issue_comments
1 row where user = 5499680 sorted by updated_at descending
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| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 267177054 | https://github.com/pydata/xarray/issues/992#issuecomment-267177054 | https://api.github.com/repos/pydata/xarray/issues/992 | MDEyOklzc3VlQ29tbWVudDI2NzE3NzA1NA== | chrisb13 5499680 | 2016-12-14T22:28:31Z | 2016-12-14T22:28:31Z | NONE | Useful for me too. For the time being there's also this hack (I haven't tested).. http://stackoverflow.com/questions/28598485/how-to-convert-fixed-size-dimension-to-unlimited-in-a-netcdf-file |
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} |
Creating unlimited dimensions with xarray.Dataset.to_netcdf 173773358 |
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CREATE TABLE [issue_comments] (
[html_url] TEXT,
[issue_url] TEXT,
[id] INTEGER PRIMARY KEY,
[node_id] TEXT,
[user] INTEGER REFERENCES [users]([id]),
[created_at] TEXT,
[updated_at] TEXT,
[author_association] TEXT,
[body] TEXT,
[reactions] TEXT,
[performed_via_github_app] TEXT,
[issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
ON [issue_comments] ([user]);
user 1