Parents breadth-first search (BFS) algorithm - Neptune Analytics

Parents breadth-first search (BFS) algorithm

The parents variant of breadth-first search is an algorithm for finding nodes from a starting node or vertices in breadth-first order and then performing a breadth-first search for the parent of each node.

It returns a key column of vertices, and a value column of the vertices that are the parents of the key vertices. The parent of a source node is itself.

Note

Because every source node passed in initiates its own execution of the algorithm, your queries should limit the number of source nodes as much as possible.

.bfs.parents   syntax

CALL neptune.algo.bfs.parents( [source-node list (required)], { edgeLabels: [list of edge labels for filtering (optional)], vertexLabel: a node label for filtering (optional), maxDepth: maximum number of hops to traverse from a source node (optional), traversalDirection: traversal direction (optional), concurrency: number of threads to use (optional) } ) YIELD the outputs to generate (source and/or node and/or parent) RETURN the outputs to return

.bfs.parents   inputs

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

    The source-node list contains the node or nodes used as the starting locations 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:
    • 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.

    • vertexLabel   (optional)   –   type: string;   example: "airport";  default: no node filtering.

      If you provide a node label to filter on then only vertices matching that label will be traversed. This does not, however, filter out any nodes in the source node list.

    • maxDepth   (optional)   –   type: positive inteeger or 0 or -1;   default: -1.

      The maximum number of hops to traverse from a source node. If set at -1 then there's no maximum depth limit. If set to 0, only the vertices in the source node list are returned.

    • traversalDirection   (optional)   –   type: string;   default: outbound.

      The direction of edge to follow. Must be one of: inbound, oubound, or both.

    • 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.

.bfs.parents   outputs

The .bfs.parents algorithm returns:

  • source   –   type: Node[].

    The source nodes.

  • node   –   type: Node[].

    The vertices that the algorithm traversed from each source node.

  • parent   –   type: Node[].

    The parents of those traversed nodes.

.bfs.parents   query examples

Thus is a standalone examples, where the source node list is explicitly provided in the query:

CALL neptune.algo.bfs.parents( ["105", "113"], { edgeLabels: ["route"], vertexLabel: "airport", maxDepth: 2, traversalDirection: "both", concurrency: 2 } ) YIELD node, parent

A query like this one would return an empty result because the source list is empty:

CALL neptune.algo.bfs.parents([], {edgeLabels: ["route"]})

This is a query integration example, where .bfs.parents follows a MATCH clause that provides the source node list for .bfs.parents:

Match (n) with n LIMIT 5 CALL neptune.algo.bfs.parents(n, {edgeLabels: ["route"]}) YIELD node RETURN n, node

This query is an example of aliasing the algorithm output:

MATCH (n {code: "AUS"}) CALL neptune.algo.bfs.parents(n, { edgeLabels: ["route"], maxDepth: 2}) YIELD node AS ReachedNode RETURN ReachedNode

This query searches for routes to BFS from BKK, returning the starting node (BKK), 5 visited vertices, and their parents:

MATCH (n) where n.code CONTAINS "BKK" CALL neptune.algo.bfs.parents(n, {edgeLabels: ["route"]}) YIELD node, parent RETURN n, node, parent LIMIT 5
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 .bfs.parents output

Here is an example of the output returned by .bfs.parents 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.bfs.parents(['101'], {maxDepth: 1}) YIELD source, node, parent RETURN source, node, parent 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", "lon": 100.747001647949, "country": "TH", "icao": "VTBS", "runways": 2 } }, "node": { "~id": "1483", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 39.49, "elev": 4557, "longest": 9186, "city": "Ordos", "type": "airport", "region": "CN-15", "desc": "Ordos Ejin Horo Airport", "code": "DSN", "lon": 109.861388889, "country": "CN", "icao": "ZBDS", "runways": 1 } }, "parent": { "~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", "lon": 100.747001647949, "country": "TH", "icao": "VTBS", "runways": 2 } } }, { "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", "lon": 100.747001647949, "country": "TH", "icao": "VTBS", "runways": 2 } }, "node": { "~id": "103", "~entityType": "node", "~labels": ["airport"], "~properties": { "lat": 55.972599029541, "elev": 622, "longest": 12139, "city": "Moscow", "type": "airport", "region": "RU-MOS", "desc": "Moscow, Sheremetyevo International Airport", "code": "SVO", "lon": 37.4146003723145, "country": "RU", "icao": "UUEE", "runways": 2 } }, "parent": { "~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", "lon": 100.747001647949, "country": "TH", "icao": "VTBS", "runways": 2 } } } ] }