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* https://www.sitepoint.com/full-stack-developer/
Kafka


…
…
>>> import multiprocessing
>>> import multiprocessing
>>> pool = multiprocessing.Pool(8)
>>> pool.map(do_some_work, jobs)
>>> Q = kafka.get_consumer(group_id=‘group_a’)
>>> Q.get_message()
load balancing(distributed!)
fault tolerance
scalability
simpler/better code/flow
10~40x
http://blog.parsely.com/post/3886/pykafka-now/








Method Cores Elapsed(secs)
mput 1 93
sst 1 98
sst 4 47
sst 6 27
sst 12 22






redirect_stderr = true
process_name=%(program_name)s
numprocs=1
[program:meta.ab.watcher]
command = python MetaWatcher.py ./MetaAB
directory = /daum/kskim/aurochs.app.git/1boon
stdout_logfile = ./Log/meta_ab_watcher.log
stdout_logfile_maxbytes = 50MB
stdout_logfile_backups = 3
redirect_stderr = true
process_name=%(program_name)s
numprocs=1
[program:meta.ab.picker]
command = python MetaPicker.py ./MetaAB
directory = /daum/kskim/aurochs.app.git/1boon
stdout_logfile = ./Log/meta_ab_picker.log
stdout_logfile_maxbytes = 50MB
stdout_logfile_backups = 3
redirect_stderr = true
process_name=%(program_name)s
numprocs=1
[eventlistener:ev]
command = python ev.py
directory = /daum/kskim/aurochs.app.git/
events=PROCESS_STATE,TICK_60
[supervisord]
[supervisorctl]
[inet_http_server]
port = *:23231
username = xxx
password = xxx
[rpcinterface:supervisor]
supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface
Kafka Load Balancing
Kafka Load Balancing
Kafka Load Balancing
Kafka Load Balancing
Kafka Load Balancing
Kafka Load Balancing
Kafka Load Balancing

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