2024-12-03 22:32:56 +00:00

286 lines
10 KiB
Python

import multiprocessing
from typing import Any
from typing import cast
from celery import bootsteps # type: ignore
from celery import Celery
from celery import signals
from celery import Task
from celery.exceptions import WorkerShutdown
from celery.signals import celeryd_init
from celery.signals import worker_init
from celery.signals import worker_ready
from celery.signals import worker_shutdown
from redis.lock import Lock as RedisLock
import danswer.background.celery.apps.app_base as app_base
from danswer.background.celery.apps.app_base import task_logger
from danswer.background.celery.celery_utils import celery_is_worker_primary
from danswer.background.celery.tasks.indexing.tasks import (
get_unfenced_index_attempt_ids,
)
from danswer.configs.constants import CELERY_PRIMARY_WORKER_LOCK_TIMEOUT
from danswer.configs.constants import DanswerRedisLocks
from danswer.configs.constants import POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME
from danswer.db.engine import get_session_with_default_tenant
from danswer.db.engine import SqlEngine
from danswer.db.index_attempt import get_index_attempt
from danswer.db.index_attempt import mark_attempt_canceled
from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
from danswer.redis.redis_connector_delete import RedisConnectorDelete
from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
from danswer.redis.redis_connector_ext_group_sync import RedisConnectorExternalGroupSync
from danswer.redis.redis_connector_index import RedisConnectorIndex
from danswer.redis.redis_connector_prune import RedisConnectorPrune
from danswer.redis.redis_connector_stop import RedisConnectorStop
from danswer.redis.redis_document_set import RedisDocumentSet
from danswer.redis.redis_pool import get_redis_client
from danswer.redis.redis_usergroup import RedisUserGroup
from danswer.utils.logger import setup_logger
from shared_configs.configs import MULTI_TENANT
logger = setup_logger()
celery_app = Celery(__name__)
celery_app.config_from_object("danswer.background.celery.configs.primary")
@signals.task_prerun.connect
def on_task_prerun(
sender: Any | None = None,
task_id: str | None = None,
task: Task | None = None,
args: tuple | None = None,
kwargs: dict | None = None,
**kwds: Any,
) -> None:
app_base.on_task_prerun(sender, task_id, task, args, kwargs, **kwds)
@signals.task_postrun.connect
def on_task_postrun(
sender: Any | None = None,
task_id: str | None = None,
task: Task | None = None,
args: tuple | None = None,
kwargs: dict | None = None,
retval: Any | None = None,
state: str | None = None,
**kwds: Any,
) -> None:
app_base.on_task_postrun(sender, task_id, task, args, kwargs, retval, state, **kwds)
@celeryd_init.connect
def on_celeryd_init(sender: Any = None, conf: Any = None, **kwargs: Any) -> None:
app_base.on_celeryd_init(sender, conf, **kwargs)
@worker_init.connect
def on_worker_init(sender: Any, **kwargs: Any) -> None:
logger.info("worker_init signal received.")
logger.info(f"Multiprocessing start method: {multiprocessing.get_start_method()}")
SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME)
SqlEngine.init_engine(pool_size=8, max_overflow=0)
# Startup checks are not needed in multi-tenant case
if MULTI_TENANT:
return
app_base.wait_for_redis(sender, **kwargs)
app_base.wait_for_db(sender, **kwargs)
app_base.wait_for_vespa(sender, **kwargs)
logger.info("Running as the primary celery worker.")
# This is singleton work that should be done on startup exactly once
# by the primary worker. This is unnecessary in the multi tenant scenario
r = get_redis_client(tenant_id=None)
# Log the role and slave count - being connected to a slave or slave count > 0 could be problematic
info: dict[str, Any] = cast(dict, r.info("replication"))
role: str = cast(str, info.get("role"))
connected_slaves: int = info.get("connected_slaves", 0)
logger.info(
f"Redis INFO REPLICATION: role={role} connected_slaves={connected_slaves}"
)
# For the moment, we're assuming that we are the only primary worker
# that should be running.
# TODO: maybe check for or clean up another zombie primary worker if we detect it
r.delete(DanswerRedisLocks.PRIMARY_WORKER)
# this process wide lock is taken to help other workers start up in order.
# it is planned to use this lock to enforce singleton behavior on the primary
# worker, since the primary worker does redis cleanup on startup, but this isn't
# implemented yet.
# set thread_local=False since we don't control what thread the periodic task might
# reacquire the lock with
lock: RedisLock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
thread_local=False,
)
logger.info("Primary worker lock: Acquire starting.")
acquired = lock.acquire(blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2)
if acquired:
logger.info("Primary worker lock: Acquire succeeded.")
else:
logger.error("Primary worker lock: Acquire failed!")
raise WorkerShutdown("Primary worker lock could not be acquired!")
