yens
Generic Description
Find multiple shortest loopless paths.
Simple example:
CALL nexyron.yens({source: 0, target: 1, k: 2})
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 yens when find multiple shortest loopless paths 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
yens 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
Yen’s differs from single shortest-path algorithms by producing ranked alternatives rather than only the best one
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
Yen’s differs from single shortest-path algorithms by producing ranked alternatives rather than only the best one.
Advanced Example
This example yields named columns from yens and returns a bounded result shape that downstream planner tooling can compose without guessing column names or row grain.
CALL nexyron.yens({source: 0, target: 1, k: 2}) YIELD rank, distance, path
RETURN rank, distance, path
LIMIT 10
Real Use Cases
- backup route analysis
- route diversity inspection
- explanation alternatives
- compare algorithm output with domain labels or time windows before operationalizing it
- feed graph-analytic scores into ranked reports, feature contracts, or investigation queues only after checking the modeling assumptions
Real Limitations And Tradeoffs
- alternative paths can still be too similar without extra diversity logic
- algorithm output reflects the projected graph, not an abstract real-world network outside the data model
- nearby algorithms can answer different questions even when their output columns look similar