Yet Another Kev-Value DataBase

PLAN: - [x] make yakvdb thread-safe - distinct RW locks on pages in the pool? - cannot use it in async context now: - the trait Sync is not implemented for RefCell<...> - [x] split Tree trait into pub KV-only and internal page-aware - to avoid leaking impl details leak into public API - [ ] CLI - connect to a file and explore it - lookup X64'00cafebabe' - insert X64'00cafebabe' X64'00deadbeef' - remove X64'00cafebabe' - above X64'00cafebabe' - below X64'00cafebabe' - min - max - len (iterate from min to max) - basic defragment/restore utilities - [ ] add async impl based on tokio::fs - you can't go back to sync though - somehow make feature switch to async?

Extremely simple (simplest possible?) single-file BTree-based key-value database.

Built for fun and learning: goal is to "demystify" the "database".

Operations amortized runtime complexity: * insert/remove: O(log(N) * log(K) + K) * lookup/min/max/above/below: O(log(N) * log(K))

Where: * N - number of entries in a tree * K - number of entries in a page

Binary search is run for each page (log(K)) and touches at most log(N) pages.

On insert/remove each page performs O(K) cleanup to keep keys ordered, as well as extra housekeeping is performed if necessary (split or merge of pages).

Each insert/remove gets flushed to disk for durability.

API

Demo

Just cargo run --release to run example from main.rs: * create/open database (file) * generate random key-value pairs * insert all key-value pairs * lookup all keys and check values match * iterate all keys in ascending order * iterate all keys in descending order * remove all keys and check database is empty

The typical result looks like one below.

```shell $ RUST_LOG=info cargo run --release [snip]

1M

[...] file="target/main_1M.tmp" count=1000000 page=4096 [...] insert: 28742 ms (rate=34792 op/s) [...] lookup: 5316 ms (rate=188111 op/s) [...] iter: min=000003cf1bb4e04d max=ffffe6e240320123 [...] iter: asc 553 ms (rate=1808318 op/s) n=1000000 [...] iter: desc 538 ms (rate=1858736 op/s) n=1000000 [...] remove: 27101 ms (rate=36899 op/s)

10M

[...] file="target/10M.db" count=10000000 page=4096 [...] insert: 371971 ms (rate=26883 op/s) [...] lookup: 95038 ms (rate=105221 op/s) [...] iter: min=00000244ad95c9eb max=ffffffbd837a505b [...] iter: asc 6793 ms (rate=1472103 op/s) n=10000000 [...] iter: desc 7008 ms (rate=1426940 op/s) n=10000000 [...] remove: 368056 ms (rate=27169 op/s)

100M

[...] file="target/100M.db" count=100000000 page=4096 [...] insert: 4387618 ms (rate=22791 op/s) [...] lookup: 1003484 ms (rate=99652 op/s) [...] iter: min=000000542c79d673 max=ffffffbd837a505b [...] iter: asc 74953 ms (rate=1334169 op/s) n=100000000 [...] iter: desc 73857 ms (rate=1353967 op/s) n=100000000 [...] remove: 4145790 ms (rate=24120 op/s) ```

Code

```rust use std::cell::Ref; use crate::api::error::Result; use crate::disk::block::Block; use crate::disk::file::File;

// Create new database with given pagesize let mut db: File = File::make(path, /*pagesize=*/4096).unwrap(); // Or open a database from an existing file let mut db: File = File::open(path).unwrap();

let r: Result>> = db.lookup(&b"key"); let _: Result<()> = db.insert(&b"key", &b"val"); let _: Result<()> = db.remove(&b"key");

// To iterate: db.min(), db.max(), db.above(&[u8]), db.below(&[u8]) ```

Other