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Elasticsearch入门(二) API

作者:互联网

Elasticsearch入门(二) API

ES部署

VSCode部署

使用RESTful API操作ES,VSCode是个好工具。

VSCode官网免费的。。。

最好把这两插件也安装好:
在这里插入图片描述

Chinese (Simplified) Language Pack for Visual Studio Code
Elasticsearch for VSCode

一个是汉化包,一个是开发ES需要的拓展包。开发ES需要new一个.es或者打开一个已有的.es文件才能编辑。。。如果不小心关闭了连接地址栏,可以右键→命令面板→set host:
在这里插入图片描述
在这里插入图片描述
输入node1:9200即可连接:
在这里插入图片描述

--标准分词
post _analyze 
{
    "analyzer":"standard", 
    "text":"好喜欢数码宝贝"
}
--IK分词
post _analyze 
{
    "analyzer":"ik_max_word", 
    "text":"好喜欢数码宝贝"
}

简单测试下,点Run Query就能运行,发现标准分词:

{
    "tokens": [
        {
            "token": "好",
            "start_offset": 0,
            "end_offset": 1,
            "type": "<IDEOGRAPHIC>",
            "position": 0
        },
        {
            "token": "喜",
            "start_offset": 1,
            "end_offset": 2,
            "type": "<IDEOGRAPHIC>",
            "position": 1
        },
        {
            "token": "欢",
            "start_offset": 2,
            "end_offset": 3,
            "type": "<IDEOGRAPHIC>",
            "position": 2
        },
        {
            "token": "数",
            "start_offset": 3,
            "end_offset": 4,
            "type": "<IDEOGRAPHIC>",
            "position": 3
        },
        {
            "token": "码",
            "start_offset": 4,
            "end_offset": 5,
            "type": "<IDEOGRAPHIC>",
            "position": 4
        },
        {
            "token": "宝",
            "start_offset": 5,
            "end_offset": 6,
            "type": "<IDEOGRAPHIC>",
            "position": 5
        },
        {
            "token": "贝",
            "start_offset": 6,
            "end_offset": 7,
            "type": "<IDEOGRAPHIC>",
            "position": 6
        }
    ]
}

一个字一个字划分的。。。好吧。。。IK分词:

{
    "tokens": [
        {
            "token": "好喜欢",
            "start_offset": 0,
            "end_offset": 3,
            "type": "CN_WORD",
            "position": 0
        },
        {
            "token": "喜欢",
            "start_offset": 1,
            "end_offset": 3,
            "type": "CN_WORD",
            "position": 1
        },
        {
            "token": "数码宝贝",
            "start_offset": 3,
            "end_offset": 7,
            "type": "CN_WORD",
            "position": 2
        },
        {
            "token": "数码",
            "start_offset": 3,
            "end_offset": 5,
            "type": "CN_WORD",
            "position": 3
        },
        {
            "token": "宝贝",
            "start_offset": 5,
            "end_offset": 7,
            "type": "CN_WORD",
            "position": 4
        }
    ]
}

好家伙,连数码宝贝都能划分出来。。。真强。。。

RESTful API

索引库管理

列举索引

GET _cat/indices

这句类似MySQL中的show databases;用于查询当前所有索引库:

[]

当然目前还没有。。。

创建job_idx索引库

PUT /job_idx
{
    "mappings": {
        "properties" : {
            "area": { "type": "text", "store": true, "analyzer": "ik_max_word"},
            "exp": { "type": "text", "store": true, "analyzer": "ik_max_word"},
            "edu": { "type": "keyword", "store": true},
            "salary": { "type": "keyword", "store": true},
            "job_type": { "type": "keyword", "store": true},
            "cmp": { "type": "text", "store": true, "analyzer": "ik_max_word"},
            "pv": { "type": "keyword", "store": true},
            "title": { "type": "text", "store": true, "analyzer": "ik_max_word"},
            "jd": { "type": "text", "store": true, "analyzer": "ik_max_word"}
        }
    },
  "settings" : {
        "number_of_shards":5,
      "number_of_replicas" : 1
    }
}

