Export to CSV

The export CSV procedures export data into a format more supported by Data Science libraries in the Python and R ecosystems. We may also want to export data into JSON format for importing into other tools or for general sharing of query results. The procedures described in this section support exporting to a file or as a stream.

For apoc.export.csv.all, apoc.export.csv.data and apoc.export.csv.graph, nodes and relationships properties are ordered alphabetically, using the following structure:

_id,_labels,<list_nodes_properties_naturally_sorted>,_start,_end,_type,<list_rel_properties_naturally_sorted>.

For a graph containing node properties age, city, kids, male, name, and street and containing relationship propeties bar and foo, we’d have the following:

_id,_labels,age,city,kids,male,name,street,_start,_end,_type,bar,foo

Labels exported are ordered alphabetically. The output of labels() function is not sorted, use it in combination with apoc.coll.sort().

Note that, to perform a correct Point serialization, it is not recommended to export a point with coordinates x,y and crs: 'wgs-84', for example point({x: 56.7, y: 12.78, crs: 'wgs-84'}). Otherwise, the point will be exported with longitude and latitude (and height) instead of x and y (and z)

Available Procedures

The table below describes the available procedures:

Qualified Name Type

Qualified Name	Type
apoc.export.csv.all `apoc.export.csv.all(file,config)` - exports whole database as csv to the provided file	`Procedure`
apoc.export.csv.data `apoc.export.csv.data(nodes,rels,file,config)` - exports given nodes and relationships as csv to the provided file	`Procedure`
apoc.export.csv.graph `apoc.export.csv.graph(graph,file,config)` - exports given graph object as csv to the provided file	`Procedure`
apoc.export.csv.query `apoc.export.csv.query(query,file,{config,…,params:{params}})` - exports results from the cypher statement as csv to the provided file	`Procedure`

apoc.export.csv.all

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

Procedure

apoc.export.csv.data

apoc.export.csv.data(nodes,rels,file,config) - exports given nodes and relationships as csv to the provided file

Procedure

apoc.export.csv.graph

apoc.export.csv.graph(graph,file,config) - exports given graph object as csv to the provided file

Procedure

apoc.export.csv.query

apoc.export.csv.query(query,file,{config,…,params:{params}}) - exports results from the cypher statement as csv to the provided file

Procedure

Exporting to a file

By default exporting to the file system is disabled. We can enable it by setting the following property in apoc.conf:

apoc.conf

apoc.export.file.enabled=true

For more information about accessing apoc.conf, see the chapter on Configuration Options.

If we try to use any of the export procedures without having first set this property, we’ll get the following error message:

Failed to invoke procedure: Caused by: java.lang.RuntimeException: Export to files not enabled, please set apoc.export.file.enabled=true in your apoc.conf. Otherwise, if you are running in a cloud environment without filesystem access, use the {stream:true} config and null as a 'file' parameter to stream the export back to your client.

Export files are written to the import directory, which is defined by the server.directories.import property. This means that any file path that we provide is relative to this directory. If we try to write to an absolute path, such as /tmp/filename, we’ll get an error message similar to the following one:

Failed to invoke procedure: Caused by: java.io.FileNotFoundException: /path/to/neo4j/import/tmp/fileName (No such file or directory)

We can enable writing to anywhere on the file system by setting the following property in apoc.conf:

apoc.conf

apoc.import.file.use_neo4j_config=false

Neo4j will now be able to write anywhere on the file system, so be sure that this is your intention before setting this property.

Exporting a stream

If we don’t want to export to a file, we can stream results back in the data column instead by passing a file name of null and providing the stream:true config.

Examples

This section includes examples showing how to use the export to CSV procedures. These examples are based on a movies dataset, which can be imported by running the following Cypher query:

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:

Export whole database to CSV

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\",\"\" "

Export specified nodes and relationships to CSV

The apoc.export.csv.data procedure exports the specified nodes and relationships to a CSV file or as a stream.

The following query exports all nodes with the :Person label with a name property that starts with L to the file movies-l.csv

MATCH (person:Person)
WHERE person.name STARTS WITH "L"
WITH collect(person) AS people
CALL apoc.export.csv.data(people, [], "movies-l.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data

Table 3. Results
file	source	format	nodes	relationships	properties	time	rows	batchSize	batches	done	data
"movies-l.csv"	"data: nodes(3), rels(0)"	"csv"	3	0	6	2	3	20000	1	TRUE	NULL

The contents of movies-l.csv are shown below:

"_id","_labels","born","name","_start","_end","_type"
"191",":Person","1961","Laurence Fishburne",,,
"193",":Person","1967","Lilly Wachowski",,,
"194",":Person","1965","Lana Wachowski",,,

The following query exports all ACTED_IN relationships and the nodes with Person and Movie labels on either side of that relationship to the file movies-actedIn.csv

