springboot学习笔记(七)集成低版本和高版本Elasticsearch 搜索引擎

た入场券 2022-06-02 00:45 730阅读 0赞

历经风雨，翻山越岭，一路坎坷，才发现原来真理就在身旁！

简述坎坷过程：

1.由于项目当中使用的是低版本的elasticsearch 1.x ，使用spring data Elasticsearch 分分钟集成。

只需导入spring-data-elasticsearch的依赖，在配置文件中配置参数即可(如下)：

<dependency>
    			<groupId>org.springframework.data</groupId>
    			<artifactId>spring-data-elasticsearch</artifactId>
    			<version>1.3.6.RELEASE</version>
    </dependency>

spring.data.elasticsearch.cluster-name=elasticsearch
    spring.data.elasticsearch.cluster-nodes=127.0.0.1:9300
    spring.data.elasticsearch.repositories.enabled=true

然后建立与搜索引擎相关的实体：

package com.bigdata.lab.ymlib.model.elasticsearch;
    
    import java.io.Serializable;
    import java.util.Date;
    
    import org.springframework.data.elasticsearch.annotations.Document;
    
    @Document(indexName = "ym_liter_text", type = "ym_liter_text")
    public class LiteratureTextSearch implements Serializable {
    
    	/**
    	 * 
    	 */
    	private static final long serialVersionUID = 1982880315717929068L;
    	
    	private String _id;
    
    	private String literId;
    
    	private long dirId;
    
    	private String filename;
    
    	private long length;
    
    	private String contentType;
    
    	private String md5;
    
    	private String suffix;
    
    	private int pageNo;
    
    	private Date uploadDate;
    
    	private String literImageId;
    
    	// 简体
    	private String zhHansContent;
    
    	// 繁体
    	private String zhHantContent;
    	
    	
    
    	public String get_id() {
    		return _id;
    	}
    
    	public void set_id(String _id) {
    		this._id = _id;
    	}
    
    	public String getLiterId() {
    		return literId;
    	}
    
    	public void setLiterId(String literId) {
    		this.literId = literId;
    	}
    
    	public long getDirId() {
    		return dirId;
    	}
    
    	public void setDirId(long dirId) {
    		this.dirId = dirId;
    	}
    
    	public String getFilename() {
    		return filename;
    	}
    
    	public void setFilename(String filename) {
    		this.filename = filename;
    	}
    
    	public long getLength() {
    		return length;
    	}
    
    	public void setLength(long length) {
    		this.length = length;
    	}
    
    	public String getContentType() {
    		return contentType;
    	}
    
    	public void setContentType(String contentType) {
    		this.contentType = contentType;
    	}
    
    	public String getMd5() {
    		return md5;
    	}
    
    	public void setMd5(String md5) {
    		this.md5 = md5;
    	}
    
    	public String getSuffix() {
    		return suffix;
    	}
    
    	public void setSuffix(String suffix) {
    		this.suffix = suffix;
    	}
    
    	public int getPageNo() {
    		return pageNo;
    	}
    
    	public void setPageNo(int pageNo) {
    		this.pageNo = pageNo;
    	}
    
    	public Date getUploadDate() {
    		return uploadDate;
    	}
    
    	public void setUploadDate(Date uploadDate) {
    		this.uploadDate = uploadDate;
    	}
    
    	public String getLiterImageId() {
    		return literImageId;
    	}
    
    	public void setLiterImageId(String literImageId) {
    		this.literImageId = literImageId;
    	}
    
    	public String getZhHansContent() {
    		return zhHansContent;
    	}
    
    	public void setZhHansContent(String zhHansContent) {
    		this.zhHansContent = zhHansContent;
    	}
    
    	public String getZhHantContent() {
    		return zhHantContent;
    	}
    
    	public void setZhHantContent(String zhHantContent) {
    		this.zhHantContent = zhHantContent;
    	}
    	
    	
    
    }

此中索引类似传统数据库的数据库，而类型类似于传统数据库中的表。

然后在业务层中 引入templat

@Autowired
    	private ElasticsearchTemplate elasticsearchTemplate;

NativeSearchQueryBuilder nsqbText = new NativeSearchQueryBuilder();
    		nsqbText.withQuery(qbText);
    		
    //		if (StringUtils.isEmpty(searchContent)) {
    //			// 如果搜索条件为空，翻页以文献为准，则在当前文献集合中拿排好序的前limit页
    //			pageable = new PageRequest(0, limit);
    //			nsqbText.withPageable(pageable);
    //		} else {
    //			// 如果有搜索条件，翻页以搜索内容数据为准
    //			pageable = new PageRequest(page, limit);
    //			nsqbText.withPageable(pageable);
    //		}
    		
    		pageable = new PageRequest(page, limit);
    		nsqbText.withPageable(pageable);
    		
    		
    		FieldSortBuilder _score = setFieldSort("_score", "desc");
    		FieldSortBuilder sortLiterId = setFieldSort("literId", "desc");
    		// FieldSortBuilder sortdirId = setFieldSort("dirId", "asc");
    		FieldSortBuilder sortPageNo = setFieldSort("pageNo", "asc");
    		nsqbText.withSort(_score);
    		nsqbText.withSort(sortLiterId);
    		// nsqbText.withSort(sortdirId);
    		nsqbText.withSort(sortPageNo);
    		SearchQuery searchQueryText = nsqbText.build();
    		Page<LiteratureTextSearch> pageLiteraturesText = null;
    		try {
    			pageLiteraturesText = elasticsearchTemplate.queryForPage(searchQueryText, LiteratureTextSearch.class);
    		} catch (Exception e) {
    			throw new YMLibWebApplicationException("搜索分类：" + literClassfication + "后根据文献ids集合查找对应的文献文本出错", e);
    		}

