我已经调查了几个太多的客户＆＃39;这里的相关主题，但仍然无法解决我的问题，所以我必须再次问这个，对我来说具体情况。
基本上，我设置了我的本地Postgres服务器，需要做成千上万的查询，所以我使用了Python psycopg2package。这是我的代码：
import psycopg2
import pandas as pd
import numpy as np
from flashtext import KeywordProcessor
from psycopg2.pool import ThreadedConnectionPool
from concurrent.futures import ThreadPoolExecutor
df = pd.DataFrame({'S':['California', 'Ohio', 'Texas'], 'T':['Dispatcher', 'Zookeeper', 'Mechanics']})
# df = pd.concat([df]*10000) # repeat df 10000 times
DSN = "postgresql://User:password@localhost/db"
tcp = ThreadedConnectionPool(1, 800, DSN)
def do_one_query(inputS, inputT):
conn = tcp.getconn()
c = conn.cursor()
q = r"SELECT * from eridata where "State" = 'California' and "Title" = 'Dispatcher' limit 1;"
c.execute(q)
all_results = c.fetchall()
for row in all_results:
return row
tcp.putconn(conn, close=True)
cnt=0
for idx, row in df.iterrows():
cnt+=1
with ThreadPoolExecutor(max_workers=1) as pool:
ret = pool.submit(do_one_query, row["S"], row["T"])
print ret.result()
print cnt
代码运行良好，带有小df。如果我重复df 10000次，我收到错误消息说连接池已用完 。我虽然我使用的连接已经被这条线关闭了：
tcp.putconn（conn，close = True） 但我猜他们实际上并没有关闭？我怎样才能解决这个问题？
答案 0 :(得分：7)
您需要在池顶部使用队列。因为我是一个非常好的人...
import gevent, sys, random, psycopg2, logging
from contextlib import contextmanager
from gevent.queue import Queue
from gevent.socket import wait_read, wait_write
from psycopg2.pool import ThreadedConnectionPool
from psycopg2 import extensions, OperationalError
import sys
logger = logging.getLogger(__name__)
poolsize = 100 #number of max connections
pdsn = '' # put your dsn here
if sys.version_info[0] >= 3:
integer_types = (int,)
else:
import __builtin__
integer_types = (int, __builtin__.long)
class ConnectorError(Exception):
""" This is a base class for all CONNECTOR related exceptions """
pass
#singleton connection pool, gets reset if a connection is bad or drops
_pgpool = None
def pgpool():
global _pgpool
if not _pgpool:
try:
_pgpool = PostgresConnectionPool(maxsize=poolsize)
except psycopg2.OperationalError as exc:
_pgpool = None
return _pgpool
class Pcursor(object):
def __init__(self, **kwargs):
#in case of a lost connection lets sit and wait till it's online
global _pgpool
if not _pgpool:
while not _pgpool:
try:
pgpool()
except:
logger.debug('Attempting Connection To Postgres...')
gevent.sleep(1)
def fetchone(self, PSQL, *args):
with _pgpool.cursor() as cursor:
try:
cursor.execute(PSQL, args)
except TypeError:
cursor.execute(PSQL, args[0])
except Exception as exc:
print(sys._getframe().f_back.f_code)
print(sys._getframe().f_back.f_code.co_name)
logger.warning(str(exc))
logger.debug(cursor.query)
return cursor.fetchone()
def fetchall(self, PSQL, *args):
with _pgpool.cursor() as cursor:
try:
cursor.execute(PSQL, args)
except TypeError:
cursor.execute(PSQL, args[0])
except Exception as exc:
print(sys._getframe().f_back.f_code)
print(sys._getframe().f_back.f_code.co_name)
logger.warning(str(exc))
logger.debug(cursor.query)
return cursor.fetchall()
def execute(self, PSQL, *args):
with _pgpool.cursor() as cursor:
try:
cursor.execute(PSQL, args)
except TypeError:
cursor.execute(PSQL, args[0])
except Exception as exc:
print(sys._getframe().f_back.f_code)
print(sys._getframe().f_back.f_code.co_name)
logger.warning(str(exc))
finally:
logger.debug(cursor.query)
return cursor.query
def fetchmany(self, PSQL, *args):
with _pgpool.cursor() as cursor:
try:
cursor.execute(PSQL, args)
except TypeError:
cursor.execute(PSQL, args[0])
while 1:
items = cursor.fetchmany()
if not items:
break
for item in items:
yield item
class AbstractDatabaseConnectionPool(object):
def __init__(self, maxsize=poolsize):
if not isinstance(maxsize, integer_types):
