def __init__(self, ip, tid, anna_client):
self.ctx = zmq.Context()
self.send_socket_cache = SocketCache(self.ctx, zmq.PUSH)
self.executor_ip = ip
self.executor_tid = tid
self.client = anna_client
# Threadsafe queue to serve as this node's inbox.
# Items are (sender string, message bytestring).
# NB: currently unbounded in size.
self.recv_inbox = queue.Queue()
# Thread for receiving messages into our inbox.
self.recv_inbox_thread = threading.Thread(
target=self._recv_inbox_listener)
self.recv_inbox_thread.do_run = True
self.recv_inbox_thread.start()
def __init__(self, elb_addr, ip, local=False, offset=0):
'''
The AnnaTcpClientTcpAnnaClient allows you to interact with a local
copy of Anna or with a remote cluster running on AWS.
elb_addr: Either 127.0.0.1 (local mode) or the address of an AWS ELB
for the routing tier
ip: The IP address of the machine being used -- if None is provided,
one is inferred by using socket.gethostbyname(); WARNING: this does not
always work
elb_ports: The ports on which the routing tier will listen; use 6450 if
running in local mode, otherwise do not change
offset: A port numbering offset, which is only needed if multiple
clients are running on the same machine
'''
self.elb_addr = elb_addr
if local:
self.elb_ports = [6450]
else:
self.elb_ports = list(range(6450, 6454))
if ip:
self.ut = UserThread(ip, offset)
else: # If the IP is not provided, we attempt to infer it.
self.ut = UserThread(socket.gethostbyname(socket.gethostname()),
offset)
self.context = zmq.Context(1)
self.address_cache = {}
self.pusher_cache = SocketCache(self.context, zmq.PUSH)
self.response_puller = self.context.socket(zmq.PULL)
self.response_puller.bind(self.ut.get_request_pull_bind_addr())
self.key_address_puller = self.context.socket(zmq.PULL)
self.key_address_puller.bind(self.ut.get_key_address_bind_addr())
self.rid = 0
self.cache = {}
class AnnaTcpClient(BaseAnnaClient):
def __init__(self, elb_addr, ip, local=False, offset=0):
'''
The AnnaTcpClientTcpAnnaClient allows you to interact with a local
copy of Anna or with a remote cluster running on AWS.
elb_addr: Either 127.0.0.1 (local mode) or the address of an AWS ELB
for the routing tier
ip: The IP address of the machine being used -- if None is provided,
one is inferred by using socket.gethostbyname(); WARNING: this does not
always work
elb_ports: The ports on which the routing tier will listen; use 6450 if
running in local mode, otherwise do not change
offset: A port numbering offset, which is only needed if multiple
clients are running on the same machine
'''
self.elb_addr = elb_addr
if local:
self.elb_ports = [6450]
else:
self.elb_ports = list(range(6450, 6454))
if ip:
self.ut = UserThread(ip, offset)
else: # If the IP is not provided, we attempt to infer it.
self.ut = UserThread(socket.gethostbyname(socket.gethostname()),
offset)
self.context = zmq.Context(1)
self.get_address_cache = {}
self.put_address_cache = {}
self.pusher_cache = SocketCache(self.context, zmq.PUSH)
self.response_puller = self.context.socket(zmq.PULL)
self.response_puller.bind(self.ut.get_request_pull_bind_addr())
self.key_address_puller = self.context.socket(zmq.PULL)
self.key_address_puller.bind(self.ut.get_key_address_bind_addr())
self.rid = 0
def get(self, keys):
if type(keys) != list:
keys = [keys]
worker_addresses = {}
for key in keys:
worker_addresses[key] = (self._get_worker_address(key, 1))
#print("Worker Address: {}".format(worker_addresses[key]))
if type(worker_addresses[key]) == list:
worker_addresses[key] = worker_addresses[key][0]
# Initialize all KV pairs to 0. Only change a value if we get a valid
# response from the server.
kv_pairs = {}
for key in keys:
kv_pairs[key] = None
request_ids = []
for key in worker_addresses:
if worker_addresses[key]:
send_sock = self.pusher_cache.get(worker_addresses[key])
req, _ = self._prepare_data_request([key])
req.type = GET
send_request(req, send_sock)
request_ids.append(req.request_id)
# Wait for all responses to return.
responses = recv_response(request_ids, self.response_puller,
KeyResponse)
for response in responses:
for tup in response.tuples:
if tup.invalidate:
self._invalidate_cache(tup.key, 'get')
if tup.error == NO_ERROR and not tup.invalidate:
kv_pairs[tup.key] = self._deserialize(tup)
return kv_pairs
def get_all(self, keys):
if type(keys) != list:
keys = [keys]
raise ValueError('`get_all` currently only supports single key' +
' GETs.')
worker_addresses = {}
for key in keys:
worker_addresses[key] = self._get_worker_address(key, False)
# Initialize all KV pairs to 0. Only change a value if we get a valid
# response from the server.
kv_pairs = {}
for key in keys:
kv_pairs[key] = None
for key in keys:
if worker_addresses[key]:
req, _ = self._prepare_data_request(key)
req.type = GET
req_ids = []
for address in worker_addresses[key]:
req.request_id = self._get_request_id()
send_sock = self.pusher_cache.get(address)
send_request(req, send_sock)
req_ids.append(req.request_id)
responses = recv_response(req_ids, self.response_puller, KeyResponse)
for resp in responses:
for tup in resp.tuples:
if tup.invalidate:
self._invalidate_cache(tup.key)
if tup.error == NO_ERROR:
val = self._deserialize(tup)
if kv_pairs[tup.key]:
kv_pairs[tup.key].merge(val)
else:
kv_pairs[tup.key] = val
return kv_pairs
def put(self, key, value):
port = random.choice(self.elb_ports)
worker_address = self._query_routing(key, port)
if type(worker_address) == list:
worker_address = worker_address[0]
if not worker_address:
return False
send_sock = self.pusher_cache.get(worker_address)
# We pass in a list because the data request preparation can prepare
# multiple tuples
req, tup = self._prepare_data_request([key])
req.type = PUT
# PUT only supports one key operations, we only ever have to look at
# the first KeyTuple returned.
tup = tup[0]
tup.payload, tup.lattice_type = self._serialize(value)
send_request(req, send_sock)
response = recv_response([req.request_id], self.response_puller,
KeyResponse)[0]
tup = response.tuples[0]
if tup.invalidate:
self._invalidate_cache(tup.key)
return tup.error == NO_ERROR
def put_all(self, key, value):
worker_addresses = self._get_worker_address(key, False)
if not worker_addresses:
return False
req, tup = self._prepare_data_request(key)
req.type = PUT
tup.payload, tup.lattice_type = self._serialize(value)
tup.timestamp = 0
req_ids = []
for address in worker_addresses:
req.request_id = self._get_request_id()
send_sock = self.pusher_cache.get(address)
send_request(req, send_sock)
req_ids.append(req.request_id)
responses = recv_response(req_ids, self.response_puller, KeyResponse)
for resp in responses:
tup = resp.tuples[0]
if tup.invalidate:
# reissue the request
self._invalidate_cache(tup.key)
return self.durable_put(key, value)
if tup.error != NO_ERROR:
return False
return True
# Returns the worker address for a particular key. If worker addresses for
# that key are not cached locally, a query is synchronously issued to the
# routing tier, and the address cache is updated.
def _get_worker_address(self, key, access_type, pick=True):
insert_to_cache = False
monitor_address = None
#if it's a GET
if access_type == 1:
if key not in self.get_address_cache:
#Key is not in cache
port = random.choice(self.elb_ports)
addresses = self._query_routing(key, port)
addresses = list(set(addresses))
for address in addresses:
#TODO: Change here the IP to the address of the Master node!
if address != "tcp://192.168.0.31:5900":
self.get_address_cache[key] = []
self.get_address_cache[key].append(address)
else:
monitor_address = address
#print(self.get_address_cache)
if len(self.get_address_cache[key]) == 0:
return None
if pick:
return random.choice(self.get_address_cache[key])
else:
return self.get_address_cache[key]
# if it's a PUT
if access_type == 2:
if key not in self.put_address_cache:
#print("Key is not in cache")
port = random.choice(self.elb_ports)
#print("Port: {}".format(port))
addresses = self._query_routing(key, port)
addresses = list(set(addresses))
#print(addresses)
#print(self.put_address_cache)
for address in addresses:
#TODO: Change here the IP to the address of the Master node!
if address != "tcp://192.168.0.31:5900":
self.put_address_cache[key] = []
self.put_address_cache[key].append(address)
insert_to_cache = True
else:
monitor_address = address
#print(self.put_address_cache)
if len(self.put_address_cache[key]) == 0:
#print('1')
return None
if pick:
#print('2')
return random.choice(self.put_address_cache[key])
else:
#print('3')
return self.put_address_cache[key]
# Invalidates the address cache for a particular key when the server tells
# the client that its cache is out of date.
def _invalidate_cache(self, key, type='both'):
if type == 'get':
del self.get_address_cache[key]
elif type == 'put':
del self.put_address_cache[key]
else:
try:
del self.get_address_cache[key]
except KeyError:
pass
try:
del self.put_address_cache[key]
except KeyError:
pass
# Issues a synchronous query to the routing tier. Takes in a key and a
# (randomly chosen) routing port to issue the request to. Returns a list of
# addresses that the routing tier returned that correspond to the input
# key.
def _query_routing(self, key, port):
key_request = KeyAddressRequest()
key_request.query_type = u'GET'
key_request.response_address = self.ut.get_key_address_connect_addr()
key_request.keys.append(key)
key_request.request_id = self._get_request_id()
dst_addr = 'tcp://' + self.elb_addr + ':' + str(port)
send_sock = self.pusher_cache.get(dst_addr)
send_request(key_request, send_sock)
response = recv_response([key_request.request_id],
self.key_address_puller,
KeyAddressResponse)[0]
if response.error != 0:
return []
result = []
for t in response.addresses:
if t.key == key:
for a in t.ips:
result.append(a)
return result
@property
def response_address(self):
return self.ut.get_request_pull_connect_addr()
def scheduler(ip, mgmt_ip, route_addr):
logging.basicConfig(filename='log_scheduler.txt', level=logging.INFO,
format='%(asctime)s %(message)s')
kvs = AnnaClient(route_addr, ip)
key_ip_map = {}
ctx = zmq.Context(1)
