On Jul 17, 2008, at 9:24 AM, Chris wrote:
>
> Hi all, I'm using SQLAlchemy to access a large table (~280 million
> rows), and I'm getting timeout issues. At 30 seconds, SQLAlchemy
> quits. In lieu of getting all tables past and future to be indexed
> differently, I was wondering if there was a way using session.query
> (*not* select()) to change the default timeout of 30 seconds to
> something more suitable for such large tables. All I have found on
> the web points to QueuePool and the pool_timeout parameter, but it is
> unclear as to how this fits in with a mapper and session.query. Here
> is a snippet of the code I am using:
>
> def createSession():
> global session, table1
> engine = create_engine('mssql://<database>', echo=False)
> metadata = MetaData()
> metadata.bind=engine
> table1 = Table('<Large Table>', metadata,\
> Column('LocationId',Integer,primary_key=True),
> autoload=True)
> mymapper1=mapper(Object,table1)
> Session = sessionmaker(bind=engine, autoflush=True,
> transactional=True)
> session = Session()
>
> def getData(lmplocation_id):
> global session, table1
> if not session:
> createSession()
> result = session.query(Object)
> return result
>
what database is this ? The "timeout" of the connection itself, or
the max time allowed to spend on an execution is typically a specific
setting within your client library. If its an argument to the DBAPI's
connect() method, it can be passed through using the "connect_args"
kwarg to create_engine() - though I usually see setting like these
within the configuration files for the database itself.
SQLA itself does not set any timeout parameters; we only have
"pool_recycle" which is turned off by default, and only takes effect
upon pool checkout for an otherwise unused connection.
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