class Node(Daemon):
"""
Node is started up on the remote instance via the bootstrapping process for that instance.
The node is responsible for tracking active streams and managing the workers that process
the jobs from thosee streams. If a stream goes idle (ie, there are no more jobs in the streams
queue and all workers have died) then node will stop tracking the stream. If jobs re-appear
on the stream Node will spawn new workers to process those jobs. If a new stream appears
Node will spawn new workers to processs the jobs on that stream. Each worker is an independent
concurrent process that inherits the stream to process from the Node.
"""
def __init__(self, queue, qauthkey, mpps= 5, dfs= None, dauthkey= None, logdir= curdir, piddir= curdir, **properties):
"""Initialize the Node's I/O stream and connect to the Queue and/or DFS."""
self.id= getipaddress()
self.queue= queue
self.qauthkey= qauthkey
self.mpps= mpps
self.dfs= dfs
self.dauthkey= dauthkey
self.properties= properties
self.shutdown= Value('i', 0)
self.workers= {}
self.alive= True
self.start_time= datetime.utcnow()
self.connect()
super(Node, self).__init__(
pidfile= path.join(piddir, self.__class__.__name__ + ".pid"),
stdout= path.join(logdir, self.__class__.__name__ + ".out"),
stderr= path.join(logdir, self.__class__.__name__ + ".err"),
stdin= path.join(logdir, self.__class__.__name__ + ".in")
)
def connect(self):
"""Connects to the Queue and/or DFS on the host/port for whic hthe Node was intialized for."""
self.qconnect()
if None not in self.dfs:
self.dconnect()
def qconnect(self):
"""
Attempts to connect to the Queue on the host/port for which the Node was initialized for.
If no connection can be made, Node will keep attempting to connect until a connection
can be established. One connection is established the remove methods requested will be
registered.
"""
# remove connection from cache:
# BaseProxy class has thread local storage which caches the connection
# which is reused for future connections causing "borken pipe" errors on
# creating new manager.
if self.queue in BaseProxy._address_to_local:
if hasattr(BaseProxy._address_to_local[self.queue][0], 'connection'):
del BaseProxy._address_to_local[self.queue][0].connection
# register handlers
SyncManager.register("get_streams")
SyncManager.register("get_queue")
SyncManager.register("get_store")
SyncManager.register("get_properties")
print "connecting to queue", self.queue
while self.alive:
try:
self.impq= SyncManager(address= self.queue, authkey= self.qauthkey)
self.impq.connect()
print "connected to queue", self.queue
break
except (EOFError, IOError, SocketError) as e:
print "could not connect ...trying again", str(e)
sleep(1)
def dconnect(self):
"""
Attempts to connect to the DFS on the host/port for which the Node was initialized for.
If no connection can be made, Node will keep attempting to connect until a connection
can be established. Once a connection can be established the remove methods requested
will be registered.
"""
# remove connection from cache:
# BaseProxy class has thread local storage which caches the connection
# which is reused for future connections causing "borken pipe" errors on
# creating new manager.
if self.dfs in BaseProxy._address_to_local:
if hasattr(BaseProxy._address_to_local[self.dfs][0], 'connection'):
del BaseProxy._address_to_local[self.dfs][0].connection
# register handlers
SyncManager.register("get_nodes")
print "connecting to dfs", self.dfs
while self.alive:
try:
self.impd= SyncManager(address= self.dfs, authkey= self.dauthkey)
self.impd.connect()
print "connected to dfs", self.dfs
break
except (EOFError, IOError, SocketError) as e:
print "could not connect ...trying again", str(e)
sleep(1)
def process(self):
"""
Starts tracking streams. When a stream is found which matches the Node's criteria
workers are assigned to the stream and spawned to start processing jobs from the
streams queue. When the stream goes idle and all workers for that stream have died
the Node will stop tracking the stream until new jobs appear on the stream. Node will
limit the amount of workers it can spawn for a stream to the configred amount. If Node was
started with the --dfs option then status updates about how many streams, workers and jobs
are being processed will continually be sent back to DFS via a configurable rate.