# tacking on our own user data to the sender
sender.primary_worker_lock = lock
# As currently designed, when this worker starts as "primary", we reinitialize redis
# to a clean state (for our purposes, anyway)
r.delete(DanswerRedisLocks.CHECK_VESPA_SYNC_BEAT_LOCK)
r.delete(DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK)
r.delete(RedisConnectorCredentialPair.get_taskset_key())
r.delete(RedisConnectorCredentialPair.get_fence_key())
RedisDocumentSet.reset_all(r)
RedisUserGroup.reset_all(r)
RedisConnectorDelete.reset_all(r)
RedisConnectorPrune.reset_all(r)
RedisConnectorIndex.reset_all(r)
RedisConnectorStop.reset_all(r)
RedisConnectorPermissionSync.reset_all(r)
RedisConnectorExternalGroupSync.reset_all(r)
# mark orphaned index attempts as failed
with get_session_with_default_tenant() as db_session:
unfenced_attempt_ids = get_unfenced_index_attempt_ids(db_session, r)
for attempt_id in unfenced_attempt_ids:
attempt = get_index_attempt(db_session, attempt_id)
if not attempt:
continue
failure_reason = (
f"Canceling leftover index attempt found on startup: "
f"index_attempt={attempt.id} "
f"cc_pair={attempt.connector_credential_pair_id} "
f"search_settings={attempt.search_settings_id}"
)
logger.warning(failure_reason)
mark_attempt_canceled(attempt.id, db_session, failure_reason)
@worker_ready.connect
def on_worker_ready(sender: Any, **kwargs: Any) -> None:
app_base.on_worker_ready(sender, **kwargs)
@worker_shutdown.connect
def on_worker_shutdown(sender: Any, **kwargs: Any) -> None:
app_base.on_worker_shutdown(sender, **kwargs)
@signals.setup_logging.connect
def on_setup_logging(
loglevel: Any, logfile: Any, format: Any, colorize: Any, **kwargs: Any
) -> None:
app_base.on_setup_logging(loglevel, logfile, format, colorize, **kwargs)
class HubPeriodicTask(bootsteps.StartStopStep):
"""Regularly reacquires the primary worker lock outside of the task queue.
Use the task_logger in this class to avoid double logging.
This cannot be done inside a regular beat task because it must run on schedule and
a queue of existing work would starve the task from running.
"""
# it's unclear to me whether using the hub's timer or the bootstep timer is better
requires = {"celery.worker.components:Hub"}
def __init__(self, worker: Any, **kwargs: Any) -> None:
self.interval = CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 8 # Interval in seconds
self.task_tref = None
def start(self, worker: Any) -> None:
if not celery_is_worker_primary(worker):
return
# Access the worker's event loop (hub)
hub = worker.consumer.controller.hub
# Schedule the periodic task
self.task_tref = hub.call_repeatedly(
self.interval, self.run_periodic_task, worker
)
task_logger.info("Scheduled periodic task with hub.")
def run_periodic_task(self, worker: Any) -> None:
try:
if not celery_is_worker_primary(worker):
return
if not hasattr(worker, "primary_worker_lock"):
return
lock: RedisLock = worker.primary_worker_lock
r = get_redis_client(tenant_id=None)
if lock.owned():
task_logger.debug("Reacquiring primary worker lock.")
lock.reacquire()
else:
task_logger.warning(
"Full acquisition of primary worker lock. "
"Reasons could be worker restart or lock expiration."
)
lock = r.lock(
DanswerRedisLocks.PRIMARY_WORKER,
timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
)
task_logger.info("Primary worker lock: Acquire starting.")
acquired = lock.acquire(
blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2
)
if acquired:
task_logger.info("Primary worker lock: Acquire succeeded.")
worker.primary_worker_lock = lock
else:
task_logger.error("Primary worker lock: Acquire failed!")
raise TimeoutError("Primary worker lock could not be acquired!")
except Exception:
task_logger.exception("Periodic task failed.")
def stop(self, worker: Any) -> None:
# Cancel the scheduled task when the worker stops
if self.task_tref:
self.task_tref.cancel()
task_logger.info("Canceled periodic task with hub.")
celery_app.steps["worker"].add(HubPeriodicTask)
celery_app.autodiscover_tasks(
[
"danswer.background.celery.tasks.connector_deletion",
"danswer.background.celery.tasks.indexing",
"danswer.background.celery.tasks.periodic",
"danswer.background.celery.tasks.doc_permission_syncing",
"danswer.background.celery.tasks.external_group_syncing",
"danswer.background.celery.tasks.pruning",
"danswer.background.celery.tasks.shared",
"danswer.background.celery.tasks.vespa",
]
)