def __init__(self, **kwargs):
super(ConsistencySimulation, self).__init__(**kwargs)
# Primary simulation variables.
self.users = kwargs.get('users', settings.simulation.users)
self.trace = kwargs.get('trace', None)
self.outages = kwargs.get('outages', None)
self.n_objects = kwargs.get('objects',
settings.simulation.max_objects_accessed)
self.replicas = []
self.network = Network()
def __init__(self, **kwargs):
super(ConsistencySimulation, self).__init__(**kwargs)
# Primary simulation variables.
self.users = kwargs.get("users", settings.simulation.users)
self.trace = kwargs.get("trace", None)
self.outages = kwargs.get("outages", None)
self.n_objects = kwargs.get("objects", settings.simulation.max_objects_accessed)
self.replicas = []
self.network = Network()
class ConsistencySimulation(Simulation):
@classmethod
def load(klass, fobj, **kwargs):
"""
Loads the simulation network from a JSON file containing the
simulation description and network graph.
"""
csim = klass(**kwargs)
if fobj is not None:
data = json.load(fobj)
# Add simulation meta information
csim.name = data['meta']['title']
csim.description = data['meta']['description']
csim.users = data['meta'].get('users', csim.users)
csim.results.settings.update(data['meta'])
# If the trace exists in the simulation meta, use it.
# Do not use the trace if it has been specified in the kwargs.
if csim.trace is None and 'trace' in data['meta']:
csim.trace = data['meta']['trace']
# If the outages exists in the simulation meta, use it.
# Do not use the outages if it has been specified in the kwargs.
if csim.outages is None and 'outages' in data['meta']:
csim.outages = data['meta']['outages']
# Add replicas to the simulation
for node in data['nodes']:
csim.replicas.append(replica_factory(csim, **node))
# Add edges to the network graph
for link in data['links']:
source = csim.replicas[link.pop('source')]
target = csim.replicas[link.pop('target')]
csim.network.add_connection(source, target, True, **link)
return csim
def __init__(self, **kwargs):
super(ConsistencySimulation, self).__init__(**kwargs)
# Primary simulation variables.
self.users = kwargs.get('users', settings.simulation.users)
self.trace = kwargs.get('trace', None)
self.outages = kwargs.get('outages', None)
self.n_objects = kwargs.get('objects',
settings.simulation.max_objects_accessed)
self.replicas = []
self.network = Network()
def complete(self):
"""
Ensure the topology is part of the results, as well as any configured
variables on that don't match the settings.
"""
# Log that the trace read is complete
if self.trace:
self.logger.info(
"access trace complete for {} accesses on {} objects".format(
self.workload.count,
len(self.workload.objects),
))
# Update the results with runtime settings and serialize the topo.
self.results.settings['users'] = self.users
self.results.topology = self.serialize()
# Compute Anti-Entropy
aedelays = map(float, [
node.ae_delay for node in filter(
lambda n: n.consistency == Consistency.EVENTUAL, self.replicas)
])
if aedelays:
self.results.settings['anti_entropy_delay'] = int(
sum(aedelays) / len(aedelays))
# Call consistency checker on all the replica logs
if settings.simulation.validate_consistency:
self.results.consistency.validate(self)
# Finialize logging and wrap up the simulation
super(ConsistencySimulation, self).complete()
def script(self):
# Create the workload that generates accesses as though they are users.
self.workload = create_workload(self,
trace=self.trace,
n_objects=self.n_objects,
users=self.users)
# Create the outages that generate partitions for realistic networks.
self.partitions = create_outages(self, outages=self.outages)
def dump(self, fobj, **kwargs):
"""
Write the simulation to disk as a D3 JSON Graph
"""
return json.dump(self, fobj, cls=JSONEncoder, **kwargs)
def serialize(self):
latency = self.network.get_latency_ranges()
network = self.network.serialize()
return {
'nodes': network['nodes'],
'links': network['links'],
'meta': {
'seed':
self.random_seed,
'title':
self.name,
'description':
getattr(self, 'description', None),
# Latency Labels
'constant':
'{}ms'.format(latency.get('constant', ('N/A ', None))[0]),
'variable':
'{}-{}ms'.format(*latency.get('variable', ('N/A', 'N/A'))),
},
}
class ConsistencySimulation(Simulation):
@classmethod
def load(klass, fobj, **kwargs):
"""
Loads the simulation network from a JSON file containing the
simulation description and network graph.
"""
csim = klass(**kwargs)
if fobj is not None:
data = json.load(fobj)
# Add simulation meta information
csim.name = data["meta"]["title"]
csim.description = data["meta"]["description"]
csim.users = data["meta"].get("users", csim.users)
csim.results.settings.update(data["meta"])
# If the trace exists in the simulation meta, use it.
# Do not use the trace if it has been specified in the kwargs.
if csim.trace is None and "trace" in data["meta"]:
csim.trace = data["meta"]["trace"]
# If the outages exists in the simulation meta, use it.
# Do not use the outages if it has been specified in the kwargs.
if csim.outages is None and "outages" in data["meta"]:
csim.outages = data["meta"]["outages"]
# Add replicas to the simulation
for node in data["nodes"]:
csim.replicas.append(replica_factory(csim, **node))
# Add edges to the network graph
for link in data["links"]:
source = csim.replicas[link.pop("source")]
target = csim.replicas[link.pop("target")]
csim.network.add_connection(source, target, True, **link)
return csim
def __init__(self, **kwargs):
super(ConsistencySimulation, self).__init__(**kwargs)
# Primary simulation variables.
self.users = kwargs.get("users", settings.simulation.users)
self.trace = kwargs.get("trace", None)
self.outages = kwargs.get("outages", None)
self.n_objects = kwargs.get("objects", settings.simulation.max_objects_accessed)
self.replicas = []
self.network = Network()
def complete(self):
"""
Ensure the topology is part of the results, as well as any configured
variables on that don't match the settings.
"""
# Log that the trace read is complete
if self.trace:
self.logger.info(
"access trace complete for {} accesses on {} objects".format(
self.workload.count, len(self.workload.objects)
)
)
# Update the results with runtime settings and serialize the topo.
self.results.settings["users"] = self.users
self.results.topology = self.serialize()
# Compute Anti-Entropy
aedelays = map(
float, [node.ae_delay for node in filter(lambda n: n.consistency == Consistency.EVENTUAL, self.replicas)]
)
if aedelays:
self.results.settings["anti_entropy_delay"] = int(sum(aedelays) / len(aedelays))
# Call consistency checker on all the replica logs
if settings.simulation.validate_consistency:
self.results.consistency.validate(self)
# Finialize logging and wrap up the simulation
super(ConsistencySimulation, self).complete()
def script(self):
# Create the workload that generates accesses as though they are users.
self.workload = create_workload(self, trace=self.trace, n_objects=self.n_objects, users=self.users)
# Create the outages that generate partitions for realistic networks.
self.partitions = create_outages(self, outages=self.outages)
def dump(self, fobj, **kwargs):
"""
Write the simulation to disk as a D3 JSON Graph
"""
return json.dump(self, fobj, cls=JSONEncoder, **kwargs)
def serialize(self):
latency = self.network.get_latency_ranges()
network = self.network.serialize()
return {
"nodes": network["nodes"],
"links": network["links"],
"meta": {
"seed": self.random_seed,
"title": self.name,
"description": getattr(self, "description", None),
# Latency Labels
"constant": "{}ms".format(latency.get("constant", ("N/A ", None))[0]),
"variable": "{}-{}ms".format(*latency.get("variable", ("N/A", "N/A"))),
},
}