Degrees All
SQL function: cugraph_degrees_all
Compute in-degree and out-degree for every vertex.
Signature
cugraph_degrees_all(table_name [, src_col, dst_col [, weight_col [, options_json]]])
Allowed argument counts: 1, 3, 4, 5.
Quickstart
SELECT * FROM cugraph_degrees_all('target_edges')
Positional arguments
| Argument | Type | Required | Default | Notes |
|---|---|---|---|---|
table_name | Utf8 | yes | ||
src_col | Utf8 | no | src | |
dst_col | Utf8 | no | dst | |
weight_col | Utf8|null | no | accepted as an edge-column binding; native algorithm execution does not consume weights; semantic effect: none for this algorithm | |
options_json | Utf8 | no |
JSON options
This algorithm has no algorithm-specific options.
Graph construction options
Shared by all cuGraph functions, shown here with this function's defaults. The construction_policy option controls whether Nexus requests Python cuGraph-compatible edge normalization or bypasses it for raw libcugraph-style construction; see graph construction options for the full policy guide.
| Option | Type | Default | Constraints | Description |
|---|---|---|---|---|
construction_policy | Utf8 | "python_cugraph" | one of "python_cugraph", "raw_libcugraph" | Edge-list construction semantics used before calling libcugraph. |
directed | Boolean | true | Whether graph construction treats edges as directed. | |
renumber | Boolean | true | Whether graph construction may renumber external vertex identifiers internally. |
Output schema
| Column | Type | Nullable | Description |
|---|---|---|---|
vertex | Int64 | no | Vertex whose degree counts are reported. |
in_degree | Int64 | no | Number of incoming edges for the vertex. |
out_degree | Int64 | no | Number of outgoing edges for the vertex. |
These are the generic registry schemas. Run cugraph_validate_call for the concrete, table-specific output schema of a particular call.
Examples
This example runs on the citation network demo dataset.
Both directions at once: the hybrid giants
One call returns in-degree and out-degree together, so a compound WHERE
finds papers that are simultaneously heavy citers and heavily cited —
encyclopedic works that anchor a field and survey it at the same time:
SELECT d.in_degree, d.out_degree, p.year, p.title
FROM cugraph_degrees_all('citation_edges', 'src', 'dst') d
JOIN papers p ON p.paper_id = d.vertex
WHERE d.out_degree > 200 AND d.in_degree > 2000
ORDER BY d.in_degree DESC
LIMIT 4;
| in_degree | out_degree | year | title |
|---|---|---|---|
| 5,115 | 434 | 1996 | Handbook of Applied Cryptography |
| 3,666 | 217 | 2002 | Machine learning in automated text categorization |
| 2,954 | 240 | 2009 | Anomaly detection: A survey |
| 2,564 | 564 | 2015 | Deep learning in neural networks |
For a single direction with metadata comparisons, see
cugraph_in_degrees_all and
cugraph_out_degrees_all.
Limitations & notes
- dry-run validates table resolution, column presence, static dtypes, and options only
- dry-run does not scan edge data, construct a graph, or prove source-vertex existence
Validate before running
Always dry-run a call before executing it. Validation checks the function, table, columns, dtypes, and options without touching the GPU:
SELECT * FROM cugraph_validate_call(
'cugraph_degrees_all',
'your_edges_table',
'{"src_col":"src","dst_col":"dst"}'
);
See Discovery & validation for the full cugraph_validate_call contract.