Source code for swh.scheduler.simulator

# Copyright (C) 2021-2024  The Software Heritage developers
# See the AUTHORS file at the top-level directory of this distribution
# License: GNU General Public License version 3, or any later version
# See top-level LICENSE file for more information

"""This package runs the scheduler in a simulated environment, to evaluate
various metrics. See :ref:`swh-scheduler-simulator`.

This module orchestrates of the simulator by initializing processes and connecting
them together; these processes are defined in modules in the package and
simulate/call specific components."""

from datetime import datetime, timedelta, timezone
import logging
from typing import Dict, Generator, Optional

from simpy import Event

from swh.scheduler.interface import SchedulerInterface
from swh.scheduler.utils import create_origin_tasks, utcnow

from . import origin_scheduler, task_scheduler
from .common import Environment, Queue, SimulationReport, Task
from .origins import generate_listed_origin, lister_process, load_task_process

logger = logging.getLogger(__name__)

[docs] def update_metrics_process( env: Environment, update_interval: int ) -> Generator[Event, None, None]: """Update the scheduler metrics every `update_interval` (simulated) seconds, and add them to the SimulationReport """ t0 = env.time while True: metrics = env.scheduler.update_metrics(timestamp=env.time), metrics) dt = env.time - t0"time:%s visits:%s", dt, yield env.timeout(update_interval)
[docs] def worker_process( env: Environment, name: str, task_queue: Queue, status_queue: Queue ) -> Generator[Event, Task, None]: """A worker which consumes tasks from the input task_queue. Tasks themselves send OriginVisitStatus objects to the status_queue.""" logger.debug("%s worker %s: Start", env.time, name) while True: task = yield task_queue.get() logger.debug( "%s worker %s: Run task %s origin=%s", env.time, name, task.visit_type, task.origin, ) yield env.process(load_task_process(env, task, status_queue=status_queue))
[docs] def setup( env: Environment, scheduler_type: str, policy: Optional[str], workers_per_type: Dict[str, int], task_queue_capacity: int, min_batch_size: int, metrics_update_interval: int, ): task_queues = { visit_type: Queue(env, capacity=task_queue_capacity) for visit_type in workers_per_type } status_queue = Queue(env) if scheduler_type == "origin_scheduler": if policy is None: raise ValueError("origin_scheduler needs a scheduling policy") env.process( origin_scheduler.scheduler_runner_process( env, task_queues, policy, min_batch_size=min_batch_size ) ) env.process( origin_scheduler.scheduler_journal_client_process(env, status_queue) ) elif scheduler_type == "task_scheduler": if policy is not None: raise ValueError("task_scheduler doesn't support a scheduling policy") env.process( task_scheduler.scheduler_runner_process( env, task_queues, min_batch_size=min_batch_size ) ) env.process(task_scheduler.scheduler_listener_process(env, status_queue)) else: raise ValueError(f"Unknown scheduler type to simulate: {scheduler_type}") env.process(update_metrics_process(env, metrics_update_interval)) for visit_type, num_workers in workers_per_type.items(): task_queue = task_queues[visit_type] for i in range(num_workers): worker_name = f"worker-{visit_type}-{i}" env.process(worker_process(env, worker_name, task_queue, status_queue)) lister = env.scheduler.get_or_create_lister(name="example") assert env.process(lister_process(env,
[docs] def fill_test_data(scheduler: SchedulerInterface, num_origins: int = 100000): """Fills the database with mock data to test the simulator.""" stored_lister = scheduler.get_or_create_lister(name="example") assert is not None # Generate 'num_origins' new origins origins = [generate_listed_origin( for _ in range(num_origins)] scheduler.record_listed_origins(origins) scheduler.create_tasks( [ task.evolve( policy="recurring", next_run=origin.last_update or utcnow(), current_interval=timedelta(days=64), ) for (origin, task) in zip(origins, create_origin_tasks(origins, scheduler)) ] )
[docs] def run( scheduler: SchedulerInterface, scheduler_type: str, policy: Optional[str], runtime: Optional[int], ): NUM_WORKERS = 48 start_time = env = Environment(start_time=start_time) env.scheduler = scheduler = SimulationReport() setup( env, scheduler_type=scheduler_type, policy=policy, workers_per_type={"git": NUM_WORKERS}, task_queue_capacity=10000, min_batch_size=1000, metrics_update_interval=3600, ) try: except KeyboardInterrupt: pass finally: end_time = env.time print("total simulated time:", end_time - start_time) metrics = env.scheduler.update_metrics(timestamp=end_time), metrics) return