def __init__(self,
device_memory_limit=None,
memory_limit=None,
local_dir="dask-worker-space"):
path = os.path.join(local_dir, "storage")
self.host_func = dict()
self.disk_func = Func(partial(serialize_bytes, on_error="raise"),
deserialize_bytes, File(path))
self.host_buffer = Buffer(self.host_func,
self.disk_func,
memory_limit,
weight=weight)
self.device_func = dict()
self.device_host_func = Func(_serialize_if_device,
_deserialize_if_device, self.host_buffer)
self.device_buffer = Buffer(self.device_func,
self.device_host_func,
device_memory_limit,
weight=weight)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer.fast.d
self.disk = self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer.fast
def __init__(
self,
device_memory_limit=None,
memory_limit=None,
local_directory="dask-worker-space",
):
path = os.path.join(local_directory, "storage")
self.host_func = dict()
self.disk_func = Func(serialize_bytelist, deserialize_bytes,
File(path))
self.host_buffer = Buffer(self.host_func,
self.disk_func,
memory_limit,
weight=weight)
self.device_keys = set()
self.device_func = dict()
self.device_host_func = Func(device_to_host, host_to_device,
self.host_buffer)
self.device_buffer = Buffer(self.device_func,
self.device_host_func,
device_memory_limit,
weight=weight)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer.fast.d
self.disk = self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer.fast
def test_simple():
a = dict()
b = dict()
buff = Buffer(a, b, n=10, weight=lambda k, v: v)
buff["x"] = 1
buff["y"] = 2
assert buff["x"] == 1
assert buff["y"] == 2
assert a == {"x": 1, "y": 2}
assert buff.fast.total_weight == 3
buff["z"] = 8
assert a == {"y": 2, "z": 8}
assert b == {"x": 1}
assert buff["x"] == 1
assert a == {"x": 1, "z": 8}
assert b == {"y": 2}
assert "x" in buff
assert "y" in buff
assert "missing" not in buff
buff["y"] = 1
assert a == {"x": 1, "y": 1, "z": 8}
assert buff.fast.total_weight == 10
assert b == {}
del buff["z"]
assert a == {"x": 1, "y": 1}
assert buff.fast.total_weight == 2
assert b == {}
del buff["y"]
assert a == {"x": 1}
assert buff.fast.total_weight == 1
assert b == {}
assert "y" not in buff
buff["a"] = 5
assert set(buff) == set(buff.keys()) == {"a", "x"}
fast_keys = set(buff.fast)
slow_keys = set(buff.slow)
assert not (fast_keys & slow_keys)
assert fast_keys | slow_keys == set(buff)
# Overweight element stays in slow mapping
buff["b"] = 1000
assert "b" in buff.slow
assert set(buff.fast) == fast_keys
assert set(buff.slow) == {"b"} | slow_keys
assert "b" in buff
assert buff["b"] == 1000
def test_simple():
a = dict()
b = dict()
buff = Buffer(a, b, n=10, weight=lambda k, v: v)
buff['x'] = 1
buff['y'] = 2
assert buff['x'] == 1
assert buff['y'] == 2
assert a == {'x': 1, 'y': 2}
assert buff.fast.total_weight == 3
buff['z'] = 8
assert a == {'y': 2, 'z': 8}
assert b == {'x': 1}
assert buff['x'] == 1
assert a == {'x': 1, 'z': 8}
assert b == {'y': 2}
assert 'x' in buff
assert 'y' in buff
assert 'missing' not in buff
buff['y'] = 1
assert a == {'x': 1, 'y': 1, 'z': 8}
assert buff.fast.total_weight == 10
assert b == {}
del buff['z']
assert a == {'x': 1, 'y': 1}
assert buff.fast.total_weight == 2
assert b == {}
del buff['y']
assert a == {'x': 1}
assert buff.fast.total_weight == 1
assert b == {}
assert 'y' not in buff
buff['a'] = 5
assert set(buff) == set(buff.keys()) == {'a', 'x'}
fast_keys = set(buff.fast)
slow_keys = set(buff.slow)
assert not (fast_keys & slow_keys)
assert fast_keys | slow_keys == set(buff)
# Overweight element stays in slow mapping
buff['b'] = 1000
assert 'b' in buff.slow
assert set(buff.fast) == fast_keys
assert set(buff.slow) == {'b'} | slow_keys
assert 'b' in buff
assert buff['b'] == 1000
def __init__(
self,
device_memory_limit=None,
memory_limit=None,
local_directory=None,
log_spilling=False,
):
self.disk_func_path = os.path.join(
local_directory or dask.config.get("temporary-directory") or os.getcwd(),
"dask-worker-space",
"storage",
)
os.makedirs(self.disk_func_path, exist_ok=True)
self.host_func = dict()
self.disk_func = Func(
functools.partial(serialize_bytelist, on_error="raise"),
deserialize_bytes,
File(self.disk_func_path),
)
host_buffer_kwargs = {}
device_buffer_kwargs = {}
buffer_class = Buffer
if log_spilling is True:
buffer_class = LoggedBuffer
host_buffer_kwargs = {"fast_name": "Host", "slow_name": "Disk"}
device_buffer_kwargs = {"fast_name": "Device", "slow_name": "Host"}
if memory_limit == 0:
self.host_buffer = self.host_func
else:
self.host_buffer = buffer_class(
self.host_func,
self.disk_func,
memory_limit,
weight=lambda k, v: safe_sizeof(v),
**host_buffer_kwargs,
)
self.device_keys = set()
self.device_func = dict()
self.device_host_func = Func(device_to_host, host_to_device, self.host_buffer)
self.device_buffer = Buffer(
self.device_func,
self.device_host_func,
device_memory_limit,
weight=lambda k, v: safe_sizeof(v),
**device_buffer_kwargs,
)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer if memory_limit == 0 else self.host_buffer.fast.d
self.disk = None if memory_limit == 0 else self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer if memory_limit == 0 else self.host_buffer.fast
def test_simple():
a = dict()
b = dict()
buff = Buffer(a, b, n=10, weight=lambda k, v: v)
buff['x'] = 1
buff['y'] = 2
assert buff['x'] == 1
assert buff['y'] == 2
assert a == {'x': 1, 'y': 2}
assert buff.fast.total_weight == 3
buff['z'] = 8
assert a == {'y': 2, 'z': 8}
assert b == {'x': 1}
assert buff['x'] == 1
assert a == {'x': 1, 'z': 8}
assert b == {'y': 2}
assert 'x' in buff
assert 'y' in buff
assert 'missing' not in buff
buff['y'] = 1
assert a == {'x': 1, 'y': 1, 'z': 8}
assert buff.fast.total_weight == 10
assert b == {}
del buff['z']
assert a == {'x': 1, 'y': 1}
assert buff.fast.total_weight == 2
assert b == {}
del buff['y']
assert a == {'x': 1}
assert buff.fast.total_weight == 1
assert b == {}
assert 'y' not in buff
buff['a'] = 5
assert set(buff) == set(buff.keys()) == {'a', 'x'}
fast_keys = set(buff.fast)
slow_keys = set(buff.slow)
assert not (fast_keys & slow_keys)
assert fast_keys | slow_keys == set(buff)
# Overweight element stays in slow mapping
buff['b'] = 1000
assert 'b' in buff.slow
assert set(buff.fast) == fast_keys
assert set(buff.slow) == {'b'} | slow_keys
assert 'b' in buff
assert buff['b'] == 1000
def __init__(
self,
device_memory_limit=None,
memory_limit=None,
local_directory=None,
jit_unspill=False,
):
if local_directory is None:
local_directory = dask.config.get(
"temporary-directory") or os.getcwd()
if not os.path.exists(local_directory):
os.makedirs(local_directory, exist_ok=True)
local_directory = os.path.join(local_directory, "dask-worker-space")
self.disk_func_path = os.path.join(local_directory, "storage")
self.host_func = dict()
self.disk_func = Func(
functools.partial(serialize_bytelist, on_error="raise"),
deserialize_bytes,
File(self.disk_func_path),
)
if memory_limit == 0:
self.host_buffer = self.host_func
else:
self.host_buffer = Buffer(self.host_func,
self.disk_func,
memory_limit,
weight=weight)
self.device_keys = set()
self.device_func = dict()
if jit_unspill:
self.device_host_func = Func(pxy_obj_device_to_host,
pxy_obj_host_to_device,
self.host_buffer)
else:
self.device_host_func = Func(device_to_host, host_to_device,
self.host_buffer)
self.device_buffer = Buffer(self.device_func,
self.device_host_func,
device_memory_limit,
weight=weight)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer if memory_limit == 0 else self.host_buffer.fast.d
self.disk = None if memory_limit == 0 else self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer if memory_limit == 0 else self.host_buffer.fast
def test_mapping():
"""
Test mapping interface for Buffer().