MATCH (person:Person)-[actedIn:ACTED_IN]->(movie:Movie)
WITH collect(DISTINCT person) AS people, collect(DISTINCT movie) AS movies, collect(actedIn) AS actedInRels
CALL apoc.export.csv.data(people + movies, actedInRels, "movies-actedIn.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data

Table 4. Results
file	source	format	nodes	relationships	properties	time	rows	batchSize	batches	done	data
"movies-actedIn.csv"	"data: nodes(5), rels(4)"	"csv"	5	4	15	2	9	20000	1	TRUE	NULL

The contents of movies-actedIn.csv are shown below:

"_id","_labels","born","name","released","tagline","title","_start","_end","_type","roles"
"189",":Person","1964","Keanu Reeves","","","",,,,
"190",":Person","1967","Carrie-Anne Moss","","","",,,,
"191",":Person","1961","Laurence Fishburne","","","",,,,
"192",":Person","1960","Hugo Weaving","","","",,,,
"188",":Movie","","","1999","Welcome to the Real World","The Matrix",,,,
,,,,,,,"189","188","ACTED_IN","[""Neo""]"
,,,,,,,"190","188","ACTED_IN","[""Trinity""]"
,,,,,,,"191","188","ACTED_IN","[""Morpheus""]"
,,,,,,,"192","188","ACTED_IN","[""Agent Smith""]"

The following query returns a stream of all ACTED_IN relationships and the nodes with Person and Movie labels on either side of that relationship in the data column

MATCH (person:Person)-[actedIn:ACTED_IN]->(movie:Movie)
WITH collect(DISTINCT person) AS people, collect(DISTINCT movie) AS movies, collect(actedIn) AS actedInRels
CALL apoc.export.csv.data(people + movies, actedInRels, null, {stream: true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data

Table 5. Results
file	nodes	relationships	properties	data
`NULL`	`5`	`4`	`15`	"\"_id\",\"_labels\",\"born\",\"name\",\"released\",\"tagline\",\"title\",\"_start\",\"_end\",\"_type\",\"roles\" \"190\",\":Person\",\"1967\",\"Carrie-Anne Moss\",\"\",\"\",\"\",,,, \"189\",\":Person\",\"1964\",\"Keanu Reeves\",\"\",\"\",\"\",,,, \"191\",\":Person\",\"1961\",\"Laurence Fishburne\",\"\",\"\",\"\",,,, \"192\",\":Person\",\"1960\",\"Hugo Weaving\",\"\",\"\",\"\",,,, \"188\",\":Movie\",\"\",\"\",\"1999\",\"Welcome to the Real World\",\"The Matrix\",,,, ,,,,,,,\"189\",\"188\",\"ACTED_IN\",\"[\"\"Neo\"\"]\" ,,,,,,,\"190\",\"188\",\"ACTED_IN\",\"[\"\"Trinity\"\"]\" ,,,,,,,\"191\",\"188\",\"ACTED_IN\",\"[\"\"Morpheus\"\"]\" ,,,,,,,\"192\",\"188\",\"ACTED_IN\",\"[\"\"Agent Smith\"\"]\" "

Export results of Cypher query to CSV

The apoc.export.csv.query procedure exports the results of a Cypher query to a CSV file or as a stream.

The following query exports all DIRECTED relationships and the nodes with Person and Movie labels on either side of that relationship to the file movies-directed.csv

WITH "MATCH path = (person:Person)-[:DIRECTED]->(movie)
      RETURN person.name AS name, person.born AS born,
             movie.title AS title, movie.tagline AS tagline, movie.released AS released" AS query
CALL apoc.export.csv.query(query, "movies-directed.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data;

Table 6. Results
file	source	format	nodes	relationships	properties	time	rows	batchSize	batches	done	data
"movies-directed.csv"	"statement: cols(5)"	"csv"	0	0	10	3	2	20000	1	TRUE	NULL

The contents of movies-directed.csv are shown below:

"name","born","role","title","tagline","released"
"Lilly Wachowski","1967","","The Matrix","Welcome to the Real World","1999"
"Lana Wachowski","1965","","The Matrix","Welcome to the Real World","1999"

The following query returns a stream of all DIRECTED relationships and the nodes with Person and Movie labels on either side of that relationship

WITH "MATCH path = (person:Person)-[:DIRECTED]->(movie)
      RETURN person.name AS name, person.born AS born,
             movie.title AS title, movie.tagline AS tagline, movie.released AS released" AS query
CALL apoc.export.csv.query(query, null, {stream: true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data;

Table 7. Results
file	nodes	relationships	properties	data
`NULL`	`0`	`0`	`10`	"\"name\",\"born\",\"title\",\"tagline\",\"released\" \"Lilly Wachowski\",\"1967\",\"The Matrix\",\"Welcome to the Real World\",\"1999\" \"Lana Wachowski\",\"1965\",\"The Matrix\",\"Welcome to the Real World\",\"1999\" "

You can also compress the files to export. See here for more information

When the config bulkImport is enable it create a list of file that can be used for Neo4j Bulk Import.

