issue_comments

Table actions

7 rows where author_association = "MEMBER" and issue = 776042664 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

issue 1

  • Faster interp · 7 ✖

author_association 1

  • MEMBER · 7 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
832044344 https://github.com/pydata/xarray/pull/4740#issuecomment-832044344 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDgzMjA0NDM0NA== dcherian 2448579 2021-05-04T15:45:50Z 2021-05-04T15:46:07Z MEMBER

OK should be good to merge. We can set the meta in a future version (It did not work on 2.15.0 which is the dask version we can bump to right now)

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
831944002 https://github.com/pydata/xarray/pull/4740#issuecomment-831944002 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDgzMTk0NDAwMg== dcherian 2448579 2021-05-04T13:31:52Z 2021-05-04T13:31:52Z MEMBER

Test failure is real and looks like some bug with dtype vs meta in our min dask version. I've bumped dask to see if it fixes it.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
778853034 https://github.com/pydata/xarray/pull/4740#issuecomment-778853034 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDc3ODg1MzAzNA== Illviljan 14371165 2021-02-14T22:33:39Z 2021-02-14T22:33:39Z MEMBER

@max-sixty It's the profiler Spyder has. It's been quite useful for hunting down various bottlenecks but it has its quirks as well. 

{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
778841404 https://github.com/pydata/xarray/pull/4740#issuecomment-778841404 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDc3ODg0MTQwNA== max-sixty 5635139 2021-02-14T21:03:02Z 2021-02-14T21:03:02Z MEMBER

Thanks for pinging @Illviljan . Looks good from my side too.

@Illviljan what's that profiling tool you're using? The hierarchy of functions looks useful!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
767770962 https://github.com/pydata/xarray/pull/4740#issuecomment-767770962 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDc2Nzc3MDk2Mg== Illviljan 14371165 2021-01-26T19:22:33Z 2021-01-26T19:22:33Z MEMBER

Well, I think this is good enough. It's quite an improvement already and I think the error will disappear if the CI is rerun. 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
752690563 https://github.com/pydata/xarray/pull/4740#issuecomment-752690563 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDc1MjY5MDU2Mw== dcherian 2448579 2020-12-30T17:00:25Z 2020-12-30T17:00:25Z MEMBER

Another more difficult idea is to improve the dask arrays shape-calculation. Perhaps saving the value and only do the cached_cumsum call when the chunks actually has changed?

Thanks for opening an issue on the dask side.

On the xarray side, we want to cache some of these properties, see #3514

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664
752286931 https://github.com/pydata/xarray/pull/4740#issuecomment-752286931 https://api.github.com/repos/pydata/xarray/issues/4740 MDEyOklzc3VlQ29tbWVudDc1MjI4NjkzMQ== Illviljan 14371165 2020-12-30T00:36:24Z 2020-12-30T00:36:24Z MEMBER

Looking good!

One thing I notice now with these changes is that ndim is now creeping up as the 2nd worst time consumer:

An easy improvement to this is adding ndim = var.ndim and replacing all the var.ndim around interp_func. That reduces the number of calls from 68000 to 58000. Another more difficult idea is to improve the dask arrays shape-calculation. Perhaps saving the value and only do the cached_cumsum call when the chunks actually has changed?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Faster interp 776042664

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]);