"""
print "processing", self.mpps
# get list of streams proxies
streams= self.impq.get_streams()
streams_tracking= {}
# if reporting to DFS
# track nodes via shared dict else maintain local dict
if hasattr(self, 'impd'):
nodes= self.impd.get_nodes()
idle_time= datetime.utcnow()
while self.alive:
# get list of streams to track we are not currently tracking
streams_to_track= filter(lambda stream_id: stream_id not in streams_tracking.keys(), streams.keys())
# if we are only tracking streams with specific properties
# TODO: need to think through this more
"""
if len(self.properties):
# get properties for all the streams we are tracking
stream_properties= [dict(self.impq.get_properties(stream_id)) for stream_id in streams_to_track]
# filter out streams we want to track based on matching subsets of properties
if "id" in self.properties:
streams_to_track= map(lambda sp: sp.get("id"), filter(lambda sp: set(sp.items()).issubset(self.properties.items()), stream_properties))
else:
streams_to_track= map(lambda sp: sp.get("id"), filter(lambda sp: set(filter(lambda (property_name, property_value): property_name != 'id', sp.items())).issubset(self.properties.items()), stream_properties))
"""
for stream_id in streams_to_track:
print "tracking stream", stream_id
streams_tracking.update([(stream_id, (self.impq.get_queue(stream_id), self.impq.get_store(stream_id), self.properties))])
# stop tracking streams which are no longer active
for stream_id in streams_tracking.keys():
if stream_id not in streams.keys():
print 'stopped tracking stream', stream_id
streams_tracking.pop(stream_id)
# stop tracking workers which are no longer active
for (pid, worker) in self.workers.items():
if not worker.is_alive():
#print "worker dead", pid, worker.stream_id
self.workers.pop(pid)
else:
idle_time= datetime.utcnow()
# create workers for streams we are currently tracking
for (stream_id, (queue, store, properties)) in streams_tracking.items():
qsize= queue.qsize()
stream_workers= filter(lambda w: w.stream_id == stream_id, self.workers.values())
num_stream_workers= min(qsize, self.mpps - len(stream_workers))
if num_stream_workers:
print "creating %s workers for %s" % (num_stream_workers, stream_id)
for i in range(1, num_stream_workers + 1):
worker= Worker(self.id, stream_id, queue, store, properties, self.shutdown)
worker.start()
self.workers.update([(worker.pid, worker)])
idle_time= datetime.utcnow()
print "created worker", i, worker.pid, stream_id
status= Status(
mpps= self.mpps,
streams= len(streams_tracking),
workers= len(self.workers),
starttime= self.start_time,
uptime= datetime.utcnow() - self.start_time,
lastactivity= idle_time,
idletime= datetime.utcnow() - idle_time,
properties= self.properties,
pid= getpid()
)
if hasattr(self, 'impd'):
nodes.update([(self.id, status)])
# if a worker has been blocked then stop all workers and shutdown
# this will then cause the Node to go idle and DFS will shut it down
# and restart a new node to take it's place
if self.shutdown.value:
print >> stderr, "node blocked", self.id
self.alive= False
sleep(1)
self.stop()
def stop(self):
"""
Starts the shutdown process for the Node. Waits for all
workers to finish their activity. If Node was started with
the --dfs option then it will de-register itself with DFS.
"""
# wait for workers to finish before shutting down
print "shutting down node..."
self.alive= False
for (pid, worker) in self.workers.items():
print "waiting for worker:", pid, worker.stream_id
worker.join()
# if reporting to DFS
# track nodes via shared dict else maintain local dict
if hasattr(self, 'impd'):
print "de-registering nodes with dfs"
nodes= self.impd.get_nodes()
try:
del nodes[self.id]
except KeyError:
print >> stderr, "node not registered with dfs", self.id
print "node shutdown complete."
super(Node, self).stop()
def run(self):
"""
Starts processing the streams which match the given properties of the Node.
If a connection error between Node and Queue/DFs occurs Node will continually
try to re-establish connection.