其中:

mappings:用于做列的定义
type:类型
store:存储原始数据
analyzer:分词器的类型
index:是否对这列构建索引,默认为true
settings:集群配置管理
"number_of_shards":5,:这个索引库有5个分区
"number_of_replicas" : 1:副本个数为1

运行后,在浏览器node1:9200
在这里插入图片描述
(边框加粗的是Leader分区,边框细的是Follower分区)

5个分区和1倍数的备份。。。和预期一致。。。

查看索引

GET /job_idx/_mapping
GET /job_idx/_settings

也可以在网页端:
在这里插入图片描述
信息→索引状态/索引信息查看。

删除索引

delete /job_idx

执行后网页端刷新,不再有内容。

数据管理

数据插入

按照这种套路:

put /index/_doc/doc_id
{
	JSON:每一列的数据
}

可以插入数据。例如:

PUT /job_idx/_doc/29097
{
    "area": "深圳-南山区",
    "exp": "1年经验",
    "edu": "大专以上",
    "salary": "6-8千/月",
    "job_type": "实习",
    "cmp": "乐有家",
    "pv": "61.6万人浏览过  / 14人评价  / 113人正在关注",
    "title": "桃园 深大销售实习 岗前培训",
    "jd": "薪酬待遇】 本科薪酬7500起 大专薪酬6800起 以上无业绩要求,同时享有业绩核算比例55%~80% 人均月收入超1.3万 【岗位职责】 1.爱学习,有耐心: 通过公司系统化培训熟悉房地产基本业务及相关法律、金融知识,不功利服务客户,耐心为客户在房产交易中遇到的各类问题; 2.会聆听,会提问: 详细了解客户的核心诉求,精准匹配合适的产品信息,具备和用户良好的沟通能力,有团队协作意识和服务意识; 3.爱琢磨,善思考: 热衷于用户心理研究,善于从用户数据中提炼用户需求,利用个性化、精细化运营手段,提升用户体验。 【岗位要求】 1.18-26周岁,自考大专以上学历; 2.具有良好的亲和力、理解能力、逻辑协调和沟通能力; 3.积极乐观开朗,为人诚实守信,工作积极主动,注重团队合作; 4.愿意服务于高端客户,并且通过与高端客户面对面沟通有意愿提升自己的综合能力; 5.愿意参加公益活动,具有爱心和感恩之心。 【培养路径】 1.上千堂课程;房产知识、营销知识、交易知识、法律法规、客户维护、目标管理、谈判技巧、心理学、经济学; 2.成长陪伴:一对一的师徒辅导 3.线上自主学习平台:乐有家学院,专业团队制作,每周大咖分享 4.储备及管理课堂: 干部训练营、月度/季度管理培训会 【晋升发展】 营销【精英】发展规划:A1置业顾问-A6资深置业专家 营销【管理】发展规划:(入职次月后就可竞聘) 置业顾问-置业经理-店长-营销副总经理-营销副总裁-营销总裁 内部【竞聘】公司职能岗位:如市场、渠道拓展中心、法务部、按揭经理等都是内部竞聘 【联系人】 黄媚主任15017903212(微信同号)"
}

执行后result.json显示内容为:

{
    "_index": "job_idx",
    "_type": "_doc",
    "_id": "29097",
    "_version": 1,
    "result": "created",
    "_shards": {
        "total": 2,
        "successful": 2,
        "failed": 0
    },
    "_seq_no": 0,
    "_primary_term": 1
}

在网页端刷新后在数据浏览分栏看到:
在这里插入图片描述

数据更新

可以这样:

POST /job_idx/_update/29097
{
    "doc": {
        "salary": "15-20千/月"
    }
}

删除数据

DELETE /job_idx/_doc/29097

右侧的result.json会显示:

{
    "_index": "job_idx",
    "_type": "_doc",
    "_id": "29097",
    "_version": 2,
    "result": "deleted",
    "_shards": {
        "total": 2,
        "successful": 2,
        "failed": 0
    },
    "_seq_no": 1,
    "_primary_term": 1
}

显然记录了版本号及删除的信息。

BulkLoad

curl -H "Content-Type: application/json" -XPOST "node1:9200/job_idx/_bulk?pretty&refresh" --data-binary "@job_info.json"

