Neo4j-admin import

In this example, you will import a small data set containing nodes and relationships. The data set is split into three CSV files, where each file has a header row describing the data.

The data set contains information about movies, actors, and roles. Data for movies and actors are stored as nodes and the roles are stored as relationships.

The files you want to import data from are:

Each movie in movies.csv has an ID, a title, and a year, stored as properties in the node. All the nodes in movies.csv also have the label Movie. A node can have several labels, as you can see in movies.csv there are nodes that also have the label Sequel. The node labels are optional, they are very useful for grouping nodes into sets where all nodes that have a certain label belong to the same set.

The actors' data in actors.csv consist of an ID and a name, stored as properties in the node. The ID in this case is a shorthand for the actor’s name. All the nodes in actors.csv have the label Actor.

The roles data in roles.csv have only one property, role. Roles are represented by relationship data that connects actor nodes with movie nodes.

There are three mandatory fields for relationship data:

To create a relationship between two nodes, the IDs defined in actors.csv and movies.csv are used for the :START_ID and :END_ID fields. You also need to provide a relationship type (in this case ACTED_IN) for the :TYPE field.

The call to neo4j-admin database import would look like this:

To query the data. Start Neo4j.

To query the imported data in the graph, try a simple Cypher query.

Stop Neo4j.

You can customize the configuration options that the import tool uses (see Options) if your data does not fit the default format.

The details of a CSV file header format can be found at CSV header format.

The following CSV files have:

The call to neo4j-admin database import would look like this:

When dealing with very large CSV files, it is more convenient to have the header in a separate file. This makes it easier to edit the header as you avoid having to open a huge data file just to change it. The header file must be specified before the rest of the files in each file group.

The import tool can also process single-file compressed archives, for example:

You will use the same data set as in the previous example but with the headers in separate files.

The call to neo4j-admin database import would look as follows:

In addition to using a separate header file, you can also provide multiple node or relationship files. Files within such an input group can be specified with multiple match strings, delimited by ,, where each matched string can be either the exact file name or a regular expression matching one or more files. Multiple matching files will be sorted according to their characters and their natural number sort order for file names containing numbers.

The call to neo4j-admin database import would look like this:

File names can be specified using regular expressions when there are many data source files. Each file name that matches the regular expression will be included.

If using separate header files, for the import to work correctly, the header file must be the first in the file group. When using regular expressions to specify the input files, the list of files will be sorted according to the names of the files that match the expression. The matching is aware of the numbers inside the file names and will sort them accordingly, without the need for padding with zeros.

Importing the data using regular expressions, the call to neo4j-admin database import can be simplified to:

If you want to use the same node label(s) for every node in your nodes file you can do this by specifying the appropriate value as an option to neo4j-admin database import. There is then no need to specify the :LABEL column in the header file and each row (node) will apply the specified labels from the command line option.

In this example, you want to have the label Movie on every node specified in movies5a.csv, and you put the labels Movie and Sequel on the nodes specified in sequels5a.csv.

The call to neo4j-admin database import would look like this:

If you want to use the same relationship type for every relationship in your relationships file this can be done by specifying the appropriate value as an option to neo4j-admin database import.

In this example, you want the relationship type ACTED_IN to be applied on every relationship specified in roles5b.csv.

The call to neo4j-admin database import would look like this:

Nodes and relationships can have properties. The property type is specified in the CSV header row, see CSV header format.

The following example creates a small graph containing one actor and one movie connected by one relationship.

There is a roles property on the relationship which contains an array of the characters played by the actor in a movie:

The call to neo4j-admin database import would look like this:

The import tool assumes that identifiers are unique across node files. This may not be the case for data sets that use sequential, auto-incremented, or otherwise colliding identifiers. Those data sets can define ID spaces where identifiers are unique within their respective ID space.

In cases where the node ID is unique only within files, using ID spaces is a way to ensure uniqueness across all node files. See Using ID spaces.

Each node processed by neo4j-admin database import must provide an ID if it is to be connected in any relationships. The node ID is used to find the start node and end node when creating a relationship.

For example, if movies and people both use sequential identifiers, then you would define Movie and Actor ID spaces.

You also need to reference the appropriate ID space in your relationships file so it knows which nodes to connect.

The call to neo4j-admin database import would look like this:

The import tool has no tolerance for bad entities (relationships or nodes) and will fail the import on the first bad entity. You can specify explicitly that you want it to ignore rows that contain bad entities.

There are two different types of bad input:

Relationships that refer to missing node IDs, either for :START_ID or :END_ID are considered bad relationships. Whether or not such relationships are skipped is controlled with the --skip-bad-relationships flag, which can have the values true or false or no value, which means true. The default is false, which means that any bad relationship is considered an error and will fail the import. For more information, see the --skip-bad-relationships option.

In the following example, there is a missing emil node referenced in the roles file.

The call to neo4j-admin database import would look like this:

Because there is a bad relationship in the input data, the import process will fail.

Let’s see what happens if you append the --skip-bad-relationships flag:

The data files are successfully imported and the bad relationship is ignored. An entry is written to the import.report file.

Nodes that specify :ID, which has already been specified within the ID space are considered bad nodes. Whether or not such nodes are skipped is controlled with --skip-duplicate-nodes flag which can have the values true or false or no value, which means true. The default is false, which means that any duplicate node is considered an error and will fail the import. For more information, see the --skip-duplicate-nodes option.

In the following example there is a node ID, laurence, that is specified twice within the same ID space.

The call to neo4j-admin database import would look like this:

Because there is a bad node in the input data, the import process will fail.

Let’s see what happens if you append the --skip-duplicate-nodes flag:

The data files are successfully imported and the bad node is ignored. An entry is written to the import.report file.