來源:blog.csdn.net/weixin_44671737/article/details/114456257
摘要
對于一家公司而言,資料量越來越多,如果快速去查找這些資訊是一個很難的問題,在計算機領域有一個專門的領域IR(Information Retrival)研究如果獲取資訊,做資訊檢索,
在國內的如百度這樣的搜索引擎也屬于這個領域,要自己實作一個搜索引擎是非常難的,不過資訊查找對每一個公司都非常重要,對于開發人員也可以選則一些市場上的開源專案來構建自己的站內搜索引擎,本文將通過ElasticSearch來構建一個這樣的資訊檢索專案,
1 技術選型
- 搜索引擎服務使用ElasticSearch
- 提供的對外web服務選則springboot web
1.1 ElasticSearch
Elasticsearch是一個基于Lucene的搜索服務器,它提供了一個分布式多用戶能力的全文搜索引擎,基于RESTful web介面,Elasticsearch是用Java語言開發的,并作為Apache許可條款下的開放原始碼發布,是一種流行的企業級搜索引擎,Elasticsearch用于云計算中,能夠達到實時搜索,穩定,可靠,快速,安裝使用方便,
官方客戶端在Java、.NET(C#)、PHP、Python、Apache Groovy、Ruby和許多其他語言中都是可用的,根據DB-Engines的排名顯示,Elasticsearch是最受歡迎的企業搜索引擎,其次是Apache Solr,也是基于Lucene,1
現在開源的搜索引擎在市面上最常見的就是ElasticSearch和Solr,二者都是基于Lucene的實作,其中ElasticSearch相對更加重量級,在分布式環境表現也更好,二者的選則需考慮具體的業務場景和資料量級,對于資料量不大的情況下,完全需要使用像Lucene這樣的搜索引擎服務,通過關系型資料庫檢索即可,
1.2 springBoot
Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can “just run”.2
現在springBoot在做web開發上是絕對的主流,其不僅僅是開發上的優勢,在布署,運維各個方面都有著非常不錯的表現,并且spring生態圈的影響力太大了,可以找到各種成熟的解決方案,
1.3 ik分詞器
elasticSearch本身不支持中文的分詞,需要安裝中文分詞插件,如果需要做中文的資訊檢索,中文分詞是基礎,此處選則了ik,下載好后放入elasticSearch的安裝位置的plugin目錄即可,
2 環境準備
需要安裝好elastiSearch以及kibana(可選),并且需要lk分詞插件,
- 安裝elasticSearch elasticsearch官網. 筆者使用的是7.5.1,
- ik插件下載 ik插件github地址. 注意下載和你下載elasticsearch版本一樣的ik插件,
- 將ik插件放入elasticsearch安裝目錄下的plugins包下,新建報名ik,將下載好的插件解壓到該目錄下即可,啟動es的時候會自動加載該插件,

- 搭建springboot專案 idea ->new project ->spring initializer

3 專案架構
- 獲取資料使用ik分詞插件
- 將資料存盤在es引擎中
- 通過es檢索方式對存盤的資料進行檢索
- 使用es的java客戶端提供外部服務

4 實作效果
4.1 搜索頁面
簡單實作一個類似百度的搜索框即可,

4.2 搜索結果頁面

點擊第一個搜索結果是我個人的某一篇博文,為了避免資料著作權問題,筆者在es引擎中存放的全是個人的博客資料,

5 具體代碼實作
5.1 全文檢索的實作物件
按照博文的基本資訊定義了如下物體類,主要需要知道每一個博文的url,通過檢索出來的文章具體查看要跳轉到該url,
package com.lbh.es.entity;
import com.fasterxml.jackson.annotation.JsonIgnore;
import javax.persistence.*;
/**
* PUT articles
* {
* "mappings":
* {"properties":{
* "author":{"type":"text"},
* "content":{"type":"text","analyzer":"ik_max_word","search_analyzer":"ik_smart"},
* "title":{"type":"text","analyzer":"ik_max_word","search_analyzer":"ik_smart"},
* "createDate":{"type":"date","format":"yyyy-MM-dd HH:mm:ss||yyyy-MM-dd"},
* "url":{"type":"text"}
* } },
* "settings":{
* "index":{
* "number_of_shards":1,
* "number_of_replicas":2
* }
* }
* }
* ---------------------------------------------------------------------------------------------------------------------
* Copyright(c)[email protected]
* @author liubinhao
* @date 2021/3/3
*/
@Entity
@Table(name = "es_article")
public class ArticleEntity {
@Id
@JsonIgnore
@GeneratedValue(strategy = GenerationType.IDENTITY)
private long id;
@Column(name = "author")
private String author;
@Column(name = "content",columnDefinition="TEXT")
private String content;
@Column(name = "title")
private String title;
@Column(name = "createDate")
private String createDate;
@Column(name = "url")
private String url;
public String getAuthor() {
return author;
}
public void setAuthor(String author) {
this.author = author;
}
public String getContent() {
return content;
}
public void setContent(String content) {
this.content = content;
}
public String getTitle() {
return title;
}
public void setTitle(String title) {
this.title = title;
}
public String getCreateDate() {
return createDate;
}
public void setCreateDate(String createDate) {
this.createDate = createDate;
}
public String getUrl() {