"""
while self.alive:
try:
self.process()
except (KeyboardInterrupt, Exception) as e:
if type(e) == KeyboardInterrupt:
self.stop()
else:
print >> stderr, "queue/dfs communication error", str(e)
self.connect()
sleep(1)
class Impetus(object):
"""
Multi-threaded library for interfacing with the Impetus system.
Hides threading considerations from the client. Determines callback
methods through introspection if callbacks are not explicitly stated.
Decorators are provided for the client to indicate methods which run on
the remote nodes and local process methods which consume the results.
Creates a single stream per instance. The client can created additional
streams through the Queue's remote methods via the "impq" handler.
"""
statuses= ("forked", "processed")
def __init__(self, address, authkey, taskdir= "tasks", id= None, **properties):
"""Creates a stream and retrieves the streams priority queue and data-store."""
self.id= id if id else str(uuid1())
self.ipaddress= getipaddress()
self.address= address
self.taskdir= path.join(taskdir, self.id)
self.properties= properties
self.impq= SyncManager(address= self.address, authkey= authkey)
self.impq.register("get_streams")
self.impq.register("create_stream")
self.impq.register("delete_stream")
self.impq.register("get_store")
self.impq.register("get_queue")
self.impq.connect()
self.jobs= []
self.impq.create_stream(id= self.id, ipaddress= self.ipaddress, **properties)
self.store= self.impq.get_store(id= self.id)
self.queue= self.impq.get_queue(id= self.id)
self.alive= True
self._current_thread= None
self._lock= Lock()
self.threads= []
self.errors= {}
self.ready= {}
self._progress= {}
try:
makedirs(self.taskdir)
except:
pass
def __del__(self):
"""Deletes the stream that was created during initialization."""
self.impq.delete_stream(self.id)
@staticmethod
def node(target):
"""
All methods that are to run on remote nodes must be staticmethods
as the context of which the methods was defined can not be serialized.
"""
return target
@staticmethod
def startup(target):
"""
Sets up the startup method for the object to run as a thread.
"""
def _process(self):
target(self)
global _declaration_order
_process.order= _declaration_order
_declaration_order+= 1
return _process
@staticmethod
def shutdown(target):
"""
Sets up the shutdown method to be excuted
after all threads have been terminated. The
ready and errors parameters will contain a dict
of file-handles pointing to the results files
(ie, ../tasks/<task_id>/<method>.ok, .err>
for each @process method.
"""
def _shutdown(self):
target(self, self.ready, self.errors, self._progress)
global _declaration_order
_shutdown.order= _declaration_order
return _shutdown
@staticmethod
def process(target):
"""
Sets up method to run as a thread. The method will be
called with a list of currently available jobs that are
either in a ready or error state. The thread will die
when it has finished processing all the jobs the previous
@process method forked and when the previous @process method
has terminatted. Each thread will be regulated so that all
threads have an eventual chance of executing. Order of execution
is not guarenteed and thread scheudling is handled by the
operating system.
"""
def _process(self):
current_thread= currentThread()
if current_thread.name == 'MainThread':
return
previous_thread= current_thread.previous_thread
while self.alive:
self._thread_regulator(current_thread, previous_thread)
with self._lock:
jobs= filter(lambda job: job.get("callback") == current_thread.name, self.store.values())
ready= filter(lambda job: job.get("status") == "ready", jobs)
errors= filter(lambda job: job.get("status") == "error", jobs)
for job in ready:
self.ready[current_thread.name].write(encode(compress(jdumps(job, cls= JobEncoder))) + "\n")
self.store.pop(job.get("id"))
for job in errors:
self.errors[current_thread.name].write(encode(compress(jdumps(job, cls= JobEncoder))) + "\n")
self.store.pop(job.get("id"))
if len(ready) or len(errors):
target(self, ready, errors)
self._thread_progress(current_thread.name, "processed", len(ready) + len(errors))
self._show_progress(current_thread)
if len(self.store) == 0 and previous_thread != None and previous_thread.is_alive() == False:
print "%s %s completed" % (datetime.utcnow(), current_thread.name)
stdout.flush()
self.alive= False
sleep(0.01)
global _declaration_order
_process.order= _declaration_order
_declaration_order+= 1
return _process
def fork(self, target, args, callback= None, priority= None, job_id= None, **properties):
"""
Turns the target method to be forked into byte-code and creates a Job. The Job
is initialized to the starting state and placed the the streams priorty queue
for execution.
