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()



以上就是本次相关内容的全部实例代码，大家可以本地测试以下，感谢你对中文源码网的支持。