Thank mdipierro.
But i want use "find" on GAE:
rows = db(db.cat.id>0).select()
rows = rows.find(lambda row:row.name.startswith("C")))
rows = rows.sort(lambda row:row.name)
rows = rows[1:10]
replace this code on RDBS: rows = db(db.cat.name.like("C%")).select
(orderby=db.cat.name,limitby=(1,10)) ?
On Jan 15, 2:14 pm, mdipierro <mdipie...@cs.depaul.edu> wrote:
> This
>
> rows = db(db.cat.id>0).select(orderby=db.cat.name,limitby=(1,10))
>
> works on GAE and it is fast.
>
> mind that you should start counting at 0, not 1.
>
> On Jan 15, 12:44 am, toan75 <toa...@gmail.com> wrote:
>
>
>
> > 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/39andalsothe
> > > > "Quick Table Management Snippet"
> > > > fromhttp://www.web2pyslices.com/main/slices/take_slice/42todevelopan
> > > > 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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