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A minimal in-memory database with relational algebraic expressions as queries

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codd

codd is a library for evaluating typed relational expressions in a minimal in-memory database with incrementally maintained views. codd is primarily developed to support an implementation of razor based on relational algebra, however, its design is consistent with common concepts of database theory and may be used as a minimal general purpose database.

Storage and incremental view maintenance follow datafrog and DBSP:

  • Every relation and view is an Instance<T> holding sorted, immutable batches of weighted tuples (a Z-set). Relations have set semantics (weights are kept at zero or one, so insert of a present tuple and retract of an absent one are no-ops); views keep the number of derivations of each tuple as its weight.
  • Changes arrive in to_add, are folded in order into one recent change, propagated to dependent views as weighted deltas, and then merged into the stable batches. Linear operators pass deltas through, bilinear operators (join, product, intersect) use ΔL⋈R + L⋈ΔR + ΔL⋈ΔR, and the non-linear ones (Difference as an antijoin, Distinct) recompute the affected tuples from the current counts of their operands.
  • Batches are shared between a database and its clones, so cloning is cheap and clones diverge independently, including by retraction.

In contrast, codd distinguishes relation instances from views and offers the trait Expression<T> and types that implement Expression<T> to query a database.

The relational algebra and database terminology in codd is adopted from Alice's book.

Build

codd is written in Rust. You can use Rust 1.54.0 or newer to build the library:

git clone https://github.com/salmans/codd.git
cd codd
cargo build

Example: music

Add codd to your project dependencies in Cargo.toml:

[dependencies]
codd = "0.1"

Use codd in your code:

use codd::{Database, Error, Expression};

Create a new database:

    let mut music = Database::new(); // music database

Add relations to the database:

    // `musician`, `band` and `song` are `Relation` expressions.
    let musician = music.add_relation("musician")?;
    let band = music.add_relation("band")?;
    let song = music.add_relation("song")?;

Insert tuples (records) to your database relations:

    music.insert(
        &musician,
        vec![
            Musician {
                name: "John Petrucci".into(),
                band: Some("Dream Theater".into()),
                instruments: vec![Guitar],
            },
            Musician {
                name: "Taylor Swift".into(),
                band: None,
                instruments: vec![Vocals],
            },
            // more tuples...
        ]
        .into(),
    )?;
    
    // add tuples to other relations...

Construct query expressions and evaluate them in the database:

    let guitarist_name = musician
        .builder()
        .select(|m| m.instruments.contains(&Guitar))
        .project(|g| g.name.to_string())
        .build();

    assert_eq!(
        vec![
            "Alex Turner".to_string(),
            "Conor Mason".into(),
            "John Petrucci".into(),
        ],
        music.evaluate(&guitarist_name)?.into_tuples() // evaluate the query and get the results
    );

Here is a more complex query:

    let dt_member = musician
        .builder()
        .with_key(|m| m.band.clone())
            // use `band` as the join key for `musician`
        .join(band.builder().with_key(|b| Some(b.name.clone()))) 
            // join with `band` with `name` as the join key
        .on(|_, m, b| (m.name.to_string(), b.name.to_string()))
            // combine tuples of `musician` and `band` in a new relation
        .select(|m| m.1 == "Dream Theater")
        .project(|m| m.0.to_string())
        .build();

    assert_eq!(
        vec!["John Petrucci".to_string(), "Jordan Rudess".into()],
        music.evaluate(&dt_member)?.into_tuples()
    );

Store views of expressions:

    let dt_member_view = music.store_view(dt_members)?; // view on `dt_member`
    let drummer_view = music.store_view(                // drummers view
        musician
            .builder()
            .select(|m| m.instruments.contains(&Drums))
            .build(),
    )?;

    // inserting more tuples:
    music.insert(
        &musician,
        vec![
            Musician {
                name: "John Myung".into(),
                band: Some("Dream Theater".into()),
                instruments: vec![Guitar],
            },
            Musician {
                name: "Mike Mangini".into(),
                band: Some("Dream Theater".into()),
                instruments: vec![Drums],
            },
        ]
        .into(),
    )?;

    // views are up-to-date:
    assert_eq!(
        vec![
            Musician {
                name: "Lars Ulrich".into(),
                band: Some("Metallica".into()),
                instruments: vec![Drums]
            },
            Musician {
                name: "Mike Mangini".into(),
                band: Some("Dream Theater".into()),
                instruments: vec![Drums]
            }
        ],
        music.evaluate(&drummer_view)?.into_tuples()
    );
    assert_eq!(
        vec![
            "John Myung".to_string(),
            "John Petrucci".into(),
            "Jordan Rudess".into(),
            "Mike Mangini".into()
        ],
        music.evaluate(&dt_member_view)?.into_tuples()
    );

    Ok(())
}

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A minimal in-memory database with relational algebraic expressions as queries

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