spring elasticsearch 按条件删除_学习ElasticSearch不要慌，小刘带你慢慢学

前段时间，小刘从硬盘找了以前的笔记，总结，和大家分享一下

一、ElasticSearch 介绍

1、简介

Elasticsearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎，基于RESTful web接口。Elasticsearch是用Java语言开发的，并作为Apache许可条款下的开放源码发布，是一种流行的企业级搜索引擎。Elasticsearch用于云计算中，能够达到实时搜索，稳定，可靠，快速，安装使用方便。官方客户端在Java、.NET(C#)、PHP、Python、Apache Groovy、Ruby和许多其他语言中都是可用的。根据DB-Engines的排名显示，Elasticsearch是最受欢迎的企业搜索引擎，其次是Apache Solr，也是基于Lucene

就连Github都是用ElasticSearch做词条搜索

0. 带着问题上路——ES是如何产生的？

(1)思考：大规模数据如何检索？

如：当系统数据量上了10亿、100亿条的时候，我们在做系统架构的时候通常会从以下角度去考虑问题： 
1)用什么数据库好？(mysql、sybase、oracle、达梦、神通、mongodb、hbase…) 
2)如何解决单点故障；(lvs、F5、A10、Zookeep、MQ) 
3)如何保证数据安全性；(热备、冷备、异地多活) 
4)如何解决检索难题；(数据库代理中间件：mysql-proxy、Cobar、MaxScale等;) 
5)如何解决统计分析问题；(离线、近实时)

(2)传统数据库的应对解决方案

对于关系型数据，我们通常采用以下或类似架构去解决查询瓶颈和写入瓶颈： 
解决要点： 
1)通过主从备份解决数据安全性问题； 
2)通过数据库代理中间件心跳监测，解决单点故障问题； 
3)通过代理中间件将查询语句分发到各个slave节点进行查询，并汇总结果 

3)非关系型数据库的解决方案

对于Nosql数据库，以mongodb为例，其它原理类似： 
解决要点： 
1)通过副本备份保证数据安全性； 
2)通过节点竞选机制解决单点问题； 
3)先从配置库检索分片信息，然后将请求分发到各个节点，最后由路由节点合并汇总结果 

另辟蹊径——完全把数据放入内存怎么样？

我们知道，完全把数据放在内存中是不可靠的，实际上也不太现实，当我们的数据达到PB级别时，按照每个节点96G内存计算，在内存完全装满的数据情况下，我们需要的机器是：1PB=1024T=1048576G
节点数=1048576/96=10922个 
实际上，考虑到数据备份，节点数往往在2.5万台左右。成本巨大决定了其不现实！

从前面讨论我们了解到，把数据放在内存也好，不放在内存也好，都不能完完全全解决问题。 
全部放在内存速度问题是解决了，但成本问题上来了。 
为解决以上问题，从源头着手分析，通常会从以下方式来寻找方法： 
1、存储数据时按有序存储； 
2、将数据和索引分离； 
3、压缩数据； 
这就引出了Elasticsearch。

二、ElasticSearch 和数据库概念

1、ElaticSearch 和 DB 的关系

在 Elasticsearch 中，文档归属于一种类型 type，而这些类型存在于索引 index 中，我们可以列一些简单的不同点，来类比传统关系型数据库：

• Relational DB -> Databases -> Tables -> Rows -> Columns
• Elasticsearch -> Indices -> Types -> Documents -> Fields

Elasticsearch 集群可以包含多个索引 indices，每一个索引可以包含多个类型 types，每一个类型包含多个文档 documents，然后每个文档包含多个字段 Fields。而在 DB 中可以有多个数据库 Databases，每个库中可以有多张表 Tables，没个表中又包含多行Rows，每行包含多列Columns。

ElasticSearch的对象模型，跟关系型数据库模型相比：

索引(Index)：相当于数据库，用于定义文档类型的存储；在同一个索引中，同一个字段只能定义一个数据类型；

文档类型(Type)：相当于关系表，用于描述文档中的各个字段的定义；不同的文档类型，能够存储不同的字段，服务于不同的查询请求；

ElasticSearch的对象模型，跟关系型数据库模型相比：

索引(Index)：相当于数据库，用于定义文档类型的存储；在同一个索引中，同一个字段只能定义一个数据类型；

文档类型(Type)：相当于关系表，用于描述文档中的各个字段的定义；不同的文档类型，能够存储不同的字段，服务于不同的查询请求；

文档(Document)：相当于关系表的数据行，存储数据的载体，包含一个或多个存有数据的字段；

字段(Field)：文档的一个Key/Value对；

词(Term)：表示文本中的一个单词；

标记(Token)：表示在字段中出现的词，由该词的文本、偏移量(开始和结束)以及类型组成；

索引是由段(Segment)组成的，段存储在硬盘(Disk)文件中，段不是实时更新的，这意味着，段在写入磁盘后，就不再被更新。ElasticSearch引擎把被删除的文档的信息存储在一个单独的文件中，在搜索数据时，

