apoc.export.csv.all

Procedure APOC Core

apoc.export.csv.all(file,config) - exports whole database as csv to the provided file

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

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?

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:

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"

More documentation of apoc.export.csv.all