ray/dashboard/datacenter.py
SangBin Cho 3222d39fb8
[Dashboard] Dashboard memory improvement (#19385)
* many ppo profiling

* completed

* improve memory usage lint

* revert temporarily

* Addressed code review

* Fix a test
2021-10-19 19:34:42 -07:00

321 lines
12 KiB
Python

import logging
import ray.dashboard.consts as dashboard_consts
import ray.dashboard.memory_utils as memory_utils
# TODO(fyrestone): Not import from dashboard module.
from ray.dashboard.modules.actor.actor_utils import \
actor_classname_from_task_spec
from ray.dashboard.utils import Dict, Signal, async_loop_forever
logger = logging.getLogger(__name__)
class GlobalSignals:
node_info_fetched = Signal(dashboard_consts.SIGNAL_NODE_INFO_FETCHED)
node_summary_fetched = Signal(dashboard_consts.SIGNAL_NODE_SUMMARY_FETCHED)
job_info_fetched = Signal(dashboard_consts.SIGNAL_JOB_INFO_FETCHED)
worker_info_fetched = Signal(dashboard_consts.SIGNAL_WORKER_INFO_FETCHED)
class DataSource:
# {node id hex(str): node stats(dict of GetNodeStatsReply
# in node_manager.proto)}
node_stats = Dict()
# {node id hex(str): node physical stats(dict from reporter_agent.py)}
node_physical_stats = Dict()
# {actor id hex(str): actor table data(dict of ActorTableData
# in gcs.proto)}
actors = Dict()
# {job id hex(str): job table data(dict of JobTableData in gcs.proto)}
jobs = Dict()
# {node id hex(str): dashboard agent [http port(int), grpc port(int)]}
agents = Dict()
# {node id hex(str): gcs node info(dict of GcsNodeInfo in gcs.proto)}
nodes = Dict()
# {node id hex(str): ip address(str)}
node_id_to_ip = Dict()
# {node id hex(str): hostname(str)}
node_id_to_hostname = Dict()
# {node id hex(str): worker list}
node_workers = Dict()
# {node id hex(str): {actor id hex(str): actor table data}}
node_actors = Dict()
# {job id hex(str): worker list}
job_workers = Dict()
# {job id hex(str): {actor id hex(str): actor table data}}
job_actors = Dict()
# {worker id(str): core worker stats}
core_worker_stats = Dict()
# {job id hex(str): {event id(str): event dict}}
events = Dict()
# {node ip (str): log entries by pid
# (dict from pid to list of latest log entries)}
ip_and_pid_to_logs = Dict()
# {node ip (str): error entries by pid
# (dict from pid to list of latest err entries)}
ip_and_pid_to_errors = Dict()
class DataOrganizer:
@staticmethod
@async_loop_forever(dashboard_consts.PURGE_DATA_INTERVAL_SECONDS)
async def purge():
# Purge data that is out of date.
# These data sources are maintained by DashboardHead,
# we do not needs to purge them:
# * agents
# * nodes
# * node_id_to_ip
# * node_id_to_hostname
logger.info("Purge data.")
alive_nodes = {
node_id
for node_id, node_info in DataSource.nodes.items()
if node_info["state"] == "ALIVE"
}
for key in DataSource.node_stats.keys() - alive_nodes:
DataSource.node_stats.pop(key)
for key in DataSource.node_physical_stats.keys() - alive_nodes:
DataSource.node_physical_stats.pop(key)
@classmethod
@async_loop_forever(dashboard_consts.ORGANIZE_DATA_INTERVAL_SECONDS)
async def organize(cls):
job_workers = {}
node_workers = {}
core_worker_stats = {}
# await inside for loop, so we create a copy of keys().
for node_id in list(DataSource.nodes.keys()):
workers = await cls.get_node_workers(node_id)
for worker in workers:
job_id = worker["jobId"]
job_workers.setdefault(job_id, []).append(worker)
for stats in worker.get("coreWorkerStats", []):
worker_id = stats["workerId"]
core_worker_stats[worker_id] = stats
node_workers[node_id] = workers
DataSource.job_workers.reset(job_workers)