# Each dag consists of a set of functions and connections. Each one of
# the functions is pinned to one or more nodes, which is tracked here.
dags = {}
thread_statuses = {}
func_locations = {}
running_counts = {}
backoff = {}
connect_socket = ctx.socket(zmq.REP)
connect_socket.bind(sutils.BIND_ADDR_TEMPLATE % (CONNECT_PORT))
func_create_socket = ctx.socket(zmq.REP)
func_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CREATE_PORT))
func_call_socket = ctx.socket(zmq.REP)
func_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CALL_PORT))
dag_create_socket = ctx.socket(zmq.REP)
dag_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CREATE_PORT))
dag_call_socket = ctx.socket(zmq.REP)
dag_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CALL_PORT))
list_socket = ctx.socket(zmq.REP)
list_socket.bind(sutils.BIND_ADDR_TEMPLATE % (LIST_PORT))
exec_status_socket = ctx.socket(zmq.PULL)
exec_status_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.STATUS_PORT))
sched_update_socket = ctx.socket(zmq.PULL)
sched_update_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SCHED_UPDATE_PORT))
backoff_socket = ctx.socket(zmq.PULL)
backoff_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.BACKOFF_PORT))
pin_accept_socket = ctx.socket(zmq.PULL)
pin_accept_socket.setsockopt(zmq.RCVTIMEO, 500)
pin_accept_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.PIN_ACCEPT_PORT))
requestor_cache = SocketCache(ctx, zmq.REQ)
pusher_cache = SocketCache(ctx, zmq.PUSH)
poller = zmq.Poller()
poller.register(connect_socket, zmq.POLLIN)
poller.register(func_create_socket, zmq.POLLIN)
poller.register(func_call_socket, zmq.POLLIN)
poller.register(dag_create_socket, zmq.POLLIN)
poller.register(dag_call_socket, zmq.POLLIN)
poller.register(list_socket, zmq.POLLIN)
poller.register(exec_status_socket, zmq.POLLIN)
poller.register(sched_update_socket, zmq.POLLIN)
poller.register(backoff_socket, zmq.POLLIN)
executors = set()
executor_status_map = {}
schedulers = _update_cluster_state(requestor_cache, mgmt_ip, executors,
key_ip_map, kvs)
# track how often each DAG function is called
call_frequency = {}
start = time.time()
while True:
socks = dict(poller.poll(timeout=1000))
if connect_socket in socks and socks[connect_socket] == zmq.POLLIN:
msg = connect_socket.recv_string()
connect_socket.send_string(route_addr)
if (func_create_socket in socks and
socks[func_create_socket] == zmq.POLLIN):
create_func(func_create_socket, kvs)
if func_call_socket in socks and socks[func_call_socket] == zmq.POLLIN:
call_function(func_call_socket, pusher_cache, executors,
key_ip_map, executor_status_map, running_counts,
backoff)
if (dag_create_socket in socks and socks[dag_create_socket]
== zmq.POLLIN):
create_dag(dag_create_socket, pusher_cache, kvs, executors, dags,
ip, pin_accept_socket, func_locations, call_frequency)
if dag_call_socket in socks and socks[dag_call_socket] == zmq.POLLIN:
call = DagCall()
call.ParseFromString(dag_call_socket.recv())
if call.name not in dags:
resp = GenericResponse()
resp.success = False
resp.error = NO_SUCH_DAG
dag_call_socket.send(resp.SerializeToString())
continue
exec_id = generate_timestamp(0)
dag = dags[call.name]
for fname in dag[0].functions:
call_frequency[fname] += 1
rid = call_dag(call, pusher_cache, dags, func_locations,
key_ip_map, running_counts, backoff)
resp = GenericResponse()
resp.success = True
resp.response_id = rid
dag_call_socket.send(resp.SerializeToString())
if list_socket in socks and socks[list_socket] == zmq.POLLIN:
logging.info('Received query for function list.')
msg = list_socket.recv_string()
prefix = msg if msg else ''
resp = FunctionList()
resp.names.extend(utils._get_func_list(kvs, prefix))
list_socket.send(resp.SerializeToString())
if exec_status_socket in socks and socks[exec_status_socket] == \
zmq.POLLIN:
status = ThreadStatus()
status.ParseFromString(exec_status_socket.recv())
key = (status.ip, status.tid)
logging.info('Received status update from executor %s:%d.' %
(key[0], int(key[1])))
if key in executor_status_map:
if status.type == PERIODIC:
if executor_status_map[key] - time.time() > 5:
del executor_status_map[key]
else:
continue
elif status.type == POST_REQUEST:
del executor_status_map[key]
# this means that this node is currently departing, so we remove it
# from all of our metadata tracking
if not status.running:
if key in thread_statuses:
old_status = thread_statuses[key]
del thread_statuses[key]
for fname in old_status.functions:
func_locations[fname].discard((old_status.ip,
old_status.tid))
executors.discard(key)
continue
if key not in executors:
executors.add(key)
if key in thread_statuses and thread_statuses[key] != status:
# remove all the old function locations, and all the new ones
# -- there will probably be a large overlap, but this shouldn't
# be much different than calculating two different set
# differences anyway
for func in thread_statuses[key].functions:
if func in func_locations:
func_locations[func].discard(key)
thread_statuses[key] = status
for func in status.functions:
if func not in func_locations:
func_locations[func] = set()
func_locations[func].add(key)
if sched_update_socket in socks and socks[sched_update_socket] == \
zmq.POLLIN:
status = SchedulerStatus()
status.ParseFromString(sched_update_socket.recv())
# retrieve any DAG that some other scheduler knows about that we do
# not yet know about
for dname in status.dags:
if dname not in dags:
payload = kvs.get(dname)
while not payload:
payload = kvs.get(dname)
dag = Dag()
dag.ParseFromString(payload.reveal()[1])
dags[dag.name] = (dag, utils._find_dag_source(dag))
for fname in dag.functions:
if fname not in call_frequency:
call_frequency[fname] = 0
if fname not in func_locations:
func_locations[fname] = set()
for floc in status.func_locations:
key = (floc.ip, floc.tid)
fname = floc.name
if fname not in func_locations:
func_locations[fname] = set()
func_locations[fname].add(key)
if backoff_socket in socks and socks[backoff_socket] == zmq.POLLIN:
msg = backoff_socket.recv_string()
splits = msg.split(':')
node, tid = splits[0], int(splits[1])
backoff[(node, tid)] = time.time()
# periodically clean up the running counts map
for executor in running_counts:
call_times = running_counts[executor]
new_set = set()
for ts in call_times:
if time.time() - ts < 2.5:
new_set.add(ts)
running_counts[executor] = new_set
remove_set = set()
for executor in backoff:
if time.time() - backoff[executor] > 5:
remove_set.add(executor)
for executor in remove_set:
del backoff[executor]
end = time.time()
if end - start > THRESHOLD:
schedulers = _update_cluster_state(requestor_cache, mgmt_ip,
executors, key_ip_map, kvs)
status = SchedulerStatus()
for name in dags.keys():
status.dags.append(name)
for fname in func_locations:
for loc in func_locations[fname]:
floc = status.func_locations.add()
floc.name = fname
floc.ip = loc[0]
floc.tid = loc[1]
msg = status.SerializeToString()
for sched_ip in schedulers:
if sched_ip != ip:
sckt = pusher_cache.get(utils._get_scheduler_update_address
(sched_ip))
sckt.send(msg)
stats = ExecutorStatistics()
for fname in call_frequency:
fstats = stats.statistics.add()
fstats.fname = fname
fstats.call_count = call_frequency[fname]
logging.info('Reporting %d calls for function %s.' %
(call_frequency[fname], fname))
call_frequency[fname] = 0
sckt = pusher_cache.get(sutils._get_statistics_report_address
(mgmt_ip))
sckt.send(stats.SerializeToString())
start = time.time()
def executor(ip, mgmt_ip, schedulers, thread_id):
# logging.basicConfig(stream=sys.stdout, level=logging.INFO, format='%(asctime)s %(message)s')
logging.basicConfig(filename='log_executor.txt',
level=logging.INFO,
filemode="w",
format='%(asctime)s %(message)s')
# Check what resources we have access to, set as an environment variable.
if os.getenv('EXECUTOR_TYPE', 'CPU') == 'GPU':
exec_type = GPU
else:
exec_type = CPU
context = zmq.Context(1)
poller = zmq.Poller()
pin_socket = context.socket(zmq.PULL)
pin_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.PIN_PORT + thread_id))
unpin_socket = context.socket(zmq.PULL)
unpin_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.UNPIN_PORT + thread_id))
exec_socket = context.socket(zmq.PULL)
exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.FUNC_EXEC_PORT + thread_id))
dag_queue_socket = context.socket(zmq.PULL)
dag_queue_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_QUEUE_PORT + thread_id))
dag_exec_socket = context.socket(zmq.PULL)
dag_exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_EXEC_PORT + thread_id))
self_depart_socket = context.socket(zmq.PULL)
self_depart_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SELF_DEPART_PORT + thread_id))
pusher_cache = SocketCache(context, zmq.PUSH)
poller = zmq.Poller()
poller.register(pin_socket, zmq.POLLIN)
poller.register(unpin_socket, zmq.POLLIN)
poller.register(exec_socket, zmq.POLLIN)
poller.register(dag_queue_socket, zmq.POLLIN)
poller.register(dag_exec_socket, zmq.POLLIN)
poller.register(self_depart_socket, zmq.POLLIN)
# If the management IP is set to None, that means that we are running in
# local mode, so we use a regular AnnaTcpClient rather than an IPC client.
has_ephe = False
if mgmt_ip:
if 'STORAGE_OR_DEFAULT' in os.environ and os.environ[
'STORAGE_OR_DEFAULT'] == '0':
client = AnnaTcpClient(os.environ['ROUTE_ADDR'],
ip,
local=False,
offset=thread_id)
has_ephe = True
else:
client = AnnaIpcClient(thread_id, context)
# force_remote_anna = 1
# if 'FORCE_REMOTE' in os.environ:
# force_remote_anna = int(os.environ['FORCE_REMOTE'])
# if force_remote_anna == 0: # remote anna only
# client = AnnaTcpClient(os.environ['ROUTE_ADDR'], ip, local=False, offset=thread_id)
# elif force_remote_anna == 1: # anna cache
# client = AnnaIpcClient(thread_id, context)
# elif force_remote_anna == 2: # control both cache and remote anna
# remote_client = AnnaTcpClient(os.environ['ROUTE_ADDR'], ip, local=False, offset=thread_id)
# cache_client = AnnaIpcClient(thread_id, context)
# client = cache_client
# user_library = CloudburstUserLibrary(context, pusher_cache, ip, thread_id, (cache_client, remote_client))
local = False
else:
client = AnnaTcpClient('127.0.0.1', '127.0.0.1', local=True, offset=1)
local = True
user_library = CloudburstUserLibrary(context,
pusher_cache,
ip,
thread_id,
client,
has_ephe=has_ephe)
status = ThreadStatus()
status.ip = ip
status.tid = thread_id
status.running = True
status.type = exec_type
utils.push_status(schedulers, pusher_cache, status)
