def __init__(self, machineNames):
"""
constructor
"""
RandomSimulator.__init__(self, machineNames)
self.badMachines = ["machine1-3", "machine2-6", "machine2-7", "machine3-1"]
self.badNodeHealthDelta = { }
for name in self.deltaMap['health']:
self.badNodeHealthDelta[name] = self.deltaMap['health'][name]
self.badNodeMemoryDelta = numpy.random.normal(loc=0.02, scale=0.05, size=1000)
self.weightedMachineNamesList = deepcopy(self.machineNames)
for name in self.badMachines:
for i in xrange(0,3):
self.weightedMachineNamesList.append(name)
self.weightedSeverities = deepcopy(self.severities)
for i in xrange(0,4):
self.weightedSeverities.append("FATAL")
for i in xrange(0,3):
self.weightedSeverities.append("ERROR")
self.weightedFacilities = deepcopy(self.facilities)
for i in xrange(0,4):
self.weightedFacilities.append("KERNEL")
def __init__(self, machineNames):
"""
constructor
"""
self.lowCpuUsageDelta = numpy.random.normal(loc=-0.025, scale=0.05, size=1000)
self.highCpuUsageDelta = numpy.random.normal(loc=0.025, scale=0.05, size=1000)
RandomSimulator.__init__(self, machineNames)
def updates(self):
updates = RandomSimulator.updates(self)
updates['start'] = []
updates['end'] = []
for mapTask in self.map:
if mapTask['start'] == self.time:
updates['start'].append(mapTask)
self.addMachine(mapTask['name'])
elif mapTask['end'] == self.time:
updates['end'].append(mapTask)
self.removeMachine(mapTask['name'])
for reduceTask in self.reduce:
if reduceTask['start'] == self.time:
updates['start'].append(reduceTask)
self.addMachine(reduceTask['name'])
elif reduceTask['end'] == self.time:
updates['end'].append(reduceTask)
self.removeMachine(reduceTask['name'])
self.time += 1
return updates
def __init__(self, machineNames, taskName, time):
RandomSimulator.__init__(self, [])
self.taskName = taskName
numberOfMapJobs = 10
self.map = []
for i in xrange(0, numberOfMapJobs):
mapJob = {
'id': i,
'name': "%s%s%d" % (self.taskName, "-mapJob", i),
'start': time + 0,
'duration': int(numpy.random.normal(loc=60, scale=5)),
'location': getRandomElement(machineNames)
}
if mapJob['duration'] <= 0:
mapJob['duration'] = 1
mapJob['end'] = int(mapJob['start'] + mapJob['duration'])
self.map.append(mapJob)
numberOfReduceJobs = 10
self.reduce = []
for i in xrange(0, numberOfReduceJobs):
reduceJob = {
'id': numberOfMapJobs + i,
'name': "%s%s%d" % (self.taskName, "-reduceJob", i),
'start': time + int(numpy.random.normal(loc=60, scale=5)),
'duration': int(numpy.random.normal(loc=60, scale=5)),
'location': getRandomElement(machineNames)
}
if reduceJob['duration'] <= 0:
reduceJob['duration'] = 1
reduceJob['end'] = int(reduceJob['start'] + reduceJob['duration'])
self.reduce.append(reduceJob)
self.time = time
def randomizeProperty(self, nodeName, propertyName, associatedData=None):
"""
Randomizes a property for a given node, returning its new value
"""
# the following machines will have poor health
if nodeName in self.badMachines:
if propertyName == "health":
return normalizeValue(self.nodeState[nodeName][propertyName] + self.badNodeHealthDelta[associatedData['severity']])
elif propertyName == "memoryUsage":
return normalizeValue(self.nodeState[nodeName][propertyName] + getRandomElement(self.badNodeMemoryDelta))
if propertyName == "memoryUsage":
return normalizeValue(self.nodeState[nodeName][propertyName] + numpy.random.normal(loc=-0.025, scale=0.05))
return RandomSimulator.randomizeProperty(self, nodeName, propertyName, associatedData)
def randomizeProperty(self, nodeName, propertyName, associatedData=None):
"""
Randomizes a property for a given node, returning its new value
"""
# rack1 will have low CPU & memory utilization
if propertyName == "cpuUsage" and "machine1" in nodeName:
return normalizeValue(self.nodeState[nodeName][propertyName] + getRandomElement(self.lowCpuUsageDelta))
# rack3 will have high CPU utilization
elif propertyName == "cpuUsage" and "machine3" in nodeName:
return normalizeValue(self.nodeState[nodeName][propertyName] + getRandomElement(self.highCpuUsageDelta))
if propertyName == "contextSwitchRate":
return normalizeValue(self.nodeState[nodeName]["cpuUsage"] + numpy.random.normal(loc=0, scale=0.10))
else:
return RandomSimulator.randomizeProperty(self, nodeName, propertyName, associatedData)
