图数据库Neo4j——SpringBoot使用Neo4j & 简单增删改查 & 复杂查询初步

た入场券 2024-02-20 11:43 17阅读 0赞

![在这里插入图片描述][cb9f8be4927e40ac89f7cdb5c6292923.png]

## 前言 ##

--------------------

图形数据库是专门用于存储图形数据的数据库，它使用图形模型来存储数据，并且支持复杂的图形查询。常见的图形数据库有Neo4j、OrientDB等。

Neo4j是用Java实现的开源NoSQL图数据库，本篇博客介绍如何在SpringBoot中使用Neo4j图数据库，如何进行简单的增删改查，以及如何进行复杂的查询。

本篇博客相关代码的git网址如下：

[https://gitee.com/pet365/spring-boot-neo4j][https_gitee.com_pet365_spring-boot-neo4j]

关于Neo4j的博客文章如下：

*  [图数据库Neo4j——Neo4j简介、数据结构 & Docker版本的部署安装 & Cypher语句的入门][Neo4j_Neo4j_ _ Docker_ _ Cypher]

#### 目录 ####

*  前言
 *  引出
 *  springBoot整合
 *   *  1、引入依赖
     *  2、配置文件
     *  3、实体类定义
     *  4、dao继承Neo4jRepository
     *  复杂查询
     *   *  最短路径查询
         *  最小成本查询
 *  总结

## 引出 ##

--------------------

1.Neo4j是用Java实现的开源NoSQL图数据库;  
2.SpringBoot使用Neo4j，继承Neo4jRepository进行简单增删改查；  
3.使用Neo4jClient进行复杂的查询；

## springBoot整合 ##

### 1、引入依赖 ###

<dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-data-neo4j</artifactId>
            </dependency>

### 2、配置文件 ###

server:
      port: 9902
    logging:
      level:
        org.springframework.data.neo4j: debug
    spring:
      application:
        name: spring-neo4j
      data:
        neo4j:
          database: neo4j
      neo4j:
        authentication:
          username: neo4j
          password: neo4j123
        uri: neo4j://192.168.150.101:7687

### 3、实体类定义 ###

![在这里插入图片描述][d6a6d3c46d1b49d98e6f6c5ac68b6879.png]

> 提取抽象类

![在这里插入图片描述][fa00631f91c5438a95f93caf3f2720a6.png]

> 不同的节点类，网点、一级转运中心、二级转运中心

![在这里插入图片描述][0dd5764e105e4e50badb5995f34a018f.png]