departing = False
# Maintains a request queue for each function pinned on this executor. Each
# function will have a set of request IDs mapped to it, and this map stores
# a schedule for each request ID.
queue = {}
# Tracks the actual function objects that are pinned to this executor.
function_cache = {}
# Tracks runtime cost of excuting a DAG function.
runtimes = {}
# If multiple triggers are necessary for a function, track the triggers as
# we receive them. This is also used if a trigger arrives before its
# corresponding schedule.
received_triggers = {}
# Tracks when we received a function request, so we can report end-to-end
# latency for the whole executio.
receive_times = {}
# Tracks the number of requests we are finishing for each function pinned
# here.
exec_counts = {}
# Tracks the end-to-end runtime of each DAG request for which we are the
# sink function.
dag_runtimes = {}
# A map with KVS keys and their corresponding deserialized payloads.
cache = {}
# A map which tracks the most recent DAGs for which we have finished our
# work.
finished_executions = {}
# The set of pinned functions and whether they support batching. NOTE: This
# is only a set for local mode -- in cluster mode, there will only be one
# pinned function per executor.
batching = False
# Internal metadata to track thread utilization.
report_start = time.time()
event_occupancy = {
'pin': 0.0,
'unpin': 0.0,
'func_exec': 0.0,
'dag_queue': 0.0,
'dag_exec': 0.0
}
total_occupancy = 0.0
while True:
socks = dict(poller.poll(timeout=1000))
if pin_socket in socks and socks[pin_socket] == zmq.POLLIN:
work_start = time.time()
batching = pin(pin_socket, pusher_cache, client, status,
function_cache, runtimes, exec_counts, user_library,
local, batching)
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['pin'] += elapsed
total_occupancy += elapsed
if unpin_socket in socks and socks[unpin_socket] == zmq.POLLIN:
work_start = time.time()
unpin(unpin_socket, status, function_cache, runtimes, exec_counts)
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['unpin'] += elapsed
total_occupancy += elapsed
if exec_socket in socks and socks[exec_socket] == zmq.POLLIN:
work_start = time.time()
# logging.info(f'Executor timer. exec_socket recv: {work_start}')
exec_function(exec_socket,
client,
user_library,
cache,
function_cache,
has_ephe=has_ephe)
user_library.close()
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['func_exec'] += elapsed
total_occupancy += elapsed
if dag_queue_socket in socks and socks[dag_queue_socket] == zmq.POLLIN:
work_start = time.time()
logging.info(
f'Executor timer. dag_queue_socket recv: {work_start}')
# In order to effectively support batching, we have to make sure we
# dequeue lots of schedules in addition to lots of triggers. Right
# now, we're not going to worry about supporting batching here,
# just on the trigger dequeue side, but we still have to dequeue
# all schedules we've received. We just process them one at a time.
while True:
schedule = DagSchedule()
try:
msg = dag_queue_socket.recv(zmq.DONTWAIT)
except zmq.ZMQError as e:
if e.errno == zmq.EAGAIN:
break # There are no more messages.
else:
raise e # Unexpected error.
schedule.ParseFromString(msg)
fname = schedule.target_function
logging.info(
'Received a schedule for DAG %s (%s), function %s.' %
(schedule.dag.name, schedule.id, fname))
if fname not in queue:
queue[fname] = {}
queue[fname][schedule.id] = schedule
if (schedule.id, fname) not in receive_times:
receive_times[(schedule.id, fname)] = time.time()
# In case we receive the trigger before we receive the schedule, we
# can trigger from this operation as well.
trkey = (schedule.id, fname)
fref = None
# Check to see what type of execution this function is.
for ref in schedule.dag.functions:
if ref.name == fname:
fref = ref
if (trkey in received_triggers and
((len(received_triggers[trkey]) == len(schedule.triggers))
or (fref.type == MULTIEXEC))):
triggers = list(received_triggers[trkey].values())
if fname not in function_cache:
logging.error('%s not in function cache', fname)
utils.generate_error_response(schedule, client, fname)
continue
exec_start = time.time()
# logging.info(f'Executor timer. dag_queue_socket exec_dag: {exec_start}')
# We don't support actual batching for when we receive a
# schedule before a trigger, so everything is just a batch of
# size 1 if anything.
success = exec_dag_function(pusher_cache, client,
[triggers],
function_cache[fname],
[schedule], user_library,
dag_runtimes, cache,
schedulers, batching)[0]
user_library.close()
del received_triggers[trkey]
if success:
del queue[fname][schedule.id]
fend = time.time()
fstart = receive_times[(schedule.id, fname)]
runtimes[fname].append(fend - work_start)
exec_counts[fname] += 1
finished_executions[(schedule.id, fname)] = time.time()
elapsed = time.time() - work_start
event_occupancy['dag_queue'] += elapsed
total_occupancy += elapsed
if dag_exec_socket in socks and socks[dag_exec_socket] == zmq.POLLIN:
work_start = time.time()
# logging.info(f'Executor timer. dag_exec_socket recv: {work_start}')
# How many messages to dequeue -- BATCH_SIZE_MAX or 1 depending on
# the function configuration.
if batching:
count = BATCH_SIZE_MAX
else:
count = 1
trigger_keys = set()
for _ in range(count): # Dequeue count number of messages.
trigger = DagTrigger()
try:
msg = dag_exec_socket.recv(zmq.DONTWAIT)
except zmq.ZMQError as e:
if e.errno == zmq.EAGAIN: # There are no more messages.
break
else:
raise e # Unexpected error.
trigger.ParseFromString(msg)
# We have received a repeated trigger for a function that has
# already finished executing.
if trigger.id in finished_executions:
continue
fname = trigger.target_function
logging.info(
'Received a trigger for schedule %s, function %s.' %
(trigger.id, fname))
key = (trigger.id, fname)
trigger_keys.add(key)
if key not in received_triggers:
received_triggers[key] = {}
if (trigger.id, fname) not in receive_times:
receive_times[(trigger.id, fname)] = time.time()
received_triggers[key][trigger.source] = trigger
# Only execute the functions for which we have received a schedule.
# Everything else will wait.
for tid, fname in list(trigger_keys):
if fname not in queue or tid not in queue[fname]:
trigger_keys.remove((tid, fname))
if len(trigger_keys) == 0:
continue
fref = None
schedule = queue[fname][list(trigger_keys)[0]
[0]] # Pick a random schedule to check.
# Check to see what type of execution this function is.
for ref in schedule.dag.functions:
if ref.name == fname:
fref = ref
break
# Compile a list of all the trigger sets for which we have
# enough triggers.
trigger_sets = []
schedules = []
for key in trigger_keys:
if (len(received_triggers[key]) == len(schedule.triggers)) or \
fref.type == MULTIEXEC:
if fref.type == MULTIEXEC:
triggers = [trigger]
else:
triggers = list(received_triggers[key].values())
if fname not in function_cache:
logging.error('%s not in function cache', fname)
utils.generate_error_response(schedule, client, fname)
continue
trigger_sets.append(triggers)
schedule = queue[fname][key[0]]
schedules.append(schedule)
exec_start = time.time()
# logging.info(f'Executor timer. dag_exec_socket exec_dag: {exec_start}')
# Pass all of the trigger_sets into exec_dag_function at once.
# We also include the batching variaible to make sure we know
# whether to pass lists into the fn or not.
if len(trigger_sets) > 0:
successes = exec_dag_function(pusher_cache, client,
trigger_sets,
function_cache[fname], schedules,
user_library, dag_runtimes,
cache, schedulers, batching)
user_library.close()
del received_triggers[key]
for key, success in zip(trigger_keys, successes):
if success:
del queue[fname][key[0]] # key[0] is trigger.id.
fend = time.time()
fstart = receive_times[key]
average_time = (fend - work_start) / len(trigger_keys)
runtimes[fname].append(average_time)
exec_counts[fname] += 1
finished_executions[(schedule.id, fname)] = time.time()
elapsed = time.time() - work_start
event_occupancy['dag_exec'] += elapsed
total_occupancy += elapsed
if self_depart_socket in socks and socks[self_depart_socket] == \
zmq.POLLIN:
# This message does not matter.
self_depart_socket.recv()
logging.info('Preparing to depart. No longer accepting requests ' +
'and clearing all queues.')
status.ClearField('functions')
status.running = False
utils.push_status(schedulers, pusher_cache, status)
departing = True
# periodically report function occupancy
report_end = time.time()
if report_end - report_start > REPORT_THRESH:
if len(cache) > 100:
extra_keys = list(cache.keys())[:len(cache) - 100]
for key in extra_keys:
del cache[key]
utilization = total_occupancy / (report_end - report_start)
status.utilization = utilization
# Periodically report my status to schedulers with the utilization
# set.
utils.push_status(schedulers, pusher_cache, status)
logging.debug('Total thread occupancy: %.6f' % (utilization))
for event in event_occupancy:
occ = event_occupancy[event] / (report_end - report_start)
logging.debug('\tEvent %s occupancy: %.6f' % (event, occ))
event_occupancy[event] = 0.0
stats = ExecutorStatistics()
for fname in runtimes:
if exec_counts[fname] > 0:
fstats = stats.functions.add()
fstats.name = fname
fstats.call_count = exec_counts[fname]
fstats.runtime.extend(runtimes[fname])
runtimes[fname].clear()
exec_counts[fname] = 0
for dname in dag_runtimes:
dstats = stats.dags.add()
dstats.name = dname
dstats.runtimes.extend(dag_runtimes[dname])
dag_runtimes[dname].clear()
# If we are running in cluster mode, mgmt_ip will be set, and we
# will report our status and statistics to it. Otherwise, we will
# write to the local conf file
if mgmt_ip:
sckt = pusher_cache.get(
sutils.get_statistics_report_address(mgmt_ip))
sckt.send(stats.SerializeToString())
sckt = pusher_cache.get(utils.get_util_report_address(mgmt_ip))
sckt.send(status.SerializeToString())
else:
logging.info(stats)
status.ClearField('utilization')
report_start = time.time()
total_occupancy = 0.0
# Periodically clear any old functions we have cached that we are
# no longer accepting requests for.
del_list = []
for fname in queue:
if len(queue[fname]) == 0 and fname not in status.functions:
del_list.append(fname)
del function_cache[fname]
del runtimes[fname]
del exec_counts[fname]
for fname in del_list:
del queue[fname]
del_list = []
for tid in finished_executions:
if (time.time() - finished_executions[tid]) > 10:
del_list.append(tid)
for tid in del_list:
del finished_executions[tid]
# If we are departing and have cleared our queues, let the
# management server know, and exit the process.
if departing and len(queue) == 0:
sckt = pusher_cache.get(utils.get_depart_done_addr(mgmt_ip))
sckt.send_string(ip)
# We specifically pass 1 as the exit code when ending our
# process so that the wrapper script does not restart us.
sys.exit(1)
def scheduler(ip, mgmt_ip, route_addr):
# If the management IP is not set, we are running in local mode.
local = (mgmt_ip is None)
kvs = AnnaTcpClient(route_addr, ip, local=local)
scheduler_id = str(uuid.uuid4())
context = zmq.Context(1)