"""
a = {}
b = {}
buff = Buffer(a, b, n=2)
utils_test.check_mapping(buff)
utils_test.check_closing(buff)
def test_simple():
a = dict()
b = dict()
buff = Buffer(a, b, n=10, weight=lambda k, v: v)
buff['x'] = 1
buff['y'] = 2
assert buff['x'] == 1
assert buff['y'] == 2
assert a == {'x': 1, 'y': 2}
assert buff.fast.total_weight == 3
buff['z'] = 8
assert a == {'y': 2, 'z': 8}
assert b == {'x': 1}
assert buff['x'] == 1
assert a == {'x': 1, 'z': 8}
assert b == {'y': 2}
assert 'x' in buff
assert 'y' in buff
assert 'missing' not in buff
del buff['z']
assert a == {'x': 1}
assert b == {'y': 2}
del buff['y']
assert a == {'x': 1}
assert b == {}
assert 'y' not in buff
buff['a'] = 5
assert set(buff) == set(buff.keys()) == {'a', 'x'}
fast_keys = set(buff.fast)
buff['b'] = 1000
assert 'b' in buff.slow
assert set(buff.fast) == fast_keys
def __init__(
self,
device_memory_limit=None,
memory_limit=None,
local_directory=None,
):
if local_directory is None:
local_directory = dask.config.get(
"temporary-directory") or os.getcwd()
os.makedirs(local_directory, exist_ok=True)
local_directory = os.path.join(local_directory,
"dask-worker-space")
self.disk_func_path = os.path.join(local_directory, "storage")
self.host_func = dict()
self.disk_func = Func(serialize_bytelist, deserialize_bytes,
File(self.disk_func_path))
self.host_buffer = Buffer(self.host_func,
self.disk_func,
memory_limit,
weight=weight)
self.device_keys = set()
self.device_func = dict()
self.device_host_func = Func(device_to_host, host_to_device,
self.host_buffer)
self.device_buffer = Buffer(self.device_func,
self.device_host_func,
device_memory_limit,
weight=weight)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer.fast.d
self.disk = self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer.fast
def setup(self, worker):
self.cache = Buffer(
fast={},
slow=Func(
dump=blosc.pack_array,
load=blosc.unpack_array,
d=Buffer(
fast={},
slow=LRU(
n=self._maxdisk,
d=File(os.path.join(worker.local_directory, 'cache')),
weight=lambda k, v: len(v),
),
n=self._maxcompressed,
weight=lambda k, v: len(v),
),
),
n=self._maxmem,
weight=lambda k, v: v.nbytes,
)
self.lock = Lock()
self.hits = 0
self.misses = 0
def test_callbacks():
f2s = []
def f2s_cb(k, v):
f2s.append(k)
s2f = []
def s2f_cb(k, v):
s2f.append(k)
a = dict()
b = dict()
buff = Buffer(
a,
b,
n=10,
weight=lambda k, v: v,
fast_to_slow_callbacks=f2s_cb,
slow_to_fast_callbacks=s2f_cb,
)
buff["x"] = 1
buff["y"] = 2
assert buff["x"] == 1
assert buff["y"] == 2
assert not f2s
assert not s2f
buff["z"] = 8
assert f2s == ["x"]
assert s2f == []
buff["z"]
assert f2s == ["x"]
assert s2f == []
buff["x"]
assert f2s == ["x", "y"]
assert s2f == ["x"]
def test_setitem_avoid_fast_slow_duplicate():
a = dict()
b = dict()
buff = Buffer(a, b, n=10, weight=lambda k, v: v)
for first, second in [(1, 12), (12, 1)]:
buff["a"] = first
assert buff["a"] == first
buff["a"] = second
assert buff["a"] == second
fast_keys = set(buff.fast)
slow_keys = set(buff.slow)
assert not (fast_keys & slow_keys)
assert fast_keys | slow_keys == set(buff)
del buff["a"]
assert "a" not in buff
assert "a" not in a
assert "a" not in b
class Worker(Server):
""" Worker Node
Workers perform two functions:
1. **Serve data** from a local dictionary
2. **Perform computation** on that data and on data from peers
Additionally workers keep a scheduler informed of their data and use that
scheduler to gather data from other workers when necessary to perform a
computation.
You can start a worker with the ``dask-worker`` command line application::
$ dask-worker scheduler-ip:port
**State**
* **data:** ``{key: object}``:
Dictionary mapping keys to actual values
* **active:** ``{key}``:
Set of keys currently under computation
* **ncores:** ``int``:
Number of cores used by this worker process
* **executor:** ``concurrent.futures.ThreadPoolExecutor``:
Executor used to perform computation
* **local_dir:** ``path``:
Path on local machine to store temporary files
* **scheduler:** ``rpc``:
Location of scheduler. See ``.ip/.port`` attributes.