### 4、dao继承Neo4jRepository ###

进行自定义查询：

<table> 
 <thead> 
  <tr> 
   <th>Keyword</th> 
   <th>Sample</th> 
   <th>Cypher snippet</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>After</td> 
   <td>findByLaunchDateAfter(Date date)</td> 
   <td>n.launchDate &gt; date</td> 
  </tr> 
  <tr> 
   <td>Before</td> 
   <td>findByLaunchDateBefore(Date date)</td> 
   <td>n.launchDate &lt; date</td> 
  </tr> 
  <tr> 
   <td>Containing (String)</td> 
   <td>findByNameContaining(String namePart)</td> 
   <td>n.name CONTAINS namePart</td> 
  </tr> 
  <tr> 
   <td>Containing (Collection)</td> 
   <td>findByEmailAddressesContains(Collection addresses) findByEmailAddressesContains(String address)</td> 
   <td>ANY(collectionFields IN [addresses] WHERE collectionFields in n.emailAddresses) ANY(collectionFields IN address WHERE collectionFields in n.emailAddresses)</td> 
  </tr> 
  <tr> 
   <td>In</td> 
   <td>findByNameIn(Iterable names)</td> 
   <td>n.name IN names</td> 
  </tr> 
  <tr> 
   <td>Between</td> 
   <td>findByScoreBetween(double min, double max) findByScoreBetween(Range range)</td> 
   <td>n.score &gt;= min AND n.score &lt;= max Depending on the Range definition n.score &gt;= min AND n.score &lt;= max or n.score &gt; min AND n.score &lt; max</td> 
  </tr> 
  <tr> 
   <td>StartingWith</td> 
   <td>findByNameStartingWith(String nameStart)</td> 
   <td>n.name STARTS WITH nameStart</td> 
  </tr> 
  <tr> 
   <td>EndingWith</td> 
   <td>findByNameEndingWith(String nameEnd)</td> 
   <td>n.name ENDS WITH nameEnd</td> 
  </tr> 
  <tr> 
   <td>Exists</td> 
   <td>findByNameExists()</td> 
   <td>EXISTS(n.name)</td> 
  </tr> 
  <tr> 
   <td>True</td> 
   <td>findByActivatedIsTrue()</td> 
   <td>n.activated = true</td> 
  </tr> 
  <tr> 
   <td>False</td> 
   <td>findByActivatedIsFalse()</td> 
   <td>NOT(n.activated = true)</td> 
  </tr> 
  <tr> 
   <td>Is</td> 
   <td>findByNameIs(String name)</td> 
   <td>n.name = name</td> 
  </tr> 
  <tr> 
   <td>NotNull</td> 
   <td>findByNameNotNull()</td> 
   <td>NOT(n.name IS NULL)</td> 
  </tr> 
  <tr> 
   <td>Null</td> 
   <td>findByNameNull()</td> 
   <td>n.name IS NULL</td> 
  </tr> 
  <tr> 
   <td>GreaterThan</td> 
   <td>findByScoreGreaterThan(double score)</td> 
   <td>n.score &gt; score</td> 
  </tr> 
  <tr> 
   <td>GreaterThanEqual</td> 
   <td>findByScoreGreaterThanEqual(double score)</td> 
   <td>n.score &gt;= score</td> 
  </tr> 
  <tr> 
   <td>LessThan</td> 
   <td>findByScoreLessThan(double score)</td> 
   <td>n.score &lt; score</td> 
  </tr> 
  <tr> 
   <td>LessThanEqual</td> 
   <td>findByScoreLessThanEqual(double score)</td> 
   <td>n.score &lt;= score</td> 
  </tr> 
  <tr> 
   <td>Like</td> 
   <td>findByNameLike(String name)</td> 
   <td>n.name =~ name</td> 
  </tr> 
  <tr> 
   <td>NotLike</td> 
   <td>findByNameNotLike(String name)</td> 
   <td>NOT(n.name =~ name)</td> 
  </tr> 
  <tr> 
   <td>Near</td> 
   <td>findByLocationNear(Distance distance, Point point)</td> 
   <td>distance( point(n),point({latitude:lat, longitude:lon}) ) &lt; distance</td> 
  </tr> 
  <tr> 
   <td>Regex</td> 
   <td>findByNameRegex(String regex)</td> 
   <td>n.name =~ regex</td> 
  </tr> 
  <tr> 
   <td>And</td> 
   <td>findByNameAndDescription(String name, String description)</td> 
   <td>n.name = name AND n.description = description</td> 
  </tr> 
  <tr> 
   <td>Or</td> 
   <td>findByNameOrDescription(String name, String description)</td> 
   <td>n.name = name OR n.description = description (Cannot be used to OR nested properties)</td> 
  </tr> 
 </tbody> 
</table>

![在这里插入图片描述][f4c7207b650142a29b6d2f6cc4711051.png]

package com.tianju.mapper;
    
    import com.tianju.entity.AgencyEntity;
    import org.mapstruct.Mapper;
    import org.springframework.data.neo4j.repository.Neo4jRepository;
    
    /**
     * 网点的mapper，比如菜鸟驿站
     */
    @Mapper
    public interface AgencyMapper extends Neo4jRepository<AgencyEntity,Long> {
        
        /**
         * 根据bid 查询
         * @param bid 业务id
         * @return 网点数据
         */
        AgencyEntity findByBid(Long bid);
    
    
        /**
         * 根据bid删除
         *
         * @param bid 业务id
         * @return 删除的数据条数
         */
        Long deleteByBid(Long bid);
    }

![在这里插入图片描述][401b2fa4a15f454bb3f53379b34f2035.png]

### 复杂查询 ###

![在这里插入图片描述][ac2ab1e951b14be08974abe9cd0bf4ef.png]

