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Update wording for ChunkCachedArray in performance guide #2905

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Update wording for ChunkCachedArray in performance guide #2905

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2 changes: 1 addition & 1 deletion docs/user_guide/examples/explanation_performance.md
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Expand Up @@ -40,7 +40,7 @@ This will make Parcels use `numpy` functions in the interpolation routines, whic

_Uses Parcels Backend: ChunkCachedArray_

**Best for: large Datasets (more than a few GB) and particles distributed over the entire domain**
**Best for: large Datasets (more than a few GB) and particles in only a small region of the domain**

If your Dataset is so large that it doesn't fit into memory, you can use the {py:func}`parcels.FieldSet.to_chunk_cached_arrays()`.
This constructs a cache where individual (dask) chunks of data are stored.
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