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For work in a similar vein, Mikeal Rogers has recently been working on IPSQL[0] based on peer-to-peer prdered search indexes[1] built on IPFS, which shares the content-addressed nature of BitTorrent.
[0]: https://github.com/mikeal/IPSQL
[1]: https://0fps.net/2020/12/19/peer-to-peer-ordered-search-inde...
Interesting question. I looked at the source code to understand that.
SQLite knows where to look for when you open a SQLite database and you run a query, right? It just asks the underlying filesystem to provide N bytes starting from an offset using a C function, then it repeats the same operation on different portions of the file, it does its computation and everybody is happy.
The software relies on sqltorrent, which is a custom VFS for SQLite. That means that SQLite function to read data from a file stored in the filesystem is replaced by a custom function. Such custom code computes which Torrent block(s) should have the highest priority, by dividing the offset and the number of bytes that SQLite wants to read by the size of the torrent blocks. It is just a division.
See: https://github.com/bittorrent/sqltorrent/blob/master/sqltorr...
With respect to IPFS and Merkle Search Trees, can anyone "in the know" comment on how they're materially different than Probabilistic B-Trees as defined by Noms[1] and Dolt[2]? I've been playing a lot with the Noms variant (Prolly Trees) lately and have often wondered where they differ from IPFS-ish Merkle Search Trees. If at all.
[1]: https://github.com/attic-labs/noms/blob/master/doc/intro.md#...
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