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K-Core

Algorithm introduction

K-Core peels nodes iteratively and keeps the maximal subgraph in which each node has degree at least K.

Iteratively peel nodes whose undirected degree is less than k and return the remaining k-core nodes.

For more information, see K-Core.

Data model

To implement the K-Core algorithm in GQL, the following data model is used to create a graph type:

  • Entities are represented by nodes of type Node, with properties id and rating.
  • Relationships are represented by edges of type Link, with property weight.

For the complete definition of the graph type, see Prepare graph data.

Procedure implementation

To compute K-Core results, a procedure is created.

For more information about the procedure, see Procedure implementation. The following section describes the key components of the procedure and how it works.

The procedure takes the following input parameters:

  • k: INT64. Minimum degree threshold: only nodes with degree >= k are kept.

Additionally, the following variables are defined within the procedure:

Variable name Variable type Description
frontier Primitive value variable Active set of nodes being processed in the current peeling step.
has_active Primitive value variable Whether any node is still active and may be peeled.
degree Node-attached SumAgg aggregator value variable Per-node remaining degree, decremented as neighbors are peeled.
alive Node-attached SumAgg aggregator value variable Per-node flag indicating the node survives the current k threshold.
result_table Table variable Output table storing surviving (vertex_id, degree) pairs.

The following steps outline the logic of the procedure:

  1. Initialize all nodes as alive and set each node's degree to its actual degree.
  2. Iteratively remove nodes whose degree is below the threshold k (peeling step); decrement neighbors' degree when a node is removed.
  3. Repeat until no more nodes are removed (has_active is false).
  4. Return the surviving nodes (vertex_id, degree) that form the k-core.

Steps

Run the following code blocks in order in the NebulaGraph Studio CONSOLE. For first-time setup, follow Prepare algorithm sample data to check where to run commands and how the directory is mounted.

1. Prepare graph data

  1. Create a graph type that matches your data model.

    '''
    CREATE GRAPH TYPE IF NOT EXISTS k_core_graph_type AS {
        NODE Node (LABEL Node {id INT PRIMARY KEY, rating INT}),
        EDGE Link (Node)-[LABEL Link {weight INT, MULTIEDGE KEY()}]->(Node)
    }
    '''
    
  2. Download these CSV files and save them with their original names in examples/algorithms/k_core/ under your deployment directory:

    Preview the CSV files
    k_core_node.csv
    id,rating
    1,0
    2,2
    3,1
    4,0
    5,0
    6,2
    7,1
    8,2
    9,0
    10,1
    11,0
    12,2
    13,1
    14,1
    15,0
    16,2
    17,0
    18,1
    19,2
    20,0
    21,2
    22,1
    23,0
    24,1
    
    k_core_edge.csv
    src_id,dst_id,weight
    1,2,4
    1,3,2
    1,4,7
    1,5,9
    2,3,1
    2,4,6
    2,5,5
    2,6,2
    3,4,3
    3,5,4
    3,6,8
    4,6,2
    4,7,6
    4,8,5
    5,6,4
    5,8,7
    5,9,6
    6,8,1
    6,9,5
    6,10,6
    7,9,2
    7,10,9
    8,9,3
    8,11,6
    8,12,4
    9,10,4
    9,12,7
    9,13,2
    10,12,1
    10,13,8
    10,14,4
    11,12,2
    11,14,5
    11,15,7
    12,14,3
    12,15,6
    12,16,5
    13,15,2
    13,16,7
    14,15,4
    14,17,8
    14,18,2
    15,16,1
    15,18,5
    15,19,3
    16,18,3
    16,19,6
    17,18,2
    17,20,7
    17,21,5
    18,19,4
    18,21,9
    18,22,6
    19,21,1
    19,22,5
    20,21,3
    20,23,6
    20,24,8
    21,22,2
    21,23,4
    21,24,7
    22,24,4
    23,24,1
    
  3. Create a temporary graph based on the graph type and load the data files into the temporary graph.

    CREATE TEMPORARY GRAPH IF NOT EXISTS #k_core_graph TYPED k_core_graph_type
    
    '''
    USE #k_core_graph IMPORT INTO GRAPH {
          NODE (v@Node {id: id, rating: rating}) FROM DATAFILE {
              PATH: "file:///examples/algorithms/k_core/k_core_node.csv",
              FORMAT: "CSV",
              DELIMITER: ','
          },
          EDGE (id: src_id)-[e@Link {weight: weight}]->(id: dst_id) FROM DATAFILE {
              PATH: "file:///examples/algorithms/k_core/k_core_edge.csv",
              FORMAT: "CSV",
              DELIMITER: ','
          }
      }
    '''
    

    After the import succeeds, run this query in the console to check the node count:

    '''
    USE #k_core_graph
    MATCH (n)
    RETURN count(n) AS node_count
    '''
    

    The expected node_count is 24. If it differs, check the files and import results before continuing.

2. Create a procedure

Create a procedure to implement the K-Core algorithm. For more information about the procedure, see Procedure implementation.

'''
CREATE OR REPLACE PROCEDURE k_core(k INT64)
RETURNS (vertex_id INT64, degree INT64)
COMMENT "Iteratively peel vertices whose undirected degree is less than k and return the remaining k-core vertices."
AS {
  VALUE frontier ACTIVE_SET
  VALUE has_active OrAgg = false

  NODE VALUE degree SumAgg<INT64> = 0
  NODE VALUE alive OrAgg = false

  TABLE result_table TYPED TABLE {vertex_id INT64, degree INT64}

  MATCH (s)
  PER NODE (s) {
    SET s.@alive = true
  }

  MATCH (s)-[e]-(t)
  PER PATH {
    SET s.@degree += 1
  }

  MATCH (s)
  WHERE s.@degree < k
  PER NODE (s) {
    SET s.@alive = false
    SET @has_active += true
  }
  FINALLY {
    SET frontier = s
  }

  WHILE @has_active = true THEN {
    SET @has_active = false

    MATCH (s)-[e]-(t)
    WHERE s IN frontier AND t.@alive = true
    PER PATH {
      SET t.@degree += -1
    }

    MATCH (t)
    WHERE t.@alive = true AND t.@degree < k
    PER NODE (t) {
      SET t.@alive = false
      SET @has_active += true
    }
    FINALLY {
      SET frontier = t
    }
  }

  MATCH (s)
  WHERE s.@alive = true
  PER NODE (s) {
    EXPORT s.id, s.@degree INTO result_table
  }

  FOR r IN result_table
  RETURN r.vertex_id AS vertex_id, r.degree AS degree
  ORDER BY degree DESC, vertex_id ASC
}
'''

3. Call your procedure

Set k to 3 and return the nodes retained in the K-Core with their degrees.

USE #k_core_graph CALL k_core(3) RETURN vertex_id, degree

Returns:

Expand to view results
+-----------+--------+
| vertex_id | degree |
+-----------+--------+
| 6         | 7      |
| 9         | 7      |
| 12        | 7      |
| 15        | 7      |
| 18        | 7      |
| 21        | 7      |
| 4         | 6      |
| 5         | 6      |
| 8         | 6      |
| 10        | 6      |
| 14        | 6      |
| 2         | 5      |
| 3         | 5      |
| 16        | 5      |
| 19        | 5      |
| 1         | 4      |
| 11        | 4      |
| 13        | 4      |
| 17        | 4      |
| 20        | 4      |
| 22        | 4      |
| 24        | 4      |
| 7         | 3      |
| 23        | 3      |
+-----------+--------+
Save results to a file or graph

To save the returned results as CSV files or write them to a graph, see EXPORT. Match the exported fields to the returned columns and target properties.