Handling large collections of files

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In certain domains, notably AI and Machine Learning, it is common to have to manage very large collections of files, meaning hundreds of thousands or more. The individual files may be fairly small, e.g. less than a few hundred kilobytes. In these cases, a problem arises due to filesystem quotas on Compute Canada clusters that limit the number of filesystem objects. So how can a user or group of users store these necessary data sets on the cluster? In this page we will present a variety of different solutions, each with its own pros and cons, so you may judge for yourself which is an appropriate one for you.

DAR

A disk archive utility. See Dar.

git

When working with Git, over time the number of files in the hidden .git repository subdirectory can grow significantly. Using git repack will pack many of the files together into a few large database files and greatly speed up Git's operations.