apoc.export.csv.all

Procedure

apoc.export.csv.all(file STRING, config MAP<STRING, ANY>) - exports the full database to the provided CSV file.

This procedure is not considered safe to run from multiple threads. It is therefore not supported by the parallel runtime (introduced in Neo4j 5.13). For more information, see the Cypher Manual → Parallel runtime.

Signature

apoc.export.csv.all(file :: STRING, config :: MAP) :: (file :: STRING, source :: STRING, format :: STRING, nodes :: INTEGER, relationships :: INTEGER, properties :: INTEGER, time :: INTEGER, rows :: INTEGER, batchSize :: INTEGER, batches :: INTEGER, done :: BOOLEAN, data :: STRING)

Input parameters

Name Type Default

file

STRING

null

config

MAP

null

Output parameters

Name Type

file

STRING

source

STRING

format

STRING

nodes

INTEGER

relationships

INTEGER

properties

INTEGER

time

INTEGER

rows

INTEGER

batchSize

INTEGER

batches

INTEGER

done

BOOLEAN

data

STRING

Usage Examples

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

CREATE (TheMatrix:Movie {title:'The Matrix', released:1999, tagline:'Welcome to the Real World'})
CREATE (Keanu:Person {name:'Keanu Reeves', born:1964})
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 (JoelS:Person {name:'Joel Silver', born:1952})
CREATE
(Keanu)-[:ACTED_IN {roles:['Neo']}]->(TheMatrix),
(Carrie)-[:ACTED_IN {roles:['Trinity']}]->(TheMatrix),
(Laurence)-[:ACTED_IN {roles:['Morpheus']}]->(TheMatrix),
(Hugo)-[:ACTED_IN {roles:['Agent Smith']}]->(TheMatrix),
(LillyW)-[:DIRECTED]->(TheMatrix),
(LanaW)-[:DIRECTED]->(TheMatrix),
(JoelS)-[:PRODUCED]->(TheMatrix);

The Neo4j Browser visualization below shows the imported graph:

play movies

The apoc.export.csv.all procedure exports the whole database to a CSV file or as a stream.

The following query exports the whole database to the file movies.csv:

CALL apoc.export.csv.all("movies.csv", {})
Table 1. Results
file source format nodes relationships properties time rows batchSize batches done data

"movies.csv"

"database: nodes(8), rels(7)"

"csv"

8

7

21

39

15

20000

1

TRUE

NULL

The contents of movies.csv are shown below:

movies.csv
"_id","_labels","born","name","released","tagline","title","_start","_end","_type","roles"
"188",":Movie","","","1999","Welcome to the Real World","The Matrix",,,,
"189",":Person","1964","Keanu Reeves","","","",,,,
"190",":Person","1967","Carrie-Anne Moss","","","",,,,
"191",":Person","1961","Laurence Fishburne","","","",,,,
"192",":Person","1960","Hugo Weaving","","","",,,,
"193",":Person","1967","Lilly Wachowski","","","",,,,
"194",":Person","1965","Lana Wachowski","","","",,,,
"195",":Person","1952","Joel Silver","","","",,,,
,,,,,,,"189","188","ACTED_IN","[""Neo""]"
,,,,,,,"190","188","ACTED_IN","[""Trinity""]"
,,,,,,,"191","188","ACTED_IN","[""Morpheus""]"
,,,,,,,"192","188","ACTED_IN","[""Agent Smith""]"
,,,,,,,"193","188","DIRECTED",""
,,,,,,,"194","188","DIRECTED",""
,,,,,,,"195","188","PRODUCED",""

The following query returns a stream of the whole database in the data column:

CALL apoc.export.csv.all(null, {stream:true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data
Table 2. Results
file nodes relationships properties data

NULL

8

7

21

"\"_id\",\"_labels\",\"born\",\"name\",\"released\",\"tagline\",\"title\",\"_start\",\"_end\",\"_type\",\"roles\" \"188\",\":Movie\",\"\",\"\",\"1999\",\"Welcome to the Real World\",\"The Matrix\",,,, \"189\",\":Person\",\"1964\",\"Keanu Reeves\",\"\",\"\",\"\",,,, \"190\",\":Person\",\"1967\",\"Carrie-Anne Moss\",\"\",\"\",\"\",,,, \"191\",\":Person\",\"1961\",\"Laurence Fishburne\",\"\",\"\",\"\",,,, \"192\",\":Person\",\"1960\",\"Hugo Weaving\",\"\",\"\",\"\",,,, \"193\",\":Person\",\"1967\",\"Lilly Wachowski\",\"\",\"\",\"\",,,, \"194\",\":Person\",\"1965\",\"Lana Wachowski\",\"\",\"\",\"\",,,, \"195\",\":Person\",\"1952\",\"Joel Silver\",\"\",\"\",\"\",,,, ,,,,,,,\"189\",\"188\",\"ACTED_IN\",\"[\"\"Neo\"\"]\" ,,,,,,,\"190\",\"188\",\"ACTED_IN\",\"[\"\"Trinity\"\"]\" ,,,,,,,\"191\",\"188\",\"ACTED_IN\",\"[\"\"Morpheus\"\"]\" ,,,,,,,\"192\",\"188\",\"ACTED_IN\",\"[\"\"Agent Smith\"\"]\" ,,,,,,,\"193\",\"188\",\"DIRECTED\",\"\" ,,,,,,,\"194\",\"188\",\"DIRECTED\",\"\" ,,,,,,,\"195\",\"188\",\"PRODUCED\",\"\" "

You can use the configuration sampling (default: false). With this config, the apoc.export.csv.all procedure uses the apoc.meta.nodeTypeProperties and the apoc.meta.relTypeProperties procedures under the hood to get the property types. You can customize the configuration of these 2 apoc.meta.* procedure, using the samplingConfig: MAP configuration, to limit the number of nodes/rels to analyze.

So you can execute with the following data set:

CREATE (:User:Sample {`last:Name`:'Galilei'}), (:User:Sample {address:'Universe'}),
    (:User:Sample {foo:'bar'})-[:KNOWS {one: 'two', three: 'four'}]->(:User:Sample {baz:'baa', foo: true})

Combined with the following query:

CALL apoc.export.csv.all('movies.csv', {sampling: true, samplingConfig: {sample: 1}})
Table 3. Results
file source format nodes relationships properties time rows batchSize batches done data

"movies.csv"

"database: nodes(4), rels(1)"

"csv"

4

1

3

4

5

20000

1

TRUE

NULL

Execution of the above query would output content similar to that below (result could change depending on the sample):

movies.csv
"_id","_labels","baz","foo","_start","_end","_type"
"0",":Sample:User","","",,,
"1",":Sample:User","","",,,
"2",":Sample:User","","bar",,,
"3",":Sample:User","baa","true",,,
,,,,"2","3","KNOWS"