* **name:** ``string``:
Alias
* **services:** ``{str: Server}``:
Auxiliary web servers running on this worker
* **service_ports:** ``{str: port}``:
Examples
--------
Create schedulers and workers in Python:
>>> from distributed import Scheduler, Worker
>>> c = Scheduler('192.168.0.100', 8786) # doctest: +SKIP
>>> w = Worker(c.ip, c.port) # doctest: +SKIP
>>> yield w._start(port=8786) # doctest: +SKIP
Or use the command line::
$ dask-scheduler
Start scheduler at 127.0.0.1:8786
$ dask-worker 127.0.0.1:8786
Start worker at: 127.0.0.1:8786
Registered with scheduler at: 127.0.0.1:8787
See Also
--------
distributed.scheduler.Scheduler:
"""
def __init__(self, scheduler_ip, scheduler_port, ip=None, ncores=None,
loop=None, local_dir=None, services=None, service_ports=None,
name=None, heartbeat_interval=1000, memory_limit=None, **kwargs):
self.ip = ip or get_ip()
self._port = 0
self.ncores = ncores or _ncores
self.local_dir = local_dir or tempfile.mkdtemp(prefix='worker-')
if not os.path.exists(self.local_dir):
os.mkdir(self.local_dir)
if memory_limit:
try:
from zict import Buffer, File, Func
except ImportError:
raise ImportError("Please `pip install zict` for spill-to-disk workers")
path = os.path.join(self.local_dir, 'storage')
storage = Func(dumps_to_disk, loads_from_disk, File(path))
self.data = Buffer({}, storage, int(float(memory_limit)), weight)
else:
self.data = dict()
self.loop = loop or IOLoop.current()
self.status = None
self.executor = ThreadPoolExecutor(self.ncores)
self.scheduler = rpc(ip=scheduler_ip, port=scheduler_port)
self.active = set()
self.name = name
self.heartbeat_interval = heartbeat_interval
self.heartbeat_active = False
self.execution_state = {'scheduler': self.scheduler.address,
'ioloop': self.loop,
'worker': self}
self._last_disk_io = None
self._last_net_io = None
self._ipython_kernel = None
if self.local_dir not in sys.path:
sys.path.insert(0, self.local_dir)
self.services = {}
self.service_ports = service_ports or {}
for k, v in (services or {}).items():
if isinstance(k, tuple):
k, port = k
else:
port = 0
self.services[k] = v(self, io_loop=self.loop)
self.services[k].listen(port)
self.service_ports[k] = self.services[k].port
handlers = {'compute': self.compute,
'gather': self.gather,
'compute-stream': self.compute_stream,
'run': self.run,
'get_data': self.get_data,
'update_data': self.update_data,
'delete_data': self.delete_data,
'terminate': self.terminate,
'ping': pingpong,
'health': self.host_health,
'upload_file': self.upload_file,
'start_ipython': self.start_ipython,
'keys': self.keys,
}
super(Worker, self).__init__(handlers, io_loop=self.loop, **kwargs)
self.heartbeat_callback = PeriodicCallback(self.heartbeat,
self.heartbeat_interval,
io_loop=self.loop)
self.loop.add_callback(self.heartbeat_callback.start)
@gen.coroutine
def heartbeat(self):
if not self.heartbeat_active:
self.heartbeat_active = True
logger.debug("Heartbeat: %s" % self.address)
try:
yield self.scheduler.register(address=self.address, name=self.name,
ncores=self.ncores,
now=time(),
info=self.process_health(),
host_info=self.host_health(),
services=self.service_ports,
**self.process_health())
finally:
self.heartbeat_active = False
else:
logger.debug("Heartbeat skipped: channel busy")
@gen.coroutine
def _start(self, port=0):
self.listen(port)
self.name = self.name or self.address
for k, v in self.services.items():
v.listen(0)
self.service_ports[k] = v.port
logger.info(' Start worker at: %20s:%d', self.ip, self.port)
for k, v in self.service_ports.items():
logger.info(' %16s at: %20s:%d' % (k, self.ip, v))
logger.info('Waiting to connect to: %20s:%d',
self.scheduler.ip, self.scheduler.port)
while True:
try:
resp = yield self.scheduler.register(
ncores=self.ncores, address=(self.ip, self.port),
keys=list(self.data),
name=self.name, nbytes=valmap(sizeof, self.data),
now=time(),
host_info=self.host_health(),
services=self.service_ports,
**self.process_health())
break
except (OSError, StreamClosedError):
logger.debug("Unable to register with scheduler. Waiting")
yield gen.sleep(0.5)
if resp != 'OK':
raise ValueError(resp)
logger.info(' Registered to: %20s:%d',
self.scheduler.ip, self.scheduler.port)
self.status = 'running'
def start(self, port=0):
self.loop.add_callback(self._start, port)
def identity(self, stream):
return {'type': type(self).__name__, 'id': self.id,
'scheduler': (self.scheduler.ip, self.scheduler.port)}
@gen.coroutine
def _close(self, report=True, timeout=10):
self.heartbeat_callback.stop()
with ignoring(RPCClosed, StreamClosedError):
if report:
yield gen.with_timeout(timedelta(seconds=timeout),
self.scheduler.unregister(address=(self.ip, self.port)),
io_loop=self.loop)
self.scheduler.close_rpc()
self.stop()
self.executor.shutdown()
if os.path.exists(self.local_dir):
shutil.rmtree(self.local_dir)
for k, v in self.services.items():
v.stop()
self.status = 'closed'
self.stop()
@gen.coroutine
def terminate(self, stream, report=True):
yield self._close(report=report)
raise Return('OK')
@property
def address(self):
return '%s:%d' % (self.ip, self.port)
@property
def address_tuple(self):
return (self.ip, self.port)
@gen.coroutine
def gather(self, stream=None, who_has=None):
who_has = {k: [coerce_to_address(addr) for addr in v]
for k, v in who_has.items()
if k not in self.data}
try:
result = yield gather_from_workers(who_has)
except KeyError as e:
logger.warn("Could not find data", e)
raise Return({'status': 'missing-data',
'keys': e.args})
else:
self.data.update(result)
raise Return({'status': 'OK'})
def deserialize(self, function=None, args=None, kwargs=None, task=None):
""" Deserialize task inputs and regularize to func, args, kwargs """
if task is not None:
task = loads(task)
if function is not None:
function = loads(function)
if args:
args = loads(args)
if kwargs:
kwargs = loads(kwargs)
if task is not None:
assert not function and not args and not kwargs
function = execute_task
args = (task,)
return function, args or (), kwargs or {}
@gen.coroutine
def gather_many(self, msgs):
""" Gather the data for many compute messages at once
Returns
-------
good: the input messages for which we have data
bad: a dict of task keys for which we could not find data
data: The scope in which to run tasks
len(remote): the number of new keys we've gathered
"""
diagnostics = {}
who_has = merge(msg['who_has'] for msg in msgs if 'who_has' in msg)
start = time()
local = {k: self.data[k] for k in who_has if k in self.data}
stop = time()
if stop - start > 0.005:
diagnostics['disk_load_start'] = start
diagnostics['disk_load_stop'] = stop
who_has = {k: v for k, v in who_has.items() if k not in local}
start = time()
remote, bad_data = yield gather_from_workers(who_has,
permissive=True)
if remote:
self.data.update(remote)
yield self.scheduler.add_keys(address=self.address, keys=list(remote))
stop = time()
if remote:
diagnostics['transfer_start'] = start
diagnostics['transfer_stop'] = stop
data = merge(local, remote)
if bad_data:
missing = {msg['key']: {k for k in msg['who_has'] if k in bad_data}
for msg in msgs if 'who_has' in msg}
bad = {k: v for k, v in missing.items() if v}
good = [msg for msg in msgs if not missing.get(msg['key'])]
else:
good, bad = msgs, {}
raise Return([good, bad, data, len(remote), diagnostics])
@gen.coroutine
def _ready_task(self, function=None, key=None, args=(), kwargs={},
task=None, who_has=None):
who_has = who_has or {}
diagnostics = {}
start = time()
data = {k: self.data[k] for k in who_has if k in self.data}
stop = time()
if stop - start > 0.005:
diagnostics['disk_load_start'] = start
diagnostics['disk_load_stop'] = stop
who_has = {k: set(map(coerce_to_address, v))
for k, v in who_has.items()
if k not in self.data}
if who_has:
try:
logger.info("gather %d keys from peers", len(who_has))
diagnostics['transfer_start'] = time()
other = yield gather_from_workers(who_has)
diagnostics['transfer_stop'] = time()
self.data.update(other)
yield self.scheduler.add_keys(address=self.address,
keys=list(other))
data.update(other)
except KeyError as e:
logger.warn("Could not find data for %s", key)
raise Return({'status': 'missing-data',
'keys': e.args,
'key': key})
try:
start = default_timer()
function, args, kwargs = self.deserialize(function, args, kwargs,
task)
diagnostics['deserialization'] = default_timer() - start
except Exception as e:
logger.warn("Could not deserialize task", exc_info=True)
emsg = error_message(e)
emsg['key'] = key
raise Return(emsg)
# Fill args with data
args2 = pack_data(args, data)
kwargs2 = pack_data(kwargs, data)
raise Return({'status': 'OK',
'function': function,
'args': args2,
'kwargs': kwargs2,
'diagnostics': diagnostics,
'key': key})
@gen.coroutine
def executor_submit(self, key, function, *args, **kwargs):
""" Safely run function in thread pool executor
We've run into issues running concurrent.future futures within
tornado. Apparently it's advantageous to use timeouts and periodic
callbacks to ensure things run smoothly. This can get tricky, so we
pull it off into an separate method.
