apoc.meta.data

Procedure

apoc.meta.data(config Map<String, Any>) - examines the given graph and returns a table of metadata.

Signature

apoc.meta.data(config = {} :: MAP?) :: (label :: STRING?, property :: STRING?, count :: INTEGER?, unique :: BOOLEAN?, index :: BOOLEAN?, existence :: BOOLEAN?, type :: STRING?, array :: BOOLEAN?, sample :: LIST? OF ANY?, left :: INTEGER?, right :: INTEGER?, other :: LIST? OF STRING?, otherLabels :: LIST? OF STRING?, elementType :: STRING?)

Input parameters

Name Type Default

config

MAP?

{}

Config parameters

The procedure support the following config parameters:

Table 1. Config parameters
name type default description

includeLabels

List<String>

[]

labels to include. Default is to include all labels

includeRels

List<String>

[]

relationship types to include. Default is to include all relationship types

excludesLabels

List<String>

[]

labels to include. Default is to include all relationship types

sample

Long

1000

number of nodes to sample per label

maxRels

Long

100

number of relationships to sample per relationship type

Table 2. Deprecated parameters
name type default description

labels

List<String>

[]

deprecated, use includeLabels

rels

List<String>

[]

deprecated, use includeRels

excludes

List<String>

[]

deprecated, use excludesLabels

Output parameters

Name Type

label

STRING?

property

STRING?

count

INTEGER?

unique

BOOLEAN?

index

BOOLEAN?

existence

BOOLEAN?

type

STRING?

array

BOOLEAN?

sample

LIST? OF ANY?

left

INTEGER?

right

INTEGER?

other

LIST? OF STRING?

otherLabels

LIST? OF STRING?

elementType

STRING?

Usage Examples

The examples in this section are based on the following sample graph:

CREATE (Keanu:Person {name:'Keanu Reeves', born:1964})
CREATE (TomH:Person {name:'Tom Hanks', born:1956})
CREATE (Carrie:Person {name:'Carrie-Anne Moss', born:1967})
CREATE (Laurence:Person {name:'Laurence Fishburne', born:1961})
CREATE (Hugo:Person {name:'Hugo Weaving', born:1960})
CREATE (LillyW:Person {name:'Lilly Wachowski', born:1967})
CREATE (LanaW:Person {name:'Lana Wachowski', born:1965})

CREATE (TheMatrix:Movie {title:'The Matrix', released:1999, tagline:'Welcome to the Real World'})
CREATE (TheMatrixReloaded:Movie {title:'The Matrix Reloaded', released:2003, tagline:'Free your mind'})
CREATE (TheMatrixRevolutions:Movie {title:'The Matrix Revolutions', released:2003, tagline:'Everything that has a beginning has an end'})
CREATE (SomethingsGottaGive:Movie {title:"Something's Gotta Give", released:2003})
CREATE (TheDevilsAdvocate:Movie {title:"The Devil's Advocate", released:1997, tagline:'Evil has its winning ways'})
CREATE (Something:Something:Else {foo: 'bar'})

CREATE (YouveGotMail:Movie {title:"You've Got Mail", released:1998, tagline:'At odds in life... in love on-line.'})
CREATE (SleeplessInSeattle:Movie {title:'Sleepless in Seattle', released:1993, tagline:'What if someone you never met, someone you never saw, someone you never knew was the only someone for you?'})
CREATE (ThatThingYouDo:Movie {title:'That Thing You Do', released:1996, tagline:'In every life there comes a time when that thing you dream becomes that thing you do'})
CREATE (CloudAtlas:Movie {title:'Cloud Atlas', released:2012, tagline:'Everything is connected'})

