实例分析python3实现并发访问水平切分表

实例分析python3实现并发访问水平切分表

场景说明

假设有一个mysql表被水平切分，分散到多个host中，每个host拥有n个切分表。

如果需要并发去访问这些表，快速得到查询结果， 应该怎么做呢？

这里提供一种方案，利用python3的asyncio异步io库及aiomysql异步库去实现这个需求。

代码演示

import logging
import random
import asynciofrom aiomysql 
import create_pool
# 假设mysql表分散在8个host, 每个host有16张子表
TBLES = {  "192.168.1.01": "table_000-015",
# 000-015表示该ip下的表明从table_000一直连续到table_015
  "192.168.1.02": "table_016-031", 
   "192.168.1.03": "table_032-047",  
    "192.168.1.04": "table_048-063", 
     "192.168.1.05": "table_064-079",  
     "192.168.1.06": "table_080-095", 
      "192.168.1.07": "table_096-0111", 
"192.168.1.08": "table_112-0127",
}
USER = "xxx"PASSWD = "xxxx"# wrapper函数，用于捕捉异常def query_wrapper(func):
  async def wrapper(*args, **kwargs):
    try:
      await func(*args, **kwargs)    except Exception as e:
      print(e)  return wrapper
      # 实际的sql访问处理函数，通过aiomysql实现异步非阻塞请求@
      query_wrapperasync def query_do_something(ip, db, table):
  async with create_pool(host=ip, db=db, user=USER, password=PASSWD) as pool:
    async with pool.get() as conn:
      async with conn.cursor() as cur:
 sql = ("select xxx from {} where xxxx")
 await cur.execute(sql.format(table))
 res = await cur.fetchall()    
 # then do something...# 生成sql访问队列, 队列的每个元素包含要对某个表进行访问的函数及参数def gen_tasks():
  tasks = []  for ip, tbls in TBLES.items():
    cols = re.split('_|-', tbls)
    tblpre = "_".join(cols[:-2])
    min_num = int(cols[-2])
    max_num = int(cols[-1])   
      for num in range(min_num, max_num+1):
      tasks.append(
 (query_do_something, ip, 'your_dbname', '{}_{}'.format(tblpre, num))
      )
 
  random.shuffle(tasks)  
   return tasks# 按批量运行sql访问请求队列def run_tasks(tasks, batch_len):
  try:  
    for idx in range(0, len(tasks), batch_len):
      batch_tasks = tasks[idx:idx+batch_len]
      logging.info("current batch, start_idx:%s len:%s" % (idx, len(batch_tasks))) 
     for i in range(0, len(batch_tasks)):
 l = batch_tasks[i]
 batch_tasks[i] = asyncio.ensure_future(
   l[0](*l[1:])
 )
      loop.run_until_complete(asyncio.gather(*batch_tasks)) 
except Exception as e:
    logging.warn(e)# main方法, 通过asyncio实现函数异步调用def main():
  loop = asyncio.get_event_loop()
 
  tasks = gen_tasks()
  batch_len = len(TBLES.keys()) * 5  # all up to you
  run_tasks(tasks, batch_len)
 
  loop.close()

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