ElasticSearch引擎首先从段中查询，再从查询结果中过滤被删除的文档，这意味着，段中存储着“被删除”的文档，这使得段中含有”正常文档“的密度降低。多个段可以通过段合并(Segment Merge)操作把“已删除”的文档将从段中物理删除，把未删除的文档合并到一个新段中，新段中没有”已删除文档“，因此，段合并操作能够提高索引的查找速度，但段合并是IO密集型的操作，需要消耗大量的硬盘IO。

三、SpringBoot集成ElasticSearch 介绍

下面介绍下 SpringBoot 如何通过 elasticsearch-rest-high-level-client 工具操作 ElasticSearch，这里需要说一下，为什么没有使用 Spring 家族封装的 spring-data-elasticsearch。

主要原因是灵活性和更新速度，Spring 将 ElasticSearch 过度封装，让开发者很难跟 ES 的 DSL 查询语句进行关联。再者就是更新速度，ES 的更新速度是非常快，但是 spring-data-elasticsearch 更新速度比较缓慢。

由于上面两点，所以选择了官方推出的 Java 客户端 elasticsearch-rest-high-level-client，它的代码写法跟 DSL 语句很相似，懂 ES 查询的使用其上手很快。

1、Maven 引入相关依赖

• lombok：lombok 工具依赖。
• fastjson：用于将 JSON 转换对象的依赖。
• spring-boot-starter-web：SpringBoot 的 Web 依赖。
• elasticsearch：ElasticSearch：依赖，需要和 ES 版本保持一致。
• elasticsearch-rest-high-level-client：用于操作 ES 的 Java 客户端。

<?xml  version="1.0" encoding="UTF-8"?><project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">    <modelVersion>4.0.0modelVersion>    <parent>        <groupId>org.springframework.bootgroupId>        <artifactId>spring-boot-starter-parentartifactId>        <version>2.2.4.RELEASEversion>        <relativePath/>     parent>    <groupId>cloud.spiritmarkgroupId>    <artifactId>springboot-elasticsearch-exampleartifactId>    <version>0.0.1-SNAPSHOTversion>    <name>springboot-elasticsearch-examplename>    <description>Demo project for ElasticSearchdescription>    <properties>        <java.version>1.8java.version>    properties>    <dependencies>                <dependency>            <groupId>org.springframework.bootgroupId>            <artifactId>spring-boot-starter-webartifactId>        dependency>                <dependency>            <groupId>org.projectlombokgroupId>            <artifactId>lombokartifactId>            <optional>trueoptional>        dependency>                       <dependency>            <groupId>org.elasticsearch.clientgroupId>            <artifactId>elasticsearch-rest-high-level-clientartifactId>            <version>6.5.4version>        dependency>        <dependency>            <groupId>org.elasticsearchgroupId>            <artifactId>elasticsearchartifactId>            <version>6.5.4version>        dependency>    dependencies>    <build>        <plugins>            <plugin>                <groupId>org.springframework.bootgroupId>                <artifactId>spring-boot-maven-pluginartifactId>            plugin>        plugins>    build>project>

2、ElasticSearch 配置

(1)、application.yml 配置文件

为了方便更改连接 ES 的连接配置，所以我们将配置信息放置于 application.yaml 中：

#baseserver:  port: 8080#springspring:  application:    name: springboot-elasticsearch#elasticsearchelasticsearch:  schema: http  address: 127.0.0.1:9200  connectTimeout: 5000  socketTimeout: 5000  connectionRequestTimeout: 5000  maxConnectNum: 100  maxConnectPerRoute: 100

