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2 rows where author_association = "OWNER", comments = 32, repo = 107914493 and type = "issue" sorted by updated_at descending
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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | pull_request | body | repo | type | active_lock_reason | performed_via_github_app | reactions | draft | state_reason |
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1217759117 | I_kwDOBm6k_c5IlYeN | 1727 | Research: demonstrate if parallel SQL queries are worthwhile | simonw 9599 | open | 0 | 32 | 2022-04-27T18:54:21Z | 2022-09-26T14:48:31Z | OWNER | I added parallel SQL query execution here: - https://github.com/simonw/datasette/issues/1723 My hunch is that this will take advantage of multiple cores, since Python's I'd really like to prove this is the case though. Just not sure how to do it! Larger question: is this performance optimization actually improving performance at all? Under what circumstances is it worthwhile? |
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770436876 | MDU6SXNzdWU3NzA0MzY4NzY= | 1150 | Maintain an in-memory SQLite table of connected databases and their tables | simonw 9599 | closed | 0 | Datasette 1.0 3268330 | 32 | 2020-12-17T23:02:13Z | 2020-12-27T14:51:39Z | 2020-12-18T22:34:12Z | OWNER | I want Datasette to have its own internal metadata about connected tables, to power features like a paginated searchable homepage in #461. I want this to be a SQLite table. This could also be part of the directory scanning mechanism prototyped in #672 - where Datasette can be set to continually scan a directory for new database files that it can serve. Also relevant to the Datasette Library concept in #417. |
datasette 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/1150/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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