apoc.import.json

Procedure

apoc.import.json(urlOrBinaryFile ANY, config MAP<STRING, ANY>) - imports a graph from the provided JSON file.

Signature

apoc.import.json(urlOrBinaryFile :: ANY, 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
urlOrBinaryFile	ANY	null
config	MAP	{}

Name

Type

Default

urlOrBinaryFile

ANY

null

config

MAP

{}

Config parameters

This procedure supports the following config parameters:

Table 1. Config parameters
name	type	default	description
unwindBatchSize	INTEGER	`5000`	the batch size of the unwind
txBatchSize	INTEGER	`5000`	the batch size of the transacttion
importIdName	STRING	`neo4jImportId`	the name of the property to be populated with the "id" field present into the json. For example a row `{"type":"node", "labels":["Language"], "id":"10"}`, with importIdName:`foo`, will create a node `(:User {foo: "10"})`
nodePropertyMappings	MAP	`{}`	The mapping label/property name/property type for Custom Neo4j types (point date). I.e. { User: { born: 'Point', dateOfBirth: 'Datetime' } }
relPropertyMappings	MAP	`{}`	The mapping rel type/property name/property type for Custom Neo4j types (point date). I.e. { KNOWS: { since: 'Datetime' } }
compression	`Enum[NONE, BYTES, GZIP, BZIP2, DEFLATE, BLOCK_LZ4, FRAMED_SNAPPY]`	`null`	Allow taking binary data, either not compressed (value: `NONE`) or compressed (other values)
cleanup	BOOLEAN	false	To remove the "id" field present into the json, if present. Note that in this way we cannot import relationship, because we leverage on "id" field to connect the nodes.
nodePropFilter	MAP<STRING, LIST<STRING>>	`{}`	A map with the labels as keys, and the list of property keys to filter during the import as values. For example `{ User: ['name', 'surname'], Another: ['foo']}` will skip the properties 'name' and 'surname' of nodes with label 'User' and the property 'foo' of (:Another) nodes. Note that if a node has multiple labels, in this example `(:User:Another {})`, all properties of both labels will be filtered, that is 'name', 'surname', and 'foo'. We can also pass a key `_all` to filter properties of all nodes, for example `{_all: ['myProp']}`
relPropFilter	MAP<STRING, LIST<STRING>>	`{}`	A map with the relationship types as keys, and the list of property keys to filter during the import as values. For example `{ MY_REL: ['foo', 'baz'] }` will skip the properties 'foo' and 'baz' of '[:MY_REL]' relationship. We can also pass a key `_all` to filter properties of all relationships, for example `{_all: ['myProp']}`

nodePropertyMappings and relPropertyMappings support the following Neo4j types:

Point
Localdate
Localtime
Localdatetime
Duration
offsettime
Zoneddatetime

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 apoc.import.json procedure can be used to import JSON files created by the apoc.export.json.* procedures, exported using the config parameter jsonFormat: 'JSON_LINES' (default config).

all.json contains a subset of Neo4j’s movies graph, and was generated by apoc.export.json.all.

all.json

{"type":"node","id":"0","labels":["User"],"properties":{"born":"2015-07-04T19:32:24","name":"Adam","place":{"crs":"wgs-84","latitude":13.1,"longitude":33.46789,"height":null},"age":42,"male":true,"kids":["Sam","Anna","Grace"]}}
{"type":"node","id":"1","labels":["User"],"properties":{"name":"Jim","age":42}}
{"type":"node","id":"2","labels":["User"],"properties":{"age":12}}
{"id":"0","type":"relationship","label":"KNOWS","properties":{"bffSince":"P5M1DT12H","since":1993},"start":{"id":"0","labels":["User"],"properties":{"born":"2015-07-04T19:32:24","name":"Adam","place":{"crs":"wgs-84","latitude":13.1,"longitude":33.46789,"height":null},"age":42,"male":true,"kids":["Sam","Anna","Grace"]}},"end":{"id":"1","labels":["User"],"properties":{"name":"Jim","age":42}}}

We can import this file using apoc.import.json.

CALL apoc.import.json("file:///all.json")

Table 2. Results
file	source	format	nodes	relationships	properties	time	rows	batchSize	batches	done	data
"file:///all.json"	"file"	"json"	3	1	15	105	4	-1	0	TRUE	NULL

Binary file

You can also import a file from a binary byte[] not compressed (default value, with config {compression: NONE}) or a compressed file (allowed compression algos are: GZIP, BZIP2, DEFLATE, BLOCK_LZ4, FRAMED_SNAPPY). That is:

CALL apoc.import.json(`binaryFileNotCompressed`, {compression: 'NONE'})

or:

CALL apoc.import.json(`binaryGzipByteArray`, {compression: 'GZIP'})

For example, this one works well with apoc.util.compress function:

WITH apoc.util.compress('{"type":"node","id":"2","labels":["User"],"properties":{"age":12}}', {compression: 'DEFLATE'}) AS jsonCompressed
CALL apoc.import.json(jsonCompressed, {compression: 'DEFLATE'})
YIELD source, format, nodes, relationships, properties
RETURN source, format, nodes, relationships, properties

Table 3. Results
source	format	nodes	relationships	properties
"binary"	"json"	1	0	2