This config can be used only with apoc.export.csv.all and apoc.export.csv.graph

All file create are named as follow:

Nodes file are construct with the name of the input file append with .nodes.[LABEL_NAME].csv
Rel file are construct with the name of the input file append with .relationships.[TYPE_NAME].csv

If Node or Relationship have more than one Label/Type it will create one file for Label/Type.

Configuration parameters

The procedures support the following config parameters:

Table 8. configuration options
param	default	description
batchSize	20000	The batch size.
delim	","	The delimiter character of the CSV file.
arrayDelim	";"	The delimiter character used for arrays (used in the bulk import).
quotes	'always'	Quote-characters used for CSV, possible values are: `none`: No quotes are added. `always`: Quotes are added around all values. `ifNeeded`: Applies quotes to strings only when necessary.
differentiateNulls	false	Creates a distinction between empty strings and null values. The behavior is influenced by the `quotes` config value: `none`: Empty strings and null are not quoted. `ifNeeded` && `differentiateNulls`: Empty strings are quoted with `""` and null values are left empty. `ifNeeded` && !`differentiateNulls`: Empty strings and null values are left empty. `always` && `differentiateNulls`: Empty strings are quoted with `""` and null values are left empty. `always` && !`differentiateNulls`: Empty strings and null values are quoted with `""`.
useTypes	false	Add the types on to the file header.
bulkImport	true	Create files for Neo4j Admin import.
timeoutSeconds	100	The maximum time in seconds the query should run before timing out.
separateHeader	false	Create two files: one for the header and one for the data.
streamStatements	false	Batch the results across multiple rows by configuring the `batchSize` config.
stream	false	Equivalent to the `streamStatements` config.

Quotes config example

It is possible to export the graph to a csv file using different quoting strategies.

The following queries are executed on a graph containing one node:

CREATE (:Quote {name: 'foo,bar,baz', array:["a","b","c"], other: 123})

Exporting without quotes

CALL apoc.export.csv.all("fileNoQuote.csv", {quotes: 'none'})

The following CSV file is returned:

fileNoQuote.csv

_id,_labels,array,name,other,_start,_end,_type
5,:Quote,["a","b","c"],foo,bar,baz,123,,,

Exporting with quotes

CALL apoc.export.csv.all("fileAlwaysQuote.csv", {quotes: 'always'})

The following CSV file is returned:

fileAlwaysQuote.csv

"_id","_labels","array","name","other","_start","_end","_type"
"5",":Quote","[""a"",""b"",""c""]","foo,bar,baz","123",,,

Exporting with quotes when needed

CALL apoc.export.csv.all("fileIfNeededQuote.csv", {quotes: 'ifNeeded'})

The following CSV file is returned:

fileIfNeededQuote.csv

_id,_labels,array,name,other,_start,_end,_type
5,:Quote,"[""a"",""b"",""c""]","foo,bar,baz",123,,,

Differentiate null values config example

By default, empty strings and null values are treated the same, but this behavior can be changed using the differentiateNulls config item.

The following queries are executed on a graph containing two nodes:

CREATE (:Quote {value1: "Hello", value2: ""})
CREATE (:Quote {value1: "I have a \"null\" value", value2: null})

Exporting with quotes and differentiating null values

CALL apoc.export.csv.all("fileAlwaysQuote.csv", {quotes: 'always', differentiateNulls: true})

The following CSV file is returned:

fileAlwaysQuote.csv

"_id","_labels","value1","value2","_start","_end","_type"
"0",":Quote","Hello","",,,
"1",":Quote","I have a ""null"" value",,,,

The empty string value for value2 is represented by quotes "", whereas the null value is left empty.

Exporting with quotes when needed and differentiating null values

CALL apoc.export.csv.all("fileIfNeededQuote.csv", {quotes: 'ifNeeded', differentiateNulls: true})

The following CSV file is returned:

fileIfNeededQuote.csv

_id,_labels,value1,value2,_start,_end,_type
0,:Quote,Hello,"",,,
1,:Quote,"I have a ""null"" value",,,,

The string Hello is left unquoted as it does not contain any special characters. The string I have a "null" value is quoted as it contains special characters. The empty string is quoted to differentiate it from a null value. The null value is empty.

Exporting without quotes

When exporting without quotes, the nulls and empty strings will always appear unquoted, regardless of what differentiateNulls is set to.

CALL apoc.export.csv.all("fileNoQuote.csv", {quotes: 'none', differentiateNulls: true})

The following CSV file is returned:

fileNoQuote.csv

_id,_labels,value1,value2,_start,_end,_type
0,:Quote,Hello,,,,
1,:Quote,I have a "null" value,,,,