Re: high temp space usage for same analytic function on latest version

A quick throwaway comment before I look at the latest github stuff. Your select is running parallel, but the insert is serialising - have you enabled parallel DML, do you want the insert to go parallel as well? If the insert runs parallel then some of the mechanism of the plan may change anyway and the problem might just go away.

Regards
Jonathan Lewis

On Sun, 13 Nov 2022 at 14:28, yudhi s <learnerdatabase99_at_gmail.com> wrote:

> Thank you Lok. Actually the join is not exactly on the columns but with
> some functions so that might be the case why it seems like Cartesian.
>
> However the point is , this query has not been changed and I agree that it
> may be because the data has been increased a lil in one of the table 'C' or
> 'T' , so the join output has been increased from 7billion to 10billion but
> how come that justifies the temp space requirement from 20gb to 2.5terabyte
> it not twice or thrice but multiple times.
>
> As this query is running in parallel-16 degree because of a underlying
> table degree , and considering no other option at hand, so I was thinking
> if by increasing or decreasing the parallelism with help of hints will help
> in completing the query at least with lesser temp space(we have 2.5TB of
> temp space with us right now currently) ? Or any other possible option to
> make this query succeed?
>
>

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