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

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)：

			org.springframework.data
			spring-data-elasticsearch
			1.3.6.RELEASE
	

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 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 {
//	@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：

           org.apache.logging.log4j
           log4j-api
           2.9.1
       
       
           org.apache.logging.log4j
           log4j-core
           2.9.1
       
       
           org.elasticsearch
           elasticsearch
           6.1.1
       
		
		
           org.elasticsearch.client
           transport
           6.1.1
       

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！