Katz Centrality
SQL function: cugraph_katz_centrality
Official cuGraph reference: C API
Score vertices from the number of walks that reach them, attenuating longer walks and adding a baseline contribution.
Signature
cugraph_katz_centrality(table_name [, src_col, dst_col [, weight_col [, options_json]]])
Quickstart
The call below expects a registered edge table or view target_edges with endpoint columns src and dst. Substitute your own registered relations.
SELECT * FROM cugraph_katz_centrality('target_edges');
Inputs
table_name must be a registered edge table or view (the edges role); parenthesized subqueries are not accepted, and metadata validation resolves the same registered name.
Endpoint columns accept numeric Int32, Int64 vertex IDs or logical string Utf8, LargeUtf8, Utf8View vertex IDs; string vertex-identity outputs are canonicalized to Utf8 (native mapping Int64) while scores, distances, counts, coordinates, and opaque labels stay numeric. The shared vertex-ID contract is summarized in Vertex ID support; the concrete call-specific schema comes from gpu_validate_call.
Logical string side-input limitations:
- edge ID columns and edge-ID predicate side inputs are not supported for logical string graphs
Arguments and options
Positional scalar arguments
src_col and dst_col name the edge endpoint columns; both are optional and default to src and dst.
| Argument | Type | Required | Default | Notes |
|---|---|---|---|---|
weight_col | Utf8|null | no | accepted as an edge-column binding; native algorithm execution does not consume weights; semantic effect: none for this algorithm |
JSON options
| Option | Type | Default | Constraints | Description |
|---|---|---|---|---|
alpha | Float64 | 0.01 | max 1; > 0 | Attenuation factor applied per path length; larger values let longer paths contribute more. cuGraph requires alpha below the inverse of the graph's largest eigenvalue for the iteration to converge. |
beta | Float64 | 1 | > 0 | Constant added to every vertex's score in each iteration. One scalar applies to all vertices; per-vertex betas are not exposed. |
epsilon | Float64 | 0.000001 | > 0 | Convergence tolerance: iteration stops once the L1 sum of score changes between consecutive iterations is below the vertex count multiplied by epsilon. Smaller values tighten convergence and may need more iterations. |
max_iterations | UInt32 | 1000 | min 1 | Upper bound on Katz iterations. |
Graph construction options
Graph construction follows the shared defaults (directed=true, renumbering, python_cugraph policy) documented in Graph Construction Options.
Output
| Column | Type | Nullable | Description |
|---|---|---|---|
vertex | Int64|Utf8 | no | Vertex receiving the Katz centrality score. |
value | Float64 | no | Katz centrality score for the vertex. |
These are generic descriptor schemas; validate the call to get the concrete, table-specific output schema.
Examples
This example runs on the citation network demo dataset.
alpha decides how deep credit flows
Katz centrality counts all incoming walks, discounting a walk of length n
by alpha^n. At the default alpha (0.01) long chains contribute almost
nothing and the ranking is nearly in-degree. Raising alpha to 0.05 shifts
credit to papers whose citers are themselves heavily cited, transitively —
window functions over the two results make the shift visible as rank
movement:
WITH katz AS (
SELECT vertex, ROW_NUMBER() OVER (ORDER BY value DESC) AS katz_rank
FROM cugraph_katz_centrality('citation_edges', 'src', 'dst', NULL,
'{"alpha": 0.05}')),
deg AS (
SELECT vertex, in_degree, ROW_NUMBER() OVER (ORDER BY in_degree DESC) AS degree_rank
FROM cugraph_in_degrees_all('citation_edges', 'src', 'dst'))
SELECT p.title, p.year, k.katz_rank, d.degree_rank, d.in_degree
FROM katz k
JOIN deg d ON d.vertex = k.vertex
JOIN papers p ON p.paper_id = k.vertex
WHERE k.katz_rank <= 8
ORDER BY k.katz_rank;
| title | year | katz_rank | degree_rank | in_degree |
|---|---|---|---|---|
| Distinctive Image Features from Scale-Invariant Keypoints | 2004 | 1 | 1 | 22,892 |
| The Nature of Statistical Learning Theory | 1995 | 2 | 6 | 14,508 |
| Histograms of oriented gradients for human detection | 2005 | 3 | 9 | 13,768 |
| Object recognition from local scale-invariant features | 1999 | 4 | 58 | 6,300 |
| New Directions in Cryptography | 1976 | 5 | 69 | 6,007 |
| The Design and Analysis of Computer Algorithms | 1974 | 6 | 103 | 5,168 |
| A Computational Approach to Edge Detection | 1986 | 7 | 24 | 9,069 |
| A method for obtaining digital signatures and public-key cryptosystems | 1978 | 8 | 50 | 6,580 |
The risers are the foundations: New Directions in Cryptography climbs from
in-degree rank #69 to Katz rank #5 and the RSA paper from #50 to #8, because
the papers citing them anchor entire downstream literatures. Katz is the natural choice on citation-style
graphs — near-acyclic structure starves
eigenvector centrality,
while the beta base score keeps every vertex non-zero here. Convergence
requires alpha below the reciprocal of the graph's largest eigenvalue:
pushing it too high fails with a convergence error rather than returning
partial scores.
Limits
No algorithm-specific limitations.
Validate the call
Dry-run validation checks registered relation metadata, column presence, static dtypes, and options only; it does not scan edge data, construct a graph, or prove source-vertex existence:
SELECT * FROM gpu_validate_call(
'cugraph_katz_centrality',
'{"schema_version":1,"relations":{"edges":{"table":"target_edges"}},"options":{"src_col":"src","dst_col":"dst"}}'
);
See GPU Function Catalog API for the full gpu_validate_call contract.