这种方式先将文件上传到Linux再批量加载文件:
在这里插入图片描述

数据查询

doc_id查询

类似MySQL根据主键查询。例如:

GET /job_idx/_search
{
    "query": {
        "ids": {
            "values": ["46313"]
        }
    }
}

查询器

GET  /job_idx/_search 
{
    "query": {
        "match": {
            "jd": "销售"
        }
    },
    "size":"100"
}

默认值显示10条,使用size标签可以显示多条。

或者使用multi_match实现多列字符串匹配查询器:

GET  /job_idx/_search
{
    "query": {
        "multi_match": {
            "query": "销售",
            "fields": ["title", "jd"]
        }
    }
}

或者分页查询:

GET  /job_idx/_search
{
    "from": 0,
    "size": 5,
    "query": {
        "multi_match": {
            "query": "销售",
            "fields": ["title", "jd"]
        }
    }
}

这种浅分页类似MySQL的limit M,N。from是开始条目的偏移量(第一条为0),size是每页显示的条目数。

自然还有深分页
第一次查询,会将整个所有数据放在内存中,从第二次开始就从内存中来自动遍历每页的数据。scroll = 1m :做深分页,将查询的结果保存在内存中1分钟。size:每一页显示多少条(能够自动进行翻页)。

例如:
第一次:

GET /job_idx/_search?scroll=1m
{
    "query": {
        "multi_match": {
          "query": "销售",
            "fields": ["title", "jd"]
      }
    },
    "size": 100
}

在result.json中抓取到:

"_scroll_id": "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAAAIWdmVueGpVeHRRd09hX3pWMU1uRUxwQQ==",

之后使用该_scroll_id就可以实现连续翻页:

GET _search/scroll?scroll=1m
{
    "scroll_id": "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAAAAnFlJfaWNiQzhvU3YydTJpMUV1OUpIZlEAAAAAAAAAIhZBTEhIaW9WS1NBT3d4X3lKWXNIREN3AAAAAAAAACgWUl9pY2JDOG9TdjJ1MmkxRXU5SkhmUQAAAAAAAAAkFmlfMXlVOHB0VGYtbUFMMUdUd1JFWVEAAAAAAAAAIxZpXzF5VThwdFRmLW1BTDFHVHdSRVlR"
}

Java API

准备工作

代码太多。。。使用//region//endregion折叠。。。

导入Maven依赖

pom.xml中:

    <dependencies>
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-high-level-client</artifactId>
            <version>7.6.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>2.11.1</version>
        </dependency>
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.62</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.12</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.testng</groupId>
            <artifactId>testng</artifactId>
            <version>6.14.3</version>
            <scope>test</scope>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.1</version>
                <configuration>
                    <target>1.8</target>
                    <source>1.8</source>
                </configuration>
            </plugin>
        </plugins>
    </build>

封装Java Bean对象

package com.aa.esClient.bean;

import com.alibaba.fastjson.annotation.JSONField;

public class JobDetail {
    //region 封装数据
    //无需将id序列化为文档
    @JSONField(serialize = false)
    private long id;            // 唯一标识
    private String area;        // 职位所在区域
    private String exp;         // 岗位要求的工作经验
    private String edu;         // 学历要求
    private String salary;      // 薪资范围
    private String job_type;    // 职位类型(全职/兼职)
    private String cmp;         // 公司名
    private String pv;          // 浏览量
    private String title;       // 岗位名称
    private String jd;          // 职位描述
    //endregion

    //region get&set
    public long getId() {
        return id;
    }

    public void setId(long id) {
        this.id = id;
    }

    public String getArea() {
        return area;
    }

    public void setArea(String area) {
        this.area = area;
    }

    public String getExp() {
        return exp;
    }

    public void setExp(String exp) {
        this.exp = exp;
    }

    public String getEdu() {
        return edu;
    }

    public void setEdu(String edu) {
        this.edu = edu;
    }

    public String getSalary() {
        return salary;
    }

    public void setSalary(String salary) {
        this.salary = salary;
    }

    public String getJob_type() {
        return job_type;
    }

    public void setJob_type(String job_type) {
        this.job_type = job_type;
    }

