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