"""
job_counter[0] += 1
# logger.info("%s:%d Starts job %d, %s", self.ip, self.port, i, key)
future = self.executor.submit(function, *args, **kwargs)
pc = PeriodicCallback(lambda: logger.debug("future state: %s - %s",
key, future._state), 1000, io_loop=self.loop); pc.start()
try:
yield future
finally:
pc.stop()
pass
result = future.result()
# logger.info("Finish job %d, %s", i, key)
raise gen.Return(result)
@gen.coroutine
def compute_stream(self, stream):
with log_errors():
logger.debug("Open compute stream")
bstream = BatchedSend(interval=2, loop=self.loop)
bstream.start(stream)
closed = False
last = gen.sleep(0)
while not closed:
try:
msgs = yield read(stream)
except StreamClosedError:
break
if not isinstance(msgs, list):
msgs = [msgs]
batch = []
for msg in msgs:
op = msg.pop('op', None)
if op == 'close':
closed = True
break
elif op == 'compute-task':
batch.append(msg)
logger.debug("%s asked to compute %s", self.address,
msg['key'])
else:
logger.warning("Unknown operation %s, %s", op, msg)
# self.loop.add_callback(self.compute_many, bstream, msgs)
last = self.compute_many(bstream, msgs)
try:
yield last # TODO: there might be more than one lingering
except (RPCClosed, RuntimeError):
pass
yield bstream.close()
logger.info("Close compute stream")
@gen.coroutine
def compute_many(self, bstream, msgs, report=False):
good, bad, data, num_transferred, diagnostics = yield self.gather_many(msgs)
for msg in msgs:
msg.pop('who_has', None)
if bad:
logger.warn("Could not find data for %s", sorted(bad))
for k, v in bad.items():
bstream.send({'status': 'missing-data',
'key': k,
'keys': list(v)})
if good:
futures = [self.compute_one(data, report=report, **msg)
for msg in good]
wait_iterator = gen.WaitIterator(*futures)
result = yield wait_iterator.next()
if diagnostics:
result.update(diagnostics)
bstream.send(result)
while not wait_iterator.done():
msg = yield wait_iterator.next()
bstream.send(msg)
@gen.coroutine
def compute_one(self, data, key=None, function=None, args=None, kwargs=None,
report=False, task=None):
logger.debug("Compute one on %s", key)
self.active.add(key)
diagnostics = dict()
try:
start = default_timer()
function, args, kwargs = self.deserialize(function, args, kwargs,
task)
diagnostics['deserialization'] = default_timer() - start
except Exception as e:
logger.warn("Could not deserialize task", exc_info=True)
emsg = error_message(e)
emsg['key'] = key
raise Return(emsg)
# Fill args with data
args2 = pack_data(args, data)
kwargs2 = pack_data(kwargs, data)
# Log and compute in separate thread
result = yield self.executor_submit(key, apply_function, function,
args2, kwargs2,
self.execution_state, key)
result['key'] = key
result.update(diagnostics)
if result['status'] == 'OK':
self.data[key] = result.pop('result')
if report:
response = yield self.scheduler.add_keys(keys=[key],
address=(self.ip, self.port))
if not response == 'OK':
logger.warn('Could not report results to scheduler: %s',
str(response))
else:
logger.warn(" Compute Failed\n"
"Function: %s\n"
"args: %s\n"
"kwargs: %s\n",
str(funcname(function))[:1000],
convert_args_to_str(args, max_len=1000),
convert_kwargs_to_str(kwargs, max_len=1000), exc_info=True)
logger.debug("Send compute response to scheduler: %s, %s", key,
result)
try:
self.active.remove(key)
except KeyError:
pass
raise Return(result)
@gen.coroutine
def compute(self, stream=None, function=None, key=None, args=(), kwargs={},
task=None, who_has=None, report=True):
""" Execute function """
self.active.add(key)
# Ready function for computation
msg = yield self._ready_task(function=function, key=key, args=args,
kwargs=kwargs, task=task, who_has=who_has)
if msg['status'] != 'OK':
try:
self.active.remove(key)
except KeyError:
pass
raise Return(msg)
else:
function = msg['function']
args = msg['args']
kwargs = msg['kwargs']
# Log and compute in separate thread
result = yield self.executor_submit(key, apply_function, function,
args, kwargs, self.execution_state,
key)
result['key'] = key
result.update(msg['diagnostics'])
if result['status'] == 'OK':
self.data[key] = result.pop('result')
if report:
response = yield self.scheduler.add_keys(address=(self.ip, self.port),
keys=[key])
if not response == 'OK':
logger.warn('Could not report results to scheduler: %s',
str(response))
else:
logger.warn(" Compute Failed\n"
"Function: %s\n"
"args: %s\n"
"kwargs: %s\n",
str(funcname(function))[:1000],
convert_args_to_str(args, max_len=1000),
convert_kwargs_to_str(kwargs, max_len=1000), exc_info=True)
logger.debug("Send compute response to scheduler: %s, %s", key,
get_msg_safe_str(msg))
try:
self.active.remove(key)
except KeyError:
pass
raise Return(result)
def run(self, stream, function=None, args=(), kwargs={}):
return run(self, stream, function=function, args=args, kwargs=kwargs)
@gen.coroutine
def update_data(self, stream=None, data=None, report=True, deserialize=True):
if deserialize:
data = valmap(loads, data)
self.data.update(data)
if report:
response = yield self.scheduler.add_keys(
address=(self.ip, self.port),
keys=list(data))
assert response == 'OK'
info = {'nbytes': {k: sizeof(v) for k, v in data.items()},
'status': 'OK'}
raise Return(info)
@gen.coroutine
def delete_data(self, stream, keys=None, report=True):
if keys:
for key in keys:
if key in self.data:
del self.data[key]
logger.info("Deleted %d keys", len(keys))
if report:
logger.debug("Reporting loss of keys to scheduler")
yield self.scheduler.remove_keys(address=self.address,
keys=list(keys))
raise Return('OK')
def get_data(self, stream, keys=None):
return {k: dumps(self.data[k]) for k in keys if k in self.data}
def start_ipython(self, stream):
"""Start an IPython kernel
Returns Jupyter connection info dictionary.
