Unidata is in the process of developing a Zarr  based variant of netcdf. As part of this effort, it was necessary to implement some support for chunking. Specifically, the problem to be solved was that of extracting a hyperslab of data from an n-dimensional variable (array in Zarr parlance) that has been divided into chunks (in the HDF5 sense). Each chunk is stored independently in the data storage -- Amazon S3, for example.
The algorithm takes a series of R slices of the form (first,stop,stride), where R is the rank of the variable. Note that a slice of the form (first, count, stride), as used by netcdf, is equivalent because stop = first + count*stride. These slices form a hyperslab.
The goal is to compute the set of chunks that intersect the hyperslab and to then extract the relevant data from that set of chunks to produce the hyperslab.[Read More]