| Commit message (Collapse) | Author | Age |
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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This is to allow for build servers where only the substitutes should be
queried, and it shouldn't be assumed that they're running Cuirass.
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I don't think this actually changes the result, but I think the query is a bit
better formed.
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To filter outputs by whether particular substitute servers have a substitute.
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This was leading to the first and last revision datetimes to be wrong.
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Mostly so that the builds can be avoided when querying for all the
derivations, as that's slow.
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Rather than derivations in general.
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This is present currently on core-updates. Ideally the valid-systems would
adapt to the revision, but for the moment just add it everywhere.
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Previously it would error in one of the INSERT queries.
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Signed-off-by: Christopher Baines <mail@cbaines.net>
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This recent change simply didn't work, the ordering was bad and the window
function wasn't properly defined. It now should hopefully work, although
there's an interesting case where different versions are available for
different systems/targets, which isn't handled particularly well.
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Somewhat untested improvements, but these make the query a bit more rigorous
in the case of multiple branches and git repositories.
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Actually check if fields can be NULL, and if they can be then include some
extra conditions for the comparison.
This will at least make the queries smaller, I'm not sure if it will have an
effect on performance.
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Mostly so whether a field can contain NULL values can be determined.
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This was redundant and slow, so don't do it.
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Rather than having two big tables looking at the history, just use the
derivations table as it has all the information.
This will allow deleting the package_versions_by_guix_revision_range table
which should help save time when importing revisions, and reduce the size of
the database.
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This might solve errors where the Guix Data Service is trying to insert a
lint_warning_message_set that already exists.
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Put the non-cross built derivations first.
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Similar to the one above for derivations, this just looks at outputs. This
filters out equivalent derivations, which can be useful.
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Rather than just the native system. I'm not quite sure of the value here, as I
guess system tests should behave the same regardless of the way the software
is compiled, but this seems like it could be useful, and being explicit about
the system the derivation is for is good.
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To increase the likelyhood that all the builds and narinfo files for the
latest revisions are fetched.
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Pulling out the recent entries first.
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Some builds from Cuirass change status at the same timestamp, so use the id
for ordering instead.
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With Guile 3, there's a potential for mock to work in even fewer
circumstances. So, adapt the code to enable writing the tests without mock.
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Support calling it with derivation-output-details-set-id, which can be used
when querying for builds.
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As some build servers do build cross derivations.
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These are the ones that relate to Guix pull.
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So that you can have the Guix Data Service only pay attention to some of the
branches.
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So that the non-cross derivations appear first.
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Stop using the system values as targets, and remove package derivation entries
where this is the case.
Switch the non-cross derivation case to have a target of "", rather than
matching the system, as this makes more sense, and is more consistent now that
the target values no longer match the system values.
Hardcode some more correct target values, and use these instead. Hopefully
this can be better integrated with Guix in the future.
This commit also includes a migration attempting to shrink some indexes.
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To speed up this step, as there is a lot of data.
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This is more performant when there is a lot of data.
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