# A mapping from a DAG's name to its protobuf representation.
dags = {}
# Tracks how often a request for each function is received.
call_frequency = {}
# Tracks the time interval between successive requests for a particular
# DAG.
interarrivals = {}
# Tracks the most recent arrival for each DAG -- used to calculate
# interarrival times.
last_arrivals = {}
# Maintains a list of all other schedulers in the system, so we can
# propagate metadata to them.
schedulers = []
connect_socket = context.socket(zmq.REP)
connect_socket.bind(sutils.BIND_ADDR_TEMPLATE % (CONNECT_PORT))
func_create_socket = context.socket(zmq.REP)
func_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CREATE_PORT))
func_call_socket = context.socket(zmq.REP)
func_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CALL_PORT))
dag_create_socket = context.socket(zmq.REP)
dag_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CREATE_PORT))
dag_call_socket = context.socket(zmq.REP)
dag_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CALL_PORT))
dag_delete_socket = context.socket(zmq.REP)
dag_delete_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_DELETE_PORT))
list_socket = context.socket(zmq.REP)
list_socket.bind(sutils.BIND_ADDR_TEMPLATE % (LIST_PORT))
exec_status_socket = context.socket(zmq.PULL)
exec_status_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.STATUS_PORT))
sched_update_socket = context.socket(zmq.PULL)
sched_update_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SCHED_UPDATE_PORT))
pin_accept_socket = context.socket(zmq.PULL)
pin_accept_socket.setsockopt(zmq.RCVTIMEO, 500)
pin_accept_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.PIN_ACCEPT_PORT))
requestor_cache = SocketCache(context, zmq.REQ)
pusher_cache = SocketCache(context, zmq.PUSH)
poller = zmq.Poller()
poller.register(connect_socket, zmq.POLLIN)
poller.register(func_create_socket, zmq.POLLIN)
poller.register(func_call_socket, zmq.POLLIN)
poller.register(dag_create_socket, zmq.POLLIN)
poller.register(dag_call_socket, zmq.POLLIN)
poller.register(dag_delete_socket, zmq.POLLIN)
poller.register(list_socket, zmq.POLLIN)
poller.register(exec_status_socket, zmq.POLLIN)
poller.register(sched_update_socket, zmq.POLLIN)
# Start the policy engine.
policy = DefaultCloudburstSchedulerPolicy(pin_accept_socket,
pusher_cache,
kvs,
ip,
local=local)
policy.update()
start = time.time()
while True:
socks = dict(poller.poll(timeout=1000))
if connect_socket in socks and socks[connect_socket] == zmq.POLLIN:
msg = connect_socket.recv_string()
connect_socket.send_string(route_addr)
if (func_create_socket in socks
and socks[func_create_socket] == zmq.POLLIN):
create_function(func_create_socket, kvs)
if func_call_socket in socks and socks[func_call_socket] == zmq.POLLIN:
call_function(func_call_socket, pusher_cache, policy)
if (dag_create_socket in socks
and socks[dag_create_socket] == zmq.POLLIN):
create_dag(dag_create_socket, pusher_cache, kvs, dags, policy,
call_frequency)
if dag_call_socket in socks and socks[dag_call_socket] == zmq.POLLIN:
call = DagCall()
call.ParseFromString(dag_call_socket.recv())
name = call.name
t = time.time()
if name in last_arrivals:
if name not in interarrivals:
interarrivals[name] = []
interarrivals[name].append(t - last_arrivals[name])
last_arrivals[name] = t
if name not in dags:
resp = GenericResponse()
resp.success = False
resp.error = NO_SUCH_DAG
dag_call_socket.send(resp.SerializeToString())
continue
dag = dags[name]
for fname in dag[0].functions:
call_frequency[fname.name] += 1
response = call_dag(call, pusher_cache, dags, policy)
dag_call_socket.send(response.SerializeToString())
if (dag_delete_socket in socks
and socks[dag_delete_socket] == zmq.POLLIN):
delete_dag(dag_delete_socket, dags, policy, call_frequency)
if list_socket in socks and socks[list_socket] == zmq.POLLIN:
msg = list_socket.recv_string()
prefix = msg if msg else ''
resp = StringSet()
resp.keys.extend(sched_utils.get_func_list(kvs, prefix))
list_socket.send(resp.SerializeToString())
if exec_status_socket in socks and socks[exec_status_socket] == \
zmq.POLLIN:
status = ThreadStatus()
status.ParseFromString(exec_status_socket.recv())
policy.process_status(status)
if sched_update_socket in socks and socks[sched_update_socket] == \
zmq.POLLIN:
status = SchedulerStatus()
status.ParseFromString(sched_update_socket.recv())
# Retrieve any DAGs that some other scheduler knows about that we
# do not yet know about.
for dname in status.dags:
if dname not in dags:
payload = kvs.get(dname)
while None in payload:
payload = kvs.get(dname)
dag = Dag()
dag.ParseFromString(payload[dname].reveal())
dags[dag.name] = (dag, sched_utils.find_dag_source(dag))
for fname in dag.functions:
if fname not in call_frequency:
call_frequency[fname] = 0
policy.update_function_locations(status.function_locations)
end = time.time()
if end - start > METADATA_THRESHOLD:
# Update the scheduler policy-related metadata.
policy.update()
# If the management IP is None, that means we arre running in
# local mode, so there is no need to deal with caches and other
# schedulers.
if mgmt_ip:
schedulers = sched_utils.get_ip_set(
sched_utils.get_scheduler_list_address(mgmt_ip),
requestor_cache, False)
if end - start > REPORT_THRESHOLD:
num_unique_executors = policy.get_unique_executors()
key = scheduler_id + ':' + str(time.time())
data = {'key': key, 'count': num_unique_executors}
status = SchedulerStatus()
for name in dags.keys():
status.dags.append(name)
for fname in policy.function_locations:
for loc in policy.function_locations[fname]:
floc = status.function_locations.add()
floc.name = fname
floc.ip = loc[0]
floc.tid = loc[1]
msg = status.SerializeToString()
for sched_ip in schedulers:
if sched_ip != ip:
sckt = pusher_cache.get(
sched_utils.get_scheduler_update_address(sched_ip))
sckt.send(msg)
stats = ExecutorStatistics()
for fname in call_frequency:
fstats = stats.functions.add()
fstats.name = fname
fstats.call_count = call_frequency[fname]
logging.info('Reporting %d calls for function %s.' %
(call_frequency[fname], fname))
call_frequency[fname] = 0
for dname in interarrivals:
dstats = stats.dags.add()
dstats.name = dname
dstats.call_count = len(interarrivals[dname]) + 1
dstats.interarrival.extend(interarrivals[dname])
interarrivals[dname].clear()
# We only attempt to send the statistics if we are running in
# cluster mode. If we are running in local mode, we write them to
# the local log file.
if mgmt_ip:
sckt = pusher_cache.get(
sutils.get_statistics_report_address(mgmt_ip))
sckt.send(stats.SerializeToString())
start = time.time()
class FluentUserLibrary(AbstractFluentUserLibrary):
# ip: Executor IP.
# tid: Executor thread ID.
# anna_client: The Anna client, used for interfacing with the kvs.
def __init__(self, ip, tid, anna_client):
self.ctx = zmq.Context()
self.send_socket_cache = SocketCache(self.ctx, zmq.PUSH)
self.executor_ip = ip
self.executor_tid = tid
self.client = anna_client
# Threadsafe queue to serve as this node's inbox.
# Items are (sender string, message bytestring).
# NB: currently unbounded in size.
self.recv_inbox = queue.Queue()
# Thread for receiving messages into our inbox.
self.recv_inbox_thread = threading.Thread(
target=self._recv_inbox_listener)
self.recv_inbox_thread.do_run = True
self.recv_inbox_thread.start()
def put(self, ref, ltc):
return self.client.put(ref, ltc)
def get(self, ref):
if type(ref) == list:
return self.client.get(ref)
return self.client.get(ref)[ref]
def getid(self):
return (self.executor_ip, self.executor_tid)
# dest is currently (IP string, thread id int) of destination executor.
def send(self, dest, bytestr):
ip, tid = dest
dest_addr = server_utils._get_user_msg_inbox_addr(ip, tid)
sender = (self.executor_ip, self.executor_tid)
socket = self.send_socket_cache.get(dest_addr)
socket.send_pyobj((sender, bytestr))
def close(self):
self.recv_inbox_thread.do_run = False
self.recv_inbox_thread.join()
def recv(self):
res = []
while True:
try:
(sender, msg) = self.recv_inbox.get(block=False)
res.append((sender, msg))
except queue.Empty:
break
return res
# Function that continuously listens for send()s sent by other nodes,
# and stores the messages in an inbox.
def _recv_inbox_listener(self):
# Socket for receiving send() messages from other nodes.
recv_inbox_socket = self.ctx.socket(zmq.PULL)
recv_inbox_socket.bind(server_utils.BIND_ADDR_TEMPLATE %
(server_utils.RECV_INBOX_PORT +
self.executor_tid))
t = threading.currentThread()
while t.do_run:
try:
(sender, msg) = recv_inbox_socket.recv_pyobj(zmq.NOBLOCK)
self.recv_inbox.put((sender, msg))
except zmq.ZMQError as e:
if e.errno == zmq.EAGAIN:
continue
else:
raise e
time.sleep(.010)
recv_inbox_socket.close()
def run(self_ip):
context = zmq.Context(1)
pusher_cache = SocketCache(context, zmq.PUSH)
restart_pull_socket = context.socket(zmq.REP)
restart_pull_socket.bind('tcp://*:7000')
churn_pull_socket = context.socket(zmq.PULL)
churn_pull_socket.bind('tcp://*:7001')
list_executors_socket = context.socket(zmq.PULL)
list_executors_socket.bind('tcp://*:7002')
function_status_socket = context.socket(zmq.PULL)
function_status_socket.bind('tcp://*:7003')
list_schedulers_socket = context.socket(zmq.REP)
list_schedulers_socket.bind('tcp://*:7004')
executor_depart_socket = context.socket(zmq.PULL)
executor_depart_socket.bind('tcp://*:7005')
statistics_socket = context.socket(zmq.PULL)
statistics_socket.bind('tcp://*:7006')
pin_accept_socket = context.socket(zmq.PULL)
pin_accept_socket.setsockopt(zmq.RCVTIMEO, 10000) # 10 seconds.
