How to count distance/hops/length (# relationships) between nodes using cypher?

Question

I'm trying to determine the "distance" between nodes in a graph. Using the example movie database, I would like to return actor nodes with the distance away from Kevin Bacon. Using the image below for effectively what I'm looking for.

How do I build this into my cypher query? This seems possible, I just can't think of a way to do it as my cypher-foo isn't very advanced yet :(

MATCH p=(bacon:Person {name:"Kevin Bacon"})-[*1..5]-(hollywood)
WHERE hollywood.name in (['Helen Hunt', 'Ed Harris'])
RETURN p

FYI - My neo4j database is v4.0

Your query only looks for paths of up to 5 steps between Kevin Bacon and either Helen Hunt or Ed Harris, so your visualization does not show "all actor nodes" at given "distances" from Kevin Bacon. Can you clarify what your actual use case is? Also, normally a single path step is considered a "distance" of 1. You seem to have a different definition of "distance" that may be difficult to calculate (or whose value can be very ambiguous) -- given that nodes can have any number of relationships of various types between them, and that the same node might appear multiple times in the same path. — cybersam
@cybersam - yes, I limited it to 5 steps in qry just for simplification of the image. I updated the image to show more clearly my need and more basic definition of distance. Define distance as the number of relationships between a specific anchor node (Kevin Bacon) and each other node in the graph. I don't actually need it for ALL nodes, just the nodes in my cypher query, so for the example query, just tack on an additional attribute of "distance" as described above. Does that make sense? — NumericOverflow

cybersam cybersam · Accepted Answer · 2020-03-06T00:53:31

This query:

MATCH p=(bacon:Person {name:"Kevin Bacon"})-[*1..5]-(hollywood)
WHERE hollywood.name IN ['Helen Hunt', 'Ed Harris']
UNWIND
  REDUCE(s = [], i IN RANGE(0, LENGTH(p)) |
    s + {dist: i, node: NODES(p)[i]}
  ) AS data
RETURN data.dist AS distance, COLLECT(DISTINCT data.node) AS nodes

returns this result:

╒══════════╤═════════════════════════════════════════════════════════════════════╕
│"distance"│"nodes"                                                              │
╞══════════╪═════════════════════════════════════════════════════════════════════╡
│0         │[{"name":"Kevin Bacon","born":1958}]                                 │
├──────────┼─────────────────────────────────────────────────────────────────────┤
│1         │[{"title":"Apollo 13","tagline":"Houston, we have a problem.","releas│
│          │ed":1995},{"title":"A Few Good Men","tagline":"In the heart of the na│
│          │tion's capital, in a courthouse of the U.S. government, one man will │
│          │stop at nothing to keep his honor, and one will stop at nothing to fi│
│          │nd the truth.","released":1992},{"title":"Frost/Nixon","tagline":"400│
│          │ million people were waiting for the truth.","released":2008}]       │
├──────────┼─────────────────────────────────────────────────────────────────────┤
│2         │[{"name":"Tom Hanks","born":1956},{"name":"Ed Harris","born":1950},{"│
│          │name":"Bill Paxton","born":1955},{"name":"Cuba Gooding Jr.","born":19│
│          │68},{"name":"Jack Nicholson","born":1937},{"name":"Ron Howard","born"│
│          │:1954}]                                                              │
├──────────┼─────────────────────────────────────────────────────────────────────┤
│3         │[{"title":"Cast Away","tagline":"At the edge of the world, his journe│
│          │y begins.","released":2000},{"title":"Twister","tagline":"Don't Breat│
│          │he. Don't Look Back.","released":1996},{"title":"As Good as It Gets",│
│          │"tagline":"A comedy from the heart that goes for the throat.","releas│
│          │ed":1997},{"title":"Apollo 13","tagline":"Houston, we have a problem.│
│          │","released":1995}]                                                  │
├──────────┼─────────────────────────────────────────────────────────────────────┤
│4         │[{"name":"Helen Hunt","born":1963},{"name":"Ed Harris","born":1950}] │
└──────────┴─────────────────────────────────────────────────────────────────────┘

Notice that the movie "Apollo 13" appears in the results at distances of 1 and 3. And that "Ed Harris" appears at distances of 2 and 4. This is because there are (undirected) paths of different lengths from "Kevin Bacon" to those two nodes.

How to count distance/hops/length (# relationships) between nodes using cypher?

1 Answers