Yes, there is a  faster alternative.  Most databases have a way to import
CSV directly. Postgresql, mysql, sqlite all can import CSV with different
degrees of complication, but I can say it is pretty easy and much faster.
The nice thing of web2py is that is independent of the database, and this
comes with a price in terms of speed.





2013/8/26 Joe Barnhart <[email protected]>

> In general processing almost a gig of CSV data is going to take a
> measurable amount of time.  It's simply unavoidable.
>
> I process similar size CSV files and I have found the Scheduler to be the
> ideal solution.  I don't actually care that much how long it takes -- I
> just want my website to remain responsive while it loads.  This is exactly
> why the scheduler exists, to fork something long-running to another process
> so your site is unaffected.  And it truly is another process -- not a
> thread.  If you have a quad-core you can support a whale of a lot of
> processing using the scheduler.
>
> I built in a little "messaging" table so when my scheduler is done it
> sends a message to me and I can see the results.  It's a marvelous piece of
> work and one of the best features of web2py.
>
> -- Joe
>
>
> On Sunday, August 25, 2013 3:15:28 PM UTC-7, Sebastian Demian wrote:
>>
>> Hi guys, I am working on an application using web2py framework, and I
>> need to import a csv file that has a size of 700MB. Is there a faster way
>> to import it into the database ? I have tried the database administration
>> tool, but it takes forever.
>>
>> PS: I am a newbie.
>>
>> Thank you.
>>
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