pin_accept_socket.bind('tcp://*:' + PIN_ACCEPT_PORT)
poller = zmq.Poller()
poller.register(restart_pull_socket, zmq.POLLIN)
poller.register(churn_pull_socket, zmq.POLLIN)
poller.register(function_status_socket, zmq.POLLIN)
poller.register(list_executors_socket, zmq.POLLIN)
poller.register(list_schedulers_socket, zmq.POLLIN)
poller.register(executor_depart_socket, zmq.POLLIN)
poller.register(statistics_socket, zmq.POLLIN)
add_push_socket = context.socket(zmq.PUSH)
add_push_socket.connect('ipc:///tmp/node_add')
remove_push_socket = context.socket(zmq.PUSH)
remove_push_socket.connect('ipc:///tmp/node_remove')
client, _ = util.init_k8s()
scaler = DefaultScaler(self_ip, context, add_push_socket, remove_push_socket, pin_accept_socket)
policy = DefaultHydroPolicy(scaler)
# Tracks the self-reported statuses of each executor thread in the system.
executor_statuses = {}
# Tracks of which executors are departing. This is used to ensure all
# threads acknowledge that they are finished before we remove a thread from
# the system.
departing_executors = {}
# Tracks how often each function is called.
function_frequencies = {}
# Tracks the aggregated runtime for each function.
function_runtimes = {}
# Tracks the arrival times of DAG requests.
arrival_times = {}
# Tracks how often each DAG is called.
dag_frequencies = {}
# Tracks how long each DAG request spends in the system, end to end.
dag_runtimes = {}
start = time.time()
while True:
socks = dict(poller.poll(timeout=1000))
if (churn_pull_socket in socks and socks[churn_pull_socket] ==
zmq.POLLIN):
msg = churn_pull_socket.recv_string()
args = msg.split(':')
if args[0] == 'add':
scaler.add_vms(args[2], args[1])
elif args[0] == 'remove':
scaler.remove_vms(args[2], args[1])
if (restart_pull_socket in socks and socks[restart_pull_socket] ==
zmq.POLLIN):
msg = restart_pull_socket.recv_string()
args = msg.split(':')
pod = util.get_pod_from_ip(client, args[1])
count = str(pod.status.container_statuses[0].restart_count)
restart_pull_socket.send_string(count)
if (list_executors_socket in socks and socks[list_executors_socket] ==
zmq.POLLIN):
# We can safely ignore this message's contents, and the response
# does not depend on it.
response_ip = list_executors_socket.recv_string()
ips = StringSet()
for ip in util.get_pod_ips(client, 'role=function'):
ips.keys.append(ip)
for ip in util.get_pod_ips(client, 'role=gpu'):
ips.keys.append(ip)
sckt = pusher_cache.get(response_ip)
sckt.send(ips.SerializeToString())
if (function_status_socket in socks and
socks[function_status_socket] == zmq.POLLIN):
# Dequeue all available ThreadStatus messages rather than doing
# them one at a time---this prevents starvation if other operations
# (e.g., pin) take a long time.
while True:
status = ThreadStatus()
try:
status.ParseFromString(function_status_socket.recv(zmq.DONTWAIT))
except:
break # We've run out of messages.
key = (status.ip, status.tid)
# If this executor is one of the ones that's currently departing,
# we can just ignore its status updates since we don't want
# utilization to be skewed downwards. The reason we might still
# receive this message is because the depart message may not have
# arrived when this was sent.
if key[0] in departing_executors:
continue
executor_statuses[key] = status
# logging.info(('Received thread status update from %s:%d: %.4f ' +
# 'occupancy, %d functions pinned') %
# (status.ip, status.tid, status.utilization,
# len(status.functions)))
logging.info(f"Functions {status.functions} is placed on node "
f"{status.ip}:{status.tid}")
if (list_schedulers_socket in socks and
socks[list_schedulers_socket] == zmq.POLLIN):
# We can safely ignore this message's contents, and the response
# does not depend on it.
list_schedulers_socket.recv_string()
ips = StringSet()
for ip in util.get_pod_ips(client, 'role=scheduler'):
ips.keys.append(ip)
list_schedulers_socket.send(ips.SerializeToString())
if (executor_depart_socket in socks and
socks[executor_depart_socket] == zmq.POLLIN):
ip = executor_depart_socket.recv_string()
departing_executors[ip] -= 1
# We wait until all the threads at this executor have acknowledged
# that they are ready to leave, and we then remove the VM from the
# system.
if departing_executors[ip] == 0:
logging.info('Removing node with ip %s' % ip)
scaler.remove_vms('function', ip)
del departing_executors[ip]
if (statistics_socket in socks and
socks[statistics_socket] == zmq.POLLIN):
stats = ExecutorStatistics()
stats.ParseFromString(statistics_socket.recv())
# Aggregates statistics reported for individual functions including
# call frequencies, processed requests, and total runtimes.
for fstats in stats.functions:
fname = fstats.name
if fname not in function_frequencies:
function_frequencies[fname] = 0
if fname not in function_runtimes:
function_runtimes[fname] = (0.0, 0)
if fstats.runtime:
old_latency = function_runtimes[fname]
# This tracks how many calls were processed for the
# function and the length of the total runtime of all
# calls.
function_runtimes[fname] = (
old_latency[0] + sum(fstats.runtime),
old_latency[1] + fstats.call_count)
else:
# This tracks how many calls are made to the function.
function_frequencies[fname] += fstats.call_count
# Aggregates statistics for DAG requests, including call
# frequencies, arrival rates, and end-to-end runtimes.
for dstats in stats.dags:
dname = dstats.name
# Tracks the interarrival rates of requests to this function as
# perceived by the scheduler.
if dname not in arrival_times:
arrival_times[dname] = []
arrival_times[dname] += list(dstats.interarrival)
# Tracks how many calls to this DAG were received.
if dname not in dag_frequencies:
dag_frequencies[dname] = 0
dag_frequencies[dname] += dstats.call_count
# Tracks the end-to-end runtime of individual requests
# completed in the last epoch.
if dname not in dag_runtimes:
dag_runtimes[dname] = []
for rt in dstats.runtimes:
dag_runtimes[dname].append(rt)
end = time.time()
if end - start > REPORT_PERIOD:
logging.info('Checking hash ring...')
check_hash_ring(client, context)
# Invoke the configured policy to check system load and respond
# appropriately.
policy.replica_policy(function_frequencies, function_runtimes,
dag_runtimes, executor_statuses,
arrival_times)
# TODO(simon): this turn off node scaling policy, which is what we want for static exp env
# policy.executor_policy(executor_statuses, departing_executors)
# Clears all metadata that was passed in for this epoch.
function_runtimes.clear()
function_frequencies.clear()
dag_runtimes.clear()
arrival_times.clear()
# Restart the timer for the next reporting epoch.
start = time.time()
def executor(ip, mgmt_ip, schedulers, thread_id):
logging.basicConfig(filename='log_executor.txt',
level=logging.INFO,
format='%(asctime)s %(message)s')
ctx = zmq.Context(1)
poller = zmq.Poller()
pin_socket = ctx.socket(zmq.PULL)
pin_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.PIN_PORT + thread_id))
unpin_socket = ctx.socket(zmq.PULL)
unpin_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.UNPIN_PORT + thread_id))
exec_socket = ctx.socket(zmq.PULL)
exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.FUNC_EXEC_PORT + thread_id))
dag_queue_socket = ctx.socket(zmq.PULL)
dag_queue_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_QUEUE_PORT + thread_id))
dag_exec_socket = ctx.socket(zmq.PULL)
dag_exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_EXEC_PORT + thread_id))
self_depart_socket = ctx.socket(zmq.PULL)
self_depart_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SELF_DEPART_PORT + thread_id))
pusher_cache = SocketCache(ctx, zmq.PUSH)
poller = zmq.Poller()
poller.register(pin_socket, zmq.POLLIN)
poller.register(unpin_socket, zmq.POLLIN)
poller.register(exec_socket, zmq.POLLIN)
poller.register(dag_queue_socket, zmq.POLLIN)
poller.register(dag_exec_socket, zmq.POLLIN)
poller.register(self_depart_socket, zmq.POLLIN)
client = IpcAnnaClient(thread_id)
status = ThreadStatus()
status.ip = ip
status.tid = thread_id
status.running = True
utils._push_status(schedulers, pusher_cache, status)
departing = False
# this is going to be a map of map of maps for every function that we have
# pinnned, we will track a map of execution ids to DAG schedules
queue = {}
# track the actual function objects that we are storing here
pinned_functions = {}
# tracks runtime cost of excuting a DAG function
runtimes = {}
# if multiple triggers are necessary for a function, track the triggers as
# we receive them
received_triggers = {}
# track when we received a function request, so we can report e2e latency
receive_times = {}
# track how many functions we're executing
exec_counts = {}
# metadata to track thread utilization
report_start = time.time()
event_occupancy = {
'pin': 0.0,
'unpin': 0.0,
'func_exec': 0.0,
'dag_queue': 0.0,
'dag_exec': 0.0
}
total_occupancy = 0.0
while True:
socks = dict(poller.poll(timeout=1000))
if pin_socket in socks and socks[pin_socket] == zmq.POLLIN:
work_start = time.time()
pin(pin_socket, client, status, pinned_functions, runtimes,
exec_counts)
utils._push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['pin'] += elapsed
total_occupancy += elapsed
if unpin_socket in socks and socks[unpin_socket] == zmq.POLLIN:
work_start = time.time()
unpin(unpin_socket, status, pinned_functions, runtimes,
exec_counts)
utils._push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['unpin'] += elapsed
total_occupancy += elapsed
if exec_socket in socks and socks[exec_socket] == zmq.POLLIN:
work_start = time.time()
exec_function(exec_socket, client, status)
elapsed = time.time() - work_start
event_occupancy['func_exec'] += elapsed
total_occupancy += elapsed
if dag_queue_socket in socks and socks[dag_queue_socket] == zmq.POLLIN:
work_start = time.time()
schedule = DagSchedule()
schedule.ParseFromString(dag_queue_socket.recv())
fname = schedule.target_function
logging.info('Received a schedule for DAG %s (%s), function %s.' %
(schedule.dag.name, schedule.id, fname))
if fname not in queue:
queue[fname] = {}
queue[fname][schedule.id] = schedule
if (schedule.id, fname) not in receive_times:
receive_times[(schedule.id, fname)] = time.time()
# in case we receive the trigger before we receive the schedule, we
# can trigger from this operation as well
trkey = (schedule.id, fname)
if trkey in received_triggers and \
len(received_triggers[trkey]) == \
len(schedule.triggers):
exec_dag_function(pusher_cache, client,
received_triggers[trkey],
pinned_functions[fname], schedule)
del received_triggers[trkey]
del queue[fname][schedule.id]
fend = time.time()
fstart = receive_times[(schedule.id, fname)]
runtimes[fname] += fend - fstart
exec_counts[fname] += 1
elapsed = time.time() - work_start
event_occupancy['dag_queue'] += elapsed
total_occupancy += elapsed
if dag_exec_socket in socks and socks[dag_exec_socket] == zmq.POLLIN:
work_start = time.time()
trigger = DagTrigger()
trigger.ParseFromString(dag_exec_socket.recv())
fname = trigger.target_function
logging.info('Received a trigger for schedule %s, function %s.' %
(trigger.id, fname))
key = (trigger.id, fname)
if trigger.id not in received_triggers:
received_triggers[key] = {}
if (trigger.id, fname) not in receive_times:
receive_times[(trigger.id, fname)] = time.time()
received_triggers[key][trigger.source] = trigger
if fname in queue and trigger.id in queue[fname]:
schedule = queue[fname][trigger.id]
if len(received_triggers[key]) == len(schedule.triggers):
exec_dag_function(pusher_cache, client,
received_triggers[key],
pinned_functions[fname], schedule)
del received_triggers[key]
del queue[fname][trigger.id]
fend = time.time()
fstart = receive_times[(trigger.id, fname)]
runtimes[fname] += fend - fstart
exec_counts[fname] += 1
elapsed = time.time() - work_start
event_occupancy['dag_exec'] += elapsed
total_occupancy += elapsed
if self_depart_socket in socks and socks[self_depart_socket] == \
zmq.POLLIN:
# This message should not matter
msg = self_depart_socket.recv()
logging.info('Preparing to depart. No longer accepting requests ' +
'and clearing all queues.')
