apoc.agg.multiStats

Function Apoc Extended

apoc.agg.multiStats(nodeOrRel, keys) - Return a multi-dimensional aggregation

Signature

apoc.agg.multiStats(value :: NODE | RELATIONSHIP, keys :: LIST OF STRING) :: (MAP?)

Input parameters

Name	Type	Default
value	NODE \| RELATIONSHIP	null

Name

Type

Default

value

NODE | RELATIONSHIP

null

Usage Examples

Given this dataset:

CREATE (:Person { louvain: 596, neo4jImportId: "18349390", wcc: 48, lpa: 598, name: "aaa", another: 548}),
    (:Person { louvain: 596, neo4jImportId: "18349390", wcc: 48, lpa: 598, name: "eee", another: 549}),
    (:Person { louvain: 596, neo4jImportId: "18349390", wcc: 48, lpa: 598, name: "eee", another: 549}),
    (:Person { louvain: 597, neo4jImportId: "18349391", wcc: 48, lpa: 598, name: "eee", another: 549}),
    (:Person { louvain: 597, neo4jImportId: "18349392", wcc: 47, lpa: 596, name: "iii", another: 549}),
    (:Person { louvain: 597, neo4jImportId: "18349393", wcc: 47, lpa: 596, name: "iii", another: 549}),
    (:Person { louvain: 597, neo4jImportId: "18349394", wcc: 47, lpa: 596, name: "iii", another: 549}),
    (:Person { louvain: 597, neo4jImportId: "18349393", wcc: 47, lpa: 596, name: "iii", another: 10}),
    (:Person { louvain: 597, neo4jImportId: "18349394", wcc: 47, lpa: 596, name: "iii", another: 10})

We can create an optimized multiple aggregation based on the property key, similar to this one:

MATCH (p:Person)
WITH p
CALL {
    WITH p
    MATCH (n:Person {louvain: p.louvain})
    RETURN sum(p.louvain) AS sumLouvain, avg(p.louvain) AS avgLouvain, count(p.louvain) AS countLouvain
}
CALL {
    WITH p
    MATCH (n:Person {wcc: p.wcc})
    RETURN sum(p.wcc) AS sumWcc, avg(p.wcc) AS avgWcc, count(p.wcc) AS countWcc
}
CALL {
    WITH p
    MATCH (n:Person {another: p.another})
    RETURN sum(p.another) AS sumAnother, avg(p.another) AS avgAnother, count(p.another) AS countAnother
}
CALL {
    WITH p
    MATCH (lpa:Person {lpa: p.lpa})
    RETURN sum(p.lpa) AS sumLpa, avg(p.lpa) AS avgLpa, count(p.lpa) AS countLpa
}
RETURN p.name,
    sumLouvain, avgLouvain, countLouvain,
    sumWcc, avgWcc, countWcc,
    sumAnother, avgAnother, countAnother,
    sumLpa, avgLpa, countLpa

executing the following query:

MATCH (p:Person)
RETURN apoc.agg.multiStats(p, ["lpa","wcc","louvain", "another"]) as output

output

Table 1. Results
output
`{ "louvain" :{"596" :{"avg" :596.0, "count" :3, "sum" :1788}, "597" :{"avg" :597.0, "count" :6, "sum" :3582}}, "wcc" :{"47" :{"avg" :47.0, "count" :5, "sum" :235}, "48" :{"avg" :48.0, "count" :4, "sum" :192}}, "another" :{"548" :{"avg" :548.0, "count" :1, "sum" :548}, "549" :{"avg" :549.0, "count" :6, "sum" :3294}, "10" :{"avg" :10.0, "count" :2, "sum" :20}}, "lpa" :{"596" :{"avg" :596.0, "count" :5, "sum" :2980}, "598" :{"avg" :598.0, "count" :4, "sum" :2392}} }`

{
  "louvain" :{"596" :{"avg" :596.0, "count" :3, "sum" :1788}, "597" :{"avg" :597.0, "count" :6, "sum" :3582}},
  "wcc" :{"47" :{"avg" :47.0, "count" :5, "sum" :235}, "48" :{"avg" :48.0, "count" :4, "sum" :192}},
  "another" :{"548" :{"avg" :548.0, "count" :1, "sum" :548}, "549" :{"avg" :549.0, "count" :6, "sum" :3294}, "10" :{"avg" :10.0, "count" :2, "sum" :20}},
  "lpa" :{"596" :{"avg" :596.0, "count" :5, "sum" :2980}, "598" :{"avg" :598.0, "count" :4, "sum" :2392}}
}

which can be used, for example, to return a result similar to the Cypher one in this way:

MATCH (p:Person)
WITH apoc.agg.multiStats(p, ["lpa","wcc","louvain", "another"]) as data
MATCH (p:Person)
RETURN p.name,
    data.wcc[toString(p.wcc)].avg AS avgWcc,
    data.louvain[toString(p.louvain)].avg AS avgLouvain,
    data.lpa[toString(p.lpa)].avg AS avgLpa

Table 2. Results
avgWcc	avgLouvain	avgLpa
48.0	596.0	598.0
48.0	596.0	598.0
48.0	596.0	598.0
47.0	597.0	596.0
47.0	597.0	596.0
47.0	597.0	596.0
47.0	597.0	596.0
47.0	597.0	596.0