Trigger computation, keeping data as chunked arrays. This operation can be used to trigger computation on underlying dask arrays, similar to ``.compute()`` or ``.load()``. However this operation keeps the data as dask arrays. This is particularly useful when using t
(self, **kwargs)
| 820 | return self |
| 821 | |
| 822 | def persist(self, **kwargs) -> Self: |
| 823 | """Trigger computation, keeping data as chunked arrays. |
| 824 | |
| 825 | This operation can be used to trigger computation on underlying dask |
| 826 | arrays, similar to ``.compute()`` or ``.load()``. However this |
| 827 | operation keeps the data as dask arrays. This is particularly useful |
| 828 | when using the dask.distributed scheduler and you want to load a large |
| 829 | amount of data into distributed memory. |
| 830 | Like compute (but unlike load), the original dataset is left unaltered. |
| 831 | |
| 832 | Parameters |
| 833 | ---------- |
| 834 | **kwargs : dict |
| 835 | Additional keyword arguments passed on to ``dask.persist``. |
| 836 | |
| 837 | Returns |
| 838 | ------- |
| 839 | object : Dataset |
| 840 | New object with all dask-backed coordinates and data variables as persisted dask arrays. |
| 841 | |
| 842 | See Also |
| 843 | -------- |
| 844 | dask.persist |
| 845 | """ |
| 846 | new = self.copy(deep=False) |
| 847 | return new._persist_inplace(**kwargs) |
| 848 | |
| 849 | @classmethod |
| 850 | def _construct_direct( |