raise TypeError('Expected integer, got %r' % (maxsize, ))
self.maxsize = maxsize
self.pool = Queue()
self.size = 0
def create_connection(self):
#overridden by PostgresConnectionPool
raise NotImplementedError()
def get(self):
pool = self.pool
if self.size >= self.maxsize or pool.qsize():
return pool.get()
self.size += 1
try:
new_item = self.create_connection()
except:
self.size -= 1
raise
return new_item
def put(self, item):
self.pool.put(item)
def closeall(self):
while not self.pool.empty():
conn = self.pool.get_nowait()
try:
conn.close()
except Exception:
pass
@contextmanager
def connection(self, isolation_level=None):
conn = self.get()
try:
if isolation_level is not None:
if conn.isolation_level == isolation_level:
isolation_level = None
else:
conn.set_isolation_level(isolation_level)
yield conn
except:
if conn.closed:
conn = None
self.closeall()
raise
else:
if conn.closed:
raise OperationalError("Cannot commit because connection was closed: %r" % (conn, ))
finally:
if conn is not None and not conn.closed:
if isolation_level is not None:
conn.set_isolation_level(isolation_level)
self.put(conn)
@contextmanager
def cursor(self, *args, **kwargs):
isolation_level = kwargs.pop('isolation_level', None)
with self.connection(isolation_level) as conn:
try:
yield conn.cursor(*args, **kwargs)
except:
global _pgpool
_pgpool = None
del(self)
class PostgresConnectionPool(AbstractDatabaseConnectionPool):
def __init__(self,**kwargs):
try:
self.pconnect = ThreadedConnectionPool(1, poolsize, dsn=pdsn)
except:
global _pgpool
_pgpool = None
raise ConnectorError('Database Connection Failed')
maxsize = kwargs.pop('maxsize', None)
self.kwargs = kwargs
AbstractDatabaseConnectionPool.__init__(self, maxsize)
def create_connection(self):
self.conn = self.pconnect.getconn()
self.conn.autocommit = True
return self.conn
def gevent_wait_callback(conn, timeout=None):
"""A wait callback useful to allow gevent to work with Psycopg."""
while 1:
state = conn.poll()
if state == extensions.POLL_OK:
break
elif state == extensions.POLL_READ:
wait_read(conn.fileno(), timeout=timeout)
elif state == extensions.POLL_WRITE:
wait_write(conn.fileno(), timeout=timeout)
else:
raise ConnectorError("Bad result from poll: %r" % state)
extensions.set_wait_callback(gevent_wait_callback)
然后您可以通过以下方式呼叫您的连接：
import db
db.Pcursor().execute(PSQL, arg1, arg2, arg3)
基本上我借用了async postgres的gevent示例并修改它以通过pyscopg2支持线程池。
https://github.com/gevent/gevent/blob/master/examples/psycopg2_pool.py
我添加了psycogreen在模块中执行的操作，因此您需要做的就是导入并调用该类。每次调用该类都会在队列中堆栈一个新查询，但只使用特定大小的池。这样你就不会用完连接。这与PGBouncer的功能基本类似，我认为这也可以消除您的问题。
答案 1 :(得分：3)
我一直在努力寻找有关ThreadedConnectionPool如何工作的非常详细的信息。 https://bbengfort.github.io/observations/2017/12/06/psycopg2-transactions.html不错，但是事实证明，它声称getconn会阻塞直到连接可用为止是不正确的。检查代码，所有ThreadedConnectionPool添加的内容都是对AbstractConnectionPool方法的锁定，以防止出现竞争情况。如果在任何时候尝试使用多个maxconn连接，则连接池已耗尽 PoolError。
如果您想要比the accepted answer更简单的方法，则可以将方法进一步包装在提供阻塞的信号量中，直到连接可用为止。
from psycopg2.pool import ThreadedConnectionPool
from threading import Semaphore
class ReallyThreadedConnectionPool(ThreadedConnectionPool):
def __init__(self, minconn, maxconn, *args, **kwargs):
self._semaphore = Semaphore(maxconn)
super().__init__(minconn, maxconn, *args, **kwargs)
def getconn(self, *args, **kwargs):
self._semaphore.acquire()
return super().getconn(*args, **kwargs)
def putconn(self, *args, **kwargs):
super().putconn(*args, **kwargs)
self._semaphore.release()
答案 2 :(得分：1)
您的问题是，您实际上没有将连接返回池，而是使用
永久关闭了该连接。tcp.putconn(conn, close=True)
请参见http://initd.org/psycopg/docs/pool.html
If close is True, discard the connection from the pool.
因此，如果将800个连接放入池中，则在801个循环后，由于连接池大小为零，您将收到“用尽的错误”。