The above procedure can be performed in a shorthand way by using the
execute()<http://docs.sqlalchemy.org/en/rel_0_9/core/connections.html#sqlalchemy.engine.Engine.execute>
method
of
Engine<http://docs.sqlalchemy.org/en/rel_0_9/core/connections.html#sqlalchemy.engine.Engine>
itself:
result = engine.execute("select username from users")for row in result:
print "username:", row['username']
So, seems engine.execute is shorthand of connection.execute.
Here is my db apis :
#!/usr/bin/env python
#coding: utf-8
from sqlalchemy.sql.expression import text, bindparam
from sqlalchemy.sql import select,insert, delete, update
from sqlalchemy.schema import Table
from sqlalchemy.orm import sessionmaker,scoped_session
from db import dba_logger,metadata,engine#session
from datetime import datetime
from exctrace import exctrace
from sqlalchemy import and_
direct_engine = True
use_raw = False
#import gevent
#from gevent import monkey
#monkey.patch_all()
import multiprocessing
from db import tables
def tmp_dbwrite(tablename,**kwargs):
"""
Used to insert exception info into database.
Params:
module : module name, indicating who raises the exception, e.g.
android,ios,psg,adpns,db .etc
type : exception type, 0 means service level while 1 is system
level.
message : exception description,length limit to 256 bytes
"""
try:
#_table=Table(tablename, metadata, autoload=True)
_table = tables[tablename]
i=_table.insert().values(**kwargs)
if direct_engine:
engine.execute(i)
#gevent.spawn(engine.execute,i)
#gevent.sleep(0)
#gevent.joinall([gevent.spawn(engine.execute,i)])
else:
session = scoped_session(sessionmaker(bind=engine))
session.execute(i)
session.commit()
session.close()
except Exception,e:
#dba_logger.log(40,'Exception when dbwriter:%s' % str(e))
#dba_logger.log(20,'Exception detail:%s' % str(kwargs))
exctrace('db','1','Error happened when writing
db',dba_logger,'Exception when dbwriter:%s' % str(e),'Exception detail:%s'
% str(kwargs))
if not direct_engine:
session.rollback()
session.close()
def tmp_dbupdate(_table,whereclause,**kwargs):
"""
Used to insert exception info into database.
Params:
module : module name, indicating who raises the exception, e.g.
android,ios,psg,adpns,db .etc
type : exception type, 0 means service level while 1 is system
level.
message : exception description,length limit to 256 bytes
"""
try:
#_table=Table(tablename, metadata, autoload=True)
#_table = tables[tablename]
i=_table.update().values(**kwargs).where(whereclause)
if direct_engine:
engine.execute(i)
#gevent.spawn(engine.execute,i)
else:
session = scoped_session(sessionmaker(bind=engine))
session.execute(i)
session.commit()
session.close()
except Exception,e:
#dba_logger.log(40,'Exception when dbwriter:%s' % str(e))
#dba_logger.log(20,'Exception detail:%s' % str(kwargs))
exctrace('db','1','Error happened when updating
db',dba_logger,'Exception when dbupdate:%s' % str(e),'Exception detail:%s'
% str(kwargs))
if not direct_engine:
session.rollback()
session.close()
def dbquery(_table,whereclause):
try:
#_table=Table(tablename, metadata, autoload=True)
#_table = tables[tablename]
i=_table.select().where(whereclause)
if direct_engine:
res = engine.execute(i)
return res
else:
session = scoped_session(sessionmaker(bind=engine))
res = session.execute(i)
return res
session.close()
except Exception,e:
#dba_logger.log(40,'Exception when dbwriter:%s' % str(e))
#dba_logger.log(20,'Exception detail:%s' % str(kwargs))
exctrace('db','1','Error happened when querying
db',dba_logger,'Exception when dbquery:%s' % str(e),'Exception detail:%s' %
str(whereclause))
#session.rollback()
if not direct_engine:
session.close()
#res =
session.execute(connection_writer._table.select().where(connection_writer._table.c.app_key==self.app_key).where(connection_writer._table.c.device_token==self._devicetoken))
pool = multiprocessing.Pool(10)
def dbwrite(tablename,**kwargs):
pool.apply_async(tmp_dbwrite, (tablename,), kwargs)
def dbupdate(tablename,whereclause,**kwargs):
pool.apply_async(tmp_dbupdate, (tablename,whereclause), kwargs)
You can see in the bottom that I use multiprocessing to do dbwrite and
dbupdate which are called by other modules.
Based on the above code, mostly I only see 4-5 processlist from mysql
server side...
That's means, I haven't reached the bottleneck of mysql server itself...
在 2014年4月8日星期二UTC+8下午9时52分58秒，Michael Bayer写道：
>
>
> On Apr 8, 2014, at 8:55 AM, Ni Wesley <[email protected] <javascript:>>
> wrote:
>
> For me, I just use engine.execute most of the time, any problem with this?
>
> Or if I use session or connect, do I need to close the session or
> connection everytime? otherwise, it will trigger the pool size limit error
> as the connection is increasing, right?
>
>
> if you use sessions or a Connection object then yes you need to make sure
> those are closed when you’re done.
>
> The docs at http://docs.sqlalchemy.org/en/rel_0_9/core/connections.htmlhave
> background on the difference between engine.execute and
> connection.execute.
>
>
>
>
> 在 2014年4月8日星期二UTC+8下午8时49分16秒，Michael Bayer写道：
>>
>> To make more connections, call connect(), and/or use more session
>> objects. Each session uses one connection.
>>
>> If you see three connections, that means your script has only worked with
>> three connections at once, such as, you opened three Session objects
>> concurrently.
>>
>> Sqlalchemy does not initiate any concurrent operations on its own.
>>
>>
>> Sent from my iPhone
>>
>> On Apr 8, 2014, at 5:03 AM, Ni Wesley <[email protected]> wrote:
>>
>> Hi all,
>> I have a question here.
>>
>> Here is my db init code snippet:
>>
>> engine = create_engine(db_url,
>> pool_size=100,max_overflow=150,echo=engine_echo,pool_recycle=3600)
>> session = scoped_session(sessionmaker(bind=engine))
>> metadata = MetaData(bind=engine)
>>
>> Then, I use engine to do update/insert operations.
>>
>> There is no problem here, then I find during the performance test that,
>> it's too slow to insert/update mysql server.
>> When my script running, on mysql server, use mysql 'show processlist;'
>> command, I see only 2 or 3 active connections kept.
>>
>> Then,within my script, I use multiprocessing.pool(defaults to cpu core
>> size, which is 4 for me) to do mysql insert/update operations.
>>
>> Finally, I see 4 or 5 connections kept from mysql server.
>>
>> So, seems db operation is bottleneck because I cannot use more
>> connections yet.
>>
>> How to push the conncurrent connections up? I am sure script generating
>> db tasks are fast enough.
>>
>> Thanks.
>> Wesley
>>
>>
>> --
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>>
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