Thread-safe edge mutation (#114)

* Implement EdgeMutation for directed AL

* Thread-safe directed adjacency list graph

* Generalize add_edge to support edge values

* Document new mutation traits

* Impl mutation traits for UndirectedALGraph

* Describe graph types in lib.rs

* Update graph_builder README.md

* Make clippy happy

* Just panic if the lock is poisoned

Co-Authored-By: Paul Horn <[email protected]>

* Remove unnecessary &mut

Co-Authored-By: Paul Horn <[email protected]>

* Remove extra lifetime + constraint from targets methods

Co-Authored-By: Paul Horn <[email protected]>

* Extend SAFETY note

Co-Authored-By: Paul Horn <[email protected]>

* Remove unneeded lifetime

Co-Authored-By: Paul Horn <[email protected]>

* Export EdgeMutationWithValues

Co-Authored-By: Paul Horn <[email protected]>

* Statically check that AL is Send + Sync

Co-Authored-By: Paul Horn <[email protected]>

---------

Co-authored-by: Paul Horn <[email protected]>

crates/builder/README.md

@@ -15,7 +15,7 @@ is tailored for fast and concurrent access to the graph topology.
 [Neo4j](https://github.com/neo4j/neo4j) developers. However, the library is
 __not__ an official product of Neo4j.
 
-## What is a graph?
+# What is a graph?
 
 A graph consists of nodes and edges where edges connect exactly two nodes. A
 graph can be either directed, i.e., an edge has a source and a target node
@@ -30,7 +30,7 @@ In an undirected graph there is no distinction between source and target
 node. A neighbor of node `u` is any node `v` for which either an edge `(u,
 v)` or `(v, u)` exists.
 
-## How to build a graph
+# How to build a graph
 
 The library provides a builder that can be used to construct a graph from a
 given list of edges.
@@ -161,4 +161,90 @@ assert_eq!(
 );
 ```
 
+# Types of graphs
+
+The crate currently ships with two graph implementations:
+
+## Compressed Sparse Row (CSR)
+
+[CSR](https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_sparse_row_(CSR,_CRS_or_Yale_format))
+is a data structure used for representing a sparse matrix. Since graphs can be modelled as adjacency
+matrix and are typically very sparse, i.e., not all possible pairs of nodes are connected
+by an edge, the CSR representation is very well suited for representing a real-world graph topology.
+
+In our current implementation, we use two arrays two model the edges. One array stores the adjacency
+lists for all nodes consecutively which requires `O(edge_count)` space. The other array stores the
+offset for each node in the first array where the corresponding adjacency list can be found which
+requires `O(node_count)` space. The degree of a node can be inferred from the offset array.
+
+Our CSR implementation is immutable, i.e., once built, the topology of the graph cannot be altered as
+it would require inserting target ids and shifting all elements to the right which is expensive and
+invalidates all offsets coming afterwards. However, building the CSR data structure from a list of
+edges is implement very efficiently using multi-threading.
+
+However, due to inlining the all adjacency lists in one `Vec`, access becomes very cache-friendly,
+as there is a chance that the adjacency list of the next node is already cached. Also, reading the
+graph from multiple threads is safe, as there will be never be a concurrent mutable access.
+
+One can use [`DirectedCsrGraph`] or [`UndirectedCsrGraph`] to build a CSR-based graph:
+
+```rust
+use graph_builder::prelude::*;
+
+let graph: DirectedCsrGraph<usize> = GraphBuilder::new()
+    .edges(vec![(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)])
+    .build();
+
+assert_eq!(graph.node_count(), 4);
+assert_eq!(graph.edge_count(), 5);
+
+assert_eq!(graph.out_degree(1), 2);
+assert_eq!(graph.in_degree(1), 1);
+
+assert_eq!(graph.out_neighbors(1).as_slice(), &[2, 3]);
+assert_eq!(graph.in_neighbors(1).as_slice(), &[0]);
+```
+
+## Adjacency List (AL)
+
+In the Adjacency List implementation, we essentially store the graph as `Vec<Vec<ID>>`. The outer
+`Vec` has a length of `node_count` and at each index, we store the neighbors for that particular
+node in its own, heap-allocated `Vec`.
+
+The downside of that representation is that - compared to CSR - it is expected to be slower, both
+in building it and also in reading from it, as cache misses are becoming more likely due to the
+isolated heap allocations for individual neighbor lists.
+
+However, in contrast to CSR, an adjacency list is mutable, i.e., it is possible to add edges to the
+graph even after it has been built. This makes the data structure interesting for more flexible graph
+construction frameworks or for algorithms that need to add new edges as part of the computation.
+Currently, adding edges is constrained by source and target node already existing in the graph.
+
+Internally, the individual neighbor lists for each node are protected by a `Mutex` in order to support
+parallel read and write operations on the graph topology.
+
+One can use [`DirectedALGraph`] or [`UndirectedALGraph`] to build a Adjacency-List-based graph:
+
+```rust
+use graph_builder::prelude::*;
+
+let graph: DirectedALGraph<usize> = GraphBuilder::new()
+    .edges(vec![(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)])
+    .build();
+
+assert_eq!(graph.node_count(), 4);
+assert_eq!(graph.edge_count(), 5);
+
+assert_eq!(graph.out_degree(1), 2);
+assert_eq!(graph.in_degree(1), 1);
+
+assert_eq!(graph.out_neighbors(1).as_slice(), &[2, 3]);
+assert_eq!(graph.in_neighbors(1).as_slice(), &[0]);
+
+// Let's mutate the graph by adding another edge
+graph.add_edge(1, 0);
+assert_eq!(graph.edge_count(), 6);
+assert_eq!(graph.out_neighbors(1).as_slice(), &[2, 3, 0]);
+```
+
 License: MIT