return url;
}
public void setUrl(String url) {
this.url = url;
}
}
5.2 客戶端配置
通過java配置es的客戶端,
package com.lbh.es.config;
import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import java.util.ArrayList;
import java.util.List;
/**
* Copyright(c)[email protected]
* @author liubinhao
* @date 2021/3/3
*/
@Configuration
public class EsConfig {
@Value("${elasticsearch.schema}")
private String schema;
@Value("${elasticsearch.address}")
private String address;
@Value("${elasticsearch.connectTimeout}")
private int connectTimeout;
@Value("${elasticsearch.socketTimeout}")
private int socketTimeout;
@Value("${elasticsearch.connectionRequestTimeout}")
private int tryConnTimeout;
@Value("${elasticsearch.maxConnectNum}")
private int maxConnNum;
@Value("${elasticsearch.maxConnectPerRoute}")
private int maxConnectPerRoute;
@Bean
public RestHighLevelClient restHighLevelClient() {
// 拆分地址
List<HttpHost> hostLists = new ArrayList<>();
String[] hostList = address.split(",");
for (String addr : hostList) {
String host = addr.split(":")[0];
String port = addr.split(":")[1];
hostLists.add(new HttpHost(host, Integer.parseInt(port), schema));
}
// 轉換成 HttpHost 陣列
HttpHost[] httpHost = hostLists.toArray(new HttpHost[]{});
// 構建連接物件
RestClientBuilder builder = RestClient.builder(httpHost);
// 異步連接延時配置
builder.setRequestConfigCallback(requestConfigBuilder -> {
requestConfigBuilder.setConnectTimeout(connectTimeout);
requestConfigBuilder.setSocketTimeout(socketTimeout);
requestConfigBuilder.setConnectionRequestTimeout(tryConnTimeout);
return requestConfigBuilder;
});
// 異步連接數配置
builder.setHttpClientConfigCallback(httpClientBuilder -> {
httpClientBuilder.setMaxConnTotal(maxConnNum);
httpClientBuilder.setMaxConnPerRoute(maxConnectPerRoute);
return httpClientBuilder;
});
return new RestHighLevelClient(builder);
}
}
5.3 業務代碼撰寫
包括一些檢索文章的資訊,可以從文章標題,文章內容以及作者資訊這些維度來查看相關資訊,
package com.lbh.es.service;
import com.google.gson.Gson;
import com.lbh.es.entity.ArticleEntity;
import com.lbh.es.repository.ArticleRepository;
import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.support.master.AcknowledgedResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.indices.CreateIndexRequest;
import org.elasticsearch.client.indices.CreateIndexResponse;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.springframework.stereotype.Service;
import javax.annotation.Resource;
import java.io.IOException;
import java.util.*;
/**
* Copyright(c)[email protected]
* @author liubinhao
* @date 2021/3/3
*/
@Service
public class ArticleService {
private static final String ARTICLE_INDEX = "article";
@Resource
private RestHighLevelClient client;
@Resource
private ArticleRepository articleRepository;
public boolean createIndexOfArticle(){
Settings settings = Settings.builder()
.put("index.number_of_shards", 1)
.put("index.number_of_replicas", 1)
.build();
// {"properties":{"author":{"type":"text"},
// "content":{"type":"text","analyzer":"ik_max_word","search_analyzer":"ik_smart"}
// ,"title":{"type":"text","analyzer":"ik_max_word","search_analyzer":"ik_smart"},
// ,"createDate":{"type":"date","format":"yyyy-MM-dd HH:mm:ss||yyyy-MM-dd"}
// }
String mapping = "{\"properties\":{\"author\":{\"type\":\"text\"},\n" +
"\"content\":{\"type\":\"text\",\"analyzer\":\"ik_max_word\",\"search_analyzer\":\"ik_smart\"}\n" +