"""
from ._ipython_utils import start_ipython
if self._ipython_kernel is None:
self._ipython_kernel = start_ipython(
ip=self.ip,
ns={'worker': self},
log=logger,
)
return self._ipython_kernel.get_connection_info()
def upload_file(self, stream, filename=None, data=None, load=True):
out_filename = os.path.join(self.local_dir, filename)
if isinstance(data, unicode):
data = data.encode()
with open(out_filename, 'wb') as f:
f.write(data)
f.flush()
if load:
try:
name, ext = os.path.splitext(filename)
if ext in ('.py', '.pyc'):
logger.info("Reload module %s from .py file", name)
name = name.split('-')[0]
reload(import_module(name))
if ext == '.egg':
sys.path.append(out_filename)
pkgs = pkg_resources.find_distributions(out_filename)
for pkg in pkgs:
logger.info("Load module %s from egg", pkg.project_name)
reload(import_module(pkg.project_name))
if not pkgs:
logger.warning("Found no packages in egg file")
except Exception as e:
logger.exception(e)
return {'status': 'error', 'exception': dumps(e)}
return {'status': 'OK', 'nbytes': len(data)}
def process_health(self, stream=None):
d = {'active': len(self.active),
'stored': len(self.data)}
return d
def host_health(self, stream=None):
""" Information about worker """
d = {'time': time()}
try:
import psutil
mem = psutil.virtual_memory()
d.update({'cpu': psutil.cpu_percent(),
'memory': mem.total,
'memory_percent': mem.percent})
net_io = psutil.net_io_counters()
if self._last_net_io:
d['network-send'] = net_io.bytes_sent - self._last_net_io.bytes_sent
d['network-recv'] = net_io.bytes_recv - self._last_net_io.bytes_recv
else:
d['network-send'] = 0
d['network-recv'] = 0
self._last_net_io = net_io
try:
disk_io = psutil.disk_io_counters()
except RuntimeError:
# This happens when there is no physical disk in worker
pass
else:
if self._last_disk_io:
d['disk-read'] = disk_io.read_bytes - self._last_disk_io.read_bytes
d['disk-write'] = disk_io.write_bytes - self._last_disk_io.write_bytes
else:
d['disk-read'] = 0
d['disk-write'] = 0
self._last_disk_io = disk_io
except ImportError:
pass
return d
def keys(self, stream=None):
return list(self.data)
def __init__(self, scheduler_ip, scheduler_port, ip=None, ncores=None,
loop=None, local_dir=None, services=None, service_ports=None,
name=None, heartbeat_interval=1000, memory_limit=None, **kwargs):
self.ip = ip or get_ip()
self._port = 0
self.ncores = ncores or _ncores
self.local_dir = local_dir or tempfile.mkdtemp(prefix='worker-')
if not os.path.exists(self.local_dir):
os.mkdir(self.local_dir)
if memory_limit:
try:
from zict import Buffer, File, Func
except ImportError:
raise ImportError("Please `pip install zict` for spill-to-disk workers")
path = os.path.join(self.local_dir, 'storage')
storage = Func(dumps_to_disk, loads_from_disk, File(path))
self.data = Buffer({}, storage, int(float(memory_limit)), weight)
else:
self.data = dict()
self.loop = loop or IOLoop.current()
self.status = None
self.executor = ThreadPoolExecutor(self.ncores)
self.scheduler = rpc(ip=scheduler_ip, port=scheduler_port)
self.active = set()
self.name = name
self.heartbeat_interval = heartbeat_interval
self.heartbeat_active = False
self.execution_state = {'scheduler': self.scheduler.address,
'ioloop': self.loop,
'worker': self}
self._last_disk_io = None
self._last_net_io = None
self._ipython_kernel = None
if self.local_dir not in sys.path:
sys.path.insert(0, self.local_dir)
self.services = {}
self.service_ports = service_ports or {}
for k, v in (services or {}).items():
if isinstance(k, tuple):
k, port = k
else:
port = 0
self.services[k] = v(self, io_loop=self.loop)
self.services[k].listen(port)
self.service_ports[k] = self.services[k].port
handlers = {'compute': self.compute,
'gather': self.gather,
'compute-stream': self.compute_stream,
'run': self.run,
'get_data': self.get_data,
'update_data': self.update_data,
'delete_data': self.delete_data,
'terminate': self.terminate,
'ping': pingpong,
'health': self.host_health,
'upload_file': self.upload_file,
'start_ipython': self.start_ipython,
'keys': self.keys,
}
super(Worker, self).__init__(handlers, io_loop=self.loop, **kwargs)
self.heartbeat_callback = PeriodicCallback(self.heartbeat,
self.heartbeat_interval,
io_loop=self.loop)
self.loop.add_callback(self.heartbeat_callback.start)
class DeviceHostFile(ZictBase):
"""Manages serialization/deserialization of objects.
Three LRU cache levels are controlled, for device, host and disk.
Each level takes care of serializing objects once its limit has been
reached and pass it to the subsequent level. Similarly, each cache
may deserialize the object, but storing it back in the appropriate
cache, depending on the type of object being deserialized.
Parameters
----------
device_memory_limit: int
Number of bytes of CUDA device memory for device LRU cache,
spills to host cache once filled.
memory_limit: int
Number of bytes of host memory for host LRU cache, spills to
disk once filled. Setting this to 0 means unlimited host memory,
implies no spilling to disk.
local_directory: path
Path where to store serialized objects on disk
log_spilling: bool
If True, all spilling operations will be logged directly to
distributed.worker with an INFO loglevel. This will eventually be
replaced by a Dask configuration flag.
"""
def __init__(
self,
device_memory_limit=None,
memory_limit=None,
local_directory=None,
log_spilling=False,
):
if local_directory is None:
local_directory = dask.config.get(
"temporary-directory") or os.getcwd()
if local_directory and not os.path.exists(local_directory):
os.makedirs(local_directory, exist_ok=True)
local_directory = os.path.join(local_directory, "dask-worker-space")
self.disk_func_path = os.path.join(local_directory, "storage")
self.host_func = dict()
self.disk_func = Func(
functools.partial(serialize_bytelist, on_error="raise"),
deserialize_bytes,
File(self.disk_func_path),
)
host_buffer_kwargs = {}
device_buffer_kwargs = {}
buffer_class = Buffer
if log_spilling is True:
buffer_class = LoggedBuffer
host_buffer_kwargs = {"fast_name": "Host", "slow_name": "Disk"}
device_buffer_kwargs = {"fast_name": "Device", "slow_name": "Host"}
if memory_limit == 0:
self.host_buffer = self.host_func
else:
self.host_buffer = buffer_class(
self.host_func,
self.disk_func,
memory_limit,
weight=lambda k, v: safe_sizeof(v),
**host_buffer_kwargs,
)
self.device_keys = set()
self.device_func = dict()
self.device_host_func = Func(device_to_host, host_to_device,
self.host_buffer)
self.device_buffer = Buffer(
self.device_func,
self.device_host_func,
device_memory_limit,
weight=lambda k, v: safe_sizeof(v),
**device_buffer_kwargs,
)
self.device = self.device_buffer.fast.d
self.host = self.host_buffer if memory_limit == 0 else self.host_buffer.fast.d
self.disk = None if memory_limit == 0 else self.host_buffer.slow.d
