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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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339388215 | https://github.com/simonw/datasette/issues/38#issuecomment-339388215 | https://api.github.com/repos/simonw/datasette/issues/38 | MDEyOklzc3VlQ29tbWVudDMzOTM4ODIxNQ== | simonw 9599 | 2017-10-25T16:25:45Z | 2017-10-25T16:25:45Z | OWNER | First experiment: hook up an iterative CSV dump (just because that’s a tiny bit easier to get started with than iterative a JSON). Have it execute a big select statement and then iterate through the result set 100 rows at a time using sqite fetchmany() - also have it async sleep for a second in between each batch of 100. Can this work without needing python threads? | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Experiment with patterns for concurrent long running queries 268462768 | |
339388771 | https://github.com/simonw/datasette/issues/38#issuecomment-339388771 | https://api.github.com/repos/simonw/datasette/issues/38 | MDEyOklzc3VlQ29tbWVudDMzOTM4ODc3MQ== | simonw 9599 | 2017-10-25T16:27:29Z | 2017-10-25T16:27:29Z | OWNER | If this does work, I need to figure it what to do about the HTML view. ASsuming I can iteratively produce JSON and CSV, what to do about HTML? One option: render the first 500 rows as HTML, then hand off to an infinite scroll experience that iteratively loads more rows as JSON. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Experiment with patterns for concurrent long running queries 268462768 | |
339389105 | https://github.com/simonw/datasette/issues/38#issuecomment-339389105 | https://api.github.com/repos/simonw/datasette/issues/38 | MDEyOklzc3VlQ29tbWVudDMzOTM4OTEwNQ== | simonw 9599 | 2017-10-25T16:28:39Z | 2017-10-25T16:28:39Z | OWNER | The gold standard here is to be able to serve up increasingly large datasets without blocking the event loop and while using a sustainable amount of RAM | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Experiment with patterns for concurrent long running queries 268462768 | |
339389328 | https://github.com/simonw/datasette/issues/38#issuecomment-339389328 | https://api.github.com/repos/simonw/datasette/issues/38 | MDEyOklzc3VlQ29tbWVudDMzOTM4OTMyOA== | simonw 9599 | 2017-10-25T16:29:23Z | 2017-10-25T16:29:23Z | OWNER | Ideally we can get some serious gains from the fact that our database file is opened with the immutable option. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Experiment with patterns for concurrent long running queries 268462768 | |
392601114 | https://github.com/simonw/datasette/issues/38#issuecomment-392601114 | https://api.github.com/repos/simonw/datasette/issues/38 | MDEyOklzc3VlQ29tbWVudDM5MjYwMTExNA== | simonw 9599 | 2018-05-28T20:47:31Z | 2018-05-28T20:47:31Z | OWNER | I think the way Datasette executes SQL queries in a thread pool introduced in #45 is a good solution for this ticket. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | Experiment with patterns for concurrent long running queries 268462768 |
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