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Improve performance of delete+insert incremental strategy with null equality check changes #834

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Improve performance of delete+insert incremental strategy with null equality check changes #834

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adrianburusdbt
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@adrianburusdbt adrianburusdbt commented Feb 21, 2025 •
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This PR merges the changes for null equality from here: #744 into existing PR: #151

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  • I have read the contributing guide and understand what's expected of me
  • I have run this code in development and it appears to resolve the stated issue
  • This PR includes tests, or tests are not required/relevant for this PR
  • This PR has no interface changes (e.g. macros, cli, logs, json artifacts, config files, adapter interface, etc) or this PR has already received feedback and approval from Product or DX

@adrianburusdbt adrianburusdbt requested a review from a team as a code owner February 21, 2025 07:41
@cla-bot cla-bot bot added the cla:yes The PR author has signed the CLA label Feb 21, 2025
@cla-bot cla-bot bot temporarily deployed to dbt-snowflake February 21, 2025 07:41 Inactive
@VanTudor
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Code lgtm, but let's address those failing tests

mikealfare
mikealfare reviewed Feb 21, 2025
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Overall this is much cleaner. Assuming tests are happy then this looks good.

...adapters/src/dbt/include/global_project/macros/materializations/models/incremental/merge.sql

delete from {{ target }}
where ({{ unique_key_str }}) in (
select distinct {{ unique_key_str }}
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I think the distinct here is unnecessary and would make it take longer since it needs to reduce dupes. I don't have proof of that, but I generally don't use distinct when using a where <x> in <y> clause.

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Two of the spark failed tests are due to an unrelated issue. The errors in the third spark run are related to the cluster not coming up in time, which we have a separate PR to fix.

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@adrianburusdbt @VanTudor @mikealfare @colin-rogers-dbt