# For Worker compatibility only, where `fast` is host memory buffer
self.fast = self.host_buffer if memory_limit == 0 else self.host_buffer.fast
def __setitem__(self, key, value):
if key in self.device_buffer:
# Make sure we register the removal of an existing key
del self[key]
if is_device_object(value):
self.device_keys.add(key)
self.device_buffer[key] = value
else:
self.host_buffer[key] = value
def __getitem__(self, key):
if key in self.device_keys:
return self.device_buffer[key]
elif key in self.host_buffer:
return self.host_buffer[key]
else:
raise KeyError(key)
def __len__(self):
return len(self.device_buffer)
def __iter__(self):
return iter(self.device_buffer)
def __delitem__(self, key):
self.device_keys.discard(key)
del self.device_buffer[key]
def set_address(self, addr):
if isinstance(self.host_buffer, LoggedBuffer):
self.host_buffer.set_address(addr)
self.device_buffer.set_address(addr)
def get_total_spilling_time(self):
ret = {}
if isinstance(self.device_buffer, LoggedBuffer):
ret = {**ret, **self.device_buffer.get_total_spilling_time()}
if isinstance(self.host_buffer, LoggedBuffer):
ret = {**ret, **self.host_buffer.get_total_spilling_time()}
return ret
def __init__(self, scheduler_ip, scheduler_port, ip=None, ncores=None,
loop=None, local_dir=None, services=None, service_ports=None,
name=None, heartbeat_interval=5000, memory_limit=TOTAL_MEMORY,
**kwargs):
self.ip = ip or get_ip()
self._port = 0
self.ncores = ncores or _ncores
self.local_dir = local_dir or tempfile.mkdtemp(prefix='worker-')
if not os.path.exists(self.local_dir):
os.mkdir(self.local_dir)
self.memory_limit = memory_limit
if memory_limit:
try:
from zict import Buffer, File, Func
except ImportError:
raise ImportError("Please `pip install zict` for spill-to-disk workers")
path = os.path.join(self.local_dir, 'storage')
storage = Func(dumps_to_disk, loads_from_disk, File(path))
self.data = Buffer({}, storage, int(float(memory_limit)), weight)
else:
self.data = dict()
self.loop = loop or IOLoop.current()
self.status = None
self.executor = ThreadPoolExecutor(self.ncores)
self.scheduler = rpc(ip=scheduler_ip, port=scheduler_port)
self.active = set()
self.name = name
self.heartbeat_interval = heartbeat_interval
self.heartbeat_active = False
self.execution_state = {'scheduler': self.scheduler.address,
'ioloop': self.loop,
'worker': self}
self._last_disk_io = None
self._last_net_io = None
self._ipython_kernel = None
if self.local_dir not in sys.path:
sys.path.insert(0, self.local_dir)
self.services = {}
self.service_ports = service_ports or {}
for k, v in (services or {}).items():
if isinstance(k, tuple):
k, port = k
else:
port = 0
self.services[k] = v(self, io_loop=self.loop)
self.services[k].listen(port)
self.service_ports[k] = self.services[k].port
handlers = {'compute': self.compute,
'gather': self.gather,
'compute-stream': self.compute_stream,
'run': self.run,
'get_data': self.get_data,
'update_data': self.update_data,
'delete_data': self.delete_data,
'terminate': self.terminate,
'ping': pingpong,
'health': self.host_health,
'upload_file': self.upload_file,
'start_ipython': self.start_ipython,
'keys': self.keys,
}
super(Worker, self).__init__(handlers, io_loop=self.loop, **kwargs)
self.heartbeat_callback = PeriodicCallback(self.heartbeat,
self.heartbeat_interval,
io_loop=self.loop)
self.loop.add_callback(self.heartbeat_callback.start)
class Worker(Server):
""" Worker Node
Workers perform two functions:
1. **Serve data** from a local dictionary
2. **Perform computation** on that data and on data from peers
Additionally workers keep a scheduler informed of their data and use that
scheduler to gather data from other workers when necessary to perform a
computation.
You can start a worker with the ``dask-worker`` command line application::
$ dask-worker scheduler-ip:port
**State**
* **data:** ``{key: object}``:
Dictionary mapping keys to actual values
* **active:** ``{key}``:
Set of keys currently under computation
* **ncores:** ``int``:
Number of cores used by this worker process
* **executor:** ``concurrent.futures.ThreadPoolExecutor``:
Executor used to perform computation
* **local_dir:** ``path``:
Path on local machine to store temporary files
* **scheduler:** ``rpc``:
Location of scheduler. See ``.ip/.port`` attributes.
* **name:** ``string``:
Alias
* **services:** ``{str: Server}``:
Auxiliary web servers running on this worker
* **service_ports:** ``{str: port}``:
Examples
--------
Create schedulers and workers in Python:
>>> from distributed import Scheduler, Worker
>>> c = Scheduler('192.168.0.100', 8786) # doctest: +SKIP
>>> w = Worker(c.ip, c.port) # doctest: +SKIP
>>> yield w._start(port=8786) # doctest: +SKIP
Or use the command line::
$ dask-scheduler
Start scheduler at 127.0.0.1:8786
$ dask-worker 127.0.0.1:8786
Start worker at: 127.0.0.1:8786
Registered with scheduler at: 127.0.0.1:8787
See Also
--------
distributed.scheduler.Scheduler:
"""
def __init__(self, scheduler_ip, scheduler_port, ip=None, ncores=None,
loop=None, local_dir=None, services=None, service_ports=None,
name=None, heartbeat_interval=5000, memory_limit=TOTAL_MEMORY,
**kwargs):
self.ip = ip or get_ip()
self._port = 0
self.ncores = ncores or _ncores
self.local_dir = local_dir or tempfile.mkdtemp(prefix='worker-')
if not os.path.exists(self.local_dir):
os.mkdir(self.local_dir)
self.memory_limit = memory_limit
if memory_limit:
try:
from zict import Buffer, File, Func
except ImportError:
raise ImportError("Please `pip install zict` for spill-to-disk workers")
path = os.path.join(self.local_dir, 'storage')
storage = Func(dumps_to_disk, loads_from_disk, File(path))
self.data = Buffer({}, storage, int(float(memory_limit)), weight)
else:
self.data = dict()
self.loop = loop or IOLoop.current()
self.status = None
self.executor = ThreadPoolExecutor(self.ncores)
self.scheduler = rpc(ip=scheduler_ip, port=scheduler_port)
self.active = set()
self.name = name
self.heartbeat_interval = heartbeat_interval
self.heartbeat_active = False
self.execution_state = {'scheduler': self.scheduler.address,
'ioloop': self.loop,
'worker': self}
self._last_disk_io = None
self._last_net_io = None
self._ipython_kernel = None
if self.local_dir not in sys.path:
sys.path.insert(0, self.local_dir)
self.services = {}
self.service_ports = service_ports or {}
for k, v in (services or {}).items():
if isinstance(k, tuple):
k, port = k
else:
port = 0
self.services[k] = v(self, io_loop=self.loop)
self.services[k].listen(port)
self.service_ports[k] = self.services[k].port
handlers = {'compute': self.compute,
'gather': self.gather,
'compute-stream': self.compute_stream,
'run': self.run,
'get_data': self.get_data,
'update_data': self.update_data,
'delete_data': self.delete_data,
'terminate': self.terminate,
