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CHAPTER 8 CACHES, MESSAGE QUEUES, AND MAP-REDUCE
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Listing 8 3. Two Schemes for Assigning Data to Servers #!/usr/bin/env python # Foundations of Python Network Programming - 8 - queuecrazy.py # Small application that uses several different message queues import random, threading, time, zmq zcontext = zmq.Context() def def def def fountain(url): """Produces a steady stream of words.""" zsock = zcontext.socket(zmq.PUSH) zsock.bind(url) words = [ w for w in dir(__builtins__) if w.islower() ] while True: zsock.send(random.choice(words)) time.sleep(0.4) responder(url, function): """Performs a string operation on each word received.""" zsock = zcontext.socket(zmq.REP) zsock.bind(url) while True: word = zsock.recv() zsock.send(function(word)) # send the modified word back processor(n, fountain_url, responder_urls): """Read words as they are produced; get them processed; print them.""" zpullsock = zcontext.socket(zmq.PULL) zpullsock.connect(fountain_url) zreqsock = zcontext.socket(zmq.REQ) for url in responder_urls: zreqsock.connect(url) while True: word = zpullsock.recv() zreqsock.send(word) print n, zreqsock.recv() start_thread(function, *args): thread = threading.Thread(target=function, args=args) thread.daemon = True # so you can easily Control-C the whole program thread.start()
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start_thread(fountain, 'tcp://127.0.0.1:6700') start_thread(responder, 'tcp://127.0.0.1:6701', str.upper) start_thread(responder, 'tcp://127.0.0.1:6702', str.lower) for n in range(3): start_thread(processor, n + 1, 'tcp://127.0.0.1:6700', ['tcp://127.0.0.1:6701', 'tcp://127.0.0.1:6702']) time.sleep(30)
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CHAPTER 8 CACHES, MESSAGE QUEUES, AND MAP-REDUCE
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The two request-reply servers are different one turns each word it receives to uppercase, while the other makes its words all lowercase and you can tell the three processors apart by the fact that each is assigned a different integer. The output of the script shows you how the words, which originate from a single source, get evenly distributed among the three workers, and by paying attention to the capitalization, you can see that the three workers are spreading their requests among the two requestreply servers: 1 2 3 1 2 3 HASATTR filter reduce float BYTEARRAY FROZENSET
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In practice, of course, you would usually use message queues for connecting entirely different servers in a cluster, but even these simple threads should give you a good idea of how a group of services can be arranged.
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How Message Queues Change Programming
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Whatever message queue you use, I should warn you that it may very well cause a revolution in your thinking and eventually make large changes to the very way that you construct large applications. Before you encounter message queues, you tend to consider the function or method call to be the basic mechanism of cooperation between the various pieces of your application. And so the problem of building a program, up at the highest level, is the problem of designing and writing all of its different pieces, and then of figuring out how they will find and invoke one another. If you happen to create multiple threads or processes in your application, then they tend to correspond to outside demands like having one server thread per external client and to execute code from across your entire code base in the performance of your duties. The thread might receive a submitted photograph, then call the routine that saves it to storage, then jump into the code that parses and saves the photograph s metadata, and then finally execute the image processing code that generates several thumbnails. This single thread of control may wind up touching every part of your application, and so the task of scaling your service becomes that of duplicating this one piece of software over and over again until you can handle your client load. If the best tools available for some of your sub-tasks happen to be written in other languages if, for example, the thumbnails can best be processed by some particular library written in the C language then the seams or boundaries between different languages take the form of Python extension libraries or interfaces like ctypes that can make the jump between different language runtimes. Once you start using message queues, however, your entire approach toward service architecture may begin to experience a Copernican revolution. Instead of thinking of complicated extension libraries as the natural way for different languages to interoperate, you will not be able to help but notice that your message broker of choice supports many different language bindings. Why should a single thread of control on one processor, after all, have to wind its way through a web framework, then a database client, and then an imaging library, when you could make each of these components a separate client of the messaging broker and connect the pieces with language-neutral messages You will suddenly realize not only that a dedicated thumbnail service might be quite easy to test and debug, but also that running it as a separate service means that it can be upgraded and expanded without any disruption to your front-end web servers. New servers can attach to the message queue, old ones can be decommissioned, and software updates can be pushed out slowly to one back end after another without the front-end clients caring at all. The queued message, rather than the library API, will become the fundamental point of rendezvous in your application.
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