还可使用仓储类进行搜索：

package com.bigdata.lab.ymlib.repository;
    
    import java.util.List;
    
    import org.springframework.data.elasticsearch.annotations.Query;
    import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;
    
    import com.bigdata.lab.ymlib.model.elasticsearch.LiteratureSearch;
    
    
    public interface ElasticsearchLiteratureRepository extends ElasticsearchRepository<LiteratureSearch, String> {
    //	@Query("{\"bool\" : {\"must\" : [{\"term\" : {\"title\" : \"?0\"}},{ \"term\" : {\"author\" : \"?1\"} }]}}")
    //	public LiteratureSearch findByTitleAndAuthor(String title, String author);
    }

然后使用 他提供的方法：

elasticsearchLiteratureRepository.search(searchQuery)

等

2.想想搜索引擎已经更新到6.1.1版本想升一下elasticsearch版本：

于是在本地部署了一个elasticsearch6.1.1版本，然后使用spring-data-elasticsearchjar包，结果控制台一直爆空指针，令人费解：百度良久：才发现，spring-data-elasticsearch还没更新到最新的搜索引擎版本！而且现在才更新支持到elasticsearch2.1.9，好吧认栽！

查看spring-data-elasticsearch版本地址：

https://mvnrepository.com/artifact/org.springframework.data/spring-data-elasticsearch

于是找了官方的java api开始集成如下：

官方文档地址：

https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/index.html

第一步：导入相关依赖：

<dependency>
               <groupId>org.apache.logging.log4j</groupId>
               <artifactId>log4j-api</artifactId>
               <version>2.9.1</version>
           </dependency>
           <dependency>
               <groupId>org.apache.logging.log4j</groupId>
               <artifactId>log4j-core</artifactId>
               <version>2.9.1</version>
           </dependency>
           <dependency>
               <groupId>org.elasticsearch</groupId>
               <artifactId>elasticsearch</artifactId>
               <version>6.1.1</version>
           </dependency>
    		
    		<dependency>
               <groupId>org.elasticsearch.client</groupId>
               <artifactId>transport</artifactId>
               <version>6.1.1</version>
           </dependency>

其中日志的jar 可以不用。

然后开始写案例

1.创建搜索引擎名称(更改了默认引擎名称的话)：

Settings settings = Settings.builder()
            .put("cluster.name", "myClusterName").build();

TransportClient client = new PreBuiltTransportClient(settings);
    
     
     
    
    
    (使用默认引擎名称)：
     
     TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)
            .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), 9300))   
    
    
    
     
     2.开始执行命令：
     首先插入一条数据：
     String json = "{" +
    			        "\"user\":\"kimchy\"," +
    			        "\"postDate\":\"2013-01-30\"," +
    			        "\"message\":\"trying out Elasticsearch\"" +
    			    "}";
    
    			IndexResponse response_insert = client.prepareIndex("xc", "test")
    			        .setSource(json, XContentType.JSON)
    			        .get();
    			
    			System.out.println(response_insert.getResult());
    
    控制台返回： 
     CREATED
    
    
     ok 我们用客户端查看一下记录：
     GET /xc/test/_search 
     返回：”
     {
      "took": 393,
      "timed_out": false,
      "_shards": {
        "total": 5,
        "successful": 5,
        "skipped": 0,
        "failed": 0
      },
      "hits": {
        "total": 1,
        "max_score": 1,
        "hits": [
          {
            "_index": "xc",
            "_type": "test",
            "_id": "YlIrm2ABcUzl4ssEeJ7X",
            "_score": 1,
            "_source": {
              "user": "kimchy",
              "postDate": "2013-01-30",
              "message": "trying out Elasticsearch"
            }
          }
        ]
      }
    }
    
    说明插入成功，并为我们生成了id 
    
    
    
     下面我们查询此条数据：
       //搜索数据
    			GetResponse response = client.prepareGet("xc", "test", "YlIrm2ABcUzl4ssEeJ7X").get();
    			 //输出结果
    	         System.out.println(response.getSourceAsString());
    
    返回： 
     loaded plugin [org.elasticsearch.index.reindex.ReindexPlugin]
    loaded plugin [org.elasticsearch.join.ParentJoinPlugin]
    loaded plugin [org.elasticsearch.percolator.PercolatorPlugin]
    loaded plugin [org.elasticsearch.script.mustache.MustachePlugin]
    loaded plugin [org.elasticsearch.transport.Netty4Plugin]
    {"user":"kimchy","postDate":"2013-01-30","message":"trying out Elasticsearch"}
    
    ok 测试成功 
     其他操作：
     GetResponse response = client.prepareGet("xc", "test", "YlIrm2ABcUzl4ssEeJ7X").get();
    			 //输出结果
    	         System.out.println(response.getSourceAsString());
    	         
    	         //删除
    			DeleteResponse response_del = client.prepareDelete("xc", "test", "YlIrm2ABcUzl4ssEeJ7X").get();
    			
    			System.out.println(response_del.getResult());
    			
    			//修改
    			UpdateRequest updateRequest = new UpdateRequest();
    			updateRequest.index("index");
    			updateRequest.type("type");
    			updateRequest.id("1");
    			updateRequest.doc(jsonBuilder()
    			        .startObject()
    			            .field("gender", "male")
    			        .endObject());
    			client.update(updateRequest).get();
    
    
    
     
     
    
    
     ok 基本的操作测试完毕，helloword完成！