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priority 1
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- [x] add `deltaEncode` chunks function
- [x] do not merge consecutive smaller chunks as these could be stored as
chunks if no similar chunk is found. Thus, it will need to be of
`chunkSize` or less. Otherwise, it could not be possibly used for
deduplication.
- [ ] read individual files
- [ ] properly store information to be DNA encoded
- [ ] tar source to keep files metadata ?
- [x] store chunks compressed
- [x] compress before storing
- [x] decompress before loading
- [ ] store compressed chunks into tracks of `trackSize` (1024o)
- [x] add chunk cache to uniquely store chunks in RAM
- [x] better tests for `(*Repo).Commit`
priority 2
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- [ ] use more the `Reader` API (which is analogous to the `IOStream` in Java)
- [ ] refactor `matchStream` as right now it is quite complex
- [x] better test for `(*Repo).matchStream`
- [ ] compress partial chunks (`TempChunks` for now)
- [ ] tail packing of `PartialChunks` (this Struct does not exist yet as it is in
fact just `TempChunks` for now)
- [ ] option to commit without deltas to save new base chunks
- [ ] custom binary marshal and unmarshal for chunks
- [x] use `loadChunkContent` in `loadChunks`
- [ ] TODO: store hashes for faster maps rebuild
- [ ] try [Fdelta](https://github.com/amlwwalker/fdelta) and
[Xdelta](https://github.com/nine-lives-later/go-xdelta) instead of Bsdiff
- [ ] maybe use an LRU cache instead of the current FIFO one.
- [x] remove `LoadedChunk` and only use `StoredChunk` instead now that the cache
is implemented
reunion 7/09
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- [ ] save recipe consecutive chunks as extents
- [ ] store recipe and files incrementally
- [ ] compress recipe
- [ ] make size comparison between recipe and chunks with some datasets
ideas
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1. Would it be a good idea to store the compressed size for each chunk?
Maybe this way we could only load the chunks needed for each file read.
2. Implement the `fs` interface of Go? Not sure if this will be useful.
3. If we don't need to reduce read amplification we could compress all chunks if
it reduces the space used.
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