#### 最短路径查询 ####

//查询两个网点之间最短路径，查询深度最大为10
    MATCH path = shortestPath((n:AGENCY) -[*..10]->(m:AGENCY))WHERE n.name = "北京市昌平区定泗路" AND m.name = "上海市浦东新区南汇"RETURN path

![在这里插入图片描述][8a05ed98a8854dc0be90f74a72d572a7.png]

![在这里插入图片描述][e010fd63151b4b6e83565574c79493d9.png]

![在这里插入图片描述][5338d3061242440cb57dfe591f72cd6c.png]

package com.tianju.mapper.impl;
    
    import cn.hutool.core.bean.BeanUtil;
    import cn.hutool.core.collection.CollUtil;
    import cn.hutool.core.map.MapUtil;
    import cn.hutool.core.util.StrUtil;
    import cn.hutool.db.meta.Column;
    import com.tianju.dto.OrganDTO;
    import com.tianju.dto.TransportLineNodeDTO;
    import com.tianju.entity.AgencyEntity;
    import com.tianju.enums.OrganTypeEnum;
    import com.tianju.mapper.TransportLineRepository;
    import org.neo4j.driver.internal.InternalPoint2D;
    import org.neo4j.driver.types.Path;
    import org.neo4j.driver.types.Relationship;
    import org.springframework.data.neo4j.core.schema.Node;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.data.neo4j.core.Neo4jClient;
    import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
    import org.springframework.stereotype.Component;
    
    import java.util.Map;
    import java.util.Optional;
    
    @Component
    public class TransportLineRepositoryImpl implements TransportLineRepository {
        
    
        @Autowired
        private Neo4jClient neo4jClient;
    
        /**
         * 查询最短路线
         * @param start 开始网点
         * @param end   结束网点
         * @return
         */
        @Override
        public TransportLineNodeDTO findShortestPath(AgencyEntity start, AgencyEntity end) {
        
            // 获取网点数据在Neo4j中的类型 @Node("AGENCY") @Node("OLT")
            String type = AgencyEntity.class.getAnnotation(Node.class).value()[0];
            // 构造Sql语句 $startId
    //        String cql = "MATCH path = shortestPath((n:AGENCY) -[*..10]->(m:AGENCY))\n" +
    //                "WHERE n.bid = $startId AND m.bid = $endId\n" +
    //                "RETURN path";
            String cql = StrUtil.format("MATCH path = shortestPath((n:{}) -[*..10]->(m:{})) " +
                    "WHERE n.bid = $startId AND m.bid = $endId " +
                    "RETURN path",type,type);
            // 执行自定义查询
            Neo4jClient.RecordFetchSpec<TransportLineNodeDTO> recordFetchSpec = neo4jClient.query(cql)
                    .bind(start.getBid()).to("startId") // 替换 $startId
                    .bind(end.getBid()).to("endId")  // 替换 $endId
                    .fetchAs(TransportLineNodeDTO.class)   // 设置响应类型，指定为 TransportLineNodeDTO 类型
                    .mappedBy((typeSystem, record) -> {
            // 设置结果集映射
                        Path path = record.get(0).asPath();// 得到第一条路线
                        TransportLineNodeDTO transportLineNodeDTO = new TransportLineNodeDTO();
    
                        path.nodes().forEach(node -> {
         // 将每个节点信息封装成一个 OrganDto
                            // 获得节点的 键值对 address: 上海市转运中心；bid：8002
                            Map<String, Object> map = node.asMap();
                            // {name=北京市昌平区定泗路,
                            // location=Point{srid=4326, x=116.37212849638287, y=40.11765281246394},
                            // address=北七家镇定泗路苍龙街交叉口, bid=100280, phone=010-86392987}
                            System.out.println("map: "+map);
    
                            // 把键值对转换成对象 OrganDTO
                            OrganDTO organDTO = BeanUtil.toBeanIgnoreError(map, OrganDTO.class);
                            // organDTO:
                            // OrganDTO(id=100280, name=北京市昌平区定泗路, type=null, phone=010-86392987,
                            // address=北七家镇定泗路苍龙街交叉口, latitude=null, longitude=null)
                            // type,latitude,longitude 没有映射成功
                            System.out.println("organDTO: "+organDTO);
    
