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@labkey-matthewb
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Rationale

These were all NOT NULL as designed in the original study.data table. This constraint seems to have been lost over time.

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@labkey-jeckels
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Agreed they shouldn't be null. What happens to existing datasets? Do we need to get this applied to them, and/or somehow fill in existing rows that have nulls?

@labkey-matthewb
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The good news is we enforce that there are no nulls (barring bugs), and things blow up if NULLs get in there (updateParticipantVisits() etc).

I don't know if we need to do anything with existing datasets. This will enforce fast-fail if we have any new (or obscure) bugs.

@labkey-matthewb
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Hmm, teamcity/github seem to be having some syncing troubles.

@labkey-jeckels
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I'm always a bit paranoid about having tables in a variety of states depending on when they were created. @labkey-adam any strong feelings either way in this case?

@labkey-adam
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I agree... I certainly prefer proactive upgrades that ensure consistency

@labkey-jeckels
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@labkey-matthewb I propose that we add these constraints to existing tables at upgrade time, but not try to handle problematic rows in the tables. We can discuss if that represents a sizable chunk of work.

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4 participants