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手机如何看外网
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手机如何看外网

Get started with O'Reilly's express安卓加速器 and discover how graph databases can help you manage and query highly connected data.

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手机如何看外网

Neo4j is a native graph database, built from the ground up to leverage not only data but also data relationships. Neo4j connects data as it’s stored, enabling queries never before imagined, at speeds never thought possible.

手机如何看外网

Unlike traditional databases, which arrange data in rows, columns and tables, Neo4j has a flexible structure defined by stored relationships between data records.

With Neo4j, each data record, or node, stores direct pointers to all the nodes it’s connected to. Because Neo4j is designed around this simple, yet powerful optimization, it performs queries with complex connections orders of magnitude faster, and with more depth, than other databases.

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手机如何看外网

With Neo4j, connections between data are stored – not computed at query time. Cypher is a powerful, graph-optimized query language that understands, and takes advantage of, these stored connections.

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Cypher

      MATCH (p:Product)-[:CATEGORY]->(l:ProductCategory)-[:PARENT*0..]->(:ProductCategory {name:"Dairy Products"})
RETURN p.name
    

Here's a similar query in SQL, which is longer and more complex. Unlike Cypher, where depth is unlimited, this SQL query selects just three levels of depth.

SQL

      SELECT p.ProductName
FROM Product AS p
JOIN ProductCategory pc ON (p.CategoryID = pc.CategoryID AND pc.CategoryName = "Dairy Products")

JOIN ProductCategory pc1 ON (p.CategoryID = pc1.CategoryID)
JOIN ProductCategory pc2 ON (pc1.ParentID = pc2.CategoryID AND pc2.CategoryName = "Dairy Products")

JOIN ProductCategory pc3 ON (p.CategoryID = pc3.CategoryID)
JOIN ProductCategory pc4 ON (pc3.ParentID = pc4.CategoryID)
JOIN ProductCategory pc5 ON (pc4.ParentID = pc5.CategoryID AND pc5.CategoryName = "Dairy Products")
;
    

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手机如何看外网

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798安卓加速器破解下载版

        // npm install --save neo4j-driver
// node example.js
var neo4j = require('neo4j-driver');
var driver = neo4j.driver('bolt://<HOST>:<BOLTPORT>', 
                  neo4j.auth.basic('<USERNAME>', '<PASSWORD>'), 
                  {encrypted: 'ENCRYPTION_OFF'});

var query = 
  `MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie)
   WHERE movie.title IN \$favorites
   RETURN rec.title as title, count(*) as freq 
   ORDER BY freq DESC LIMIT 5`;

var params = {"favorites": ["The Matrix"]};

var session = driver.session();

session.run(query, params)
  .then(function(result) {
    result.records.forEach(function(record) {
        console.log(record.get('title'));
    })
	session.close();
    driver.close();
  })
  .catch(function(error) {
    console.log(error);
  });

      

        # pip install neo4j-driver
# python example.py

from neo4j import GraphDatabase, basic_auth

driver = GraphDatabase.driver(
    "bolt://<HOST>:<BOLTPORT>", 
    auth=basic_auth("<USERNAME>", "<PASSWORD>"))
session = driver.session()

cypher_query = '''
MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie)
WHERE movie.title IN $favorites
RETURN rec.title as title, count(*) as freq 
ORDER BY freq DESC LIMIT 5
'''

results = session.run(cypher_query,
  parameters={"favorites":["The Matrix"]})

for record in results:
  print(record['title'])

      

        //Install-Package Neo4j.Driver -Version 4.0.1
//Connecting to a 3.5.x Neo4j instance

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Neo4j.Driver;

public class SimpleExample
{
	private readonly IDriver _driver;
	public SimpleExample(string uri, string user, string password)
	{
		_driver = GraphDatabase.Driver(uri, AuthTokens.Basic(user, password), builder => builder.WithEncryptionLevel(EncryptionLevel.None));
	}
	
	public async Task<IEnumerable<string>> GetMovieRecommendations(string favoriteMovieTitle)
	{
		var cypherQuery =
			  @$"MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) 
				WHERE movie.title IN ${nameof(favoriteMovieTitle)}
				RETURN rec.title AS title, count(*) AS freq
				ORDER BY freq DESC LIMIT 5";
		IAsyncSession session = _driver.AsyncSession();
		var runQuery = await session.ReadTransactionAsync(async tx =>
		{
			var result = await tx.RunAsync(cypherQuery, new { favoriteMovieTitle });
			return await result.ToListAsync();
		});
		await session?.CloseAsync();
		return runQuery.Select(q => q.Values["title"].As<string>());
	}
	
