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https://github.com/vale981/ray
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This is the second part of https://docs.google.com/document/d/12qP3x5uaqZSKS-A_kK0ylPOp0E02_l-deAbmm8YtdFw/edit#. After this PR, dashboard agents will fully work with minimal ray installation. Note that this PR requires to introduce "aioredis", "frozenlist", and "aiosignal" to the minimal installation. These dependencies are very small (or will be removed soon), and including them to minimal makes thing very easy. Please see the below for the reasoning.
173 lines
6.9 KiB
Python
173 lines
6.9 KiB
Python
import json
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import logging
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import yaml
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import os
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import aiohttp.web
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from aioredis.pubsub import Receiver
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import ray
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import ray.dashboard.modules.reporter.reporter_consts as reporter_consts
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import ray.dashboard.utils as dashboard_utils
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import ray.dashboard.optional_utils as dashboard_optional_utils
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from ray._private.gcs_pubsub import gcs_pubsub_enabled, \
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GcsAioResourceUsageSubscriber
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import ray._private.services
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import ray._private.utils
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from ray.ray_constants import (DEBUG_AUTOSCALING_STATUS,
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DEBUG_AUTOSCALING_STATUS_LEGACY,
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DEBUG_AUTOSCALING_ERROR)
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from ray.core.generated import reporter_pb2
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from ray.core.generated import reporter_pb2_grpc
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import ray.experimental.internal_kv as internal_kv
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from ray.dashboard.datacenter import DataSource
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logger = logging.getLogger(__name__)
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routes = dashboard_optional_utils.ClassMethodRouteTable
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class ReportHead(dashboard_utils.DashboardHeadModule):
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def __init__(self, dashboard_head):
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super().__init__(dashboard_head)
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self._stubs = {}
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self._ray_config = None
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DataSource.agents.signal.append(self._update_stubs)
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async def _update_stubs(self, change):
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if change.old:
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node_id, port = change.old
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ip = DataSource.node_id_to_ip[node_id]
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self._stubs.pop(ip)
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if change.new:
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node_id, ports = change.new
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ip = DataSource.node_id_to_ip[node_id]
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options = (("grpc.enable_http_proxy", 0), )
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channel = ray._private.utils.init_grpc_channel(
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f"{ip}:{ports[1]}", options=options, asynchronous=True)
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stub = reporter_pb2_grpc.ReporterServiceStub(channel)
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self._stubs[ip] = stub
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@routes.get("/api/launch_profiling")
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async def launch_profiling(self, req) -> aiohttp.web.Response:
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ip = req.query["ip"]
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pid = int(req.query["pid"])
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duration = int(req.query["duration"])
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reporter_stub = self._stubs[ip]
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reply = await reporter_stub.GetProfilingStats(
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reporter_pb2.GetProfilingStatsRequest(pid=pid, duration=duration))
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profiling_info = (json.loads(reply.profiling_stats)
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if reply.profiling_stats else reply.std_out)
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return dashboard_optional_utils.rest_response(
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success=True,
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message="Profiling success.",
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profiling_info=profiling_info)
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@routes.get("/api/ray_config")
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async def get_ray_config(self, req) -> aiohttp.web.Response:
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if self._ray_config is None:
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try:
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config_path = os.path.expanduser("~/ray_bootstrap_config.yaml")
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with open(config_path) as f:
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cfg = yaml.safe_load(f)
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except yaml.YAMLError:
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return dashboard_optional_utils.rest_response(
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success=False,
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message=f"No config found at {config_path}.",
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)
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except FileNotFoundError:
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return dashboard_optional_utils.rest_response(
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success=False,
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message="Invalid config, could not load YAML.")
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payload = {
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"min_workers": cfg.get("min_workers", "unspecified"),
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"max_workers": cfg.get("max_workers", "unspecified")
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}
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try:
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payload["head_type"] = cfg["head_node"]["InstanceType"]
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except KeyError:
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payload["head_type"] = "unknown"
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try:
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payload["worker_type"] = cfg["worker_nodes"]["InstanceType"]
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except KeyError:
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payload["worker_type"] = "unknown"
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self._ray_config = payload
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return dashboard_optional_utils.rest_response(
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success=True,
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message="Fetched ray config.",
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**self._ray_config,
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)
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@routes.get("/api/cluster_status")
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async def get_cluster_status(self, req):
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"""Returns status information about the cluster.
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Currently contains two fields:
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autoscaling_status (str): a status message from the autoscaler.
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autoscaling_error (str): an error message from the autoscaler if
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anything has gone wrong during autoscaling.
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These fields are both read from the GCS, it's expected that the
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autoscaler writes them there.
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"""
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assert ray.experimental.internal_kv._internal_kv_initialized()
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legacy_status = internal_kv._internal_kv_get(
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DEBUG_AUTOSCALING_STATUS_LEGACY)
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formatted_status_string = internal_kv._internal_kv_get(
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DEBUG_AUTOSCALING_STATUS)
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formatted_status = json.loads(formatted_status_string.decode()
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) if formatted_status_string else {}
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error = internal_kv._internal_kv_get(DEBUG_AUTOSCALING_ERROR)
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return dashboard_optional_utils.rest_response(
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success=True,
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message="Got cluster status.",
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autoscaling_status=legacy_status.decode()
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if legacy_status else None,
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autoscaling_error=error.decode() if error else None,
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cluster_status=formatted_status if formatted_status else None,
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)
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async def run(self, server):
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if gcs_pubsub_enabled():
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gcs_addr = await self._dashboard_head.get_gcs_address()
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subscriber = GcsAioResourceUsageSubscriber(gcs_addr)
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await subscriber.subscribe()
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while True:
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try:
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# The key is b'RAY_REPORTER:{node id hex}',
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# e.g. b'RAY_REPORTER:2b4fbd...'
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key, data = await subscriber.poll()
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if key is None:
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continue
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data = json.loads(data)
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node_id = key.split(":")[-1]
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DataSource.node_physical_stats[node_id] = data
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except Exception:
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logger.exception("Error receiving node physical stats "
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"from reporter agent.")
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else:
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receiver = Receiver()
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aioredis_client = self._dashboard_head.aioredis_client
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reporter_key = "{}*".format(reporter_consts.REPORTER_PREFIX)
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await aioredis_client.psubscribe(receiver.pattern(reporter_key))
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logger.info(f"Subscribed to {reporter_key}")
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async for sender, msg in receiver.iter():
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try:
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key, data = msg
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data = json.loads(ray._private.utils.decode(data))
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key = key.decode("utf-8")
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node_id = key.split(":")[-1]
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DataSource.node_physical_stats[node_id] = data
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except Exception:
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logger.exception("Error receiving node physical stats "
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"from reporter agent.")
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@staticmethod
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def is_minimal_module():
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return False
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