'ping': pingpong,
'health': self.host_health,
'upload_file': self.upload_file,
'start_ipython': self.start_ipython,
'keys': self.keys,
}
super(Worker, self).__init__(handlers, io_loop=self.loop, **kwargs)
self.heartbeat_callback = PeriodicCallback(self.heartbeat,
self.heartbeat_interval,
io_loop=self.loop)
self.loop.add_callback(self.heartbeat_callback.start)
@property
def worker_address(self):
""" For API compatibility with Nanny """
return self.address
@gen.coroutine
def heartbeat(self):
if not self.heartbeat_active:
self.heartbeat_active = True
logger.debug("Heartbeat: %s" % self.address)
try:
yield self.scheduler.register(address=self.address, name=self.name,
ncores=self.ncores,
now=time(),
host_info=self.host_health(),
services=self.service_ports,
memory_limit=self.memory_limit,
**self.process_health())
finally:
self.heartbeat_active = False
else:
logger.debug("Heartbeat skipped: channel busy")
@gen.coroutine
def _start(self, port=0):
self.listen(port)
self.name = self.name or self.address
for k, v in self.services.items():
v.listen(0)
self.service_ports[k] = v.port
logger.info(' Start worker at: %20s:%d', self.ip, self.port)
for k, v in self.service_ports.items():
logger.info(' %16s at: %20s:%d' % (k, self.ip, v))
logger.info('Waiting to connect to: %20s:%d',
self.scheduler.ip, self.scheduler.port)
while True:
try:
resp = yield self.scheduler.register(
ncores=self.ncores, address=(self.ip, self.port),
keys=list(self.data),
name=self.name, nbytes=valmap(sizeof, self.data),
now=time(),
host_info=self.host_health(),
services=self.service_ports,
memory_limit=self.memory_limit,
**self.process_health())
break
except (OSError, StreamClosedError):
logger.debug("Unable to register with scheduler. Waiting")
yield gen.sleep(0.5)
if resp != 'OK':
raise ValueError(resp)
logger.info(' Registered to: %20s:%d',
self.scheduler.ip, self.scheduler.port)
self.status = 'running'
def start(self, port=0):
self.loop.add_callback(self._start, port)
def identity(self, stream):
return {'type': type(self).__name__, 'id': self.id,
'scheduler': (self.scheduler.ip, self.scheduler.port),
'ncores': self.ncores,
'memory_limit': self.memory_limit}
@gen.coroutine
def _close(self, report=True, timeout=10):
self.heartbeat_callback.stop()
with ignoring(RPCClosed, StreamClosedError):
if report:
yield gen.with_timeout(timedelta(seconds=timeout),
self.scheduler.unregister(address=(self.ip, self.port)),
io_loop=self.loop)
self.scheduler.close_rpc()
self.stop()
self.executor.shutdown()
if os.path.exists(self.local_dir):
shutil.rmtree(self.local_dir)
for k, v in self.services.items():
v.stop()
self.status = 'closed'
self.stop()
@gen.coroutine
def terminate(self, stream, report=True):
yield self._close(report=report)
raise Return('OK')
@property
def address(self):
return '%s:%d' % (self.ip, self.port)
@property
def address_tuple(self):
return (self.ip, self.port)
@gen.coroutine
def gather(self, stream=None, who_has=None):
who_has = {k: [coerce_to_address(addr) for addr in v]
for k, v in who_has.items()
if k not in self.data}
try:
result = yield gather_from_workers(who_has)
except KeyError as e:
logger.warn("Could not find data", e)
raise Return({'status': 'missing-data',
'keys': e.args})
else:
self.data.update(result)
raise Return({'status': 'OK'})
def deserialize(self, function=None, args=None, kwargs=None, task=None):
""" Deserialize task inputs and regularize to func, args, kwargs """
if task is not None:
task = loads(task)
if function is not None:
function = loads(function)
if args:
args = loads(args)
if kwargs:
kwargs = loads(kwargs)
if task is not None:
assert not function and not args and not kwargs
function = execute_task
args = (task,)
return function, args or (), kwargs or {}
@gen.coroutine
def gather_many(self, msgs):
""" Gather the data for many compute messages at once
Returns
-------
good: the input messages for which we have data
bad: a dict of task keys for which we could not find data
data: The scope in which to run tasks
len(remote): the number of new keys we've gathered
"""
diagnostics = {}
who_has = merge(msg['who_has'] for msg in msgs if 'who_has' in msg)
start = time()
local = {k: self.data[k] for k in who_has if k in self.data}
stop = time()
if stop - start > 0.005:
diagnostics['disk_load_start'] = start
diagnostics['disk_load_stop'] = stop
who_has = {k: v for k, v in who_has.items() if k not in local}
start = time()
remote, bad_data = yield gather_from_workers(who_has,
permissive=True)
if remote:
self.data.update(remote)
yield self.scheduler.add_keys(address=self.address, keys=list(remote))
stop = time()
if remote:
diagnostics['transfer_start'] = start
diagnostics['transfer_stop'] = stop
data = merge(local, remote)
if bad_data:
missing = {msg['key']: {k for k in msg['who_has'] if k in bad_data}
for msg in msgs if 'who_has' in msg}
bad = {k: v for k, v in missing.items() if v}
good = [msg for msg in msgs if not missing.get(msg['key'])]
else:
good, bad = msgs, {}
raise Return([good, bad, data, len(remote), diagnostics])
@gen.coroutine
def _ready_task(self, function=None, key=None, args=(), kwargs={},
task=None, who_has=None):
who_has = who_has or {}
diagnostics = {}
start = time()
data = {k: self.data[k] for k in who_has if k in self.data}
stop = time()
if stop - start > 0.005:
diagnostics['disk_load_start'] = start
diagnostics['disk_load_stop'] = stop
who_has = {k: set(map(coerce_to_address, v))
for k, v in who_has.items()
if k not in self.data}
if who_has:
try:
logger.info("gather %d keys from peers", len(who_has))
diagnostics['transfer_start'] = time()
other = yield gather_from_workers(who_has)
diagnostics['transfer_stop'] = time()
self.data.update(other)
yield self.scheduler.add_keys(address=self.address,
keys=list(other))
data.update(other)
except KeyError as e:
logger.warn("Could not find data for %s", key)
raise Return({'status': 'missing-data',
'keys': e.args,
'key': key})
try:
start = default_timer()
function, args, kwargs = self.deserialize(function, args, kwargs,
task)
diagnostics['deserialization'] = default_timer() - start
except Exception as e:
logger.warn("Could not deserialize task", exc_info=True)
emsg = error_message(e)
emsg['key'] = key
raise Return(emsg)
# Fill args with data
args2 = pack_data(args, data)
kwargs2 = pack_data(kwargs, data)
raise Return({'status': 'OK',
'function': function,
'args': args2,
'kwargs': kwargs2,
'diagnostics': diagnostics,
'key': key})
@gen.coroutine
def executor_submit(self, key, function, *args, **kwargs):
""" Safely run function in thread pool executor
We've run into issues running concurrent.future futures within
tornado. Apparently it's advantageous to use timeouts and periodic
callbacks to ensure things run smoothly. This can get tricky, so we
pull it off into an separate method.
