利用Redis实现SQL伸缩的方法

def incr_and_check_limit(user_id, limit): 
 key = '{user_id}:{epoch}'.format(user_id, int(time() / 60)) 
  
 pipe = redis.pipeline() 
 pipe.incr(key) 
 pipe.expire(key, 60) 
 current_rate, _ = pipe.execute() 
  
 return int(current_rate) > limit 

def incr_and_check_limit_memcache(user_id, limit): 
 key = '{user_id}:{epoch}'.format(user_id, int(time() / 60)) 
  
 if cache.add(key, 0, 60): 
  return False 
  
 current_rate = cache.incr(key) 
  
 return current_rate > limit 

from contextlib import contextmanagerr = Redis()@contextmanagerdef lock(key, nowait=True): 
 while not r.setnx(key, '1'): 
  if nowait: 
   raise Locked('try again soon!') 
  sleep(0.01) 
  
 # limit lock time to 10 seconds 
 r.expire(key, 10) 
  
 # do something crazy 
 yield 
  
 # explicitly unlock 
 r.delete(key) 

{ 
 
  "<type enum>:<epoch>:<shard number>": { 
 
    "<id>": <count> 
 
  }} 

 { 
 
  "1:1399958363:0": { 
 
    "1": 53, 
 
    "2": 72, 
 
  }} 

"1:1399958363:0:1": 53 

def get_range(self, model, keys, start, end, rollup=None): 
 """ To get a range of data for group ID=[1, 2, 3]: Start and end are both inclusive. >>> now = timezone.now() >>> get_keys(tsdb.models.group, [1, 2, 3], >>>   start=now - timedelta(days=1), >>>   end=now) """ 
 normalize_to_epoch = self.normalize_to_epoch 
 normalize_to_rollup = self.normalize_to_rollup 
 make_key = self.make_key 
  
 if rollup is None: 
  rollup = self.get_optimal_rollup(start, end) 
  
 results = [] 
 timestamp = end 
 with self.conn.map() as conn: 
  while timestamp >= start: 
   real_epoch = normalize_to_epoch(timestamp, rollup) 
   norm_epoch = normalize_to_rollup(timestamp, rollup) 
  
   for key in keys: 
    model_key = self.get_model_key(key) 
    hash_key = make_key(model, norm_epoch, model_key) 
    results.append((real_epoch, key, conn.hget(hash_key, model_key))) 
  
   timestamp = timestamp - timedelta(seconds=rollup) 
  
 results_by_key = defaultdict(dict) 
 for epoch, key, count in results: 
  results_by_key[key][epoch] = int(count or 0) 
  
 for key, points in results_by_key.iteritems(): 
  results_by_key[key] = sorted(points.items()) 
 return dict(results_by_key)