                            // 获得标签的名称 OLT,TLT,
                            String first = CollUtil.getFirst(node.labels());
                            // 根据OLT获得枚举类型 OLT(1, "一级转运中心"),
                            OrganTypeEnum organTypeEnum = OrganTypeEnum.valueOf(first);
                            // 再获得枚举类型的 code ：1、2、3
                            organDTO.setType(organTypeEnum.getCode()); // 设置类型的映射
    
                            // 经纬度 "location": point({srid:4326, x:121.59815370294322, y:31.132409729356993})
                            InternalPoint2D location = MapUtil.get(map, "location", InternalPoint2D.class); // 经纬度 BeanUtil.getProperty(map.get("location"),"x");
                            organDTO.setLatitude(location.x());  // 设置经纬度映射
                            organDTO.setLongitude(location.y()); // 经纬度映射
                            // OrganDTO(id=100280, name=北京市昌平区定泗路, type=3,
                            // phone=010-86392987, address=北七家镇定泗路苍龙街交叉口,
                            // latitude=116.37212849638287, longitude=40.11765281246394)
                            System.out.println("organDTO: "+organDTO);
    
                            transportLineNodeDTO.getNodeList().add(organDTO);
                        });
    
                        System.out.println("transportLineNodeDTO: "+transportLineNodeDTO);
    
                        path.relationships().forEach(relationship -> {
        
                            // 路径下面的关系
                            Map<String, Object> map = relationship.asMap();
                            Double cost = MapUtil.get(map, "cost", Double.class);
                            transportLineNodeDTO.setCost(cost + transportLineNodeDTO.getCost());
                        });
    
                        System.out.println("transportLineNodeDTO: "+transportLineNodeDTO);
                        return transportLineNodeDTO;
                    });
            Optional<TransportLineNodeDTO> one = recordFetchSpec.one(); // Optional，1.8提供的，可以处理null的情况
            return one.orElse(null); // 如果为null，就返回null，如果不是null，就返回结果
        }
    }

#### 最小成本查询 ####

![在这里插入图片描述][cc422a6686214bd288ded58bff5d5f86.png]

package com.tianju.mapper.impl;
    
    import cn.hutool.core.bean.BeanUtil;
    import cn.hutool.core.collection.CollUtil;
    import cn.hutool.core.map.MapUtil;
    import cn.hutool.core.util.StrUtil;
    import cn.hutool.db.meta.Column;
    import com.tianju.dto.OrganDTO;
    import com.tianju.dto.TransportLineNodeDTO;
    import com.tianju.entity.AgencyEntity;
    import com.tianju.enums.OrganTypeEnum;
    import com.tianju.mapper.TransportLineRepository;
    import org.neo4j.driver.internal.InternalPoint2D;
    import org.neo4j.driver.types.Path;
    import org.neo4j.driver.types.Relationship;
    import org.springframework.data.neo4j.core.schema.Node;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.data.neo4j.core.Neo4jClient;
    import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
    import org.springframework.stereotype.Component;
    
    import java.util.Map;
    import java.util.Optional;
    
    @Component
    public class TransportLineRepositoryImpl implements TransportLineRepository {
        
    
        @Autowired
        private Neo4jClient neo4jClient;
    
    
        @Override
        public TransportLineNodeDTO findCostLeastPath(AgencyEntity start, AgencyEntity end) {
        
            String type = AgencyEntity.class.getAnnotation(Node.class).value()[0];
    
            String cqlB = "MATCH path = (n:{}) -[*..10]->(m:{}) " +
                    "WHERE n.bid = $startId AND m.bid = $endId " +
                    "UNWIND relationships(path) AS r " +
                    "WITH sum(r.cost) AS cost, path " +
                    "RETURN path ORDER BY cost ASC, LENGTH(path) ASC LIMIT 1";
            String cql = StrUtil.format(cqlB, type,type);
    
            Optional<TransportLineNodeDTO> one = neo4jClient.query(cql)
                    .bind(start.getBid()).to("startId")
                    .bind(end.getBid()).to("endId")
                    .fetchAs(TransportLineNodeDTO.class)
                    .mappedBy(((typeSystem, record) -> {
        