	public static void WriteToConsole(IEnumerable<string> titles)
	{
		foreach (var title in titles)
			Console.WriteLine(title);
	}
	
	public static async Task Main()
	{
		var example = new SimpleExample("bolt://<HOST>:<BOLTPORT>", "<USERNAME>", "<PASSWORD>");
		var movies = await example.GetMovieRecommendations("The Matrix");
		WriteToConsole(movies);
	}
}
      

        // Java Driver Dependency: http://search.maven.org/#artifactdetails|org.neo4j.driver|neo4j-java-driver|4.0.1|jar
// Reactive Streams http://search.maven.org/#artifactdetails|org.reactivestreams|reactive-streams|1.0.3|jar
// javac -cp neo4j-java-driver-*.jar Example.java && java -cp neo4j-java-driver-*.jar:reactive-streams-*.jar:. Example

import org.neo4j.driver.*;
import static org.neo4j.driver.Values.parameters;

import java.util.List;
import static java.util.Arrays.asList;
import static java.util.Collections.singletonMap;

public class Example {

    public static void main(String...args) {
        Config noSSL = Config.builder().withoutEncryption().build();
        try (Driver driver = GraphDatabase.driver("bolt://<HOST>:<BOLTPORT>",AuthTokens.basic("<USERNAME>","<PASSWORD>"),noSSL);
		     Session session = driver.session()) {
            String cypherQuery =
                "MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) "+
                "WHERE movie.title IN $favorites "+
                "RETURN rec.title as title, count(*) as freq "+
                "ORDER BY freq DESC LIMIT 5";
            Result result = session.run(cypherQuery, parameters("favorites",asList("The Matrix")));
            while (result.hasNext()) {
                System.out.println(result.next().get("title").asString());
            }
	    }
    }
}



      

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express安卓加速器

"Graph visualization helps with communication as well as analysis," said Amin Jalali, a researcher at Stockholm University. Complex problems are perfectly suited to a native graph database like Neo4j, which fully reflects the reality of vast connected data. Interactions between all the compounds in ...

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Fine-Grained Access Control for Security and Privacy

手机如何看外网

手机如何看外网

手机如何看外网

手机如何看外网

Free O'Reilly Ebook
Graph Algorithms: Examples in Spark and Neo4j

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Get Started Quickly with the Neo4j Sandbox

手机如何看外网

手机如何看外网

手机如何看外网

手机如何看外网

Cypher

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手机如何看外网

手机如何看外网

Neo4j for RDBMS Developers

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Graph Expertise

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Neo4j Bloom Tips and Tricks for Domain Knowledge Experts

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798安卓加速器破解下载版

Case Study: Lockheed Martin

Fine-Grained Access Control for Better Security and Privacy

Fine-Grained Access Control for Security and Privacy

手机如何看外网

手机如何看外网

手机如何看外网

手机如何看外网

Free O'Reilly Ebook Graph Algorithms: Examples in Spark and Neo4j

No Download Required Get Started Quickly with the Neo4j Sandbox

手机如何看外网

手机如何看外网

手机如何看外网

手机如何看外网

Cypher

SQL

手机如何看外网

Neo4j for RDBMS Developers

express加速器ios使用

Graph Expertise

Neo4j Blog Neo4j Bloom Tips and Tricks for Domain Knowledge Experts

express安卓加速器

Neo4j Blog Designing the Enterprise: HR Applications at Scale

In the News

Content is king but context is queen

4 Ways to Excel as a Female Data Scientist

Developers should consider using graph databases

Graphdatenbank: Neo4j 4.1 soll sicherer und robuster arbeiten

798安卓加速器破解下载版

Free O'Reilly Ebook
Graph Algorithms: Examples in Spark and Neo4j

No Download Required
Get Started Quickly with the Neo4j Sandbox

Neo4j Blog
Neo4j Bloom Tips and Tricks for Domain Knowledge Experts

Neo4j Blog
Designing the Enterprise: HR Applications at Scale