"""
if self.properties.get('mss'):
stall_time= 1
while len(self.store) > int(self.properties.get('mss')):
print "throttling size %s exceeds mss %s" % (len(self.store), self.properties.get('mss'))
sleep(stall_time)
stall_time+= 1
if stall_time >= 10:
break
current_thread= currentThread()
job= Job(
client= {"id": self.id, "ipaddress": self.ipaddress},
name= target.func_name,
code= encode(compress(mdumps(target.func_code))),
args= args,
callback= callback if callback else current_thread.next_thread.name,
result= None,
transport= None,
**properties
)
if priority:
setattr(job, "priority", priority)
self.store.update([(job.get("id"), job)])
self.queue.put([(job.get("priority"), job.get("id"))])
#print "forked", len(self.store)
self.jobs.append(job.get("id"))
self._thread_progress(current_thread.name, "forked", 1)
return job.get("id")
def _thread_progress(self, name, status, count):
"""
Keeps track of how many jobs the current
thread has forked/processed.
"""
with self._lock:
progress= self._progress.get(name, dict([(s, 0) for s in self.statuses]))
progress.update([(status, progress.get(status, 0) + count)])
self._progress.update([(name, progress)])
def _show_progress(self, current_thread):
"""Displays the current threads progress to stdout."""
msg= []
with self._lock:
for thread in self.threads:
progress= self._progress.get(thread.name, dict([(s, 0) for s in self.statuses]))
msg.append("%s %s/%s -> " % (thread.name, progress.get("forked"), progress.get("processed")))
print "thread: %s via %s" % (''.join(msg)[:-4], current_thread.name)
def _thread_regulator(self, current_thread, previous_thread):
"""
Regulates the current thread so all threads have an eventual
chance to run. Thread scheduling is handled by the operating-system.
If the operating-system repeatively schedules the same thread than
that thread is immediately put to sleep so the operating-system
can schedule a new thread.
"""
stall_time= 1
while self._current_thread == current_thread:
#print "stalling:", current_thread.name, stall_time
sleep(stall_time)
stall_time+= 1
if stall_time >= 10:
break
if current_thread.name == self.threads[-1].name and previous_thread != None and previous_thread.is_alive() == False:
with self._lock:
self._current_thread= self.threads[0]
with self._lock:
#print "setting current thread", current_thread.name
self._current_thread= current_thread
def _create_thread(self, name, method):
"""
Creates thread for the @process method as well
as error/ready file handlers for which all jobs
in an error/ready state are written to. All threads
are maintained in an internal thread list.
"""
thread= Thread(target= method, name= name, args= (self, ))
self.errors[name]= open(path.join(self.taskdir, '.'.join((name, "err"))), 'ab+')
self.ready[name]= open(path.join(self.taskdir, '.'.join((name, "ok"))), 'ab+')
return thread
def _link_threads(self, threads):
"""
Creates previous/next properties for each thread based
on the threads declaration order.
"""
for i in range(len(threads)):
setattr(threads[i], "previous_thread", threads[i-1] if i > 0 else None)
setattr(threads[i], "next_thread", threads[i+1] if i < len(threads)-1 else None)
return threads[0]
def _start_threads(self, threads):
"""Starts all threads based on their delcaration order."""
[thread.start() for thread in threads]
[thread.join() for thread in threads]
def run(self):
self.threads= [self._create_thread(name, method) for (name, method) in sorted(filter(lambda (name, method): type(method) == FunctionType and method.__name__ == "_process", self.__class__.__dict__.items()), key= lambda (name, method): method.order)]
