def getInitialScheme(self):
periodDB = shelve.open(periodRecoderFile)
periodDB[periodRecoder] = None
periodDB.close()
fiboDB = shelve.open(fiboDataFile)
fiboDB[fiboDataName] = None
fiboDB.close()
clearAllData()
PerformanceDBUtil.clearPerformanceDataTable()
WorkloadDBUtil.clearWorkloadTable()
uiCount = UsingInstancesDBUtil.getUsingInstancesCount()
if uiCount < initUsingInstancesNumbers:
TomcatInstanceUtil.resetAllUsingInstances()
self.acrcPlacementComponent.getPlacementScheme(
initUsingInstancesNumbers - uiCount, True)
elif uiCount > initUsingInstancesNumbers:
self.acrcPlacementComponent.getPlacementScheme(
uiCount - initUsingInstancesNumbers, False)
TomcatInstanceUtil.resetAllUsingInstances()
else:
TomcatInstanceUtil.resetAllUsingInstances()
def getNumberOfVMsShouldBeScaled(self):
if not self.predictor or not self.ruleChecker:
raise Exception('no predictor or ruleChecker')
newestHD = WorkloadDBUtil.getNewestWorkload()
if not newestHD:
raise Exception('Can not get newest workload')
addWLToACRCWindow(newestHD['realWL'])
predictWL = self.predictor.getNextPeriodWorkload()
addPWLToACRCWindow(predictWL)
#预测写入Workload表
periodNoDB = shelve.open(periodRecoderFile)
periodNo = periodNoDB.get(periodRecoder, None)
if not periodNo:
raise Exception('Can not get periodNo')
WorkloadDBUtil.addPredictWorkloadToSpecificPeriod(periodNo, predictWL)
#记录供给的虚拟机数目的分布
provisionInfoDB = shelve.open(provisionInfoFile)
#查询需要的VM
predictVMNumbers = WorkloadVMMapDBUtil.getTargetVMsToSpecificWorkload(predictWL)
provisionInfoDB[predictProvisionVMNumbers] = predictVMNumbers
logger.info('PredictWorkload:' + str(predictWL) + ' predictVMNumbers:' + str(predictVMNumbers))
addedVMNumbers = self.ruleChecker.getNextAddedVMs()
provisionInfoDB[reactiveProvisionVMNumbers] = addedVMNumbers
logger.info('addedVMNumbers:' + str(addedVMNumbers))
provisionInfoDB.close()
nextPeriodVMNumbers = predictVMNumbers + addedVMNumbers
usingInstancesCount = UsingInstancesDBUtil.getUsingInstancesCount()
gab = abs(usingInstancesCount - nextPeriodVMNumbers)
if usingInstancesCount > nextPeriodVMNumbers:
return {'vmNumbers':gab, 'isUp':False}
elif usingInstancesCount < nextPeriodVMNumbers:
return {'vmNumbers':gab, 'isUp':True}
else:
return {'vmNumbers':gab}
def getNumberOfVMsShouldBeScaled(self):
if not self.predictor or not self.ruleChecker:
raise Exception('no predictor or ruleChecker')
newestHD = WorkloadDBUtil.getNewestWorkload()
if not newestHD:
raise Exception('Can not get newest workload')
addWLToACRCWindow(newestHD['realWL'])
predictWL = self.predictor.getNextPeriodWorkload()
addPWLToACRCWindow(predictWL)
# 预测写入Workload表
periodNoDB = shelve.open(periodRecoderFile)
periodNo = periodNoDB.get(periodRecoder, None)
if not periodNo:
raise Exception('Can not get periodNo')
# do linear regression in given windowSize
# TODO: temporarily use default windowSize = sys.maxint
pairs = WorkloadDBUtil.getRealWorkloadAndRealTotalCalculationInPairs()
wl = pairs[0]
tc = pairs[1]
# TODO: do not fix the interception temporarily, might let the line cross the origin later
regression = np.polyfit(wl, tc, 1)
k = float(regression[0])
b = float(regression[1])
if k < 0 or wl.__len__() == 1:
# actually k should be positive, here to eliminate corner case when there's not much log
logger.warning("k = " + str(k) +
" is negative or length of log is 0!")