DataSource.node_workers.reset(node_workers)
DataSource.core_worker_stats.reset(core_worker_stats)
@classmethod
async def get_node_workers(cls, node_id):
workers = []
node_ip = DataSource.node_id_to_ip[node_id]
node_logs = DataSource.ip_and_pid_to_logs.get(node_ip, {})
node_errs = DataSource.ip_and_pid_to_errors.get(node_ip, {})
node_physical_stats = DataSource.node_physical_stats.get(node_id, {})
node_stats = DataSource.node_stats.get(node_id, {})
# Merge coreWorkerStats (node stats) to workers (node physical stats)
pid_to_worker_stats = {}
pid_to_language = {}
pid_to_job_id = {}
pids_on_node = set()
for core_worker_stats in node_stats.get("coreWorkersStats", []):
pid = core_worker_stats["pid"]
pids_on_node.add(pid)
pid_to_worker_stats.setdefault(pid, []).append(core_worker_stats)
pid_to_language[pid] = core_worker_stats["language"]
pid_to_job_id[pid] = core_worker_stats["jobId"]
# Clean up logs from a dead pid.
dead_pids = set(node_logs.keys()) - pids_on_node
for dead_pid in dead_pids:
if dead_pid in node_logs:
node_logs.mutable().pop(dead_pid)
for worker in node_physical_stats.get("workers", []):
worker = dict(worker)
pid = worker["pid"]
worker["logCount"] = len(node_logs.get(str(pid), []))
worker["errorCount"] = len(node_errs.get(str(pid), []))
worker["coreWorkerStats"] = pid_to_worker_stats.get(pid, [])
worker["language"] = pid_to_language.get(
pid, dashboard_consts.DEFAULT_LANGUAGE)
worker["jobId"] = pid_to_job_id.get(
pid, dashboard_consts.DEFAULT_JOB_ID)
await GlobalSignals.worker_info_fetched.send(node_id, worker)
workers.append(worker)
return workers
@classmethod
async def get_node_info(cls, node_id):
node_physical_stats = dict(
DataSource.node_physical_stats.get(node_id, {}))
node_stats = dict(DataSource.node_stats.get(node_id, {}))
node = DataSource.nodes.get(node_id, {})
node_ip = DataSource.node_id_to_ip.get(node_id)
# Merge node log count information into the payload
log_info = DataSource.ip_and_pid_to_logs.get(node_ip, {})
node_log_count = 0
for entries in log_info.values():
node_log_count += len(entries)
error_info = DataSource.ip_and_pid_to_errors.get(node_ip, {})
node_err_count = 0
for entries in error_info.values():
node_err_count += len(entries)
node_stats.pop("coreWorkersStats", None)
view_data = node_stats.get("viewData", [])
ray_stats = cls._extract_view_data(
view_data,
{"object_store_used_memory", "object_store_available_memory"})
node_info = node_physical_stats
# Merge node stats to node physical stats under raylet
node_info["raylet"] = node_stats
node_info["raylet"].update(ray_stats)
# Merge GcsNodeInfo to node physical stats
node_info["raylet"].update(node)
# Merge actors to node physical stats
node_info["actors"] = DataSource.node_actors.get(node_id, {})
# Update workers to node physical stats
node_info["workers"] = DataSource.node_workers.get(node_id, [])
node_info["logCount"] = node_log_count
node_info["errorCount"] = node_err_count
await GlobalSignals.node_info_fetched.send(node_info)
return node_info
@classmethod
async def get_node_summary(cls, node_id):
node_physical_stats = dict(
DataSource.node_physical_stats.get(node_id, {}))
node_stats = dict(DataSource.node_stats.get(node_id, {}))
node = DataSource.nodes.get(node_id, {})
node_physical_stats.pop("workers", None)
node_stats.pop("workersStats", None)
view_data = node_stats.get("viewData", [])
ray_stats = cls._extract_view_data(
view_data,
{"object_store_used_memory", "object_store_available_memory"})
node_stats.pop("viewData", None)
