issue_comments

Table actions

1 row where author_association = "MEMBER", issue = 995207525 and user = 5635139 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

  • max-sixty · 1 ✖

issue 1

  • combining 2 arrays with xr.merge() causes temporary spike in memory usage ~3x the combined size of the arrays · 1 ✖

author_association 1

  • MEMBER · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
918583565 https://github.com/pydata/xarray/issues/5790#issuecomment-918583565 https://api.github.com/repos/pydata/xarray/issues/5790 IC_kwDOAMm_X842wHkN max-sixty 5635139 2021-09-13T21:15:56Z 2021-09-13T21:15:56Z MEMBER

I'll let others respond, but temporary memory usage of 3X sounds within expectations, albeit towards the higher end.

If we can reduce it that would be great, but probably needs someone to work on this fairly methodically.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   combining 2 arrays with xr.merge() causes temporary spike in memory usage ~3x the combined size of the arrays 995207525

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);