    public String getCmp() {
        return cmp;
    }

    public void setCmp(String cmp) {
        this.cmp = cmp;
    }

    public String getPv() {
        return pv;
    }

    public void setPv(String pv) {
        this.pv = pv;
    }

    public String getTitle() {
        return title;
    }

    public void setTitle(String title) {
        this.title = title;
    }

    public String getJd() {
        return jd;
    }

    public void setJd(String jd) {
        this.jd = jd;
    }

    //endregion

    //region 重写toString方法
    @Override
    public String toString() {
        return "JobDetail{" +
                "id=" + id +
                ", area='" + area + '\'' +
                ", exp='" + exp + '\'' +
                ", edu='" + edu + '\'' +
                ", salary='" + salary + '\'' +
                ", job_type='" + job_type + '\'' +
                ", cmp='" + cmp + '\'' +
                ", pv='" + pv + '\'' +
                ", title='" + title + '\'' +
                ", jd='" + jd + '\'' +
                '}';
    }
    //endregion
}

封装接口

package com.aa.esClient.service;

import com.aa.esClient.bean.JobDetail;

import java.io.IOException;
import java.util.List;
import java.util.Map;

public interface JobFullTextService {
    //region 封装方法

    //添加一个职位数据
    void add(JobDetail jobDetail);

    // 修改职位薪资
    void update(JobDetail jobDetail) throws IOException;

    // 根据ID删除指定位置数据
    void deleteById(long id) throws IOException;

    // 根据ID检索指定职位数据
    JobDetail findById(long id) throws IOException;

    // 根据关键字检索数据
    List<JobDetail> searchByKeywords(String keywords) throws IOException;

    // 分页检索
    Map<String, Object> searchByPage(String keywords, int pageNum, int pageSize) throws IOException;

    // scroll分页解决深分页问题
    Map<String, Object> searchByScrollPage(String keywords, String scrollId, int pageSize) throws IOException;

    // 关闭ES连接
    void close() throws IOException;

    //endregion

}

编写实现类

package com.aa.esClient.impl;

import com.aa.esClient.bean.JobDetail;
import com.aa.esClient.service.JobFullTextService;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import org.apache.http.HttpHost;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchScrollRequest;
import org.elasticsearch.action.update.UpdateRequest;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.unit.TimeValue;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.index.query.MultiMatchQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;

import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class JobFullTextServiceImpl implements JobFullTextService {
    //region 初始化
    //定义了一个连接对象
    private RestHighLevelClient restHighLevelClient;
    //定义索引库的名称
    private static final String JOB_IDX_NAME = "job_idx";

    //构造函数,用于new实例的时候,构建连接
    public JobFullTextServiceImpl() {
        restHighLevelClient = new RestHighLevelClient(RestClient.builder(
                new HttpHost("node1", 9200, "http")
                , new HttpHost("node2", 9200, "http")
                , new HttpHost("node3", 9200, "http")
        ));
    }
    //endregion

    //region 实现接口的方法

    //region 往ES中写入一条JSON格式的数据
    @Override
    public void add(JobDetail jobDetail) {
        //构建了一个索引请求器对象,用于写入,制定了请求器请求的索引库的名称
        IndexRequest indexRequest = new IndexRequest(JOB_IDX_NAME);
        //封装数据到请求器中:doc_Id + JSON数据
        //从参数的对象中获取id作为docId
        indexRequest.id(jobDetail.getId() +"");
        //将JavaBean对象转换为JSON字符串
        String jsonString = JSON.toJSONString(jobDetail);
        //将JSON数据加载到请求器中,指定数据为JSON格式
        indexRequest.source(jsonString, XContentType.JSON);
        try {
            //客户端连接调用index方法实现写入:第一个参数是索引请求器
            restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    //endregion