CREATE (Keanu)-[:ACTED_IN {roles:['Neo']}]->(TheMatrix)
CREATE (Keanu)-[:ACTED_IN {roles:['Neo']}]->(TheMatrixReloaded)
CREATE (Keanu)-[:ACTED_IN {roles:['Neo']}]->(TheMatrixRevolutions)
CREATE (Keanu)-[:ACTED_IN {roles:['Julian Mercer']}]->(SomethingsGottaGive)
CREATE (Keanu)-[:ACTED_IN {roles:['Kevin Lomax']}]->(TheDevilsAdvocate)

CREATE (TomH)-[:ACTED_IN {roles:['Joe Fox']}]->(YouveGotMail)
CREATE (TomH)-[:ACTED_IN {roles:['Sam Baldwin']}]->(SleeplessInSeattle)
CREATE (TomH)-[:ACTED_IN {roles:['Mr. White']}]->(ThatThingYouDo)
CREATE (TomH)-[:ACTED_IN {roles:['Zachry', 'Dr. Henry Goose', 'Isaac Sachs', 'Dermot Hoggins']}]->(CloudAtlas)

CREATE (Keanu)-[:LIKES {rate:10}]->(Carrie)
CREATE (Keanu)-[:LIKES {rate:6}]->(TomH)
CREATE (Keanu)-[:LIKES {rate:4}]->(Laurence)
CREATE (Keanu)-[:LIKES {rate:8}]->(Hugo)
CREATE (Keanu)-[:LIKES {rate:9}]->(LillyW)
CREATE (Keanu)-[:LIKES {rate:6}]->(LanaW)
CREATE (Keanu)-[:LIKES {rate:100}]->(TheMatrix)
CREATE (Carrie)-[:LIKES {rate:7}]->(Keanu)

CREATE (Something)-[:RELATED_TO {rate:99}]->(TheMatrix)
CREATE (Keanu)-[:RELATED_TO {rate:12}]->(TheMatrix)
CREATE (Keanu)-[:RELATED_TO {rate:12}]->(TheMatrixReloaded)
CREATE (Keanu)-[:RELATED_TO {rate:23}]->(TheMatrixRevolutions)
CREATE (Carrie)-[:RELATED_TO {rate:34}]->(TheMatrix)
CREATE (TheMatrix)-[:RELATED_TO {rate:34}]->(Laurence)
CREATE (TheMatrixReloaded)-[:RELATED_TO {rate:345}]->(LanaW)
CALL apoc.meta.data();
Table 3. Results
label property count unique index existence type array sample left right other otherLabels elementType

"ACTED_IN"

"Person"

2

false

false

false

"RELATIONSHIP"

true

null

4

0

["Movie"]

[]

"relationship"

"ACTED_IN"

"roles"

0

false

false

false

"LIST"

true

null

0

0

[]

[]

"relationship"

"LIKES"

"Person"

2

false

false

false

"RELATIONSHIP"

true

null

4

1

["Movie", "Person"]

[]

"relationship"

"LIKES"

"rate"

0

false

false

false

"INTEGER"

false

null

0

0

[]

[]

"relationship"

"RELATED_TO"

"Person"

2

false

false

false

"RELATIONSHIP"

true

null

2

0

["Movie"]

[]

"relationship"

"RELATED_TO"

"rate"

0

false

false

false

"INTEGER"

false

null

0

0

[]

[]

"relationship"

"RELATED_TO"

"Movie"

2

false

false

false

"RELATIONSHIP"

false

null

1

2

["Person"]

[]

"relationship"

"RELATED_TO"

"Something"

1

false

false

false

"RELATIONSHIP"

false

null

1

0

["Movie"]

[]

"relationship"

"RELATED_TO"

"Else"

1

false

false

false

"RELATIONSHIP"

false

null

1

0

["Movie"]

[]

"relationship"

"Person"

"RELATED_TO"

2

false

false

false

"RELATIONSHIP"

true

null

2

0

["Movie"]

[]

"node"

"Person"

"ACTED_IN"

2

false

false

false

"RELATIONSHIP"

true

null

4

0

["Movie"]

[]

"node"

"Person"

"LIKES"

2

false

false

false

"RELATIONSHIP"

true

null

4

1

["Movie", "Person"]