node_summary = node_physical_stats
# Merge node stats to node physical stats
node_summary["raylet"] = node_stats
node_summary["raylet"].update(ray_stats)
# Merge GcsNodeInfo to node physical stats
node_summary["raylet"].update(node)
await GlobalSignals.node_summary_fetched.send(node_summary)
return node_summary
@classmethod
async def get_all_node_summary(cls):
return [
await DataOrganizer.get_node_summary(node_id)
for node_id in DataSource.nodes.keys()
]
@classmethod
async def get_all_node_details(cls):
return [
await DataOrganizer.get_node_info(node_id)
for node_id in DataSource.nodes.keys()
]
@classmethod
async def get_all_actors(cls):
return {
actor_id: await cls._get_actor(actor)
for actor_id, actor in DataSource.actors.items()
}
@staticmethod
async def _get_actor(actor):
actor = dict(actor)
worker_id = actor["address"]["workerId"]
core_worker_stats = DataSource.core_worker_stats.get(worker_id, {})
actor_constructor = core_worker_stats.get("actorTitle",
"Unknown actor constructor")
actor["actorConstructor"] = actor_constructor
actor.update(core_worker_stats)
# TODO(fyrestone): remove this, give a link from actor
# info to worker info in front-end.
node_id = actor["address"]["rayletId"]
pid = core_worker_stats.get("pid")
node_physical_stats = DataSource.node_physical_stats.get(node_id, {})
actor_process_stats = None
actor_process_gpu_stats = []
if pid:
for process_stats in node_physical_stats.get("workers", []):
if process_stats["pid"] == pid:
actor_process_stats = process_stats
break
for gpu_stats in node_physical_stats.get("gpus", []):
for process in gpu_stats.get("processes", []):
if process["pid"] == pid:
actor_process_gpu_stats.append(gpu_stats)
break
actor["gpus"] = actor_process_gpu_stats
actor["processStats"] = actor_process_stats
return actor
@classmethod
async def get_actor_creation_tasks(cls):
infeasible_tasks = sum(
(list(node_stats.get("infeasibleTasks", []))
for node_stats in DataSource.node_stats.values()), [])
new_infeasible_tasks = []
for task in infeasible_tasks:
task = dict(task)
task["actorClass"] = actor_classname_from_task_spec(task)
task["state"] = "INFEASIBLE"
new_infeasible_tasks.append(task)
resource_pending_tasks = sum(
(list(data.get("readyTasks", []))
for data in DataSource.node_stats.values()), [])
new_resource_pending_tasks = []
for task in resource_pending_tasks:
task = dict(task)
task["actorClass"] = actor_classname_from_task_spec(task)
task["state"] = "PENDING_RESOURCES"
new_resource_pending_tasks.append(task)
results = {
task["actorCreationTaskSpec"]["actorId"]: task
for task in new_resource_pending_tasks + new_infeasible_tasks
}
return results
@classmethod
async def get_memory_table(cls,
sort_by=memory_utils.SortingType.OBJECT_SIZE,
group_by=memory_utils.GroupByType.STACK_TRACE):
all_worker_stats = []
for node_stats in DataSource.node_stats.values():
all_worker_stats.extend(node_stats.get("coreWorkersStats", []))
memory_information = memory_utils.construct_memory_table(
all_worker_stats, group_by=group_by, sort_by=sort_by)
return memory_information
@staticmethod
def _extract_view_data(views, data_keys):
view_data = {}
for view in views:
view_name = view["viewName"]
if view_name in data_keys:
if not view.get("measures"):
view_data[view_name] = 0
continue
measure = view["measures"][0]
if "doubleValue" in measure:
measure_value = measure["doubleValue"]
elif "intValue" in measure:
measure_value = measure["intValue"]
else:
measure_value = 0
view_data[view_name] = measure_value
return view_data