more efficient caching
- Dominant language
- Python
- Stars
- 28
- Forks
- 37
- Avg merge
- 1d 17h
- Merged PRs (30d)
- 9
Description
the two imaging dandisets are large and will continuously run into caching efficiency. giacomo’s is only about 5TB but lee’s is around 120TB and growing. any kind of bids-related rewrite could thus involve significant checksum computation overhead that could take weeks. i would say it’s time to consider efficiency of both zarr versions and large files qua local checksum computation. i would say the overall problem is to ensure that a local directory can be checksummed efficiently.
one easy way is to maintain a table of mtime+size checksum alongside a dandi-etag in the cache. a rename or a move of a file doesn’t change this checksum and can be copied even across filesystems with both of those elements maintained. thus having a table that is simply an LRU type cache would allow for local movement instead of tying it to a path name.
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