Re: entry completion for hundreds of thousands of items

On Sep 4, 2010, at 8:34 AM, Yoann Padioleau wrote:

> 
> 
> On Sep 4, 2010, at 3:37 AM, Adrien wrote:
> 
>> 
>> Hi,
>> 
>> I've only taken a very quick look at your code but I think that what
>> you need is described in the treeview tutorial[1].
> 
> Your link explains that I should detach my model from the view but
> I use the entry/entry-completion widget, not the treeview, and in my code
> I build a model without any view/entry attached anyway to and it is already slow. Also
> I don't see any method to disable sorting on GTree.list_store.

Hmm I didn't see the advice on using a custom model at the first reading.

> 
>> 
>> Also, I've experienced such issues with pretty short lists or trees.
>> No need to have 1000 elements, something like 50 or 100 may be enough
>> to notice a slowdown.
>> 
>> Hope this helps.

Yes, the custom model should help I think. I've tried inserting 100000 elements
using lablgtk/examples/custom_list_generic.ml and it is way faster. I just have
to adapt the example to use instead the entry completion widget.


>> 
>> [1] http://plus.kaist.ac.kr/~shoh/ocaml/lablgtk2/treeview-tutorial/ch03s03.html#sec-treestore-adding-many-rows
>> 
>> --
>> Adrien Nader
>> 
>> 
>> On 04/09/2010, yoann padioleau <[email protected]> wrote:
>>> Hi,
>>> 
>>> I want to provide some completion for text where the corpus of items is
>>> above 100000. I've tried to build a GTree.list_store with those 100000 items
>>> but it takes a too long time to build the model. I've then tried to
>>> split those 100 000 iterms
>>> in chunk of 1000 based on common prefix.  Then as the user start to
>>> type a string, I build a model
>>> with only the relevant 1000 items. But even building a model with only
>>> 1000 items takes more than 2 seconds
>>> which makes the whole application look slow. Is there a way to
>>> accelerate the insertion of items
>>> in a list_store ?
>>> 
>>> I've attached my modification of src/examples/entrycompletion.ml
>>> showing how slow it is.
>>> 
>> 
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