"""
job_counter[0] += 1
# logger.info("%s:%d Starts job %d, %s", self.ip, self.port, i, key)
future = self.executor.submit(function, *args, **kwargs)
pc = PeriodicCallback(lambda: logger.debug("future state: %s - %s",
key, future._state), 1000, io_loop=self.loop); pc.start()
try:
yield future
finally:
pc.stop()
pass
result = future.result()
# logger.info("Finish job %d, %s", i, key)
raise gen.Return(result)
@gen.coroutine
def compute_stream(self, stream):
with log_errors():
logger.debug("Open compute stream")
bstream = BatchedSend(interval=2, loop=self.loop)
bstream.start(stream)
closed = False
last = gen.sleep(0)
while not closed:
try:
msgs = yield read(stream)
except StreamClosedError:
break
if not isinstance(msgs, list):
msgs = [msgs]
batch = []
for msg in msgs:
op = msg.pop('op', None)
if op == 'close':
closed = True
break
elif op == 'compute-task':
batch.append(msg)
logger.debug("%s asked to compute %s", self.address,
msg['key'])
else:
logger.warning("Unknown operation %s, %s", op, msg)
# self.loop.add_callback(self.compute_many, bstream, msgs)
last = self.compute_many(bstream, msgs)
try:
yield last # TODO: there might be more than one lingering
except (RPCClosed, RuntimeError):
pass
yield bstream.close()
logger.info("Close compute stream")
@gen.coroutine
def compute_many(self, bstream, msgs, report=False):
good, bad, data, num_transferred, diagnostics = yield self.gather_many(msgs)
for msg in msgs:
msg.pop('who_has', None)
if bad:
logger.warn("Could not find data for %s", sorted(bad))
for k, v in bad.items():
bstream.send({'status': 'missing-data',
'key': k,
'keys': list(v)})
if good:
futures = [self.compute_one(data, report=report, **msg)
for msg in good]
wait_iterator = gen.WaitIterator(*futures)
result = yield wait_iterator.next()
if diagnostics:
result.update(diagnostics)
bstream.send(result)
while not wait_iterator.done():
msg = yield wait_iterator.next()
bstream.send(msg)
@gen.coroutine
def compute_one(self, data, key=None, function=None, args=None, kwargs=None,
report=False, task=None):
logger.debug("Compute one on %s", key)
self.active.add(key)
diagnostics = dict()
try:
start = default_timer()
function, args, kwargs = self.deserialize(function, args, kwargs,
task)
diagnostics['deserialization'] = default_timer() - start
except Exception as e:
logger.warn("Could not deserialize task", exc_info=True)
emsg = error_message(e)
emsg['key'] = key
raise Return(emsg)
# Fill args with data
args2 = pack_data(args, data)
kwargs2 = pack_data(kwargs, data)
# Log and compute in separate thread
result = yield self.executor_submit(key, apply_function, function,
args2, kwargs2,
self.execution_state, key)
result['key'] = key
result.update(diagnostics)
if result['status'] == 'OK':
self.data[key] = result.pop('result')
if report:
response = yield self.scheduler.add_keys(keys=[key],
address=(self.ip, self.port))
if not response == 'OK':
logger.warn('Could not report results to scheduler: %s',
str(response))
else:
logger.warn(" Compute Failed\n"
"Function: %s\n"
"args: %s\n"
"kwargs: %s\n",
str(funcname(function))[:1000],
convert_args_to_str(args, max_len=1000),
convert_kwargs_to_str(kwargs, max_len=1000), exc_info=True)
logger.debug("Send compute response to scheduler: %s, %s", key,
result)
try:
self.active.remove(key)
except KeyError:
pass
raise Return(result)
@gen.coroutine
def compute(self, stream=None, function=None, key=None, args=(), kwargs={},
task=None, who_has=None, report=True):
""" Execute function """
self.active.add(key)
# Ready function for computation
msg = yield self._ready_task(function=function, key=key, args=args,
kwargs=kwargs, task=task, who_has=who_has)
if msg['status'] != 'OK':
try:
self.active.remove(key)
except KeyError:
pass
raise Return(msg)
else:
function = msg['function']
args = msg['args']
kwargs = msg['kwargs']
# Log and compute in separate thread
result = yield self.executor_submit(key, apply_function, function,
args, kwargs, self.execution_state,
key)
result['key'] = key
result.update(msg['diagnostics'])
if result['status'] == 'OK':
self.data[key] = result.pop('result')
if report:
response = yield self.scheduler.add_keys(address=(self.ip, self.port),
keys=[key])
if not response == 'OK':
logger.warn('Could not report results to scheduler: %s',
str(response))
else:
logger.warn(" Compute Failed\n"
"Function: %s\n"
"args: %s\n"
"kwargs: %s\n",
str(funcname(function))[:1000],
convert_args_to_str(args, max_len=1000),
convert_kwargs_to_str(kwargs, max_len=1000), exc_info=True)
logger.debug("Send compute response to scheduler: %s, %s", key,
get_msg_safe_str(msg))
try:
self.active.remove(key)
except KeyError:
pass
raise Return(result)
def run(self, stream, function=None, args=(), kwargs={}):
return run(self, stream, function=function, args=args, kwargs=kwargs)
@gen.coroutine
def update_data(self, stream=None, data=None, report=True, deserialize=True):
if deserialize:
data = valmap(loads, data)
self.data.update(data)
if report:
response = yield self.scheduler.add_keys(
address=(self.ip, self.port),
keys=list(data))
assert response == 'OK'
info = {'nbytes': {k: sizeof(v) for k, v in data.items()},
'status': 'OK'}
raise Return(info)
@gen.coroutine
def delete_data(self, stream, keys=None, report=True):
if keys:
for key in keys:
if key in self.data:
del self.data[key]
logger.info("Deleted %d keys", len(keys))
if report:
logger.debug("Reporting loss of keys to scheduler")
yield self.scheduler.remove_keys(address=self.address,
keys=list(keys))
raise Return('OK')
def get_data(self, stream, keys=None):
return {k: dumps(self.data[k]) for k in keys if k in self.data}
def start_ipython(self, stream):
"""Start an IPython kernel
Returns Jupyter connection info dictionary.
"""
from ._ipython_utils import start_ipython
if self._ipython_kernel is None:
self._ipython_kernel = start_ipython(
ip=self.ip,
ns={'worker': self},
log=logger,
)
return self._ipython_kernel.get_connection_info()
def upload_file(self, stream, filename=None, data=None, load=True):
out_filename = os.path.join(self.local_dir, filename)
if isinstance(data, unicode):
data = data.encode()
with open(out_filename, 'wb') as f:
f.write(data)
f.flush()
if load:
try:
name, ext = os.path.splitext(filename)
if ext in ('.py', '.pyc'):
logger.info("Reload module %s from .py file", name)
name = name.split('-')[0]
reload(import_module(name))
if ext == '.egg':
sys.path.append(out_filename)
pkgs = pkg_resources.find_distributions(out_filename)
for pkg in pkgs:
logger.info("Load module %s from egg", pkg.project_name)
reload(import_module(pkg.project_name))
if not pkgs:
logger.warning("Found no packages in egg file")
except Exception as e:
logger.exception(e)
return {'status': 'error', 'exception': dumps(e)}
return {'status': 'OK', 'nbytes': len(data)}
def process_health(self, stream=None):
d = {'active': len(self.active),
'stored': len(self.data)}
return d
def host_health(self, stream=None):
""" Information about worker """
d = {'time': time()}
try:
import psutil
mem = psutil.virtual_memory()
d.update({'cpu': psutil.cpu_percent(),
'memory': mem.total,
'memory_percent': mem.percent})
net_io = psutil.net_io_counters()
if self._last_net_io:
d['network-send'] = net_io.bytes_sent - self._last_net_io.bytes_sent
d['network-recv'] = net_io.bytes_recv - self._last_net_io.bytes_recv
else:
d['network-send'] = 0
d['network-recv'] = 0
self._last_net_io = net_io
try:
disk_io = psutil.disk_io_counters()
except RuntimeError:
# This happens when there is no physical disk in worker
pass
else:
if self._last_disk_io:
d['disk-read'] = disk_io.read_bytes - self._last_disk_io.read_bytes
d['disk-write'] = disk_io.write_bytes - self._last_disk_io.write_bytes
else:
d['disk-read'] = 0
d['disk-write'] = 0
self._last_disk_io = disk_io
except ImportError:
pass
return d
def keys(self, stream=None):
return list(self.data)
