Data import is a critical step in building graph databases with Neo4j. This post explores the Neo4j Data Importer, a powerful tool designed for creating graph data models from CSV files. The process involves creating nodes, labels, relationships, and properties, as well as setting constraints, unique IDs, and indexes to ensure optimal performance.

Understanding the Neo4j Data Importer

The Neo4j Data Importer is a browser-based tool that allows you to visually map your data from CSV files to a graph model. It generates Cypher statements for data import, which can be executed directly or saved for later use.

Preparing Your Data

Before importing, ensure your CSV files are well-structured:

1. Use consistent delimiters (commas are standard)

2. Include a header row with column names

3. Ensure data types are consistent within each column

4. Handle null values appropriately (empty fields or explicit “NULL” strings)

Creating Nodes and Labels

To create nodes:

1. Select the CSV file containing node data

2. Choose the columns that will become node properties

3. Assign a label to the node (e.g., :Person, :Product)

Example Cypher generated by the importer:

LOAD CSV WITH HEADERS FROM 'file:///movies.csv' AS row
MERGE (:Movie {movieId: toInteger(row.movieId)})
ON CREATE SET 
  .title = row.title,
  .releaseYear = toInteger(row.releaseYear)

Defining Relationships

To create relationships:

1. Select the source and target node types

2. Choose the relationship type

3. Map CSV columns to relationship properties (if any)

Example Cypher:

LOAD CSV WITH HEADERS F
ROM 'file:///acted_in.csv' AS row
MATCH (m:Movie {movieId: toInteger(row.movieId)})
MATCH (a:Actor {actorId: toInteger(row.actorId)})
CREATE (a)-[:ACTED_IN {
  role: row.role,
  year: toInteger(row.year)
}]->(m)

Setting Unique IDs and Constraints

When using the Neo4j Data Importer, setting a unique ID automatically creates both a constraint and an index for the specified property. This approach ensures data integrity and query performance optimization in one step.

To set a unique ID:

1. Select a node in the Data Importer interface

2. Navigate to the ‘Constraints & Indexes’ tab

3. Choose the property to serve as the unique ID

For example, setting movieId as the unique ID for the Movie node will:

• Create a unique constraint named movieId_Movie_uniq on the movieId property

• Automatically create an index for movieId

The generated Cypher for this constraint would look like:

CREATE CONSTRAINT movieId_Movie_uniq IF NOT EXISTS
FOR (n:Movie) REQUIRE n.movieId IS UNIQUE

Important points to note:

• The constraint ensures uniqueness across all nodes with the same label

• Attempting to create a new node with a duplicate movieId will result in an error

• Setting a unique ID causes the importer to use MERGE instead of CREATE, updating existing nodes rather than creating duplicates

Creating Indexes

Indexes in Neo4j significantly improve query performance by expediting node lookups based on specific properties. The Data Importer provides two ways to create indexes:

1. Automatic index creation for unique ID properties

2. Manual index creation for additional properties

To manually create an index:

1. Select the node in the Data Importer

2. Go to the ‘Constraints & Indexes’ tab

3. Click the ‘+’ button in the ‘Indexes’ section

4. Choose the property to index (e.g., title for Movie nodes)

The Data Importer will create a default index, which in Neo4j is a RANGE index. The generated Cypher for this would be:

CREATE INDEX title_Movie IF NOT EXISTS FOR (n:Movie) ON (n.title)

Key points about indexing:

• The unique ID index (e.g., movieId_Movie_uniq) is created automatically

• Additional indexes (e.g., title_Movie) can be added manually

• Indexes speed up queries that filter or search on the indexed properties

To view all created indexes after import, you can run:

SHOW INDEXES

This will display all indexes, including those created automatically for unique IDs and those added manually.

Conclusion

The Neo4j Data Importer simplifies the process of creating a graph data model from CSV files. By carefully considering your data structure, setting appropriate constraints and indexes, you can efficiently build robust graph databases in Neo4j.

Remember that while the Data Importer is powerful, complex import scenarios may require custom Cypher scripts or ETL processes. Always test your import process thoroughly, especially with large datasets, to ensure data integrity and optimal performance.