at first I thought, I need this "caching" **per request**,
but maybe this would not be the problem to set it for several seconds
or even minutes
A)
if I want to use **dict[key]** notation (for clear'er code),
I could do like this:
for row in db(...).select(...,cache=(cache.ram,expiration))::
data.MyTable[row.id] = row
B) or I could inherit Storage and overload like this?
def __getitem__ (self, key):
self.rows.find(lambda r: r.id==key)
Question: which variant woud be better?
I am not sure, but seems to me - A ?
On 19 Rugs, 01:32, mdipierro <mdipie...@cs.depaul.edu> wrote:
> Something like that is there:
>
> expiration=3600 # seconds
> rows=db(...).select(...,cache=(cache.ram,expiration))
>
> reset with
>
> rows=db(...).select(...,cache=(cache.ram,0))
>
> On Sep 18, 5:27 pm, Jurgis Pralgauskis <jurgis.pralgaus...@gmail.com>
> wrote:
>
> > Hello,
>
> > I think I got a bit trapped by DAL in GAE :)
> > maybe because of often used db.MyTable[i].somefield
>
> > /default/topic_examples/27001/view 200 2721ms 5145cpu_ms
> > 2906api_cpu_ms
>
> > service.call #RPCs real time api time
> > datastore_v3.Get 62 712ms 516ms
> > datastore_v3.RunQuery 35 706ms 2390ms
> > memcache.Get 3 27ms 0ms
> > memcache.Set 2 12ms 0ms
>
> > Though my tables are still quite small: ~ 5 main tables with ~ 100
> > records in each.
>
> > in order to decrease db requests, I think to make some singleton like
> > interface, so I could ask
> > data.MyTable[i].somefield
>
> > instead of
> > db.MyTable[i].somefield
>
> > data would hold storage copies of Tables which I need to access often
> > by index
>
> > and if data doesn't have particular table or its record, it could
> > call db.MyTable.. then (and optionaly cache the result the Singleton
> > way)
>
> > maybe this could be called select_cache.
> > by the way, find() probably could also be more appropriate than
> > separate select in such cases?
>
> > this is just a plan now, am I on a sound way?
> > how big the tables should grow (approximatelly) for my mechanizm to
> > become useless??
>
>
