TopK hop-limited single source (weighted) shortest path algorithm - Neptune Analytics

TopK hop-limited single source (weighted) shortest path algorithm

The .topkssspalgorithm finds the single-source weighted shortest paths from a source node to its neighbors out to the distance specified by maxDepth. It accumulates the path lengths using the edge weights along the paths and then returns a sorted list of the shortest paths.

.topksssp   syntax

CALL neptune.algo.topksssp( [source-node list (required)], { hopCount: maximum hops on the shortest path (required), perHopLimits: [a list of the maximum number of nodes to carry forward at each hop (required)], edgeLabels: [list of edge labels for filtering (optional)], edgeWeightProperty: a numeric edge property to weight the traversal (optional), edgeWeightType: numeric type of the specified edgeWeightProperty (optional), vertexLabel: a node label for filtering (optional), traversalDirection: traversal direction (optional, default: outbound), costFunction: determines whether the topK distances are in ascending or descending order (optional), concurrency: number of threads to use (optional) } ) YIELD source, node, distance RETURN source, node, distance

Inputs for the topksssp algorithm

  • a source node list   (required)   –   type: Node[] or NodeId[];   default: none.

    The node or nodes to use as the starting location(s) for the algorithm.

    • Each starting node triggers its own execution of the algorithm.

    • If the source-node list is empty then the query result is also empty.

    • If the algorithm is called following a MATCH clause (this is known as query-algorithm integration), the output of the MATCH clause is used as the source-node list for the algorithm.

  • a configuration object that contains:
    • hopCount (required)   –   type: positive integer;   default: none.

      Restricts the number of hops on a shortest path, which restricts the number of iterations of the SSSP algorithm to be used.

    • perHopLimits (required)   –   type: a list of integers;   valid values: positive integers, or -1 meaning unlimited;   default: none.

      Each integer represents the maximum number of candidate vertices to carry to the next hop.

    • edgeLabels   (optional)   –   type: a list of edge label strings;   example: ["route", ...];   default: no edge filtering.

      To filter on one more edge labels, provide a list of the ones to filter on. If no edgeLabels field is provided then all edge labels are processed during traversal.

    • edgeWeightProperty (optional)   –   type: string;   default: none.

      The edge weight predicate to for traversal. If no property is specified then the algorithm runs unweighted. If multiple properties exist on an edge having the specified name, then one of them is selected at random for the weight value.

    • edgeWeightType (optional)   –   type: string;   valid values: "int", "long", "float", "double".

      The numeric data type of the values in the property specified by edgeWeightProperty. If the edgeWeightProperty is not present, edgeWeightType is ignored and the algorithm runs unweighted. If an edge contains a property specified by edgeWeightProperty that has a numeric type different from what is specified in edgeWeightType, the property value is typecast to the type specified by edgeWeightType.

    • vertexLabel (optional)   –   type: string;   default: none.

      A node label for node filtering. If a node label is provided, vertices matching the label are the only vertices that are included, including vertices in the input list.

    • costFunction (optional)   –   type: string;   valid values: "min", "max";   default: "min".

      Specifies the ordering of the topK distances returned. A "min" value indicates that the topK distances between the source and target vertices should be returned in descending order, whereas a "max" value indicates that they should be returned in ascending order.

    • concurrency   (optional)   –   type: 0 or 1;   default: 0.

      Controls the number of concurrent threads used to run the algorithm.

      If set to 0, uses all available threads to complete execution of the individual algorithm invocation. If set to 1, uses a single thread. This can be useful when requiring the invocation of many algorithms concurrently.

Outputs for the topksssp algorithm

For every node that can be reached from the specified source list, the algorithm returns:

  • source   –   The source node.

  • node   –   A node found traversing from the source.

  • distance   –   The distance between the source node and the found node.

.topksssp   query examples

This ia a standalone query, where the source node list is explicitly provided in the query:

CALL neptune.algo.topksssp( ["101"], { edgeLabels: ["route"], hopCount: 3, perHopLimits: [10, 100, 1000], edgeWeightProperty: "dist", edgeWeightType: "int" } )

This is a query integration example, where .topksssp follows a MATCH clause and uses the output of the MATCH clause as its source node list:

MATCH (n) WHERE id(n) IN ["108","109"] CALL neptune.algo.topksssp( n, { edgeLabels: ["route"], edgeWeightProperty: "dist", edgeWeightType: "int", hopCount: 5, perHopLimits: [5,10,15,20,25] } ) YIELD distance RETURN n, collect(distance) AS distances'
Warning

It is not good practice to use MATCH(n) without restriction in query integrations. Keep in mind that every node returned by the MATCH(n) clause invokes the algorithm once, which can result a very long-running query if a large number of nodes is returned. Use LIMIT or put conditions on the MATCH clause to restrict its output appropriately.

Sample .topksssp output

Here is an example of the output returned by .topksssp when run against the sample air-routes dataset [nodes], and sample air-routes dataset [edges], when using the following query:

aws neptune-graph execute-query \ --graph-identifier ${graphIdentifier} --query-string "CALL neptune.algo.topksssp(['101'], {hopCount: 2, perHopLimits: [3, 5]}) YIELD source, node, distance RETURN source, node, distance limit 2" \ --language open_cypher /tmp/out.txt cat /tmp/out.txt { "results": [ { "source": { "~id": "101", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 13.6810998916626, "elev": 5, "longest": 13123, "city": "Bangkok", "type": "airport", "region": "TH-10", "desc": "Suvarnabhumi Bangkok International Airport", "code": "BKK", "prscore": 0.002498496090993285, "degree": 308, "lon": 100.747001647949, "wccid": 2357352929951779, "country": "TH", "icao": "VTBS", "runways": 2 } }, "node": { "~id": "170", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 40.8860015869, "elev": 294, "longest": 8622, "city": "Naples", "type": "airport", "region": "IT-72", "desc": "Naples International Airport", "code": "NAP", "prscore": 0.001119577675126493, "degree": 222, "lon": 14.2908000946, "wccid": 2357352929951779, "country": "IT", "icao": "LIRN", "runways": 1 } }, "distance": 2.0 }, { "source": { "~id": "101", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 13.6810998916626, "elev": 5, "longest": 13123, "city": "Bangkok", "type": "airport", "region": "TH-10", "desc": "Suvarnabhumi Bangkok International Airport", "code": "BKK", "prscore": 0.002498496090993285, "degree": 308, "lon": 100.747001647949, "wccid": 2357352929951779, "country": "TH", "icao": "VTBS", "runways": 2 } }, "node": { "~id": "12", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 40.63980103, "elev": 12, "longest": 14511, "city": "New York", "type": "airport", "region": "US-NY", "desc": "New York John F. Kennedy International Airport", "code": "JFK", "prscore": 0.002885053399950266, "degree": 403, "lon": -73.77890015, "wccid": 2357352929951779, "country": "US", "icao": "KJFK", "runways": 4 } }, "distance": 2.0 } ] }