>From what I understand people use DAL or ORM layers for abstraction purposes.
So a struct with pointer to functions in C will have less overhead
than a class with member functions in C++. However working at this
higher level of abstraction allows for some fancy time-saving
mechanisms such as multiple inheritance, templates, encapsulation and
subtype polymorphism.
In the database world: queries would of course run much faster when
written by hand, and stored-procedures will speed up the equivalent
function built inn Python with the layer in-between. Does this mean we
should just write pure SQL and stored-procedures?
Yes and no. It depends on what you are setting out to do. If
performance is your goal and your willing to sacrifice abstraction to
achieve it, then do as much as you can database and query side.
{An additional advantage of using DAL or ORM layers is the ability to
move to a different database engine (e.g.: a NoSQL one or from sqlite
to postgres [use one for dev one for production])/}
<apologies if I went to much into philosophy here, if you have actual
ideas on how to speed up queries without sacrificing abstraction I'm
sure your patches will be accepted :]>
On Fri, Jun 22, 2012 at 4:54 PM, pbreit <pbreitenb...@gmail.com> wrote:
> I have an app where I pull down 5,000 records. I started with DAL and
> db.item.ALL and it was taking around 4 seconds. I added 5 fields to the
> select() which got it down to around 2 seconds. Then I implemented the same
> thing with executesql and got it down to 500 ms.
>
> So, selecting only the fields you need is a good optimization. But going
> with raw SQL is much better.
>
> --
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