WebGrid can handle large datasets as it limits the query by the page
size if the datasource is a Set or Table(s). The performance hit will
come in when the filter row is enabled since each filter is a query
for all distinct values in a field. I would try disabling the filter
row with:
grid.enabled_rows.remove('filter')
On Jan 14, 9:12 am, Johann Spies <[email protected]> wrote:
> Is web2py suitable if I want to work with large datasets?
>
> I am currently developing a database and want to use web2py to make it
> available to the client.
>
> Up to now I was using the shell and appadmin interfaces to the databasis.
>
> When trying out thewebgrid-slice
> fromhttp://www.web2pyslices.com/main/slices/take_slice/39and also the
> "Quick Table Management Snippet"
> fromhttp://www.web2pyslices.com/main/slices/take_slice/42to develop an
> interface to one of the tables containing about 168800 records python
> used up all the resources on my computer (more than 3.4G of memory)
> and I had to kill the process.
>
> In both cases I referred to the table as the datasource.
>
> What I do not understand is that in the appadmin interface I do not
> have the same problem.
>
> How do I prevent web2py loading whole dataset into memory? After all
> what is the use of a sql database if the everything is loaded into
> RAM?
>
> Regards
> Johann
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