neo4j是一套noSQL的图形数据库，适合存储点、线、面等图数据结构。
基于Java开发，缺点是占用大量内存。
适配Java、Python、ruby等语言。
适用场景：
Social Network（社交网络，企业用户比如Linkedin）
Network and IT Operation（网络或者运维）
Fraud Detection （反诈骗）
Graph Based Search（图算法，类似于我之前研究的拓扑算法，ebay把这个应用在快递分发系统）
Identity and Access（登陆信息验证，挪威电信Telenor公司在用，我的前东家甲方公司）
Master Data Management（主数据管理，这个就不太清楚了，pitney bowes供应链公司）
Recommendation Engine（商品评论引擎，Walmart德国沃尔玛等电商系统）
官网地址：https://neo4j.com/
Windows环境下载exe安装，用的是免费社区版
启动服务，简单的Java Swing程序
登陆试玩，引导界面还是蛮不错的：
用了官方的一套demo：
import org.neo4j.driver.v1.*;
import java.util.Collections;
import java.util.List;
import static java.util.Arrays.asList;
import static org.neo4j.driver.v1.Values.parameters;
public class Social {
public static void main(String...args) {
Config noSSL = Config.build().withEncryptionLevel(Config.EncryptionLevel.NONE).toConfig();
Driver driver = GraphDatabase.driver("bolt://localhost",AuthTokens.basic("neo4j","123456"),noSSL); // <password>
try (Session session = driver.session()) {
List data =
asList(asList("Jim","Mike"),asList("Jim","Billy"),asList("Anna","Jim"),
asList("Anna","Mike"),asList("Sally","Anna"),asList("Joe","Sally"),
asList("Joe","Bob"),asList("Bob","Sally"));
String insertQuery = "UNWIND {pairs} as pair " +
"MERGE (p1:Person {name:pair[0]}) " +
"MERGE (p2:Person {name:pair[1]}) " +
"MERGE (p1)-[:KNOWS]-(p2);";
session.run(insertQuery, Collections.<String, Object>singletonMap("pairs",data)).consume();
StatementResult result;
String foafQuery =
" MATCH (person:Person)-[:KNOWS]-(friend)-[:KNOWS]-(foaf) "+
" WHERE person.name = {name} " +
" AND NOT (person)-[:KNOWS]-(foaf) " +
" RETURN foaf.name AS name ";
result = session.run(foafQuery, parameters("name","Joe"));
while (result.hasNext()) System.out.println(result.next().get("name"));
String commonFriendsQuery =
"MATCH (user:Person)-[:KNOWS]-(friend)-[:KNOWS]-(foaf:Person) " +
" WHERE user.name = {from} AND foaf.name = {to} " +
" RETURN friend.name AS friend";
result = session.run(commonFriendsQuery, parameters("from","Joe","to","Sally"));
while (result.hasNext()) System.out.println(result.next().get("friend"));
String connectingPathsQuery =
"MATCH path = shortestPath((p1:Person)-[:KNOWS*..6]-(p2:Person)) " +
" WHERE p1.name = {from} AND p2.name = {to} " +
" RETURN [n IN nodes(path) | n.name] as names";
result = session.run(connectingPathsQuery, parameters("from","Joe","to","Billy"));
while (result.hasNext()) System.out.println(result.next().get("names"));
}
}
}
MAVEN地址
图数据库相关书籍
《图数据库(第2版)》
