from __future__ import print_function, division, absolute_import
from collections import defaultdict
import logging
import uuid
from tornado import gen
import tornado.queues
try:
from cytoolz import assoc
except ImportError:
from toolz import assoc
from .client import Future, _get_global_client, Client
from .utils import tokey, sync
from .worker import get_client
logger = logging.getLogger(__name__)
class QueueExtension(object):
""" An extension for the scheduler to manage queues
This adds the following routes to the scheduler
* queue_create
* queue_release
* queue_put
* queue_get
* queue_size
"""
def __init__(self, scheduler):
self.scheduler = scheduler
self.queues = dict()
self.client_refcount = dict()
self.future_refcount = defaultdict(lambda: 0)
self.scheduler.handlers.update({'queue_create': self.create,
'queue_release': self.release,
'queue_put': self.put,
'queue_get': self.get,
'queue_qsize': self.qsize})
self.scheduler.client_handlers['queue-future-release'] = self.future_release
self.scheduler.extensions['queues'] = self
def create(self, stream=None, name=None, client=None, maxsize=0):
if name not in self.queues:
self.queues[name] = tornado.queues.Queue(maxsize=maxsize)
self.client_refcount[name] = 1
else:
self.client_refcount[name] += 1
def release(self, stream=None, name=None, client=None):
self.client_refcount[name] -= 1
if self.client_refcount[name] == 0:
del self.client_refcount[name]
futures = self.queues[name].queue
del self.queues[name]
self.scheduler.client_releases_keys(keys=[f.key for f in futures],
client='queue-%s' % name)
@gen.coroutine
def put(self, stream=None, name=None, key=None, data=None, client=None, timeout=None):
if key is not None:
record = {'type': 'Future', 'value': key}
self.future_refcount[name, key] += 1
self.scheduler.client_desires_keys(keys=[key], client='queue-%s' % name)
else:
record = {'type': 'msgpack', 'value': data}
yield self.queues[name].put(record, timeout=timeout)
def future_release(self, name=None, key=None, client=None):
self.future_refcount[name, key] -= 1
if self.future_refcount[name, key] == 0:
self.scheduler.client_releases_keys(keys=[key],
client='queue-%s' % name)
del self.future_refcount[name, key]
@gen.coroutine
def get(self, stream=None, name=None, client=None, timeout=None,
batch=False):
def process(record):
""" Add task status if known """
if record['type'] == 'Future':
try:
state = self.scheduler.task_state[record['value']]
except KeyError:
state = 'lost'
return assoc(record, 'state', state)
else:
return record
if batch:
q = self.queues[name]
out = []
if batch is True:
while not q.empty():
record = yield q.get()
out.append(record)
else:
if timeout is not None:
msg = ("Dask queues don't support simultaneous use of "
"integer batch sizes and timeouts")
raise NotImplementedError(msg)
for i in range(batch):
record = yield q.get()
out.append(record)
out = [process(o) for o in out]
raise gen.Return(out)
else:
record = yield self.queues[name].get(timeout=timeout)
record = process(record)
raise gen.Return(record)
def qsize(self, stream=None, name=None, client=None):
return self.queues[name].qsize()
[docs]class Queue(object):
""" Distributed Queue
This allows multiple clients to share futures or small bits of data between
each other with a multi-producer/multi-consumer queue. All metadata is
sequentialized through the scheduler.
Elements of the Queue must be either Futures or msgpack-encodable data
(ints, strings, lists, dicts). All data is sent through the scheduler so
it is wise not to send large objects. To share large objects scatter the
data and share the future instead.
.. warning::
This object is experimental and has known issues in Python 2
Examples
--------
>>> from dask.distributed import Client, Queue # doctest: +SKIP
>>> client = Client() # doctest: +SKIP
>>> queue = Queue('x') # doctest: +SKIP
>>> future = client.submit(f, x) # doctest: +SKIP
>>> queue.put(future) # doctest: +SKIP
See Also
--------
Variable: shared variable between clients
"""
def __init__(self, name=None, client=None, maxsize=0):
self.client = client or _get_global_client()
self.name = name or 'queue-' + uuid.uuid4().hex
if self.client.asynchronous:
self._started = self.client.scheduler.queue_create(name=self.name,
maxsize=maxsize)
else:
sync(self.client.loop, self.client.scheduler.queue_create,
name=self.name, maxsize=maxsize)
self._started = gen.moment
def __await__(self):
@gen.coroutine
def _():
yield self._started
raise gen.Return(self)
return _().__await__()
@gen.coroutine
def _put(self, value, timeout=None):
if isinstance(value, Future):
yield self.client.scheduler.queue_put(key=tokey(value.key),
timeout=timeout,
name=self.name)
else:
yield self.client.scheduler.queue_put(data=value,
timeout=timeout,
name=self.name)
[docs] def put(self, value, timeout=None):
""" Put data into the queue """
return self.client.sync(self._put, value, timeout=timeout)
[docs] def get(self, timeout=None, batch=False):
""" Get data from the queue
Parameters
----------
timeout: Number (optional)
Time in seconds to wait before timing out
batch: boolean, int (optional)
If True then return all elements currently waiting in the queue.
If an integer than return that many elements from the queue
If False (default) then return one item at a time
"""
return self.client.sync(self._get, timeout=timeout, batch=batch)
[docs] def qsize(self):
""" Current number of elements in the queue """
return self.client.sync(self._qsize)
@gen.coroutine
def _get(self, timeout=None, batch=False):
resp = yield self.client.scheduler.queue_get(timeout=timeout,
name=self.name,
batch=batch)
def process(d):
if d['type'] == 'Future':
value = Future(d['value'], self.client, inform=True,
state=d['state'])
self.client._send_to_scheduler({'op': 'queue-future-release',
'name': self.name,
'key': d['value']})
else:
value = d['value']
return value
if batch is False:
result = process(resp)
else:
result = list(map(process, resp))
raise gen.Return(result)
@gen.coroutine
def _qsize(self):
result = yield self.client.scheduler.queue_qsize(name=self.name)
raise gen.Return(result)
def _release(self):
if self.client.status == 'running': # TODO: can leave zombie futures
self.client._send_to_scheduler({'op': 'queue_release',
'name': self.name})
def __del__(self):
self._release()
def __getstate__(self):
return (self.name, self.client.scheduler.address)
def __setstate__(self, state):
name, address = state
try:
client = get_client(address)
assert client.address == address
except (AttributeError, AssertionError):
client = Client(address, set_as_default=False)
self.__init__(name=name, client=client)