[]

"node"

"Person"

"born"

0

false

false

false

"INTEGER"

false

null

0

0

[]

[]

"node"

"Person"

"name"

0

false

false

false

"STRING"

false

null

0

0

[]

[]

"node"

"Movie"

"RELATED_TO"

2

false

false

false

"RELATIONSHIP"

false

null

1

2

["Person"]

[]

"node"

"Movie"

"title"

0

false

false

false

"STRING"

false

null

0

0

[]

[]

"node"

"Movie"

"tagline"

0

false

false

false

"STRING"

false

null

0

0

[]

[]

"node"

"Movie"

"released"

0

false

false

false

"INTEGER"

false

null

0

0

[]

[]

"node"

"Something"

"RELATED_TO"

1

false

false

false

"RELATIONSHIP"

false

null

1

0

["Movie"]

[]

"node"

"Something"

"foo"

0

false

false

false

"STRING"

false

null

0

0

[]

[]

"node"

"Else"

"RELATED_TO"

1

false

false

false

"RELATIONSHIP"

false

null

1

0

["Movie"]

[]

"node"

"Else"

"foo"

0

false

false

false

"STRING"

false

null

0

0

[]

[]

"node"

The unique column shows if there is an unique constraint in that specific label and property. Similarly, the index column show if there is an index or not, while the existence looks for an existence constraint.

The array column check if the row is of type array and, in case type columns is "RELATIONSHIP", the result will be true if there is at least one node with 2 outgoing relationships with the type of relation given by label or property column, so ACTED_IN in the example above.

The left, right and count columns regard only rows with column type equals to "RELATIONSHIP" (otherwise they are equal to 0). Please note that, because we examine a sample, these counts are just estimates to give an overview and proximity to actual values depends on the dataset and the sample set (default 100).

In particular the count column indicates the number of nodes with an outgoing relationship (e.g. the row with label = ACTED_IN and property = Person has count 2 because there are 2 nodes (node:Person)-[:ACTED_IN]→(), i.e. (Keanu) and (TomH)).

The left value represents the ratio (rounded down) of the count of the outgoing patterns for a certain label and a specific type of relationship to count. In cypher, it corresponds to:

MATCH p=(start:`<LABEL>`)-[:`<TYPE>`]->()
WITH count(distinct start) as nodes, count(p) as counts
RETURN CASE when nodes = 0 then 0 else counts / nodes end

For example, regarding the row with label = RELATED_TO and property = Movie, there are 2 relationships (:Movie)-[rel:RELATED_TO]→(), i.e (TheMatrix)-[:RELATED_TO {rate:34}]→(Laurence) and (TheMatrixReloaded)-[:RELATED_TO {rate:345}]→(LanaW). So the left value is 1 (2 relationships divided by 2 nodes found).

Instead, regarding the row with label = LIKES and property = Person, there are 8 relationships (:Person)-[rel:LIKES]→(), 7 starting from (Keanu) node, and 1 from (Carrie). Then the left value is 4 (8 relationships divided by 2 nodes found).

The right value is the ratio (rounded down) of the count of the incoming patterns for a certain label and a specific type of relationship to count, where the patterns included in the count are those in which there is an equivalent outgoing relationship. In cypher it corresponds to:

MATCH p=(start:`<LABEL>`)<-[:`<TYPE>`]-()
WHERE exists((start:`<LABEL>`)-[:`<TYPE>`]->())
WITH count(distinct start) as nodes, count(p) as counts
RETURN CASE when nodes = 0 then 0 else counts / nodes end

For example, regarding the row with label = RELATED_TO and property = Movie, the (TheMatrix) node, which has an outgoing RELATED_TO relationship, has 3 incoming relationships as well, while the TheMatrixReloaded node has 1 incoming relationship. So the right value is 2, that is 4 divided by 2 node founds.

Therefore, via the right and left values, we provide a dataset estimate of the possible degree averages.