Crates.io | lattices |
lib.rs | lattices |
version | 0.5.8 |
source | src |
created_at | 2023-05-03 02:06:18.010815 |
updated_at | 2024-11-08 19:26:19.712601 |
description | Lattice data types for simplifying distributed state by providing associativity, commutativity, and idempotence. |
homepage | |
repository | |
max_upload_size | |
id | 855071 |
size | 364,208 |
lattices
CrateThe lattices
crate provides ergonomic and composable lattice types. You can also implement custom
lattices via a few simple traits.
Lattices are an incredibly powerful mathematical concept which can greatly simplify the trickiness of distributed computing. They align very well with the reality of what happens physically in a distributed system: messages can always arrive out-of-order or duplicated. But if that data is represented as lattices then all machines will always reach the same end result simply by merging the data together. One popular way that lattices are currently used in distributed systems is as the data underlying Conflict-free Replicated Data Types (CRDTs).
Lattices also allow us to harness the power of the CALM Theorem: "a program has a consistent, coordination-free distributed implementation if and only if it is monotonic." Lattice state is always monotonic, meaning any part of a distributed system built on lattice state can be freely distributed with no coordination overhead. The goal of the Hydro Project is to allow users to write programs that automatically scale and distribute effortlessly.
For more information on the underlying mathematics of lattices and monotonicity, take a look at Lattice Math section of the Hydroflow Book and Section 2 of the Hydroflow Thesis (2021).
Take a look at the lattice
rustdocs.
lattices
provides implementations of common lattice types:
Min<T>
] and [Max<T>
] - totally-ordered lattices.set_union::SetUnion<T>
] - set-union lattice of scalar values.map_union::MapUnion<K, Lat>
] - scalar keys with nested lattice values.union_find::UnionFind<K>
] - union partitions of a set of scalar values.VecUnion<Lat>
] - growing Vec
of nested lattices, like MapUnion<<usize, Lat>>
but without missing entries.WithBot<Lat>
] - wraps a lattice in Option
with None
as the new bottom value.WithTop<Lat>
] - wraps a lattice in Option
with None
as the new top value.Pair<LatA, LatB>
] - product of two nested lattices.DomPair<LatKey, LatVal>
]* - a versioned pair where the LatKey
dominates the LatVal
.Conflict<T>
]* - adds a "conflict" top to domain T
. Merging inequal T
s results in top.Point<T, *>
]* - a single "point lattice" value which cannot be merged with any inequal value.()
- the "unit" lattice, a "point lattice" with unit ()
as the only value in the domain.*Special implementations which do not obey all lattice properties but are still useful under certain circumstances.
Additionally, custom lattices can be made by implementing the traits below.
A type becomes a lattice by implementing one or more traits starting with Merge
. These traits
are already implemented for all the provided lattice types.
Merge
The main trait is [Merge
], which defines a lattice merge function (AKA "join" or "least upper
bound"). Implementors must define the [Merge::merge
] method which does a merge in-place into
&mut self
. The method must return true
if self
was modified (i.e. the value got larger in the
lattice partial order) and false
otherwise (i.e. other
was smaller than self
). The [Merge::merge_owned
]
function, which merges two owned values, is provided.
The merge
method must be associative, commutative, and idempotent. This is not checked by the
compiler, but the implementor can use the [test::check_lattice_properties
] method to spot-check
these properties on a collection of values.
PartialOrd
, LatticeOrd
, and NaiveLatticeOrd
Rust already has a trait for partial orders, [PartialOrd
], which should be implemented on lattice
types. However that trait is not specific to lattice partial orders, therefore we provide the[LatticeOrd<Rhs>
]: PartialOrd<Rhs>
marker trait to denote when a PartialOrd
implementation is a lattice partial order. LatticeOrd
must always agree with the Merge
function.
Additionally, the sealed [NaiveLatticeOrd
] trait is provided on all lattice types that implement
Merge
and Clone
. This trait provides a naive_cmp
method which derives a lattice order from
the Merge
function directly. However the implementation is generally slow and inefficient.
Implementors should use the [test::check_partial_ord_properties
] method to check their
PartialOrd
implementation, and should use the [test::check_lattice_ord
] to ensure the partial
order agrees with the Merge
-derived NaiveLatticeOrd
order.
LatticeFrom
[LatticeFrom
] is equivalent to the [std::convert::From
] trait but specific to lattices.
LatticeFrom
should be implemented only between different representations of the same lattice
type, e.g. between [set_union::SetUnionBTreeSet
] and [set_union::SetUnionHashSet
]. For compound
lattice (lattices with nested lattice types), the LatticeFrom
implementation should be recursive
for those nested lattices.
IsBot
, IsTop
, and Default
A bottom (⊥) is strictly less than all other values. A top (⊤) is strictly greater than all other
values. IsBot::is_bot
and IsTop::is_top
determine if a lattice instance is top or bottom
respectively.
For lattice types, Default::default()
must create a bottom value. IsBot::is_bot(&Default::default())
should always return true for all lattice types.
Atomize
[Atomize::atomize
] converts a lattice point into a bunch of smaller lattice points. When these
"atoms" are merged together they will form the original lattice point. See the docs for more
precise semantics.
DeepReveal
[DeepReveal
] allows recursive "revealing" of the underlying data within latties. Particularly
useful for revealing nested lattices.