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85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
"""
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This file encapsulates a class that is intended to perform learning
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"""
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from __future__ import division
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import numpy as np
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from threading import Thread,RLock
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from utils.transport import *
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from utils.ml import AnomalyDetection,ML
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from utils.params import PARAMS
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import time
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"""
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This class is intended to apply anomaly detection to various areas of learning
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The areas of learning that will be skipped are :
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['_id','_rev','learn'] ...
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@TODO:
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- Find a way to perform dimensionality reduction if need be
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"""
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class Anomalies(Thread) :
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def __init__(self,lock):
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Thread.__init__(self)
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path = PARAMS['path']
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self.name = self.__class__.__name__.lower()
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if os.path.exists(path) :
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f = open(path)
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self.config = json.loads(f.read())
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f.close()
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#
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# Initializing data store & factory class
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#
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self.id = self.config['id']
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self.apps = self.config['procs'] if 'procs' in self.config else []
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self.rclass = self.config['store']['class']['read']
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self.wclass = self.config['store']['class']['write']
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self.rw_args = self.config['store']['args']
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self.factory = DataSourceFactory()
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self.quit = False
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self.lock = lock
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def format(self,stream):
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pass
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def stop(self):
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self.quit = True
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def run(self):
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DELAY = self.config['delay'] * 60
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reader = self.factory.instance(type=self.rclass,args=self.rw_args)
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data = reader.read()
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key = 'apps'
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rdata = data[key]
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features = ['memory_usage','cpu_usage']
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yo = {"1":["running"],"name":"status"}
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while self.quit == False :
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print ' *** ',self.name, ' ' , str(datetime.today())
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for app in self.apps:
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print '\t',app,str(datetime.today()),' ** ',app
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logs = ML.Filter('label',app,rdata)
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if logs :
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handler = AnomalyDetection()
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value = handler.learn(logs,'label',app,features,yo)
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if value is not None:
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value = dict(value,**{"features":features})
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value = dict({"id":self.id},**value)
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#r[id][app] = value
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self.lock.acquire()
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writer = self.factory.instance(type=self.wclass,args=self.rw_args)
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writer.write(label='learn',row=value)
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self.lock.release()
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#
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if 'MONITOR_CONFIG_PATH' in os.environ :
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break
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time.sleep(DELAY)
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print ' *** Exiting ',self.name.replace('a','A')
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class Regression(Thread):
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def __init__(self,params):
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pass
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if __name__ == '__main__' :
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lock = RLock()
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thread = Anomalies(lock)
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thread.start() |