The technical principle analysis and practice of NEO4J database

The technical principle analysis and practice of NEO4J database Summary: NEO4J is a NOSQL database for graph -oriented data. Its core principle is based on the theory of graphology and diagram database, which provides the ability to store, query and operate large -scale diagram data.This article will explore the technical principles of the NEO4J database and demonstrate the use of NEO4J through practice. 1 Introduction Neo4J is a high -performance map database that is designed to process complex relationship data.Compared with the traditional relationship database, Neo4J stores data in the graph structure. Each data entity is a node, and the relationship between entities is edge.The advantage of this data model is that it can quickly query the relationship between the entities, and it is suitable for the fields of social network analysis, recommendation systems, and knowledge maps. 2. Technical principle analysis 2.1 Database Neo4J is a NOSQL database based on the theory of graphic database.The diagram database is a database type specifically used to store and process graph data. Its core concept is nodes and edges.Nodes indicate data entities, while representing the relationship between entities.The combination of nodes and edges can constitute a complex relationship network, which makes the graph database have a natural advantage in processing complex relationship data. 2.2 Properties diagram model NEO4J uses attribute graph models to represent and store data.The attribute diagram model consists of nodes, relationships and attributes.Nodes represent entity, relationships represent the relationship between entities, and attributes are the additional attributes of entity and relationship.Both nodes and relationships can have multiple attributes, and the attributes can be a key value pair of any type.The flexibility of the attribute chart model enables NEO4J to store rich data structures, not limited to simple key values. 2.3 Storage engine Neo4J uses a storage engine called "Property Graph Store" to manage data.The storage engine decomposes the data data into smaller units in order to store and processes efficiently.Property Graph Store uses a storage structure based on page files. Pages are basic units of storage data. Each page contains one or more nodes and relationships.Through reasonable page organizations and indexes, Neo4J realizes efficient data access and query. 3. Practice demonstration 3.1 Installation and configuration First, we need to download and install the Neo4J database.After the installation is completed, the relevant parameters of the database need to be configured, such as the monitoring address, the port number, and the certification configuration.The configuration method can be implemented by editing the configuration file or using the management tools provided by NEO4J. 3.2 Data import and query Neo4J provides a variety of ways to import data, including CSV files, via API, etc.After the data is imported, we can use CyPher to query the language to query the data.Cypher is a unique query language of NEO4J. It is a statement -style query language similar to SQL, which can flexibly define diagram query and operation. 3.3 Data visualization Neo4J provides its own visualization tool Neo4J Browser to visualize the data data.Through Neo4J Browser, we can intuitively view and operate diagram data, such as the style settings of nodes and relationships, nodes and relationships.In addition, third -party visualization tools such as Gephi can be used to visualize more flexibly. 4 Conclusion This article understands the technical principles of the NEO4J database, and demonstrates the use of NEO4J and related configurations through practice.As a high -performance graph database, Neo4J can play an important role in processing complex relationship data.By understanding the technical principles and functions of NEO4J, it can help us better cope with the challenges of relationship data mining and analysis. Code example: cypher // Create nodes CREATE (n:Person {name: 'Alice', age: 30}) // Create relationships CREATE (p1:Person {name: 'Bob', age: 35}) CREATE (p2:Person {name: 'Charlie', age: 40}) CREATE (n)-[:KNOWS]->(p1) CREATE (n)-[:KNOWS]->(p2) // Query nodes and relationships MATCH (n)-[r:KNOWS]->(p) WHERE n.name = 'Alice' RETURN n, r, p // Update node attributes MATCH (n:Person {name: 'Alice'}) SET n.age = 31 RETURN n // Delete nodes and relationships MATCH (n:Person {name: 'Bob'}) DETACH DELETE n Configuration example: # And port dbms.default_listen_address=0.0.0.0 dbms.default_listen_port=7474 # 认 认 dbms.security.auth_enabled=true dbms.security.auth_providers=neo4j dbms.security.auth_ldap.server=localhost:389 dbms.security.auth_ldap.realm=example.com The above is the analysis and practice of the technical principles of the Neo4J database. I hope it will help you understand and use NEO4J.By learning and practice, you will be able to better use the NEO4J database to store and process complex graph data.