    //region 实现更新,将新的数据替换老的数据
    @Override
    public void update(JobDetail jobDetail) throws IOException {
        //先判断是否存在
        GetRequest getRequest = new GetRequest(JOB_IDX_NAME);
        getRequest.id(jobDetail.getId()+"");
        //判断是否存在
        boolean exists = restHighLevelClient.exists(getRequest, RequestOptions.DEFAULT);
        //如果不存在,方法调用结束
        if(!exists) return;
        //构建更新请求器:索引库名 + 指定更新的docid
        UpdateRequest updateRequest = new UpdateRequest(JOB_IDX_NAME,jobDetail.getId()+"");
        //更新请求器加载新数据
        updateRequest.doc(JSON.toJSONString(jobDetail),XContentType.JSON);
        //调用客户端连接中的更新方法
        restHighLevelClient.update(updateRequest,RequestOptions.DEFAULT);
    }
    //endregion

    //region 定义删除功能
    @Override
    public void deleteById(long id) throws IOException {
        //构建删除请求器
        DeleteRequest deleteRequest = new DeleteRequest(JOB_IDX_NAME);
        //添加指定删除的docid
        deleteRequest.id(id+"");
        //调用删除方法
        restHighLevelClient.delete(deleteRequest,RequestOptions.DEFAULT);
    }
    //endregion

    //region 用于通过docId来查找数据
    @Override
    public JobDetail findById(long id) throws IOException {
        //构建一个Get请求器对象
        GetRequest getRequest = new GetRequest(JOB_IDX_NAME);
        //指定get请求器的docid
        getRequest.id(id+"");
        //客户端连接对象调用get方法来获取某个docId对应的数据:传递get请求器
        GetResponse documentFields = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);
        //将每一列对应的数据取出转换为JSON String
        String sourceAsString = documentFields.getSourceAsString();
        //将JSONString转换为JavaBean独享
        JobDetail jobDetail = JSON.parseObject(sourceAsString, JobDetail.class);
        return jobDetail;
    }
    //endregion

    //region 关键词查询
    @Override
    public List<JobDetail> searchByKeywords(String keywords) throws IOException {
        List<JobDetail> lists = new ArrayList<>();//用作返回值

        //构建Search的请求器
        SearchRequest searchRequest = new SearchRequest();
        //构建条件的建造器
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        //构建一个符合需求的查询器
        MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title");
//        MatchQueryBuilder c1 = QueryBuilders.matchQuery(keywords, "jd");//关键词单列查询器,模糊查询,做分词
//        TermQueryBuilder c2 = QueryBuilders.termQuery(keywords, "jd");//关键词单列查询器,精准查询,不做分词
//        RangeQueryBuilder c3 = QueryBuilders.rangeQuery("age").gt("18").lt("30");//范围查询 gt代表big than>,lt代表less than<
//        QueryBuilders.boolQuery().must(c2).must(c3).should(c1); //must代表and并列,should表示or或,多条件组合查询

        //条件建造器加载查询器
        searchSourceBuilder.query(multiMatchQueryBuilder).size(100);
        //加载查询的条件
        searchRequest.source(searchSourceBuilder);
        //调用客户端连接的search方法,实现查询
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = search.getHits().getHits();
        for (SearchHit hit : hits) {//iter迭代
            //获取每一条数据,将数据的内容转换为JAVA Bean
            JobDetail jobDetail = JSON.parseObject(hit.getSourceAsString(), JobDetail.class);
            //将docId设置为id
            jobDetail.setId(Long.parseLong(hit.getId()));
            lists.add(jobDetail);
        }
        return lists;
    }
    //endregion

    //region 浅分页查询
    @Override
    public Map<String, Object> searchByPage(String keywords, int pageNum, int pageSize) throws IOException {
        SearchRequest searchRequest = new SearchRequest();
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title");
        //建造器中指定查询器,指定from和size
        searchSourceBuilder.query(multiMatchQueryBuilder)
                .from(pageNum)
                .size(pageSize);
        searchRequest.source(searchSourceBuilder);
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        //取的是第一层hits
        SearchHits hits = search.getHits();
        List<JobDetail> lists = new ArrayList<>();
        for (SearchHit hit : hits) {
            JobDetail jobDetail = JSON.parseObject(hit.getSourceAsString(), JobDetail.class);
            jobDetail.setId(Long.parseLong(hit.getId()));
            lists.add(jobDetail);
        }
        //构建返回值:返回值为Map集合
        Map<String, Object> result = new HashMap<>();
        //第一条数据:Key:total,Value:返回值的总条数
        result.put("total", hits.getTotalHits().value);
        //第二条数据:Key:content,Value:每条数据的List集合
        result.put("content", lists);