",\"title\":{\"type\":\"text\",\"analyzer\":\"ik_max_word\",\"search_analyzer\":\"ik_smart\"}\n" +
",\"createDate\":{\"type\":\"date\",\"format\":\"yyyy-MM-dd HH:mm:ss||yyyy-MM-dd\"}\n" +
"},\"url\":{\"type\":\"text\"}\n" +
"}";
CreateIndexRequest indexRequest = new CreateIndexRequest(ARTICLE_INDEX)
.settings(settings).mapping(mapping,XContentType.JSON);
CreateIndexResponse response = null;
try {
response = client.indices().create(indexRequest, RequestOptions.DEFAULT);
} catch (IOException e) {
e.printStackTrace();
}
if (response!=null) {
System.err.println(response.isAcknowledged() ? "success" : "default");
return response.isAcknowledged();
} else {
return false;
}
}
public boolean deleteArticle(){
DeleteIndexRequest request = new DeleteIndexRequest(ARTICLE_INDEX);
try {
AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
return response.isAcknowledged();
} catch (IOException e) {
e.printStackTrace();
}
return false;
}
public IndexResponse addArticle(ArticleEntity article){
Gson gson = new Gson();
String s = gson.toJson(article);
//創建索引創建物件
IndexRequest indexRequest = new IndexRequest(ARTICLE_INDEX);
//檔案內容
indexRequest.source(s,XContentType.JSON);
//通過client進行http的請求
IndexResponse re = null;
try {
re = client.index(indexRequest, RequestOptions.DEFAULT);
} catch (IOException e) {
e.printStackTrace();
}
return re;
}
public void transferFromMysql(){
articleRepository.findAll().forEach(this::addArticle);
}
public List<ArticleEntity> queryByKey(String keyword){
SearchRequest request = new SearchRequest();
/*
* 創建 搜索內容引數設定物件:SearchSourceBuilder
* 相對于matchQuery,multiMatchQuery針對的是多個fi eld,也就是說,當multiMatchQuery中,fieldNames引數只有一個時,其作用與matchQuery相當;
* 而當fieldNames有多個引數時,如field1和field2,那查詢的結果中,要么field1中包含text,要么field2中包含text,
*/
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders
.multiMatchQuery(keyword, "author","content","title"));
request.source(searchSourceBuilder);
List<ArticleEntity> result = new ArrayList<>();
try {
SearchResponse search = client.search(request, RequestOptions.DEFAULT);
for (SearchHit hit:search.getHits()){
Map<String, Object> map = hit.getSourceAsMap();
ArticleEntity item = new ArticleEntity();
item.setAuthor((String) map.get("author"));
item.setContent((String) map.get("content"));
item.setTitle((String) map.get("title"));
item.setUrl((String) map.get("url"));
result.add(item);
}
return result;
} catch (IOException e) {
e.printStackTrace();
}
return null;
}
public ArticleEntity queryById(String indexId){
GetRequest request = new GetRequest(ARTICLE_INDEX, indexId);
GetResponse response = null;
try {
response = client.get(request, RequestOptions.DEFAULT);
} catch (IOException e) {
e.printStackTrace();
}
if (response!=null&&response.isExists()){
Gson gson = new Gson();
return gson.fromJson(response.getSourceAsString(),ArticleEntity.class);
}
return null;
}
}
5.4 對外介面
和使用springboot開發web程式相同,
Spring Boot 基礎就不介紹了,推薦下這個實戰教程:
https://github.com/javastacks/spring-boot-best-practice
package com.lbh.es.controller;
import com.lbh.es.entity.ArticleEntity;
import com.lbh.es.service.ArticleService;
import org.elasticsearch.action.index.IndexResponse;
import org.springframework.web.bind.annotation.*;
import javax.annotation.Resource;
import java.util.List;
/**
* Copyright(c)[email protected]
* @author liubinhao
