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1 row where reactions = "{"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0}" and "updated_at" is on date 2020-06-16 sorted by created_at descending
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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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645030262 | https://github.com/simonw/datasette/issues/850#issuecomment-645030262 | https://api.github.com/repos/simonw/datasette/issues/850 | MDEyOklzc3VlQ29tbWVudDY0NTAzMDI2Mg== | simonw 9599 | 2020-06-16T21:51:01Z | 2020-06-16T21:51:39Z | OWNER | File locking is interesting here. https://docs.aws.amazon.com/lambda/latest/dg/services-efs.html > Amazon EFS supports [file locking](https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html#consistency) to prevent corruption if multiple functions try to write to the same file system at the same time. Locking in Amazon EFS follows the NFS v4.1 protocol for advisory locking, and enables your applications to use both whole file and byte range locks. SQLite can apparently work on NFS v4.1. I think I'd rather set things up so there's only ever one writer - so a Datasette instance could scale reads by running lots more lambda functions but only one function ever writes to a file at a time. Not sure if that's feasible with Lambda though - maybe by adding some additional shared state mechanism like Redis? | {"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0} | Proof of concept for Datasette on AWS Lambda with EFS 639993467 |
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updated_at (date) 1 ✖