        return result;
    }
    //endregion

    //region 深分页查询
    @Override
    public Map<String, Object> searchByScrollPage(String keywords, String scrollId, int pageSize) throws IOException {
        //构建返回值
        Map<String, Object> result = new HashMap<>();
        List<JobDetail> jobList = new ArrayList<>();

        try {
            SearchResponse searchResponse = null;
            //如果为null,这是第一次请求
            if(scrollId == null) {
                // 1. 创建搜索请求
                SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME);
                // 2. 构建查询条件
                SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
                searchSourceBuilder.query(QueryBuilders.multiMatchQuery(keywords, "title", "jd"));
                // 3. 设置分页大小
                searchSourceBuilder.size(pageSize);
                // 4. 设置查询条件、并设置滚动快照有效时间
                searchRequest.source(searchSourceBuilder);
                //指定数据在内存中放置时间
                searchRequest.scroll(TimeValue.timeValueMinutes(1));
                // 5. 发起请求
                //提交查询器
                searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
            }
            //不是第一次,直接根据scrollid来查询
            else {
                //构建深分页查询器,传递scrollid
                SearchScrollRequest searchScrollRequest = new SearchScrollRequest(scrollId);
                searchScrollRequest.scroll(TimeValue.timeValueMinutes(1));
                //调用scroll实现深分页
                searchResponse = restHighLevelClient.scroll(searchScrollRequest, RequestOptions.DEFAULT);
            }

            // 6. 迭代响应结果
            SearchHits hits = searchResponse.getHits();
            for (SearchHit hit : hits) {
                JobDetail jobDetail = JSONObject.parseObject(hit.getSourceAsString(), JobDetail.class);
                jobDetail.setId(Long.parseLong(hit.getId()));
                jobList.add(jobDetail);
            }
            //第一条数据:数据的呃逆荣
            result.put("content", jobList);
            //第二条数据;scrollid
            result.put("scroll_id", searchResponse.getScrollId());

        }
        catch (IOException e) {
            e.printStackTrace();
        }

        return result;
    }
    //endregion

    //region 释放资源
    @Override
    public void close() throws IOException {
        try {
            restHighLevelClient.close();
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    //endregion

    //endregion
}

编写测试工具类

import com.aa.esClient.bean.JobDetail;
import com.aa.esClient.impl.JobFullTextServiceImpl;
import org.junit.After;
import org.junit.Before;
import org.junit.Test;

import java.io.IOException;
import java.util.List;
import java.util.Map;

public class JobFullTextServiceTest {
    private JobFullTextServiceImpl jobFullTextService;

    @Before
    public void getInstance(){
        //构建实现类的实例对象:构建连接
        jobFullTextService = new JobFullTextServiceImpl();
    }

    //测试实现类add方法,写入数据
    @Test
    public void testAdd(){
        //构建JaIndexRequestvaBean实例
        JobDetail jobDetail = new JobDetail();
        jobDetail.setId(1);
        jobDetail.setArea("山西省-太原市");
        jobDetail.setCmp("上兰村大学");
        jobDetail.setEdu("本科及以上");
        jobDetail.setExp("一年工作经验");
        jobDetail.setTitle("大数据工程师");
        jobDetail.setJob_type("全职");
        jobDetail.setPv("1700次浏览");
        jobDetail.setJd("会Hadoop就行");
        jobDetail.setSalary("5-9千/月");
        //调用add方法
        jobFullTextService.add(jobDetail);
    }

    //测试实现类根据docID读取数据
    @Test
    public void testGetById() throws IOException {
        //调用查询方法
        JobDetail byId = jobFullTextService.findById(1);
        System.out.println(byId);
    }

    //测试更新
    @Test
    public void testUpdate() throws IOException {
        JobDetail jobDetail = new JobDetail();
        jobDetail.setId(1);
        jobDetail.setArea("山西省-太原市");
        jobDetail.setCmp("上兰村大学");
        jobDetail.setEdu("本科及以上");
        jobDetail.setExp("一年工作经验");
        jobDetail.setTitle("大数据工程师");
        jobDetail.setJob_type("全职");
        jobDetail.setPv("1700次浏览");
        jobDetail.setJd("会Hadoop就行");
        jobDetail.setSalary("20-40千/月");
        //调用更新方法进行更新
        jobFullTextService.update(jobDetail);
    }

