場景說明
假設有一個mysql表被水平切分，分散到多個host中，每個host擁有n個切分表。
如果需要并發去訪問這些表，快速得到查詢結果， 應該怎么做呢？
這里提供一種方案，利用python3的asyncio異步io庫及aiomysql異步庫去實現這個需求。
代碼演示
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import loggingimport randomimport asynciofrom aiomysql import create_pool# 假設mysql表分散在8個host, 每個host有16張子表TBLES = { "192.168.1.01": "table_000-015",# 000-015表示該ip下的表明從table_000一直連續到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函數，用于捕捉異常def query_wrapper(func): async def wrapper(*args, **kwargs): try: await func(*args, **kwargs) except Exception as e: print(e) return wrapper # 實際的sql訪問處理函數，通過aiomysql實現異步非阻塞請求@ 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訪問隊列, 隊列的每個元素包含要對某個表進行訪問的函數及參數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# 按批量運行sql訪問請求隊列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, 通過asyncio實現函數異步調用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() |
以上就是本次相關內容的全部實例代碼，大家可以本地測試以下，感謝你對服務器之家的支持。
