.degreeDistribution centrality algorithm - Neptune Analytics
SyntaxInputsQuery examplesSample output

.degreeDistribution centrality algorithm

The .degreeDistribution algorithm is a tool for analyzing and visualizing the structural characteristics of a graph. It calculates the frequency distribution of vertex degrees across the entire network and provides basic statistics of the distribution.

.degreeDistribution provides insight into the topology and connectivity patterns of the network, such as identifying the hubs (i.e., super nodes or high-degree nodes) and distinguishing different network types (e.g., tree vs. scale-free), which can help making informed decisions on selecting appropriate algorithms for analysis.

The %degreeDistribution magic command in the notebook provides an interactive visualization of the output, please see the notebook magics documentation for details.

.degreeDistribution   syntax

CALL neptune.algo.degreeDistribution(
  {
    edgeLabels: [a list of edge labels for filtering (optional)],
    vertexLabel: "a list of vertex labels for filtering (optional)",
    binWidth: a positive integer that specifies the size of each bin in the degree distribution (optional, default: 1),
    traversalDirection: the direction of edge used for degree computation (optional, default: "both",
    concurrency: number of threads to use (optional)
  }
)
YIELD output
RETURN output

Inputs for the .degreeDistribution algorithm

  • a configuration object that contains:

    • edgeLabels   (optional)   –   type: a list of edge label strings;   example: ["route", ...];   default: no edge filtering.

      To filter on one more edge labels, provide a list of the ones to filter on. If no edgeLabels field is provided then all edge labels are processed during traversal.

    • vertexLabel (optional)   –   type: a list of vertex label strings;   default: no vertex filtering.

      To filter on one or more vertex labels, provide a list of the ones to filter on. If no vertexLabels field is provided then all vertex labels are considered for degree computation.

    • binWidth (optional)   –   type: integer;   default: 1.

      To specify the size of each bin in the degree distribution, provide an integer value.

    • traversalDirection (optional)   –   type: string;   default: "both".

      The direction of edge to follow. Must be one of: "inbound", "outbound", or "both".

    • concurrency   (optional)   –   type: 0 or 1;   default: 0.

      Controls the number of concurrent threads used to run the algorithm.

      If set to 0, uses all available threads to complete execution of the individual algorithm invocation. If set to 1, uses a single thread. This can be useful when requiring the invocation of many algorithms concurrently.

Query examples for .degreeDistribution

This is a standalone example, where the source node list is explicitly specified in the query:

CALL neptune.algo.degree(["101"], {edgeLabel: "route"})

This is a more complicated standalone query submitted using the AWS CLI:

aws neptune-graph execute-query \
  --graph-identifier ${graphIdentifier} \
  --query-string 'CALL neptune.algo.degree(
        ["101", "102", "103"],
        {
          edgeLabels: ["route"],
          vertexLabel: "airport",
          traversalDirection: "inbound",
          concurrency: 2
        }
      )
      YIELD node, degree
      RETURN node, degree' \
  --language open_cypher \
  /tmp/out.txt

This is a query integration example with frontier injection, where .degree follows a MATCH clause and finds the degree value for all vertices returned by MATCH(n:airport):

MATCH(n:airport)
CALL neptune.algo.degree(n, {edgeLabels: ["route"]})
YIELD degree
RETURN n, degree'

This is an example of multiple .degree invocations chained together, where the output of one invocation serves as the input of another:

CALL neptune.algo.degree(
  ["108"],
  {
    edgeLabels: ["route"],
    vertexLabel: "airport"
  }
)
YIELD node
CALL neptune.algo.degree(
  node,
  {
    edgeLabels: ["route"],
    vertexLabel: "airport"
  }
)
YIELD node AS node2 WITH id(node2) AS id
RETURN id
Warning

It is not good practice to use MATCH(n) without restriction in query integrations. Keep in mind that every node returned by the MATCH(n) clause invokes the algorithm once, which can result a very long-running query if a large number of nodes is returned. Use LIMIT or put conditions on the MATCH clause to restrict its output appropriately.

Sample   .degreeDistribution   output

Here is an example of the output returned by .degree when run against the sample air-routes dataset [nodes], and sample air-routes dataset [edges], when using the following query:

aws neptune-graph execute-query \
  --graph-identifier ${graphIdentifier} \
  --query-string 'MATCH (n)
      CALL neptune.algo.degree(n)
      YIELD node, degree
      RETURN node, degree
      LIMIT 2' \
  --language open_cypher \
  /tmp/out.txt
  
cat /tmp/out.txt  
{
  "results": [
    {
      "node": {
        "~id": "10",
        "~entityType": "node",
        "~labels": ["airport"],
        "~properties": {
          "lat": 38.94449997,
          "elev": 313,
          "longest": 11500,
          "city": "Washington D.C.",
          "type": "airport",
          "region": "US-VA",
          "desc": "Washington Dulles International Airport",
          "code": "IAD",
          "prscore": 0.002264724113047123,
          "lon": -77.45580292,
          "wccid": 2357352929951779,
          "country": "US",
          "icao": "KIAD",
          "runways": 4
        }
      },
      "degree": 312
    },
    {
      "node": {
        "~id": "12",
        "~entityType": "node",
        "~labels": ["airport"],
        "~properties": {
          "lat": 40.63980103,
          "elev": 12,
          "longest": 14511,
          "city": "New York",
          "type": "airport",
          "region": "US-NY",
          "desc": "New York John F. Kennedy International Airport",
          "code": "JFK",
          "prscore": 0.002885053399950266,
          "lon": -73.77890015,
          "wccid": 2357352929951779,
          "country": "US",
          "icao": "KJFK",
          "runways": 4
        }
      },
      "degree": 403
    }
  ]
}