    //测试删除
    @Test
    public void testDelete() throws IOException {
        jobFullTextService.deleteById(1);
    }

    //测试关键词查询
    @Test
    public void testSearch() throws IOException {
        List<JobDetail> jobDetails = jobFullTextService.searchByKeywords("销售");
        for (JobDetail jobDetail : jobDetails) {
            System.out.println(jobDetail);
        }
    }

    //测试浅分页
    @Test
    public void testFromSize() throws IOException {
        Map<String, Object> objectMap = jobFullTextService.searchByPage("销售", 0, 100);
        System.out.println("总共:"+objectMap.get("total"));
        List<JobDetail> lists = (List<JobDetail>) objectMap.get("content");
        for (JobDetail list : lists) {
            System.out.println(list);
        }
    }

    //第一次运行
    @Test
    public void searchByScrollPageTest1() throws IOException {
        Map<String, Object> result = jobFullTextService.searchByScrollPage("销售", null, 10);
        System.out.println("scrollId: " + result.get("scroll_id"));
        List<JobDetail> content = (List<JobDetail>)result.get("content");

        for (JobDetail jobDetail : content) {
            System.out.println(jobDetail);
        }
    }

    //第二次开始
    @Test
    public void searchByScrollPageTest2() throws IOException {
        Map<String, Object> result = jobFullTextService.searchByScrollPage("销售", "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAAAA1FkFMSEhpb1ZLU0FPd3hfeUpZc0hEQ3cAAAAAAAAANxZBTEhIaW9WS1NBT3d4X3lKWXNIREN3AAAAAAAAADYWQUxISGlvVktTQU93eF95SllzSERDdwAAAAAAAAA8FlJfaWNiQzhvU3YydTJpMUV1OUpIZlEAAAAAAAAAPRZSX2ljYkM4b1N2MnUyaTFFdTlKSGZR", 10);
        System.out.println("scrollId: " + result.get("scroll_id"));
        List<JobDetail> content = (List<JobDetail>)result.get("content");

        for (JobDetail jobDetail : content) {
            System.out.println(jobDetail);
        }
    }

    @After
    public void close(){
        try {
            //释放ES的连接对象
            jobFullTextService.close();
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

插入数据

在这里插入图片描述

查询数据

JobDetail{id=0, area='山西省-太原市', exp='一年工作经验', edu='本科及以上', salary='5-9千/月', job_type='全职', cmp='上兰村大学', pv='1700次浏览', title='大数据工程师', jd='会Hadoop就行'}

Process finished with exit code 0

更新数据

更新前:
在这里插入图片描述
更新后:
在这里插入图片描述
缺少Log4j的报错不用理会:

ERROR StatusLogger No Log4j 2 configuration file found. Using default configuration (logging only errors to the console), or user programmatically provided configurations. Set system property 'log4j2.debug' to show Log4j 2 internal initialization logging. See https://logging.apache.org/log4j/2.x/manual/configuration.html for instructions on how to configure Log4j 2

Process finished with exit code 0

删除数据

在这里插入图片描述

关键词查询

在这里插入图片描述

浅分页查询

在这里插入图片描述
数了一下,确实是100行。。。

深分页查询

第一次运行捕获:

scrollId: DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAABoWTl9iLWotOHZRZ21fcDk4a2JkVGc1Zw==

在这里插入图片描述
第二次及以后运行需要按第一次运行捕获的数据修改:

Map<String, Object> result = jobFullTextService.searchByScrollPage("销售",         "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAABsWTl9iLWotOHZRZ21fcDk4a2JkVGc1Zw==", 10);

在这里插入图片描述
串码和内存地址有关,每次使用可能都不一样。。。貌似成功实现了深分页查询。

标签:入门,id,String,API,Elasticsearch,import,type,public,jobDetail
来源: https://blog.csdn.net/qq_41990268/article/details/117483479