Pure AWS S3 backend

[wlandau]

Prework

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Proposal

Similar to #2, but directly implemented on top of AWS S3 through something like aws.s3, paws, or botor. Use the historical versioning and tagging capabilities of buckets.

[wlandau]

Probably precedes #2. May actually want to look at DVC first. It may already do a lot of the stuff I mention below.

[wlandau]

Setback: an S3 object can only have up to 10 tags. Poses a problem if a target is part of more than 10 snapshots, which is likely to come up for almost all projects.

[wlandau]

Another idea: the metadata already has hashes, which is half the battle for a key-value store.

Snapshot

1. Commit _targets/meta/meta to a local git repo. Do not commit _targets/objects.
2. For each target in _targets/meta/meta, upload the file in _targets/objects an S3 bucket. In the bucket, the object name should be the hash recorded in _targets/meta/meta. If the object already exists in the bucket, skip the upload.

Checkout

1. Check out the metadata file.
2. For each target in the metadata, if the hash in _targets/meta/meta disagrees with the actual hash of the file, attempt to find the correct hash in the bucket and download the object to _targets/objects/.

Hopefully (2) will be possible without cloning a bunch of infrastructure from targets.

Status

Git status of _targets/meta/meta + checking the hashes of _targets/meta/meta vs _targets/objects files vs the bucket.

[wlandau]

Closing in favor of ropensci/targets#711

[wlandau]

Reopening. Relative to native AWS versioning in targets, an AWS gittargets backend would allow less frequent uploads and allow users to opt in later in the project’s life cycle.

[wlandau]

On reflection: if you're already using AWS S3, then https://books.ropensci.org/targets/cloud-storage.html is way better.