 in actor's runtime env "
"or when starting the cluster. Recording actor task's log could be "
"expensive, so Ray turns it off by default."
)
elif log_info is None:
raise FileNotFoundError(
"Could not find log file for task attempt:"
f"{task_id}({attempt_number})."
f"Worker id = {worker_id}, node id = {node_id},"
f"log_info = {log_info}"
)
filename_key = "stdout_file" if suffix == "out" else "stderr_file"
log_filename = log_info.get(filename_key, None)
if log_filename is None:
raise FileNotFoundError(
f"Missing log filename info in {log_info} for task {task_id},"
f"attempt {attempt_number}"
)
start_offset = log_info.get(f"std{suffix}_start", None)
end_offset = log_info.get(f"std{suffix}_end", None)
return node_id, log_filename, start_offset, end_offset
async def resolve_filename(
self,
*,
node_id: Optional[str] = None,
log_filename: Optional[str] = None,
actor_id: Optional[str] = None,
task_id: Optional[str] = None,
attempt_number: Optional[int] = None,
pid: Optional[str] = None,
get_actor_fn: Optional[
Callable[[ActorID], Awaitable[Optional[ActorTableData]]]
] = None,
timeout: int = DEFAULT_RPC_TIMEOUT,
suffix: str = "out",
submission_id: Optional[str] = None,
) -> ResolvedStreamFileInfo:
"""Return the file name given all options.
Args:
node_id: The node's id from which logs are resolved.
log_filename: Filename of the log file.
actor_id: Id of the actor that generates the log file.
task_id: Id of the task that generates the log file.
attempt_number: The attempt number of the task. Used with
``task_id`` to disambiguate retries.
pid: Id of the worker process that generates the log file.
get_actor_fn: Callback to get the actor's data by id.
timeout: Timeout for the gRPC to listing logs on the node
specified by `node_id`.
suffix: Log suffix if no `log_filename` is provided, when
resolving by other ids'. Default to "out".
submission_id: The submission id for a submission job.
Returns:
A ``ResolvedStreamFileInfo`` describing the resolved node id,
filename, and (optional) byte offsets to stream.
"""
start_offset = None
end_offset = None
if suffix not in ["out", "err"]:
raise ValueError(f"Suffix {suffix} is not supported. ")
# TODO(rickyx): We should make sure we do some sort of checking on the log
# filename
if actor_id:
node_id, log_filename = await self._resolve_actor_filename(
ActorID.from_hex(actor_id), get_actor_fn, suffix, timeout
)
elif task_id:
(
node_id,
log_filename,
start_offset,
end_offset,
) = await self._resolve_task_filename(
task_id, attempt_number, suffix, timeout
)
elif submission_id:
node_id, log_filename = await self._resolve_job_filename(submission_id)
elif pid:
if node_id is None:
raise ValueError(
"Node id needs to be specified for resolving"
f" filenames of pid {pid}"
)
log_filename = await self._resolve_worker_file(
node_id_hex=node_id,
worker_id_hex=None,
pid=pid,
suffix=suffix,
timeout=timeout,
)
if log_filename is None:
raise FileNotFoundError(
"Could not find a log file. Please make sure the given "
"option exists in the cluster.\n"
f"\tnode_id: {node_id}\n"
f"\tfilename: {log_filename}\n"
f"\tactor_id: {actor_id}\n"
f"\ttask_id: {task_id}\n"
f"\tpid: {pid}\n"
f"\tsuffix: {suffix}\n"
f"\tsubmission_id: {submission_id}\n"
f"\tattempt_number: {attempt_number}\n"
)
res = ResolvedStreamFileInfo(
node_id=node_id,
filename=log_filename,
start_offset=start_offset,
end_offset=end_offset,
)
logger.info(f"Resolved log file: {res}")
return res
def _categorize_log_files(self, log_files: List[str]) -> Dict[str, List[str]]:
"""Categorize the given log files after filterieng them out using a given glob.
Args:
log_files: Filenames returned from a ``list_logs`` query, already
filtered by the caller's glob.
Returns:
Dictionary of {component_name -> list of log files}
"""
result = defaultdict(list)
for log_file in log_files:
if "worker" in log_file and (log_file.endswith(".out")):
result["worker_out"].append(log_file)
elif "worker" in log_file and (log_file.endswith(".err")):
result["worker_err"].append(log_file)
elif "core-worker" in log_file and log_file.endswith(".log"):
result["core_worker"].append(log_file)
elif "core-driver" in log_file and log_file.endswith(".log"):
result["driver"].append(log_file)
elif "raylet." in log_file:
result["raylet"].append(log_file)
elif "gcs_server." in log_file:
result["gcs_server"].append(log_file)
elif "log_monitor" in log_file:
result["internal"].append(log_file)
elif "monitor" in log_file:
result["autoscaler"].append(log_file)
elif "agent." in log_file:
result["agent"].append(log_file)
elif "dashboard." in log_file:
result["dashboard"].append(log_file)
else:
result["internal"].append(log_file)
return result