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- array facet: don't materialize unnecessary columns · 4 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | issue | performed_via_github_app |
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1407716963 | https://github.com/simonw/datasette/pull/2008#issuecomment-1407716963 | https://api.github.com/repos/simonw/datasette/issues/2008 | IC_kwDOBm6k_c5T6A5j | cldellow 193185 | 2023-01-29T17:04:03Z | 2023-01-29T17:04:03Z | CONTRIBUTOR | Performance tests - I think most places don't have them as a formal gate enforced by CI. TypeScript and scalac seem to have tests that run to capture timings. The timings are included by a bot as a comment or build check, and also stored in a database so you can graph changes over time to spot regressions. Probably overkill for Datasette! Window functions - oh, good point. Looks like Ubuntu shipped JSON1 support as far back as sqlite 3.11. I'll let this PR linger until there's a way to run against different SQLite versions. For now, I'm shipping this with Tests - there actually did end up being test changes to capture the undercount bug of the current implementation, so the current implementation would fail against the new tests. Perhaps a non-window function version could be written that uses |
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array facet: don't materialize unnecessary columns 1560982210 | |
1407561308 | https://github.com/simonw/datasette/pull/2008#issuecomment-1407561308 | https://api.github.com/repos/simonw/datasette/issues/2008 | IC_kwDOBm6k_c5T5a5c | cldellow 193185 | 2023-01-29T04:50:50Z | 2023-01-29T04:50:50Z | CONTRIBUTOR | I pushed a revised version which ends up being faster -- the example which currently takes 4 seconds now runs in 500ms. |
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array facet: don't materialize unnecessary columns 1560982210 | |
1407558284 | https://github.com/simonw/datasette/pull/2008#issuecomment-1407558284 | https://api.github.com/repos/simonw/datasette/issues/2008 | IC_kwDOBm6k_c5T5aKM | cldellow 193185 | 2023-01-29T04:23:58Z | 2023-01-29T04:24:27Z | CONTRIBUTOR | Ack, this PR is broken. I see now that the That fixes the overcounting, but I think can undercount when the rows have the same data, eg a view like:
will produce a count of If I guess a general solution would be to compute a window function so we have a distinct ID for each row. Will fiddle to see if I can get that working. |
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array facet: don't materialize unnecessary columns 1560982210 | |
1407470429 | https://github.com/simonw/datasette/pull/2008#issuecomment-1407470429 | https://api.github.com/repos/simonw/datasette/issues/2008 | IC_kwDOBm6k_c5T5Etd | cldellow 193185 | 2023-01-28T19:34:29Z | 2023-01-28T19:34:29Z | CONTRIBUTOR | I don't know how/if you do automated tests for performance, so I haven't changed any of the tests. |
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array facet: don't materialize unnecessary columns 1560982210 |
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