html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/4714#issuecomment-748486801,https://api.github.com/repos/pydata/xarray/issues/4714,748486801,MDEyOklzc3VlQ29tbWVudDc0ODQ4NjgwMQ==,18488,2020-12-19T15:13:36Z,2020-12-19T15:14:59Z,NONE,"Thanks for the response. I think `reindex` would need to be changed as well because this code:

```python
sensor_data.reindex({
    'time': [1],
    'sensor': ['A', 'B']
}, method='ffill')
```

Is not equivalent to this code:
```python
sensor_data.reindex({
    'time': [1],
    'sensor': ['A', 'B']
}).ffill(dim='time').ffill(dim='sensor')
```

So if I understand your `to_dataset` idea correctly, you are proposing:

```python
ds = sensor_data.to_dataset(dim='sensor')
xr.concat([
    ds[sensor].sel({'time': time}, method='ffill', drop=True)
    for sensor, time in zip(['A', 'A', 'A', 'B', 'C'], [0, 1, 2, 0, 0])
], dim='sample')
```

I guess this works but it's a bit cumbersome and unlikely to be fast. I think there must be something I'm not understanding here - I'm not familiar with all the nuances of the `xarray` api.

Your idea of `reindex` followed by `sel` is an interesting one, but it does do something slightly different than what I was asking for: it does not fail if one of the sensors in the query list is missing, but rather inserts a NaN. I suppose you could fix this by doing an extra check afterwards, assuming that your original pre-reindex data contained no NaNs.

In general `min(S*N,T*N)` could be much larger than `S*T`, so for big queries it's quite possible that you wouldn't have enough space to allocate the intermediate even if you could fit 100s of copies of the original `S*T` matrix. Using a dask cluster would make this situation less likely of course, but it seems like it would be better to avoid all this copying (even on a beefy cluster) even if just for performance reasons.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653
https://github.com/pydata/xarray/issues/4714#issuecomment-748479287,https://api.github.com/repos/pydata/xarray/issues/4714,748479287,MDEyOklzc3VlQ29tbWVudDc0ODQ3OTI4Nw==,18488,2020-12-19T14:06:36Z,2020-12-19T14:06:36Z,NONE,"Thanks for the suggestion. One issue with this alternative is it creates a potentially large intermediate object.

If you have T times and S sensors, and want to sample them at N (time, sensor) pairs, then the intermediate object with your approach has size `T*N` (if you index sensors first) or `S*N` (if you index time first). If you can index both dimensions in one `sel` call then we should only need to allocate memory for the result of size `N`, which is considerably better.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653
https://github.com/pydata/xarray/issues/4714#issuecomment-748477889,https://api.github.com/repos/pydata/xarray/issues/4714,748477889,MDEyOklzc3VlQ29tbWVudDc0ODQ3Nzg4OQ==,18488,2020-12-19T13:53:53Z,2020-12-19T13:53:53Z,NONE,I guess it would also make sense to have this in `reindex` if you did decide to add it.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653