(2)、java 连接配置类

这里需要写一个 Java 配置类读取 application 中的配置信息：

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;/** * ElasticSearch 配置 */@Configurationpublic class ElasticSearchConfig {    /** 协议 */    @Value("${elasticsearch.schema:http}")    private String schema;    /** 集群地址，如果有多个用“,”隔开 */    @Value("${elasticsearch.address}")    private String address;    /** 连接超时时间 */    @Value("${elasticsearch.connectTimeout:5000}")    private int connectTimeout;    /** Socket 连接超时时间 */    @Value("${elasticsearch.socketTimeout:10000}")    private int socketTimeout;    /** 获取连接的超时时间 */    @Value("${elasticsearch.connectionRequestTimeout:5000}")    private int connectionRequestTimeout;    /** 最大连接数 */    @Value("${elasticsearch.maxConnectNum:100}")    private int maxConnectNum;    /** 最大路由连接数 */    @Value("${elasticsearch.maxConnectPerRoute:100}")    private int maxConnectPerRoute;    @Bean    public RestHighLevelClient restHighLevelClient() {        // 拆分地址        List 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));        }// 转换成 HttpHost 数组        HttpHost[] httpHost = hostLists.toArray(new HttpHost[]{});// 构建连接对象        RestClientBuilder builder = RestClient.builder(httpHost);// 异步连接延时配置        builder.setRequestConfigCallback(requestConfigBuilder -> {            requestConfigBuilder.setConnectTimeout(connectTimeout);            requestConfigBuilder.setSocketTimeout(socketTimeout);            requestConfigBuilder.setConnectionRequestTimeout(connectionRequestTimeout);return requestConfigBuilder;        });// 异步连接数配置        builder.setHttpClientConfigCallback(httpClientBuilder -> {            httpClientBuilder.setMaxConnTotal(maxConnectNum);            httpClientBuilder.setMaxConnPerRoute(maxConnectPerRoute);return httpClientBuilder;        });return new RestHighLevelClient(builder);    }}

四、索引操作示例

1、Restful 操作示例

创建索引

创建名为 mydlq-user 的索引与对应 Mapping。

请求格式 ：PUT /mydlq-user

{  "mappings": {    "doc": {      "dynamic": true,      "properties": {        "name": {          "type": "text",          "fields": {            "keyword": {              "type": "keyword"            }          }        },        "address": {          "type": "text",          "fields": {            "keyword": {              "type": "keyword"            }          }        },        "remark": {          "type": "text",          "fields": {            "keyword": {              "type": "keyword"            }          }        },        "age": {          "type": "integer"        },        "salary": {          "type": "float"        },        "birthDate": {          "type": "date",          "format": "yyyy-MM-dd"        },        "createTime": {          "type": "date"        }      }    }  }}

删除索引

删除 mydlq-user 索引。

DELETE /mydlq-user

2、Java 代码示例

import lombok.extern.slf4j.Slf4j;import org.elasticsearch.action.admin.indices.create.CreateIndexRequest;import org.elasticsearch.action.admin.indices.create.CreateIndexResponse;import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;import org.elasticsearch.action.support.master.AcknowledgedResponse;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.common.settings.Settings;import org.elasticsearch.common.xcontent.XContentBuilder;import org.elasticsearch.common.xcontent.XContentFactory;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import java.io.IOException;@Slf4j@Servicepublic class IndexService2 {    @Autowired    private RestHighLevelClient restHighLevelClient;    /**     * 创建索引     */    public void createIndex() {        try {            // 创建 Mapping            XContentBuilder mapping = XContentFactory.jsonBuilder()                .startObject()                    .field("dynamic", true)                    .startObject("properties")                        .startObject("name")                            .field("type","text")                            .startObject("fields")                                .startObject("keyword")                                    .field("type","keyword")                                .endObject()                            .endObject()                        .endObject()                        .startObject("address")                            .field("type","text")                            .startObject("fields")                                .startObject("keyword")                                    .field("type","keyword")                                .endObject()                            .endObject()                        .endObject()                        .startObject("remark")                            .field("type","text")                            .startObject("fields")                                .startObject("keyword")                                    .field("type","keyword")                                .endObject()                            .endObject()                        .endObject()                        .startObject("age")                            .field("type","integer")                        .endObject()                        .startObject("salary")                            .field("type","float")                        .endObject()                        .startObject("birthDate")                            .field("type","date")                            .field("format", "yyyy-MM-dd")                        .endObject()                        .startObject("createTime")                            .field("type","date")                        .endObject()                    .endObject()                .endObject();            // 创建索引配置信息，配置            Settings settings = Settings.builder()                    .put("index.number_of_shards", 1)                    .put("index.number_of_replicas", 0)                    .build();            // 新建创建索引请求对象，然后设置索引类型(ES 7.0 将不存在索引类型)和 mapping 与 index 配置            CreateIndexRequest request = new CreateIndexRequest("mydlq-user", settings);            request.mapping("doc", mapping);            // RestHighLevelClient 执行创建索引            CreateIndexResponse createIndexResponse = restHighLevelClient.indices().create(request, RequestOptions.DEFAULT);            // 判断是否创建成功            boolean isCreated = createIndexResponse.isAcknowledged();            log.info("是否创建成功：{}", isCreated);        } catch (IOException e) {            log.error("", e);        }    }    /**     * 删除索引     */    public void deleteIndex() {        try {            // 新建删除索引请求对象            DeleteIndexRequest request = new DeleteIndexRequest("mydlq-user");            // 执行删除索引            AcknowledgedResponse acknowledgedResponse = restHighLevelClient.indices().delete(request, RequestOptions.DEFAULT);            // 判断是否删除成功            boolean siDeleted = acknowledgedResponse.isAcknowledged();            log.info("是否删除成功：{}", siDeleted);        } catch (IOException e) {            log.error("", e);        }    }}

