import multiprocessing

import time

import redis

import sys

import argparse

from urlparse import urlparse

import os

from collections import defaultdict

import math

def ping(r):

r.ping()

def jsonset(r):

r.execute_command('JSON.SET', 'j', '.', '{}')

def runWorker(ctx):

return rep

if __name__ == '__main__':

parser = argparse.ArgumentParser(description='ReJSON Benchmark', formatter_class=argparse.ArgumentDefaultsHelpFormatter)

parser.add_argument('-c', '--count', type=int, default=100000, help='total number of operations')

parser.add_argument('-p', '--pipeline', type=int, default=0, help='pipeline size')

parser.add_argument('-w', '--workers', type=int, default=8, help='number of worker processes')

parser.add_argument('-u', '--uri', type=str, default='redis://localhost:6379', help='Redis server URI')

args = parser.parse_args()

uri = urlparse(args.uri)

r = redis.Redis(host=uri.hostname, port=uri.port)

pool = multiprocessing.Pool(args.workers)

s0 = time.time()

ctx = {

'count': args.count / args.workers,

'pipeline': args.pipeline,

'host': uri.hostname,

'port': uri.port,

'work': jsonset,

}

print 'Starting workers: ',

sys.stdout.flush()

results = pool.map(runWorker, (ctx, ) * args.workers)

print

sys.stdout.flush()

s1 = time.time() - s0

agg = defaultdict(int)

for res in results:

for k, v in res.iteritems():

agg[k] += v

print

print 'Count: {}, Workers: {}, Pipeline: {}'.format(args.count, args.workers, args.pipeline)

print 'Using hireds: {}'.format(redis.utils.HIREDIS_AVAILABLE)

print 'Runtime: {} seconds'.format(round(s1, 2))

print 'Throughput: {} requests per second'.format(round(args.count/s1, 2))

for k, v in sorted(agg.items()):

perc = 100.0 * v / args.count

print '{}% <= {} milliseconds'.format(perc, k)