status.ClearField('functions')
status.running = False
utils._push_status(schedulers, pusher_cache, status)
departing = True
# periodically report function occupancy
report_end = time.time()
if report_end - report_start > REPORT_THRESH:
utilization = total_occupancy / (report_end - report_start)
status.utilization = utilization
sckt = pusher_cache.get(utils._get_util_report_address(mgmt_ip))
sckt.send(status.SerializeToString())
logging.info('Total thread occupancy: %.6f%%' % (utilization))
for event in event_occupancy:
occ = event_occupancy[event]
logging.info('Event %s occupancy: %.6f%%' % (event, occ))
event_occupancy[event] = 0.0
stats = ExecutorStatistics()
for fname in runtimes:
if exec_counts[fname] > 0:
fstats = stats.statistics.add()
fstats.fname = fname
fstats.runtime = runtimes[fname]
fstats.call_count = exec_counts[fname]
runtimes[fname] = 0.0
exec_counts[fname] = 0
sckt = pusher_cache.get(sutils._get_statistics_report_address \
(mgmt_ip))
sckt.send(stats.SerializeToString())
report_start = time.time()
total_occupancy = 0.0
# periodically clear any old functions we have cached that we are
# no longer accepting requests for
for fname in queue:
if len(queue[fname]) == 0 and fname not in status.functions:
del queue[fname]
del pinned_functions[fname]
del runtimes[fname]
del exec_counts[fname]
# if we are departing and have cleared our queues, let the
# management server know, and exit the process
if departing and len(queue) == 0:
sckt = pusher_cache.get(utils._get_depart_done_addr(mgmt_ip))
sckt.send_string(ip)
return 0
def executor(ip, mgmt_ip, schedulers, thread_id):
global_util = 0
logging.basicConfig(filename='log_executor.txt', level=logging.INFO)
ctx = zmq.Context(1)
poller = zmq.Poller()
pin_socket = ctx.socket(zmq.REP)
pin_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.PIN_PORT + thread_id))
unpin_socket = ctx.socket(zmq.REP)
unpin_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.UNPIN_PORT + thread_id))
exec_socket = ctx.socket(zmq.REP)
exec_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.FUNC_EXEC_PORT + thread_id))
dag_queue_socket = ctx.socket(zmq.REP)
dag_queue_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.DAG_QUEUE_PORT
+ thread_id))
dag_exec_socket = ctx.socket(zmq.PULL)
dag_exec_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.DAG_EXEC_PORT
+ thread_id))
self_depart_socket = ctx.socket(zmq.PULL)
self_depart_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.SELF_DEPART_PORT +
thread_id))
pusher_cache = SocketCache(ctx, zmq.PUSH)
poller = zmq.Poller()
poller.register(pin_socket, zmq.POLLIN)
poller.register(unpin_socket, zmq.POLLIN)
poller.register(exec_socket, zmq.POLLIN)
poller.register(dag_queue_socket, zmq.POLLIN)
poller.register(dag_exec_socket, zmq.POLLIN)
poller.register(self_depart_socket, zmq.POLLIN)
client = IpcAnnaClient()
status = ThreadStatus()
status.ip = ip
status.tid = thread_id
status.running = True
utils._push_status(schedulers, pusher_cache, status)
departing = False
# this is going to be a map of map of maps for every function that we have
# pinnned, we will track a map of execution ids to DAG schedules
queue = {}
# track the actual function objects that we are storing here
pinned_functions = {}
# tracks runtime cost of excuting a DAG function
runtimes = {}
# metadata to track thread utilization
report_start = time.time()
event_occupancy = { 'pin': 0.0, 'unpin': 0.0, 'func_exec': 0.0,
'dag_queue': 0.0, 'dag_exec': 0.0 }
total_occupancy = 0.0
while True:
socks = dict(poller.poll(timeout=1000))
if pin_socket in socks and socks[pin_socket] == zmq.POLLIN:
work_start = time.time()
pin(pin_socket, client, status, pinned_functions, runtimes)
utils._push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['pin'] += elapsed
total_occupancy += elapsed
if unpin_socket in socks and socks[unpin_socket] == zmq.POLLIN:
work_start = time.time()
unpin(unpin_socket, status, pinned_functions, runtimes)
utils._push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['unpin'] += elapsed
total_occupancy += elapsed
if exec_socket in socks and socks[exec_socket] == zmq.POLLIN:
work_start = time.time()
exec_function(exec_socket, client, status)
elapsed = time.time() - work_start
event_occupancy['func_exec'] += elapsed
total_occupancy += elapsed
if dag_queue_socket in socks and socks[dag_queue_socket] == zmq.POLLIN:
work_start = time.time()
schedule = DagSchedule()
schedule.ParseFromString(dag_queue_socket.recv())
fname = schedule.target_function
logging.info('Received a schedule for DAG %s, function %s.' %
(schedule.dag.name, fname))
# if we are trying to kill this node or unpin this function, we
# don't accept requests anymore for DAG schedules; this also checks
# to make sure it's the right IP for the target
if not status.running or (fname not in status.functions and \
fname in queue and \
schedule.id not in queue[fname].keys()) or \
schedule.locations[fname].split(':')[0] != ip:
sutils.error.error = INVALID_TARGET
dag_queue_socket.send(sutils.error.SerializeToString())
continue
if fname not in queue:
queue[fname] = {}
queue[fname][schedule.id] = schedule
dag_queue_socket.send(sutils.ok_resp)
elapsed = time.time() - work_start
event_occupancy['dag_queue'] += elapsed
total_occupancy += elapsed
if dag_exec_socket in socks and socks[dag_exec_socket] == zmq.POLLIN:
work_start = time.time()
trigger = DagTrigger()
trigger.ParseFromString(dag_exec_socket.recv())
fname = trigger.target_function
exec_dag_function(pusher_cache, client, trigger,
pinned_functions[fname], queue[fname][trigger.id])
elapsed = time.time() - work_start
event_occupancy['dag_exec'] += elapsed
total_occupancy += elapsed
runtimes[fname] += elapsed
if self_depart_socket in socks and socks[self_depart_socket] == \
zmq.POLLIN:
# This message should not matter
msg = self_depart_socket.recv()
logging.info('Preparing to depart. No longer accepting requests ' +
'and clearing all queues.')
status.ClearField('functions')
status.running = False
utils._push_status(schedulers, pusher_cache, status)
departing = True
# periodically report function occupancy
report_end = time.time()
if report_end - report_start > REPORT_THRESH:
utilization = total_occupancy / (report_end - report_start)
status.utilization = utilization
sckt = pusher_cache.get(utils._get_util_report_address(mgmt_ip))
sckt.send(status.SerializeToString())
logging.info('Total thread occupancy: %.4f%%' % (utilization))
for event in event_occupancy:
occ = event_occupancy[event]
logging.info('Event %s occupancy: %.4f%%' % (event, occ))
event_occupancy[event] = 0.0
stats = ExecutorStatistics()
for fname in runtimes:
fstats = stats.statistics.add()
fstats.fname = fname
fstats.runtime = runtimes[fname]
runtimes[fname] = 0.0
sckt = pusher_cache.get(sutils._get_statistics_report_address \
(mgmt_ip))
sckt.send(stats.SerializeToString())
report_start = time.time()
total_occupancy = 0.0
# periodically clear any old functions we have cached that we are
# no longer accepting requests for
for fname in queue:
if len(queue[fname]) == 0 and fname not in status.functions:
del queue[fname]
del pinned_functions[fname]
# if we are departing and have cleared our queues, let the
# management server know, and exit the process
if departing and len(queue) == 0:
sckt = pusher_cache.get(utils._get_depart_done_addr(mgmt_ip))
sckt.send_string(ip)
return 0
def executor(ip, mgmt_ip, schedulers, thread_id):
logging.basicConfig(filename='log_executor.txt',
level=logging.INFO,
format='%(asctime)s %(message)s')
context = zmq.Context(1)
poller = zmq.Poller()
pin_socket = context.socket(zmq.PULL)
pin_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.PIN_PORT + thread_id))
unpin_socket = context.socket(zmq.PULL)
unpin_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.UNPIN_PORT + thread_id))
exec_socket = context.socket(zmq.PULL)
exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.FUNC_EXEC_PORT + thread_id))
dag_queue_socket = context.socket(zmq.PULL)
dag_queue_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_QUEUE_PORT + thread_id))
dag_exec_socket = context.socket(zmq.PULL)
dag_exec_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.DAG_EXEC_PORT + thread_id))
self_depart_socket = context.socket(zmq.PULL)
self_depart_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SELF_DEPART_PORT + thread_id))
pusher_cache = SocketCache(context, zmq.PUSH)
poller = zmq.Poller()
poller.register(pin_socket, zmq.POLLIN)
poller.register(unpin_socket, zmq.POLLIN)
poller.register(exec_socket, zmq.POLLIN)
poller.register(dag_queue_socket, zmq.POLLIN)
poller.register(dag_exec_socket, zmq.POLLIN)
poller.register(self_depart_socket, zmq.POLLIN)
# If the management IP is set to None, that means that we are running in
# local mode, so we use a regular AnnaTcpClient rather than an IPC client.
if mgmt_ip:
client = AnnaIpcClient(thread_id, context)
else:
client = AnnaTcpClient('127.0.0.1', '127.0.0.1', local=True, offset=1)
user_library = CloudburstUserLibrary(context, pusher_cache, ip, thread_id,
client)
status = ThreadStatus()
status.ip = ip
status.tid = thread_id
status.running = True
utils.push_status(schedulers, pusher_cache, status)
