Sorry, but I don't think this is suitable.
If somebody has 100M rows per Table then, he should prolly think about
sharding/replication anyway. So the ORM would still suffer anyway.
Currently my company has a few tables with a high count as well but since
we never used the django-admin and managed to shard some of the data, we
never ran into such problems.

Django is a headstart for many projects / products, but once you have
certain amount of data you still need to program a few things by yourself.

If your patches are enough than live with it, but I don't see a reason for
optimizing django against big tables.



2014-11-18 19:27 GMT+01:00 Rick van Hattem <wo...@wol.ph>:

> That certainly solves one part of the problem. After that I would still
> opt for an optional configurable default for slicing. Personally I prefer
> to raise an error when unsliced querysets are used since it's almost always
> harmful or at least dangerous behaviour.
>
> On 18 November 2014 19:18, Claude Paroz <cla...@2xlibre.net> wrote:
>
>> On Tuesday, November 18, 2014 1:58:00 PM UTC+1, Rick van Hattem wrote:
>>>
>>> Hi guys,
>>>
>>> As it is right now Django has the tendency to kill either your browser
>>> (if you're lucky) or the entire application server when confronted with a
>>> large database. For example, the admin always does counts for pagination
>>> and a count over a table with many rows (say, in the order of 100M) can
>>> really stall your app and database servers.
>>>
>>
>>
>>
>> https://docs.djangoproject.com/en/dev/ref/contrib/admin/#django.contrib.admin.ModelAdmin.show_full_result_count
>> seems to go in your direction, at least. count(*) performance is
>> implementation-specific, so once again, no one-size-fits-all.
>> Maybe the documentation could be completed, here and there.
>>
>> Claude
>>
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