Glossary

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.).