1 unstable release
0.1.0 | Nov 1, 2020 |
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#304 in Database implementations
200KB
5K
SLoC
codd
codd
is a library for evaluating typed relational expressions in a monotonically growing minimal database in memory. 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.
The implementation of database instances in codd
is borrowed from datafrog
:
Instance<T>
(Variable<T>
indatafrog
) contains tuples of typeT
,- Incremental view maintenance is implemented by maintaining tuples of
Instance<T>
in three sets ofto_add
(candidate tuples to be inserted),recent
(recently added tuples), andstable
(old tuples that have been reflected in all views).
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 1.46.0 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(())
}
Dependencies
~285–760KB
~18K SLoC