python kafka consumer

be release to re-acquire the get () * mutex.release () $ Panax Notoginseng - the #With Mutex: + #get () A the if __name__=='__main__': +mutex=Lock () - forIinchRange (10): $P=process (target=task,args=(mutex,)) $ P.start () - #P.join ()Mock grab ticket3. IPC Communication mechanismCommunication between processes must find a medium that must meet1, is shared by all processes2. Must be memory spaceAdditional: Help us to handle the lock problem automaticallyA, from multipro

Producer consumers are using a container to solve the problem of strong coupling between producers and consumers. Producers and consumers do not communicate directly, but by blocking the queue. The blocking queue is quite a buffer, balancing the processing power of producers and consumers.ImportTime,randomImportQueue,threadingq=queue. Queue ()defProducer (name): Count=0 whileCount : Print("making .....") Time.sleep (5) Q.put (count)Print('Producer%s has produced%s Baozi .'%(name, count)) Coun

; num: Print ("...") print ("") Val.foreachrdd (Takeandprint)if __name__=='__main__': Zkquorum='datacollect-1:2181,datacollect-2:2181,datacollect-3:2181'Topic= {'speech-1': 1,'speech-2': 1,'speech-3': 1,'speech-4': 1,'speech-5': 1} groupid="rokid-speech-get-location"Master="local[*]"AppName="Sparkstreamingrokid"Timecell= 5SC= Sparkcontext (Master=master, appname=appName) SSC=StreamingContext (SC, Timecell)#ssc.checkpoint ("Checkpoint_" +time.strftime ("%y-%m-%d", Time.localtime (Time.time () )))

queue. Q.full (): When this method is called, Q is full to return true, and the result is unreliable, for example, in the process of returning true, if the items in the queue are taken away. Q.qsize (): Returns the correct number of current items in the queue, and the results are unreliable, for the same reason as Q.empty () and Q.full ()Application:#队列 # 1. You can put any type of # 2 into the queue. FIFO from multiprocessing import process,queueq= Queue (3) q.put (' first ') #默认block =trueq.