def copy_object(obj_id, src, dst):
obj = get_object(src, obj_id)
if obj is not None:
put_object(dst, obj_id, obj)
statsd.increment(CONTENT_BYTES_METRIC, len(obj))
return len(obj)
return 0
def pre_add(self, kw):
"""Called before the 'add' method."""
statsd.increment(
"swh_objstorage_in_bytes_total",
len(kw["content"]),
tags={"endpoint": "add_bytes"},
)
def process(self, worker_fn):
"""Polls Kafka for a batch of messages, and calls the worker_fn
with these messages.
Args:
worker_fn Callable[Dict[str, List[dict]]]: Function called with
the messages as
argument.
"""
total_objects_processed = 0
# timeout for message poll
timeout = 1.0
with statsd.status_gauge(JOURNAL_STATUS_METRIC,
statuses=["idle", "processing",
"waiting"]) as set_status:
set_status("idle")
while True:
batch_size = self.batch_size
if self.stop_after_objects:
if total_objects_processed >= self.stop_after_objects:
break
# clamp batch size to avoid overrunning stop_after_objects
batch_size = min(
self.stop_after_objects - total_objects_processed,
batch_size,
)
set_status("waiting")
for i in cycle(reversed(range(10))):
messages = self.consumer.consume(timeout=timeout,
num_messages=batch_size)
if messages:
break
# do check for an EOF condition iff we already consumed
# messages, otherwise we could detect an EOF condition
# before messages had a chance to reach us (e.g. in tests)
if total_objects_processed > 0 and self.stop_on_eof and i == 0:
at_eof = all(
(tp.topic, tp.partition) in self.eof_reached
for tp in self.consumer.assignment())
if at_eof:
break
if messages:
set_status("processing")
batch_processed, at_eof = self.handle_messages(
messages, worker_fn)
set_status("idle")
# report the number of handled messages
statsd.increment(JOURNAL_MESSAGE_NUMBER_METRIC,
value=batch_processed)
total_objects_processed += batch_processed
if at_eof:
break
return total_objects_processed
def process(self, type, event, message):
"""Process the received event by dispatching it to the appropriate
handler."""
handler = self.handlers.get(type) or self.handlers.get("*")
if handler:
handler(event, message)
statsd.increment(
"swh_scheduler_listener_handled_event_total", tags={"event_type": type}
)
def __call__(self, retry_state):
if not retry_state.outcome.failed:
statsd.increment(
CONTENT_RETRY_METRIC,
tags={
"operation": retry_state.fn.__name__,
"attempt": str(retry_state.attempt_number),
},
)
return False
def process_replay_objects(all_objects: Dict[str, List[BaseModel]], *,
storage: StorageInterface) -> None:
for (object_type, objects) in all_objects.items():
logger.debug("Inserting %s %s objects", len(objects), object_type)
with statsd.timed(GRAPH_DURATION_METRIC,
tags={"object_type": object_type}):
_insert_objects(object_type, objects, storage)
statsd.increment(GRAPH_OPERATIONS_METRIC,
len(objects),
tags={"object_type": object_type})
if notify:
notify("WATCHDOG=1")
def send_metric(metric, count, method_name):
"""Send statsd metric with count for method `method_name`
If count is 0, the metric is discarded. If the metric is not
parseable, the metric is discarded with a log message.
Args:
metric (str): Metric's name (e.g content:add, content:add:bytes)
count (int): Associated value for the metric
method_name (str): Method's name
Returns:
Bool to explicit if metric has been set or not
"""
if count == 0:
return False
metric_type = metric.split(":")
_length = len(metric_type)
if _length == 2:
object_type, operation = metric_type
metric_name = OPERATIONS_METRIC
elif _length == 3:
object_type, operation, unit = metric_type
metric_name = OPERATIONS_UNIT_METRIC.format(unit=unit)
else:
logging.warning("Skipping unknown metric {%s: %s}" % (metric, count))
return False
statsd.increment(
metric_name,
count,
tags={
"endpoint": method_name,
"object_type": object_type,
"operation": operation,
},
)
return True
def process_event(event, scheduler_backend):
uuid = event.get("uuid")
if not uuid:
return
event_type = event["type"]
statsd.increment("swh_scheduler_listener_handled_event_total",
tags={"event_type": event_type})
if event_type == "task-started":
scheduler_backend.start_task_run(
uuid,
timestamp=utcnow(),
metadata={"worker": event.get("hostname")},
)
elif event_type == "task-result":
result = event["result"]
status = None
if isinstance(result, dict) and "status" in result:
status = result["status"]
if status == "success":
status = "eventful" if result.get("eventful") else "uneventful"
if status is None:
status = "eventful" if result else "uneventful"
scheduler_backend.end_task_run(uuid,
timestamp=utcnow(),
status=status,
result=result)
elif event_type == "task-failed":
scheduler_backend.end_task_run(uuid,
timestamp=utcnow(),
status="failed")
def _copy_object(obj):
nonlocal nb_skipped
nonlocal nb_failures
obj_id = obj[ID_HASH_ALGO]
if obj["status"] != "visible":
nb_skipped += 1
logger.debug("skipped %s (status=%s)", hash_to_hex(obj_id),
obj["status"])
statsd.increment(
CONTENT_OPERATIONS_METRIC,
tags={
"decision": "skipped",
"status": obj["status"]
},
)
elif exclude_fn and exclude_fn(obj):
nb_skipped += 1
logger.debug("skipped %s (manually excluded)", hash_to_hex(obj_id))
statsd.increment(CONTENT_OPERATIONS_METRIC,
tags={"decision": "excluded"})
elif check_dst and obj_in_objstorage(obj_id, dst):
nb_skipped += 1
logger.debug("skipped %s (in dst)", hash_to_hex(obj_id))
statsd.increment(CONTENT_OPERATIONS_METRIC,
tags={"decision": "in_dst"})
else:
try:
copied = copy_object(obj_id, src, dst)
except ObjNotFoundError:
nb_skipped += 1
statsd.increment(CONTENT_OPERATIONS_METRIC,
tags={"decision": "not_in_src"})
else:
if copied is None:
nb_failures += 1
statsd.increment(CONTENT_OPERATIONS_METRIC,
tags={"decision": "failed"})
else:
vol.append(copied)
statsd.increment(CONTENT_OPERATIONS_METRIC,
tags={"decision": "copied"})
def test_increment_doesnt_send_none(statsd):
statsd.increment("metric", None)
assert statsd.socket.recv() is None
def run_ready_tasks(backend: SchedulerInterface, app) -> List[Dict]:
"""Schedule tasks ready to be scheduled.
