实例分析python3实现并发访问水平切分表

Python  /  管理员 发布于 7年前   206

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 loggingimport randomimport 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，感谢你的支持。