The design on this page should be considered obsolete - it doesn't actually solve the problems I was hoping it would solve. Some of the discussion is still useful, as I think it provides at least some hints at a general path forward. In the meantime, I think I have a much smaller modification to the current in algorithm in hand that should address the DM-19988 issue (while leaving more challenging problems - particularly the "jointcal problem" noted below) for the future.
The Main Problem
Jira |
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server | JIRA |
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columns | key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution |
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serverId | 9da94fb6-5771-303d-a785-1b6c5ab0f2d2 |
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key | DM-19988 |
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is a symptom of a fairly deep problem in the current QuantumGraph generation algorithm: the algorithm at present assumes the set of data IDs to be processed is defined by a strict intersection of all relevant dimensions, according to their (usually spatial) relationships. Because dimensions also provide a form of discretization that expands what's covered by that intersection, this does what we want as long as there is just one pairwise relationship in the query (i.e. visit_detector_region to patch), but it falls apart when that's not the case, such as:
...