issue_comments

Table actions

3 rows where author_association = "MEMBER", issue = 129150619 and user = 1217238 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

These facets timed out: author_association, issue

user 1

  • shoyer · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
184390218 https://github.com/pydata/xarray/issues/729#issuecomment-184390218 https://api.github.com/repos/pydata/xarray/issues/729 MDEyOklzc3VlQ29tbWVudDE4NDM5MDIxOA== shoyer 1217238 2016-02-15T20:57:35Z 2016-02-15T20:57:35Z MEMBER

I just downloaded the data, too, and will see if can simply the task graph into something understandable by humans :).

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Cannot write dask Dataset to NetCDF file 129150619
178661780 https://github.com/pydata/xarray/issues/729#issuecomment-178661780 https://api.github.com/repos/pydata/xarray/issues/729 MDEyOklzc3VlQ29tbWVudDE3ODY2MTc4MA== shoyer 1217238 2016-02-02T16:14:24Z 2016-02-02T16:14:24Z MEMBER

Something like einsum or a broadcasting matrix multiplication could help a little bit here, by replacing (M * FLUX).sum('Paliers') with M.dot(FLUX, dim='Paliers') and thereby reducing peak memory consumption, but even there I'm calculating peak chunk size at 950000 elements. This should be totally fine on most machines.

@mrocklin Unfortunately, I don't know an easy way to create a copy of a netCDF file with random data, but that's a good idea for a little project....

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Cannot write dask Dataset to NetCDF file 129150619
176362189 https://github.com/pydata/xarray/issues/729#issuecomment-176362189 https://api.github.com/repos/pydata/xarray/issues/729 MDEyOklzc3VlQ29tbWVudDE3NjM2MjE4OQ== shoyer 1217238 2016-01-28T19:37:17Z 2016-01-28T19:37:17Z MEMBER

This is almost certainly an issue with dask's scheduler. cc @mrocklin

Could you share a summary of how you create this dataset? Is it something that should be possible to calculate in a single pass over the data?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Cannot write dask Dataset to NetCDF file 129150619

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]);