                        Path path = record.get(0).asPath();
                        TransportLineNodeDTO transportLineNodeDTO = new TransportLineNodeDTO();
    
                        path.nodes().forEach(node -> {
        
                            Map<String, Object> map = node.asMap();
                            OrganDTO organDTO = BeanUtil.toBeanIgnoreError(map, OrganDTO.class);
                            // 获得标签的名称 OLT,TLT,
                            String first = CollUtil.getFirst(node.labels());
                            // 根据OLT获得枚举类型 OLT(1, "一级转运中心"),
                            OrganTypeEnum organTypeEnum = OrganTypeEnum.valueOf(first);
                            // 再获得枚举类型的 code ：1、2、3
                            organDTO.setType(organTypeEnum.getCode()); // 设置类型的映射
    
                            // 经纬度 "location": point({srid:4326, x:121.59815370294322, y:31.132409729356993})
                            InternalPoint2D location = MapUtil.get(map, "location", InternalPoint2D.class); // 经纬度 BeanUtil.getProperty(map.get("location"),"x");
                            organDTO.setLatitude(location.x());  // 设置经纬度映射
                            organDTO.setLongitude(location.y()); // 经纬度映射
                            transportLineNodeDTO.getNodeList().add(organDTO);
                        });
    
                        path.relationships().forEach(relationship -> {
        
                            // 路径下面的关系
                            Map<String, Object> map = relationship.asMap();
                            Double cost = MapUtil.get(map, "cost", Double.class);
                            transportLineNodeDTO.setCost(cost + transportLineNodeDTO.getCost());
                        });
                        return transportLineNodeDTO;
                    })).one();
            return one.orElse(null);
        }
    
        private void findShortestPathMy(){
        
            String cql = "MATCH path = shortestPath((n:AGENCY) -[*..10]->(m:AGENCY)) " +
                    "WHERE n.bid = 210127 AND m.bid = 100260 " +
                    "RETURN path";
            // 执行自定义查询
            Neo4jClient.UnboundRunnableSpec query = neo4jClient.query(cql);
    
            ThreadPoolTaskExecutor threadPoolTaskExecutor = new ThreadPoolTaskExecutor();
    
    
        }
    }

![在这里插入图片描述][71915e115eff4c64a3422b4f064f4c37.png]

--------------------

## 总结 ##

1.Neo4j是用Java实现的开源NoSQL图数据库;  
2.SpringBoot使用Neo4j，继承Neo4jRepository进行简单增删改查；  
3.使用Neo4jClient进行复杂的查询；

[cb9f8be4927e40ac89f7cdb5c6292923.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/36ca9c422a0b4d76af55bc8926568d29.png
[https_gitee.com_pet365_spring-boot-neo4j]: https://gitee.com/pet365/spring-boot-neo4j
[Neo4j_Neo4j_ _ Docker_ _ Cypher]: https://blog.csdn.net/Pireley/article/details/134147928
[d6a6d3c46d1b49d98e6f6c5ac68b6879.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/d566c6791be44d2b825c826c91a5d1fd.png
[fa00631f91c5438a95f93caf3f2720a6.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/c0a4a4c5c6124ebbb457590b69ef20f1.png
[0dd5764e105e4e50badb5995f34a018f.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/250e5e70b3504520a436b05ad1c2ae49.png
[f4c7207b650142a29b6d2f6cc4711051.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/528b8a57a57e41c68e7e5617b480cb8d.png
[401b2fa4a15f454bb3f53379b34f2035.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/f995010d0c724699bf594076a0147b47.png
[ac2ab1e951b14be08974abe9cd0bf4ef.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/eac9350ca83841c99429739b70673312.png
[8a05ed98a8854dc0be90f74a72d572a7.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/52eb91d486664e388dbbc4922712fe40.png
[e010fd63151b4b6e83565574c79493d9.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/d14336b27a514afda8d717e0c4e53163.png
[5338d3061242440cb57dfe591f72cd6c.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/cc1d9fa2161546fc8600cf815180d2b6.png
[cc422a6686214bd288ded58bff5d5f86.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/8f48d1bd1b2049849714258078b4c038.png
[71915e115eff4c64a3422b4f064f4c37.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/02/20/ee678e0b48094821ad436b6deccfc799.png