departing = False
# Maintains a request queue for each function pinned on this executor. Each
# function will have a set of request IDs mapped to it, and this map stores
# a schedule for each request ID.
queue = {}
# Tracks the actual function objects that are pinned to this executor.
function_cache = {}
# Tracks runtime cost of excuting a DAG function.
runtimes = {}
# If multiple triggers are necessary for a function, track the triggers as
# we receive them. This is also used if a trigger arrives before its
# corresponding schedule.
received_triggers = {}
# Tracks when we received a function request, so we can report end-to-end
# latency for the whole executio.
receive_times = {}
# Tracks the number of requests we are finishing for each function pinned
# here.
exec_counts = {}
# Tracks the end-to-end runtime of each DAG request for which we are the
# sink function.
dag_runtimes = {}
# A map with KVS keys and their corresponding deserialized payloads.
cache = {}
# Internal metadata to track thread utilization.
report_start = time.time()
event_occupancy = {
'pin': 0.0,
'unpin': 0.0,
'func_exec': 0.0,
'dag_queue': 0.0,
'dag_exec': 0.0
}
total_occupancy = 0.0
while True:
socks = dict(poller.poll(timeout=1000))
if pin_socket in socks and socks[pin_socket] == zmq.POLLIN:
work_start = time.time()
pin(pin_socket, pusher_cache, client, status, function_cache,
runtimes, exec_counts, user_library)
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['pin'] += elapsed
total_occupancy += elapsed
if unpin_socket in socks and socks[unpin_socket] == zmq.POLLIN:
work_start = time.time()
unpin(unpin_socket, status, function_cache, runtimes, exec_counts)
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['unpin'] += elapsed
total_occupancy += elapsed
if exec_socket in socks and socks[exec_socket] == zmq.POLLIN:
work_start = time.time()
exec_function(exec_socket, client, user_library, cache,
function_cache)
user_library.close()
utils.push_status(schedulers, pusher_cache, status)
elapsed = time.time() - work_start
event_occupancy['func_exec'] += elapsed
total_occupancy += elapsed
if dag_queue_socket in socks and socks[dag_queue_socket] == zmq.POLLIN:
work_start = time.time()
schedule = DagSchedule()
schedule.ParseFromString(dag_queue_socket.recv())
fname = schedule.target_function
logging.info('Received a schedule for DAG %s (%s), function %s.' %
(schedule.dag.name, schedule.id, fname))
if fname not in queue:
queue[fname] = {}
queue[fname][schedule.id] = schedule
if (schedule.id, fname) not in receive_times:
receive_times[(schedule.id, fname)] = time.time()
# In case we receive the trigger before we receive the schedule, we
# can trigger from this operation as well.
trkey = (schedule.id, fname)
if (trkey in received_triggers and
(len(received_triggers[trkey]) == len(schedule.triggers))):
exec_dag_function(pusher_cache, client,
received_triggers[trkey],
function_cache[fname], schedule,
user_library, dag_runtimes, cache)
user_library.close()
del received_triggers[trkey]
del queue[fname][schedule.id]
fend = time.time()
fstart = receive_times[(schedule.id, fname)]
runtimes[fname].append(fend - fstart)
exec_counts[fname] += 1
elapsed = time.time() - work_start
event_occupancy['dag_queue'] += elapsed
total_occupancy += elapsed
if dag_exec_socket in socks and socks[dag_exec_socket] == zmq.POLLIN:
work_start = time.time()
trigger = DagTrigger()
trigger.ParseFromString(dag_exec_socket.recv())
fname = trigger.target_function
logging.info('Received a trigger for schedule %s, function %s.' %
(trigger.id, fname))
key = (trigger.id, fname)
if key not in received_triggers:
received_triggers[key] = {}
if (trigger.id, fname) not in receive_times:
receive_times[(trigger.id, fname)] = time.time()
received_triggers[key][trigger.source] = trigger
if fname in queue and trigger.id in queue[fname]:
schedule = queue[fname][trigger.id]
if len(received_triggers[key]) == len(schedule.triggers):
exec_dag_function(pusher_cache, client,
received_triggers[key],
function_cache[fname], schedule,
user_library, dag_runtimes, cache)
user_library.close()
del received_triggers[key]
del queue[fname][trigger.id]
fend = time.time()
fstart = receive_times[(trigger.id, fname)]
runtimes[fname].append(fend - fstart)
exec_counts[fname] += 1
elapsed = time.time() - work_start
event_occupancy['dag_exec'] += elapsed
total_occupancy += elapsed
if self_depart_socket in socks and socks[self_depart_socket] == \
zmq.POLLIN:
# This message does not matter.
self_depart_socket.recv()
logging.info('Preparing to depart. No longer accepting requests ' +
'and clearing all queues.')
status.ClearField('functions')
status.running = False
utils.push_status(schedulers, pusher_cache, status)
departing = True
# periodically report function occupancy
report_end = time.time()
if report_end - report_start > REPORT_THRESH:
cache.clear()
utilization = total_occupancy / (report_end - report_start)
status.utilization = utilization
# Periodically report my status to schedulers with the utilization
# set.
utils.push_status(schedulers, pusher_cache, status)
logging.info('Total thread occupancy: %.6f' % (utilization))
for event in event_occupancy:
occ = event_occupancy[event] / (report_end - report_start)
logging.info('\tEvent %s occupancy: %.6f' % (event, occ))
event_occupancy[event] = 0.0
stats = ExecutorStatistics()
for fname in runtimes:
if exec_counts[fname] > 0:
fstats = stats.functions.add()
fstats.name = fname
fstats.call_count = exec_counts[fname]
fstats.runtime.extend(runtimes[fname])
runtimes[fname].clear()
exec_counts[fname] = 0
for dname in dag_runtimes:
dstats = stats.dags.add()
dstats.name = dname
dstats.runtimes.extend(dag_runtimes[dname])
dag_runtimes[dname].clear()
# If we are running in cluster mode, mgmt_ip will be set, and we
# will report our status and statistics to it. Otherwise, we will
# write to the local conf file
if mgmt_ip:
sckt = pusher_cache.get(
sutils.get_statistics_report_address(mgmt_ip))
sckt.send(stats.SerializeToString())
sckt = pusher_cache.get(utils.get_util_report_address(mgmt_ip))
sckt.send(status.SerializeToString())
else:
logging.info(stats)
status.ClearField('utilization')
report_start = time.time()
total_occupancy = 0.0
# Periodically clear any old functions we have cached that we are
# no longer accepting requests for.
del_list = []
for fname in queue:
if len(queue[fname]) == 0 and fname not in status.functions:
del_list.append(fname)
del function_cache[fname]
del runtimes[fname]
del exec_counts[fname]
for fname in del_list:
del queue[fname]
# If we are departing and have cleared our queues, let the
# management server know, and exit the process.
if departing and len(queue) == 0:
sckt = pusher_cache.get(utils.get_depart_done_addr(mgmt_ip))
sckt.send_string(ip)
# We specifically pass 1 as the exit code when ending our
# process so that the wrapper script does not restart us.
os._exit(1)
def scheduler(ip, mgmt_ip, route_addr, policy_type):
# If the management IP is not set, we are running in local mode.
local = (mgmt_ip is None)
kvs = AnnaTcpClient(route_addr, ip, local=local)
scheduler_id = str(uuid.uuid4())
context = zmq.Context(1)
context.set(zmq.MAX_SOCKETS, 10000)
# A mapping from a DAG's name to its protobuf representation.
dags = {}
# Tracks how often a request for each function is received.
call_frequency = {}
# Tracks the time interval between successive requests for a particular
# DAG.
interarrivals = {}
# Tracks the most recent arrival for each DAG -- used to calculate
# interarrival times.
last_arrivals = {}
# Maintains a list of all other schedulers in the system, so we can
# propagate metadata to them.
schedulers = set()
connect_socket = context.socket(zmq.REP)
connect_socket.bind(sutils.BIND_ADDR_TEMPLATE % (CONNECT_PORT))
func_create_socket = context.socket(zmq.REP)
func_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CREATE_PORT))
func_call_socket = context.socket(zmq.REP)
func_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CALL_PORT))
# This is for handle the invocation from queue
# Mainly for storage event
func_call_queue_socket = context.socket(zmq.PULL)
func_call_queue_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(FUNC_CALL_QUEUE_PORT))
dag_create_socket = context.socket(zmq.REP)
dag_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CREATE_PORT))
dag_call_socket = context.socket(zmq.REP)
dag_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CALL_PORT))
dag_delete_socket = context.socket(zmq.REP)
dag_delete_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_DELETE_PORT))
list_socket = context.socket(zmq.REP)
list_socket.bind(sutils.BIND_ADDR_TEMPLATE % (LIST_PORT))
exec_status_socket = context.socket(zmq.PULL)
exec_status_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.STATUS_PORT))
sched_update_socket = context.socket(zmq.PULL)
sched_update_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SCHED_UPDATE_PORT))
pin_accept_socket = context.socket(zmq.PULL)
pin_accept_socket.setsockopt(zmq.RCVTIMEO, 10000) # 10 seconds.
pin_accept_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.PIN_ACCEPT_PORT))
continuation_socket = context.socket(zmq.PULL)
continuation_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.CONTINUATION_PORT))
if not local:
management_request_socket = context.socket(zmq.REQ)
management_request_socket.setsockopt(zmq.RCVTIMEO, 500)
# By setting this flag, zmq matches replies with requests.
management_request_socket.setsockopt(zmq.REQ_CORRELATE, 1)
# Relax strict alternation between request and reply.
# For detailed explanation, see here: http://api.zeromq.org/4-1:zmq-setsockopt
management_request_socket.setsockopt(zmq.REQ_RELAXED, 1)
management_request_socket.connect(
sched_utils.get_scheduler_list_address(mgmt_ip))
pusher_cache = SocketCache(context, zmq.PUSH)
poller = zmq.Poller()
poller.register(connect_socket, zmq.POLLIN)
poller.register(func_create_socket, zmq.POLLIN)
poller.register(func_call_socket, zmq.POLLIN)
poller.register(func_call_queue_socket, zmq.POLLIN)
poller.register(dag_create_socket, zmq.POLLIN)
poller.register(dag_call_socket, zmq.POLLIN)
poller.register(dag_delete_socket, zmq.POLLIN)
poller.register(list_socket, zmq.POLLIN)
poller.register(exec_status_socket, zmq.POLLIN)
poller.register(sched_update_socket, zmq.POLLIN)
poller.register(continuation_socket, zmq.POLLIN)
