dijkstra

Generic Description

Find shortest-path distances in non-negative weighted graphs.

Simple example:

CALL nexyron.dijkstra({source: 0, weight: 'km'})

Shortest-path and routing procedures compute feasible routes under different cost and graph assumptions. They are useful for logistics, dependency chains, impact paths, and path-based explainability.

Consumer-Level Explanation

Use dijkstra when find shortest-path distances in non-negative weighted graphs is the graph-analysis or operational question you actually need to answer. Keep the call explicit because its YIELD columns, row grain, and required runtime state determine how the rest of the Cypher pipeline can safely compose it. Choose the routing algorithm based on weights, negative costs, DAG assumptions, heuristic availability, and whether you need one path, all-pairs distances, or multiple alternatives.

Conceptual Explanation

dijkstra should be read as one named procedure contract in the broader Nexyron Cypher surface. The procedure call is not only a syntax hook: it defines what runtime state, projection, registry entry, or graph algorithm is being asked to operate, and it determines which output columns downstream YIELD, WITH, and RETURN stages can safely use.

More Detailed Explanation

This is the classic efficient weighted shortest-path algorithm and differs from Bellman-Ford by assuming no negative-weight issues

In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with YIELD and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.

How It Differs From Nearby Algorithms

This is the classic efficient weighted shortest-path algorithm and differs from Bellman-Ford by assuming no negative-weight issues.

Advanced Example

This example yields named columns from dijkstra and returns a bounded result shape that downstream planner tooling can compose without guessing column names or row grain.

CALL nexyron.dijkstra({source: 0, weight: 'km'}) YIELD node_id, distance
RETURN node_id, distance
LIMIT 10

Real Use Cases

Real Limitations And Tradeoffs