This lookups any tasks per task type and mass schedules those accordingly (send
messages to rabbitmq and mark as scheduled equivalent tasks in the scheduler
backend).
If tasks (per task type) with priority exist, they will get redirected to dedicated
high priority queue (standard queue name prefixed with `save_code_now:`).
Args:
backend: scheduler backend to interact with (read/update tasks)
app (App): Celery application to send tasks to
Returns:
A list of dictionaries::
{
'task': the scheduler's task id,
'backend_id': Celery's task id,
'scheduler': utcnow()
}
The result can be used to block-wait for the tasks' results::
backend_tasks = run_ready_tasks(self.scheduler, app)
for task in backend_tasks:
AsyncResult(id=task['backend_id']).get()
"""
all_backend_tasks: List[Dict] = []
while True:
task_types = {}
pending_tasks = []
for task_type in backend.get_task_types():
task_type_name = task_type["type"]
task_types[task_type_name] = task_type
max_queue_length = task_type["max_queue_length"]
if max_queue_length is None:
max_queue_length = 0
backend_name = task_type["backend_name"]
if max_queue_length:
try:
queue_length = app.get_queue_length(backend_name)
except ValueError:
queue_length = None
if queue_length is None:
# Running without RabbitMQ (probably a test env).
num_tasks = MAX_NUM_TASKS
else:
num_tasks = min(max_queue_length - queue_length,
MAX_NUM_TASKS)
else:
num_tasks = MAX_NUM_TASKS
# only pull tasks if the buffer is at least 1/5th empty (= 80%
# full), to help postgresql use properly indexed queries.
if num_tasks > min(MAX_NUM_TASKS, max_queue_length) // 5:
# Only grab num_tasks tasks with no priority
grabbed_tasks = backend.grab_ready_tasks(task_type_name,
num_tasks=num_tasks)
if grabbed_tasks:
pending_tasks.extend(grabbed_tasks)
logger.info("Grabbed %s tasks %s", len(grabbed_tasks),
task_type_name)
statsd.increment(
"swh_scheduler_runner_scheduled_task_total",
len(grabbed_tasks),
tags={"task_type": task_type_name},
)
# grab max_queue_length (or 10) potential tasks with any priority for the
# same type (limit the result to avoid too long running queries)
grabbed_priority_tasks = backend.grab_ready_priority_tasks(
task_type_name, num_tasks=max_queue_length or 10)
if grabbed_priority_tasks:
pending_tasks.extend(grabbed_priority_tasks)
logger.info(
"Grabbed %s tasks %s (priority)",
len(grabbed_priority_tasks),
task_type_name,
)
statsd.increment(
"swh_scheduler_runner_scheduled_task_total",
len(grabbed_priority_tasks),
tags={"task_type": task_type_name},
)
if not pending_tasks:
return all_backend_tasks
backend_tasks = []
celery_tasks: List[Tuple[bool, str, str, List, Dict]] = []
for task in pending_tasks:
args = task["arguments"]["args"]
kwargs = task["arguments"]["kwargs"]
backend_name = task_types[task["type"]]["backend_name"]
backend_id = uuid()
celery_tasks.append((
task.get("priority") is not None,
backend_name,
backend_id,
args,
kwargs,
))
data = {
"task": task["id"],
"backend_id": backend_id,
"scheduled": utcnow(),
}
backend_tasks.append(data)
logger.debug("Sent %s celery tasks", len(backend_tasks))
backend.mass_schedule_task_runs(backend_tasks)
for with_priority, backend_name, backend_id, args, kwargs in celery_tasks:
kw = dict(
task_id=backend_id,
args=args,
kwargs=kwargs,
)
if with_priority:
kw["queue"] = f"save_code_now:{backend_name}"
app.send_task(backend_name, **kw)
all_backend_tasks.extend(backend_tasks)
def post_get(self, ret, kw):
"""Called after the 'get' method."""
statsd.increment("swh_objstorage_out_bytes_total",
len(ret),
tags={"endpoint": "get_bytes"})