k = tc[-1] / wl[-1]
b = 0
logger.warning("using k = " + str(k) + " b = 0 instead")
predictVMNumbers = math.ceil(
k * predictWL /
(TomcatInstanceUtil.getCalculationCapacityPerInstance() - b))
predictTC = k * predictWL + predictVMNumbers * b
WorkloadDBUtil.addPredictWorkloadAndPredictTotalCalculationToSpecificPeriod(
periodNo, predictWL, predictTC)
# 记录供给的虚拟机数目的分布
provisionInfoDB = shelve.open(provisionInfoFile)
provisionInfoDB[predictProvisionVMNumbers] = predictVMNumbers
logger.info('PredictWorkload:' + str(predictWL) +
' predictVMNumbers:' + str(predictVMNumbers) +
' predictTC: ' + str(predictTC))
addedVMNumbers = self.ruleChecker.getNextAddedVMs()
provisionInfoDB[reactiveProvisionVMNumbers] = addedVMNumbers
logger.info('addedVMNumbers:' + str(addedVMNumbers))
provisionInfoDB.close()
nextPeriodVMNumbers = predictVMNumbers + addedVMNumbers
usingInstancesCount = UsingInstancesDBUtil.getUsingInstancesCount()
gab = abs(usingInstancesCount - nextPeriodVMNumbers)
if usingInstancesCount > nextPeriodVMNumbers:
rt = {'vmNumbers': gab, 'isUp': False}
elif usingInstancesCount < nextPeriodVMNumbers:
rt = {'vmNumbers': gab, 'isUp': True}
else:
rt = {'vmNumbers': gab}
logger.info('return with:' + str(rt))
return rt
#!/usr/bin/env python # encoding: utf-8 from DBUtil.PerformanceDBUtil import PerformanceDBUtil from DBUtil.WorkloadDBUtil import WorkloadDBUtil print WorkloadDBUtil.getAllWorkloadInfo() print PerformanceDBUtil.getPerformanceDataCount()
#!/usr/bin/env python
# encoding: utf-8
from DBUtil.PerformanceDBUtil import PerformanceDBUtil
from DBUtil.WorkloadDBUtil import WorkloadDBUtil
WorkloadDBUtil.clearWorkloadTable()
WorkloadDBUtil.addFirstPeriodRealWorkload(5000)
WorkloadDBUtil.addPredictWorkloadToSpecificPeriod(2, 300)
WorkloadDBUtil.addRealWorkloadToSpecificPeriod(2, 305)
print WorkloadDBUtil.getAllWorkloadInfo()
performanceData = {
'minResponseTime': 105.8,
'maxResponseTime': 13.2,
'avgResponseTime': 22.3,
'breakSLAPercent': 0.2,
'avgCpuUtil': 0.3,
'avgMemoryUtil': 0.6
}
PerformanceDBUtil.addPerformanceDataToSpecificPeriod(6, performanceData)
performanceData = {
'minResponseTime': 205.3,
'maxResponseTime': 13.2,
'avgResponseTime': 22.3,
'breakSLAPercent': 0.2,
'avgCpuUtil': 0.3,
'avgMemoryUtil': 0.6
}
PerformanceDBUtil.addPerformanceDataToSpecificPeriod(5, performanceData)
def periodPerformanceDataHandler2(self, req):
minResponseTime = req.params.get('minResponseTime')
avgResponseTime = req.params.get('avgResponseTime')
maxResponseTime = req.params.get('maxResponseTime')
totalRequestCount = req.params.get('totalRequestCount')
breakSLACount = req.params.get('breakSLACount')
jumpServer = req.params.get('jumpServer')
infos = SampleUtil.getThreadInfosOverAllUsingInstances(jumpServer)
avgCpuUtil = round(infos[0] / 100.0, 4)
totalCalculation = round(infos[1] / 100.0, 4)
avgMemoryUtil = round(SampleUtil.getAllUsingInstancesPeriodAVGMemoryUtil() / 100.0, 4)
if not (isDecimal(minResponseTime) or isNumber(minResponseTime)) \
or not (isDecimal(maxResponseTime) or isNumber(maxResponseTime)) \
or not (isDecimal(avgResponseTime) or isNumber(avgResponseTime)) \
or not isNumber(totalRequestCount) \
or not isNumber(breakSLACount):
return errorResultJson('Please pass the params correctly')
elif avgCpuUtil == None or avgMemoryUtil == None or totalCalculation == None:
raise Exception("can not get avgCpuUtil or avgMemoryUtil or totalCalculation data")
else:
minResponseTime = float(minResponseTime)
avgResponseTime = float(avgResponseTime)
maxResponseTime = float(maxResponseTime)
totalRequestCount = int(totalRequestCount)
breakSLACount = int(breakSLACount)
# 确认periodNo
periodNoDB = shelve.open(periodRecoderFile)
periodNo = periodNoDB.get(periodRecoder, None)
if not periodNo:
periodNo = 1
periodNoDB[periodRecoder] = periodNo + 1
periodNoDB.close()
# 计算breakSLAPercent
breakSLAPercent = float(breakSLACount) / totalRequestCount
breakSLAPercent = round(breakSLAPercent, 4)
# 计算刚刚过去的这个周期的可用性
placementTool = ACRCPlacementComponent()
availabilityData = placementTool.calculateAvailability()
# 得到刚刚过去这个周期的虚拟机数目
vmNumbers = UsingInstancesDBUtil.getUsingInstancesCount()
# 添加上个周期应该提供的虚拟机数目
shouldVMNumbers = WorkloadVMMapDBUtil.getTargetVMsToSpecificWorkload(totalRequestCount)
if periodNo == 1:
ppVMNumbers = vmNumbers
rpVMNumbers = 0
else:
provisionInfoDB = shelve.open(provisionInfoFile)
ppVMNumbers = provisionInfoDB.get(predictProvisionVMNumbers, None)
rpVMNumbers = provisionInfoDB.get(reactiveProvisionVMNumbers, None)
# 添加performanceData
performanceData = {'minResponseTime': minResponseTime, 'maxResponseTime': maxResponseTime,
'avgResponseTime': avgResponseTime, 'breakSLAPercent': breakSLAPercent,
'avgCpuUtil': avgCpuUtil, 'avgMemoryUtil': avgMemoryUtil,
'availability': availabilityData, 'vmNumbers': vmNumbers,
'shouldVMNumbers': shouldVMNumbers, 'predictProvisionVMNumbers': ppVMNumbers,
'reactiveProvisionVMNumbers': rpVMNumbers}
PerformanceDBUtil.addPerformanceDataToSpecificPeriod(periodNo, performanceData)
# 向数据库中添加workload信息
if periodNo == 1:
WorkloadDBUtil.addFirstPeriodRealWorkloadAndRealTotalCalculation(totalRequestCount, totalCalculation)
else:
WorkloadDBUtil.addRealWorkloadAndRealTotalCalculationToSpecificPeriod(periodNo, totalRequestCount,
totalCalculation)
acrCtl = ACRController()
acrCtl.autonomicPeriodHandler()
TomcatInstanceUtil.ensureAllUsingInstancesActive()
return UsingInstancesDBUtil.getAllUsingInstancesInfo()