zeroMQ初体验-3.分而治之模式(push/pull)

push/pull模式:

模型描述:

1.上游(任务发布)

2.工人(中间,具体工作)

3.下游(信号采集或者工作结果收集)

上游代码:

import zmq
import random
import time

context = zmq.Context()

# Socket to send messages on
sender = context.socket(zmq.PUSH)
sender.bind("tcp://*:5557")

print "Press Enter when the workers are ready: "
_ = raw_input()
print "Sending tasks to workers..."

# The first message is "0" and signals start of batch
sender.send('0')

# Initialize random number generator
random.seed()

# Send 100 tasks
total_msec = 0
for task_nbr in range(100):
    # Random workload from 1 to 100 msecs
    workload = random.randint(1, 100)
    total_msec += workload
    sender.send(str(workload))
print "Total expected cost: %s msec" % total_msec

工作代码:

import sys
import time
import zmq

context = zmq.Context()

# Socket to receive messages on
receiver = context.socket(zmq.PULL)
receiver.connect("tcp://localhost:5557")

# Socket to send messages to
sender = context.socket(zmq.PUSH)
sender.connect("tcp://localhost:5558")

# Process tasks forever
while True:
    s = receiver.recv()

    # Simple progress indicator for the viewer
    sys.stdout.write('.')
    sys.stdout.flush()

    # Do the work
    time.sleep(int(s)*0.001)

    # Send results to sink
    sender.send('')

下游代码:

import sys
import time
import zmq

context = zmq.Context()

# Socket to receive messages on
receiver = context.socket(zmq.PULL)
receiver.bind("tcp://*:5558")

# Wait for start of batch
s = receiver.recv()

# Start our clock now
tstart = time.time()

# Process 100 confirmations
total_msec = 0
for task_nbr in range(100):
    s = receiver.recv()
    if task_nbr % 10 == 0:
        sys.stdout.write(':')
    else:
        sys.stdout.write('.')

# Calculate and report duration of batch
tend = time.time()
print "Total elapsed time: %d msec" % ((tend-tstart)*1000)

注意点:

这种模式与pub/sub模式一样都是单向的,区别有两点:

1,该模式下在没有消费者的情况下,发布者的信息是不会消耗的(由发布者进程维护)

2,多个消费者消费的是同一列信息,假设A得到了一条信息,则B将不再得到

这种模式主要针对在消费者能力不够的情况下,提供的多消费者并行消费解决方案(也算是之前的pub/sub模式的那个"堵塞问题"的一个解决策略吧)

由上面的模型图可以看出,这是一个N:N的模式,在1:N的情况下,各消费者并不是平均消费的,而在N:1的情况下,则有所不同,如下图:

这种模式主要关注点在于,可以扩展中间worker,来到达并发的目的。

(未完待续)

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