On RDBS, i have code:
rows = db(db.cat.id>0).select(orderby=db.cat.name,limitby=(1,10))
but on GAE:
rows = db(db.cat.id>0).select()
rows = rows.sort(lambda row:row.name)
rows = rows[1:10]
It spend long time in a large datasets.
Is there some other way i can use to make the performance?
Regards,
Toan.
On Jan 15, 12:30 pm, "mr.freeze" <nat...@freezable.com> wrote:
> 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 <johann.sp...@gmail.com> 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/39andalso the
> > "Quick Table Management Snippet"
> > fromhttp://www.web2pyslices.com/main/slices/take_slice/42todevelop 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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