* @date 2021/3/3
*/
@RestController
@RequestMapping("article")
public class ArticleController {
@Resource
private ArticleService articleService;
@GetMapping("/create")
public boolean create(){
return articleService.createIndexOfArticle();
}
@GetMapping("/delete")
public boolean delete() {
return articleService.deleteArticle();
}
@PostMapping("/add")
public IndexResponse add(@RequestBody ArticleEntity article){
return articleService.addArticle(article);
}
@GetMapping("/fransfer")
public String transfer(){
articleService.transferFromMysql();
return "successful";
}
@GetMapping("/query")
public List<ArticleEntity> query(String keyword){
return articleService.queryByKey(keyword);
}
}
5.5 頁面
此處頁面使用thymeleaf,主要原因是筆者真滴不會前端,只懂一丟丟簡單的h5,就隨便做了一個可以展示的頁面,
搜索頁面
<!DOCTYPE html>
<html lang="en" xmlns:th="http://www.thymeleaf.org">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>YiyiDu</title>
<!--
input:focus設定當輸入框被點擊時,出現藍色外邊框
text-indent: 11px;和padding-left: 11px;設定輸入的字符的起始位置與左邊框的距離
-->
<style>
input:focus {
border: 2px solid rgb(62, 88, 206);
}
input {
text-indent: 11px;
padding-left: 11px;
font-size: 16px;
}
</style>
<!--input初始狀態-->
<style >
.input {
width: 33%;
height: 45px;
vertical-align: top;
box-sizing: border-box;
border: 2px solid rgb(207, 205, 205);
border-right: 2px solid rgb(62, 88, 206);
border-bottom-left-radius: 10px;
border-top-left-radius: 10px;
outline: none;
margin: 0;
display: inline-block;
background: url(/static/img/camera.jpg?watermark/2/text/5YWs5LyX5Y-377ya6IqL6YGT5rqQ56CB/font/5a6L5L2T/fontsize/400/fill/cmVk) no-repeat 0 0;
background-position: 565px 7px;
background-size: 28px;
padding-right: 49px;
padding-top: 10px;
padding-bottom: 10px;
line-height: 16px;
}
</style>
<!--button初始狀態-->
<style >
.button {
height: 45px;
width: 130px;
vertical-align: middle;
text-indent: -8px;
padding-left: -8px;
background-color: rgb(62, 88, 206);
color: white;
font-size: 18px;
outline: none;
border: none;
border-bottom-right-radius: 10px;
border-top-right-radius: 10px;
margin: 0;
padding: 0;
}
</style>
</head>
<body>
<!--包含table的div-->
<!--包含input和button的div-->
<div style="font-size: 0px;">
<div align="center" style="margin-top: 0px;">
<img src="https://img.uj5u.com/2021/12/31/293412310618267.png" th:src = "https://www.cnblogs.com/javastack/p/@{/static/img/yyd.png}" alt="一億度" />
</div>
<div align="center">
<!--action實作跳轉-->
<form action="/home/query">
<input type="text" name="keyword" />
<input type="submit" value="https://www.cnblogs.com/javastack/p/一億度下" />
</form>
</div>
</div>
</body>
</html>
搜索結果頁面
<!DOCTYPE html>
<html lang="en" xmlns:th="http://www.thymeleaf.org">
<head>
<link rel="stylesheet" href="https://cdn.staticfile.org/twitter-bootstrap/4.3.1/css/bootstrap.min.css">
<meta charset="UTF-8">
<title>xx-manager</title>
</head>
<body>
<header th:replace="search.html"></header>
<div >
<ul th:each="article : ${articles}">
<a th:href="https://www.cnblogs.com/javastack/p/${article.url}"><li th:text="${article.author}+${article.content}"></li></a>
</ul>
</div>
<footer th:replace="footer.html"></footer>
</body>
</html>
6 小結
上班擼代碼,下班繼續擼代碼寫博客,花了兩天研究了以下es,其實這個玩意兒還是挺有意思的,現在IR領域最基礎的還是基于統計學的,所以對于es這類搜索引擎而言在大資料的情況下具有良好的表現,
每一次寫實戰筆者其實都感覺有些無從下手,因為不知道做啥?所以也希望得到一些有意思的點子筆者會將實戰做出來,
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標籤:Java
