issue_comments

Sorry, my comment in https://github.com/pydata/xarray/issues/4428#issuecomment-711034128 was incorrect in a couple ways

1. We still do the splitting, even when slicing with an out-of-order indexer. Checking on if that's appropriate.
2. I'm checking in on a logic bug when computing the number of chunks. I don't think we properly handle non-uniform chunking on the other axes.

I assume that the indices [np.argsort(da.x.data)] are not going to be monotonically increasing. That induces a different slicing pattern. The docs in https://docs.dask.org/en/latest/array-slicing.html#efficiency describe the case where the indices are sorted, but doesn't discuss the non-sorted case (yet).

@TomAugspurger @jbusecke is seeing some funny behaviour in https://github.com/jbusecke/cmip6_preprocessing/issues/58

Here's a reproducer ``` python import dask import numpy as np import xarray as xr

dask.config.set( **{ "array.slicing.split_large_chunks": True, "array.chunk-size": "24 MiB", } )

da = xr.DataArray( dask.array.random.random((10, 1000, 2000), chunks=(-1, -1, 200)), dims=["x", "y", "time"], coords={"x": [3, 4, 5, 6, 7, 9, 8, 0, 2, 1]}, ) da ```

Which is basically

python da.data[np.argsort(da.x.data), ...]

I don't understand why its rechunking when we are indexing with a list along a dimension with a single chunk...

Closing the loop here, with https://github.com/dask/dask/pull/6665 the behavior of Dask=2.25.0 should be restored (possibly with a warning about creating large chunks).

So this can probably be closed, though there may be parts of xarray that should be updated to avoid creating large chunks, or we could rely on the user to do that through the dask config system.

This looks like a consequence of https://github.com/dask/dask/pull/6514 . That change helps with cases like https://github.com/pydata/xarray/issues/4112

sortby is basically an isel indexing operation; so dask is automatically rechunking to make chunks with size < the default. You could fix this by setting an appropriate value in array.chunk-size either temporarily or permanently

python with dask.config.set({"array.chunk-size": "256MiB"}): # or appropriate value ...