Explore the technical principles of the NEO4J database
NEO4J is an open source database management system with a highly scalable and graphical database function.It uses graphics structure to store and process data to make the relationship and connection between data more intuitive and easy to understand.This article will deeply explore the technical principles of the NEO4J database, including its basic concepts, data models, query language and graphic processing engines.
** 1. Basic concept **
The basic concepts of NEO4J databases include nodes (Node), Relationship, and Property.Nodes are the basic unit of data and can have any amount of attributes.Relations indicate the connection between nodes and can also have attributes.The attribute is the key value to the form data, which is used to describe the characteristics of nodes and relationships.
** 2. Data model **
The data model of NEO4J is based on graphics, where nodes and relationships constitute graphic databases.Nodes are used to represent entities or objects, such as people, objects, or concepts, while the relationship describes the connection between nodes.This model is very suitable for the relationship between complex entities, such as social networks, knowledge maps and recommendation systems.
** 3. Query language **
Neo4j uses a query language called CyPher, which is similar to SQL, but it is more suitable for processing graphic data.Cypher query language allows users to describe the required data in graphics mode and retrieve nodes and relationships that meet conditions.By matching the mode of nodes and relationships, the data in the graphical database can be very flexible.
cypher
// Find the names and age of all "friends"
MATCH (p:Person)-[:FRIEND]->(friend:Person)
RETURN friend.name, friend.age
The above example demonstrates how to use CyPher to query the nodes of all nodes of "Person" and its "Friend" relationship, and return the names and age of these nodes.
** 4. Graphic processing engine **
Neo4j uses the Property Graph data model and is equipped with a powerful graphical processing engine.The engine uses indexes and efficient traversal algorithms to support complex graphic query and graphic algorithms.It can quickly find nodes and relationships, and supports flexible filtering and aggregation based on nodes and relationships.This makes it possible to perform high -performance query in large -scale graphic databases.
** Example code and related configuration **
Below is an example code using NEO4J to create a simple graphical database and perform some basic query operations.
python
from neo4j import GraphDatabase
# To NEO4J database
uri = "bolt://localhost:7687"
driver = GraphDatabase.driver(uri, auth=("neo4j", "password"))
# Create a session
with driver.session() as session:
# Create node
session.run("CREATE (:Person {name: 'Alice', age: 30})")
session.run("CREATE (:Person {name: 'Bob', age: 35})")
# 创 创
session.run("MATCH (a:Person {name: 'Alice'}), (b:Person {name: 'Bob'}) "
"CREATE (a)-[:FRIEND]->(b)")
# Query node and relationship
result = session.run("MATCH (p:Person)-[:FRIEND]->(:Person) "
"RETURN p.name, p.age")
# Treatment query results
for record in result:
print(record["p.name"], record["p.age"])
# Close connection
driver.close()
In the above example code, we use the Py2neo Python driver to connect to the Neo4J database.First, we insert data by creating nodes and relationships.We then perform a CyPher query and handle the query results.
In order to make the code work normally, we need to install the Py2neo Python driver and modify the URI and certification information connected to the database according to the actual situation.
By exploring the technical principles of the NEO4J database, we understand its basic concepts, data models, query language and graphic processing engines.Neo4J provides a intuitive and efficient method to process graphics data, and has strong support in many applications, such as social network analysis, recommendation system and knowledge map construction.