github
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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576582604 | MDU6SXNzdWU1NzY1ODI2MDQ= | 694 | datasette publish cloudrun --memory option | 9599 | closed | 0 | 8 | 2020-03-05T22:59:57Z | 2020-06-23T17:10:51Z | 2020-03-05T23:49:41Z | OWNER | Got this error deploying large (603MB) database with Cloud Run ``` X Deploying... Cloud Run error: Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable. Logs for this revi sion might contain more information. X Creating Revision... Cloud Run error: Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable. Logs for this revision might contain more information. . Routing traffic... ✓ Setting IAM Policy... Deployment failed ERROR: (gcloud.run.deploy) Cloud Run error: Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable. Logs for this revision might contain more information. ``` | 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/694/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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643510821 | MDU6SXNzdWU2NDM1MTA4MjE= | 862 | Set an upper limit on total facet suggestion time for a page | 9599 | open | 0 | 1 | 2020-06-23T03:57:55Z | 2020-06-23T03:58:48Z | OWNER | If a table has 100 columns the facet suggestion code will currently run 100 times, taking a max of `facet_suggest_time_limit_ms` which defaults to 50ms per column: https://github.com/simonw/datasette/blob/000528192eaf891118932250141dabe7a1561ece/datasette/facets.py#L142-L162 So for 100 columns, that's 100 * 50ms = 5s total time that might be spent attempting to calculate facets on a large table! I should implement a hard upper limit on the total amount of time taken suggesting facets - probably of around 500ms. If it takes longer than that the remaining columns will not be considered. | 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/862/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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642652808 | MDU6SXNzdWU2NDI2NTI4MDg= | 861 | Script to generate larger SQLite test files | 9599 | closed | 0 | 3 | 2020-06-21T22:30:58Z | 2020-06-23T03:44:18Z | 2020-06-23T03:44:18Z | OWNER | > I'll write a little script which generates a 300MB SQLite file with a bunch of tables with lots of randomly generated rows in to help test this. > > Having a tool like that which can generate larger databases with different gnarly performance characteristics will be useful for other performance work too. _Originally posted by @simonw in https://github.com/simonw/datasette/issues/859#issuecomment-647189948_ | 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/861/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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