Ho, I don't pass an array of datasets, just an array of values. Didn't
realize your ds1 / ds2 were datasets!
So, don't know if it works, so don't know the perf implications, sorry :)




Le mer. 17 juin 2020 à 14:09, Aryk Grosz <[email protected]> a écrit :

> Crazy, I didn't know you could pass an array of datasets. Never saw that
> before.
>
> What are the performance implications of doing it the way you are showing
> vs using UNION? Is it approx the same?
>
>
> On Wednesday, June 17, 2020 at 2:23:03 PM UTC+3, Michael Monerau wrote:
>>
>> Is there a design reason why you're avoiding something like:
>>
>>   ids = []
>>   ids.push(ds1) if x
>>   ids.push(ds2) if z
>>   ids.push(ds2) if y
>>
>>   ds.exclude(id: ids)
>>
>> Maybe the code around your snippet prevents that. Looking at why may give
>> a clue at a simple refactor?
>>
>> Best,
>> Michael
>>
>>
>>
>> Le mer. 17 juin 2020 à 13:11, Aryk Grosz <[email protected]> a écrit :
>>
>>> I was thinking to UNION ALL all the datasets with the pks, and then on
>>> the last UNION don't use "ALL" so that they get uniqued before being fed
>>> into the main query.
>>>
>>>
>>> On Wednesday, June 17, 2020 at 1:37:05 PM UTC+3, Aryk Grosz wrote:
>>>>
>>>> Many times I find myself writing.
>>>>
>>>> ds = ds.exclude(id: ds1) if x
>>>> ds = ds.exclude(id: ds2) if z
>>>> ds = ds.exclude(id: ds2) if y
>>>>
>>>> Is there any material performance impact of separating out the column
>>>> loopups?
>>>>
>>>> Should I be "UNION"ing the list of ids of first and then just do one
>>>> exclude/where statement? My guess is it doesn't really matter ultimately
>>>> because it's a direct lookup on an indexed field even if it's called
>>>> multiple times.
>>>>
>>>> Aryk
>>>>
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