# k-Core Decomposition

Supported Graph Characteristics
 Unweighted edges Directed edges Undirected edges Homogeneous vertex types

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph.

This algorithm takes a range of values for k and returns the vertex set that constitutes the k-core with the highest possible value of k within the range.

To obtain the k-core of a graph, the algorithm first deletes the vertices whose outdegree is less than k. It then updates the outdegree of the neighbors of the deleted vertices, and if that causes a vertex’s outdegree to fall below k, it will also delete that vertex. The algorithm repeats this operation until every vertex left in the subgraph has an outdegree of at least k.

## Specifications

``````tg_kcore(STRING v_type, STRING e_type, INT k_min = 0,
INT k_max = -1, BOOL print_results = TRUE,
STRING result_attribute = "", STRING file_path = "",
BOOL print_all_k = FALSE, BOOL show_shells=FALSE)``````

### Parameters

Parameter Description

`STRING v_type`

Vertex type to include in the k-core

`STRING e_type`

Edge type to count for k-core connections

`INT k_min`

Minimum value of k. If the actual maximum core is below `k_min`, the algorithm will return an empty set.

`INT k_max`

Maximum value of k. If `k_max` is smaller than `k_min`, the algorithm will ignore this parameter and keep looking for k-cores until it reaches a value of k where a k-core cannot be found.

`BOOL print_results`

Boolean value that decides whether the algorithm will return output in JSON

`STRING result_attribute`

An attribute of the vertex to save the core level of the vertex to. If `attr` is provided, the core level of the vertex will be saved to this attribute of the vertex.

`STRING file_path`

If `file_path` is provided, the algorithm will output results to a file specified by the file path in CSV format.

`BOOL print_all_k`

Whether to print all k connections

`BOOL show_shells`

The k-shell is the set of vertices that are part of the k-core but not part of the (k+1)-core. If `show_shells` is `true`, the algorithm will return the k-shells found for every value of k. within the range provided. For each k-shell, the results will include its member vertices.

### Time complexity

O(E), where E is the number of edges in the graph.

### Run commands

#### Schema-Free Query

``RUN QUERY tg_kcore (<parameters>)``

#### Packaged Template Query

``CALL GDBMS_ALGO.community.kcore (<parameters>)``

## Example

In the example below based on the `social` graph from GSQL 101, we can see that Dan, Tom, and Jenny make up a 2-core, which is the max-core of the graph:

If we run the `kcore` algorithm on this small graph like so:

``RUN QUERY tg_kcore("person", "friendship", 0, -1, TRUE, "", "", FALSE, FALSE)``

Here is the returned JSON response, which includes a 2-core that is comprised of Dan, Jenny, and Tom:

``````[
{
"core_size": 3,
"k": 2,             // the k-core with the highest possible k is returned
"max_core": [
{
"attributes": {
"@core": 2,
"@deg": 0,
"age": 40,
"gender": "male",
"name": "Tom",
"state": "ca"
},
"v_id": "Tom",
"v_type": "person"
},
{
"attributes": {
"@core": 2,
"@deg": 0,
"age": 34,
"gender": "male",
"name": "Dan",
"state": "ny"
},
"v_id": "Dan",
"v_type": "person"
},
{
"attributes": {
"@core": 2,
"@deg": 0,
"age": 25,
"gender": "female",
"name": "Jenny",
"state": "tx"
},
"v_id": "Jenny",
"v_type": "person"
}
]
}
]``````