K-Core

SQL function: cugraph_k_core

Return the graph k-core edge set.

Signature

cugraph_k_core(table_name [, src_col, dst_col [, weight_col [, options_json]]])

Allowed argument counts: 1, 3, 4, 5.

Quickstart

SELECT * FROM cugraph_k_core('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

Option	Type	Default	Constraints	Description
degree_type	Utf8	"in_out"	one of "in", "out", "in_out"
k	UInt32	2	min 1

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	false		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
src	Int64	no	Source vertex of an edge retained in the k-core subgraph.
dst	Int64	no	Destination vertex of an edge retained in the k-core subgraph.

note

These are the generic registry schemas. Run cugraph_validate_call for the concrete, table-specific output schema of a particular call.

Examples

These examples run on the citation network demo dataset.

Extract the conversation backbone — then audit it with SQL

Unlike most functions here, cugraph_k_core returns edges, not scores: the subgraph where every remaining vertex keeps at least k in-edges and k out-edges. Because the output is reused as an edge relation, materialize it in the local workspace; plain SQL can then verify the contract it promises:

-- Local workspace materialization; this does not write to lake.citation_network.
CREATE TABLE kcore30 AS
SELECT src, dst FROM cugraph_k_core('citation_edges', 'src', 'dst', NULL, '{"k":30}');

WITH deg AS (
  SELECT v, SUM(o) AS outd, SUM(i) AS ind
  FROM (SELECT src AS v, 1 AS o, 0 AS i FROM kcore30
        UNION ALL
        SELECT dst AS v, 0 AS o, 1 AS i FROM kcore30) u
  GROUP BY v)
SELECT COUNT(*) AS vertices, MIN(outd) AS min_out, MIN(ind) AS min_in
FROM deg;

vertices	min_out	min_in
33,389	30	30

45.6M edges collapse to a 33k-vertex backbone of papers that both cite and are cited heavily — and the audit confirms every vertex meets the k=30 floor in both directions.

note

The k-core edge list comes back symmetrized: each undirected core edge appears in both directions (2,043,052 rows here, i.e. ~1.0M undirected edges). Note also that this per-direction floor is a stricter condition than cugraph_core_number's in_out degree, which sums the two directions.

Chain it into the next algorithm

The materialized backbone is itself a valid edge relation, so it can feed another cugraph_* call — a two-stage GPU pipeline held together by a local workspace table name:

SELECT p.year, p.title
FROM cugraph_pagerank('kcore30', 'src', 'dst') r
JOIN papers p ON p.paper_id = r.vertex
ORDER BY r.value DESC
LIMIT 5;

year	title
2004	Distinctive Image Features from Scale-Invariant Keypoints
2014	VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
2005	Histograms of oriented gradients for human detection
2009	ImageNet: A large-scale hierarchical image database
2016	Deep Residual Learning for Image Recognition

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_k_core',
  'your_edges_table',
  '{"src_col":"src","dst_col":"dst"}'
);

See Discovery & validation for the full cugraph_validate_call contract.