# Start the policy engine.
policy = DefaultCloudburstSchedulerPolicy(pin_accept_socket,
pusher_cache,
kvs,
ip,
policy_type,
local=local)
policy.update()
start = time.time()
while True:
socks = dict(poller.poll(timeout=1000))
if connect_socket in socks and socks[connect_socket] == zmq.POLLIN:
msg = connect_socket.recv_string()
connect_socket.send_string(route_addr)
if (func_create_socket in socks
and socks[func_create_socket] == zmq.POLLIN):
create_function(func_create_socket, kvs)
if func_call_socket in socks and socks[func_call_socket] == zmq.POLLIN:
call_function(func_call_socket, pusher_cache, policy)
if func_call_queue_socket in socks and socks[
func_call_queue_socket] == zmq.POLLIN:
call_function_from_queue(func_call_queue_socket, pusher_cache,
policy)
if (dag_create_socket in socks
and socks[dag_create_socket] == zmq.POLLIN):
create_dag(dag_create_socket, pusher_cache, kvs, dags, policy,
call_frequency)
if dag_call_socket in socks and socks[dag_call_socket] == zmq.POLLIN:
start_t = int(time.time() * 1000000)
call = DagCall()
call.ParseFromString(dag_call_socket.recv())
name = call.name
t = time.time()
if name in last_arrivals:
if name not in interarrivals:
interarrivals[name] = []
interarrivals[name].append(t - last_arrivals[name])
last_arrivals[name] = t
if name not in dags:
resp = GenericResponse()
resp.success = False
resp.error = NO_SUCH_DAG
dag_call_socket.send(resp.SerializeToString())
continue
dag = dags[name]
for fname in dag[0].functions:
call_frequency[fname.name] += 1
response = call_dag(call, pusher_cache, dags, policy)
sched_t = int(time.time() * 1000000)
logging.info(
f'App function {name} recv: {start_t}, scheduled: {sched_t}')
dag_call_socket.send(response.SerializeToString())
if (dag_delete_socket in socks
and socks[dag_delete_socket] == zmq.POLLIN):
delete_dag(dag_delete_socket, dags, policy, call_frequency)
if list_socket in socks and socks[list_socket] == zmq.POLLIN:
msg = list_socket.recv_string()
prefix = msg if msg else ''
resp = StringSet()
resp.keys.extend(sched_utils.get_func_list(kvs, prefix))
list_socket.send(resp.SerializeToString())
if exec_status_socket in socks and socks[exec_status_socket] == \
zmq.POLLIN:
status = ThreadStatus()
status.ParseFromString(exec_status_socket.recv())
policy.process_status(status)
if sched_update_socket in socks and socks[sched_update_socket] == \
zmq.POLLIN:
status = SchedulerStatus()
status.ParseFromString(sched_update_socket.recv())
# Retrieve any DAGs that some other scheduler knows about that we
# do not yet know about.
for dname in status.dags:
if dname not in dags:
payload = kvs.get(dname)
while None in payload:
payload = kvs.get(dname)
dag = Dag()
dag.ParseFromString(payload[dname].reveal())
dags[dag.name] = (dag, sched_utils.find_dag_source(dag))
for fname in dag.functions:
if fname.name not in call_frequency:
call_frequency[fname.name] = 0
policy.update_function_locations(status.function_locations)
if continuation_socket in socks and socks[continuation_socket] == \
zmq.POLLIN:
start_t = int(time.time() * 1000000)
continuation = Continuation()
continuation.ParseFromString(continuation_socket.recv())
call = continuation.call
call.name = continuation.name
result = Value()
result.ParseFromString(continuation.result)
dag, sources = dags[call.name]
for source in sources:
call.function_args[source].values.extend([result])
call_dag(call, pusher_cache, dags, policy, continuation.id)
sched_t = int(time.time() * 1000000)
print(
f'App function {call.name} recv: {start_t}, scheduled: {sched_t}'
)
for fname in dag.functions:
call_frequency[fname.name] += 1
end = time.time()
if end - start > METADATA_THRESHOLD:
# Update the scheduler policy-related metadata.
policy.update()
# If the management IP is None, that means we arre running in
# local mode, so there is no need to deal with caches and other
# schedulers.
if not local:
latest_schedulers = sched_utils.get_ip_set(
management_request_socket, False)
if latest_schedulers:
schedulers = latest_schedulers
if end - start > REPORT_THRESHOLD:
status = SchedulerStatus()
for name in dags.keys():
status.dags.append(name)
for fname in policy.function_locations:
for loc in policy.function_locations[fname]:
floc = status.function_locations.add()
floc.name = fname
floc.ip = loc[0]
floc.tid = loc[1]
msg = status.SerializeToString()
for sched_ip in schedulers:
if sched_ip != ip:
sckt = pusher_cache.get(
sched_utils.get_scheduler_update_address(sched_ip))
sckt.send(msg)
stats = ExecutorStatistics()
for fname in call_frequency:
fstats = stats.functions.add()
fstats.name = fname
fstats.call_count = call_frequency[fname]
logging.debug('Reporting %d calls for function %s.' %
(call_frequency[fname], fname))
call_frequency[fname] = 0
for dname in interarrivals:
dstats = stats.dags.add()
dstats.name = dname
dstats.call_count = len(interarrivals[dname]) + 1
dstats.interarrival.extend(interarrivals[dname])
interarrivals[dname].clear()
# We only attempt to send the statistics if we are running in
# cluster mode. If we are running in local mode, we write them to
# the local log file.
if mgmt_ip:
sckt = pusher_cache.get(
sutils.get_statistics_report_address(mgmt_ip))
sckt.send(stats.SerializeToString())
start = time.time()
def scheduler(ip, mgmt_ip, route_addr):
logging.basicConfig(filename='log_scheduler.txt', level=logging.INFO)
kvs = AnnaClient(route_addr, ip)
key_cache_map = {}
key_ip_map = {}
ctx = zmq.Context(1)
# Each dag consists of a set of functions and connections. Each one of
# the functions is pinned to one or more nodes, which is tracked here.
dags = {}
thread_statuses = {}
func_locations = {}
connect_socket = ctx.socket(zmq.REP)
connect_socket.bind(sutils.BIND_ADDR_TEMPLATE % (CONNECT_PORT))
func_create_socket = ctx.socket(zmq.REP)
func_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CREATE_PORT))
func_call_socket = ctx.socket(zmq.REP)
func_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (FUNC_CALL_PORT))
dag_create_socket = ctx.socket(zmq.REP)
dag_create_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CREATE_PORT))
dag_call_socket = ctx.socket(zmq.REP)
dag_call_socket.bind(sutils.BIND_ADDR_TEMPLATE % (DAG_CALL_PORT))
list_socket = ctx.socket(zmq.REP)
list_socket.bind(sutils.BIND_ADDR_TEMPLATE % (LIST_PORT))
exec_status_socket = ctx.socket(zmq.PULL)
exec_status_socket.bind(sutils.BIND_ADDR_TEMPLATE % (sutils.STATUS_PORT))
sched_update_socket = ctx.socket(zmq.PULL)
sched_update_socket.bind(sutils.BIND_ADDR_TEMPLATE %
(sutils.SCHED_UPDATE_PORT))
requestor_cache = SocketCache(ctx, zmq.REQ)
pusher_cache = SocketCache(ctx, zmq.PUSH)
poller = zmq.Poller()
poller.register(connect_socket, zmq.POLLIN)
poller.register(func_create_socket, zmq.POLLIN)
poller.register(func_call_socket, zmq.POLLIN)
poller.register(dag_create_socket, zmq.POLLIN)
poller.register(dag_call_socket, zmq.POLLIN)
poller.register(list_socket, zmq.POLLIN)
poller.register(exec_status_socket, zmq.POLLIN)
poller.register(sched_update_socket, zmq.POLLIN)
departed_executors = set()
executors, schedulers = _update_cluster_state(requestor_cache, mgmt_ip,
departed_executors,
key_cache_map, key_ip_map,
kvs)
# track how often each DAG function is called
call_frequency = {}
start = time.time()
while True:
socks = dict(poller.poll(timeout=1000))
if connect_socket in socks and socks[connect_socket] == zmq.POLLIN:
msg = connect_socket.recv_string()
connect_socket.send_string(routing_addr)
if func_create_socket in socks and socks[
func_create_socket] == zmq.POLLIN:
create_func(func_create_socket, kvs)
if func_call_socket in socks and socks[func_call_socket] == zmq.POLLIN:
call_function(func_call_socket, requestor_cache, executors,
key_ip_map)
if dag_create_socket in socks and socks[
dag_create_socket] == zmq.POLLIN:
create_dag(dag_create_socket, requestor_cache, kvs, executors,
dags, func_locations, call_frequency)
if dag_call_socket in socks and socks[dag_call_socket] == zmq.POLLIN:
call = DagCall()
call.ParseFromString(dag_call_socket.recv())
exec_id = generate_timestamp(0)
dag = dags[call.name]
for fname in dag[0].functions:
call_frequency[fname] += 1
accepted, error, rid = call_dag(call, requestor_cache,
pusher_cache, dags, func_locations,
key_ip_map)
while not accepted:
# the assumption here is that the request was not accepted
# because the cluster was out of date -- so we update cluster
# state before proceeding
executors, schedulers = _update_cluster_state(
requestor_cache, mgmt_ip, departed_executors,
key_cache_map, key_ip_map, kvs)
accepted, error, rid = call_dag(call, requestor_cache,
pusher_cache, dags,
func_locations, key_ip_map)
resp = GenericResponse()
resp.success = True
resp.response_id = rid
dag_call_socket.send(resp.SerializeToString())
if list_socket in socks and socks[list_socket] == zmq.POLLIN:
logging.info('Received query for function list.')
msg = list_socket.recv_string()
prefix = msg if msg else ''
resp = FunctionList()
resp.names.extend(utils._get_func_list(kvs, prefix))
list_socket.send(resp.SerializeToString())
if exec_status_socket in socks and socks[exec_status_socket] == \
zmq.POLLIN:
status = ThreadStatus()
status.ParseFromString(exec_status_socket.recv())
key = (status.ip, status.tid)
logging.info('Received status update from executor %s:%d.' %
(key[0], int(key[1])))
# this means that this node is currently departing, so we remove it
# from all of our metadata tracking
if not status.running:
old_status = thread_statuses[key]
executors.remove(key)
departed_executors.add(status.ip)
del thread_statuses[key]
for fname in old_status.functions:
func_locations[fname].remove(old_status.ip, old_status.tid)
continue
if key not in thread_statuses:
thread_statuses[key] = status
if key not in executors:
executors.add(key)
elif thread_statuses[key] != status:
# remove all the old function locations, and all the new ones
# -- there will probably be a large overlap, but this shouldn't
# be much different than calculating two different set
# differences anyway
for func in thread_statuses[key].functions:
if func in func_locations:
func_locations[func].discard(key)
for func in status.functions:
if func not in func_locations:
func_locations[func] = set()
func_locations[func].add(key)
thread_statuses[key] = status
if sched_update_socket in socks and socks[sched_update_socket] == \
zmq.POLLIN:
logging.info('Received update from another scheduler.')
ks = KeySet()
ks.ParseFromString(sched_update_socket.recv())
# retrieve any DAG that some other scheduler knows about that we do
# not yet know about
for dname in ks.keys:
if dname not in dags:
dag = Dag()
dag.ParseFromString(kvs.get(dname).value)
dags[dname] = dag
end = time.time()
if end - start > THRESHOLD:
executors, schedulers = _update_cluster_state(
requestor_cache, mgmt_ip, departed_executors, key_cache_map,
key_ip_map, kvs)
dag_names = KeySet()
for name in dags.keys():
dag_names.keys.append(name)
msg = dag_names.SerializeToString()
for sched_ip in schedulers:
if sched_ip != ip:
pusher_cache.get(
utils._get_scheduler_update_address(sched_ip))
sckt.send(msg)
stats = ExecutorStatistics()
for fname in call_frequency:
fstats = stats.statistics.add()
fstats.fname = fname
fstats.call_count = call_frequency[fname]
call_frequency[fname] = 0
sckt = pusher_cache.get(sutils._get_statistics_report_address \
(mgmt_ip))
sckt.send(stats.SerializeToString())
start = time.time()
