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2 rows where "created_at" is on date 2021-08-25 and user = 2670795 sorted by id
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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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905899177 | https://github.com/simonw/datasette/issues/859#issuecomment-905899177 | https://api.github.com/repos/simonw/datasette/issues/859 | IC_kwDOBm6k_c41_uyp | brandonrobertz 2670795 | 2021-08-25T21:48:00Z | 2021-08-25T21:48:00Z | CONTRIBUTOR | Upon first stab, there's two issues here: - DB/table/row counts (as discussed above). This isn't too bad if the DBs are actually above the MAX limit check. - Populating the internal DB. On first load of a giant set of DBs, it can take 10-20 mins to populate. By altering datasette and persisting the internal DB to disk, this problem is vastly improved, but I'm sure this will cause problems elsewhere. |
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Database page loads too slowly with many large tables (due to table counts) 642572841 | |
905904540 | https://github.com/simonw/datasette/issues/859#issuecomment-905904540 | https://api.github.com/repos/simonw/datasette/issues/859 | IC_kwDOBm6k_c41_wGc | brandonrobertz 2670795 | 2021-08-25T21:59:14Z | 2021-08-25T21:59:55Z | CONTRIBUTOR | I did two tests: one with 1000 5-30mb DBs and a second with 20 multi gig DBs. For the second, I created them like so:
This was for deciding whether to use lots of small DBs or to group things into a smaller number of bigger DBs. The second strategy wins. By simply persisting the |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Database page loads too slowly with many large tables (due to table counts) 642572841 |
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