A glossary of common terms used throughout Jupyter Book.
- Chunk
- Smaller, more manageable pieces of a larger dataset.
- Chunking
- The process of breaking down large amounts of data into smaller, more manageable pieces.
- Chunk shape
- The actual shape of a chunk, specifying the number of elements in each dimension.
- Chunk size
- The size of the chunk in terms of memory, which depends on the chunk shape.
- Coordinate Reference System
- A framework used to precisely measure locations on the surface of Earth as coordinates.
- Larger-than-memory
- A dataset whose memory footprint is too large to fit into memory all at once.
- Partial Chunk
- The final chunk along a dimensions of a dataset that is not completely full of data due to the chosen chunk shape not being an integer divisor of the dataset’s dimensions.
- Rechunking
- The process of changing the current chunk shape of a dataset to another chunk shape.
- Stored chunks
- The chunks that are physically stored on disk.
- Virtual Zarr Store
- A virtual representation of a Zarr store generated by mapping any number of real datasets in individual files (e.g., NetCDF/HDF5, GRIB2, TIFF) together into a single, sliceable dataset via an interface layer, which contains information about the original files (e.g., chunking, compression, etc.).