五、ElasticSearch操作示例

1、Restful 操作示例

增加文档信息

在索引 mydlq-user 中增加一条文档信息。

POST /mydlq-user/doc{    "address": "北京市",    "age": 29,    "birthDate": "1990-01-10",    "createTime": 1579530727699,    "name": "张三",    "remark": "来自北京市的张先生",    "salary": 100}

获取文档信息

获取 mydlq-user 的索引 id=1 的文档信息。

GET /mydlq-user/doc/1

更新文档信息

更新之前创建的 id=1 的文档信息。

PUT /mydlq-user/doc/1{    "address": "北京市海淀区",    "age": 29,    "birthDate": "1990-01-10",    "createTime": 1579530727699,    "name": "张三",    "remark": "来自北京市的张先生",    "salary": 100}

删除文档信息

删除之前创建的 id=1 的文档信息。

DELETE /mydlq-user/doc/1

2、Java 代码示例

import cloud.spiritmark.elasticsearch.model.entity.UserInfo;import com.alibaba.fastjson.JSON;import lombok.extern.slf4j.Slf4j;import org.elasticsearch.action.delete.DeleteRequest;import org.elasticsearch.action.delete.DeleteResponse;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.update.UpdateRequest;import org.elasticsearch.action.update.UpdateResponse;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.common.xcontent.XContentType;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import java.io.IOException;import java.util.Date;@Slf4j@Servicepublic class IndexService {    @Autowired    private RestHighLevelClient restHighLevelClient;    /**     * 增加文档信息     */    public void addDocument() {        try {            // 创建索引请求对象            IndexRequest indexRequest = new IndexRequest("mydlq-user", "doc", "1");            // 创建员工信息            UserInfo userInfo = new UserInfo();            userInfo.setName("张三");            userInfo.setAge(29);            userInfo.setSalary(100.00f);            userInfo.setAddress("北京市");            userInfo.setRemark("来自北京市的张先生");            userInfo.setCreateTime(new Date());            userInfo.setBirthDate("1990-01-10");            // 将对象转换为 byte 数组            byte[] json = JSON.toJSONBytes(userInfo);            // 设置文档内容            indexRequest.source(json, XContentType.JSON);            // 执行增加文档            IndexResponse response = restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);            log.info("创建状态：{}", response.status());        } catch (Exception e) {            log.error("", e);        }    }    /**     * 获取文档信息     */    public void getDocument() {        try {            // 获取请求对象            GetRequest getRequest = new GetRequest("mydlq-user", "doc", "1");            // 获取文档信息            GetResponse getResponse = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);            // 将 JSON 转换成对象            if (getResponse.isExists()) {                UserInfo userInfo = JSON.parseObject(getResponse.getSourceAsBytes(), UserInfo.class);                log.info("员工信息：{}", userInfo);            }        } catch (IOException e) {            log.error("", e);        }    }    /**     * 更新文档信息     */    public void updateDocument() {        try {            // 创建索引请求对象            UpdateRequest updateRequest = new UpdateRequest("mydlq-user", "doc", "1");            // 设置员工更新信息            UserInfo userInfo = new UserInfo();            userInfo.setSalary(200.00f);            userInfo.setAddress("北京市海淀区");            // 将对象转换为 byte 数组            byte[] json = JSON.toJSONBytes(userInfo);            // 设置更新文档内容            updateRequest.doc(json, XContentType.JSON);            // 执行更新文档            UpdateResponse response = restHighLevelClient.update(updateRequest, RequestOptions.DEFAULT);            log.info("创建状态：{}", response.status());        } catch (Exception e) {            log.error("", e);        }    }    /**     * 删除文档信息     */    public void deleteDocument() {        try {            // 创建删除请求对象            DeleteRequest deleteRequest = new DeleteRequest("mydlq-user", "doc", "1");            // 执行删除文档            DeleteResponse response = restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT);            log.info("删除状态：{}", response.status());        } catch (IOException e) {            log.error("", e);        }    }}

六、插入初始化数据

执行查询示例前，先往索引中插入一批数据：

1、单条插入

POST mydlq-user/_doc

{"name":"小白","address":"北京市海定区","remark":"低层员工","age":29,"salary":3000,"birthDate":"1990-11-11","createTime":"2019-11-11T08:18:00.000Z"}

2、批量插入

POST _bulk

{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"刘一","address":"北京市丰台区","remark":"低层员工","age":30,"salary":3000,"birthDate":"1989-11-11","createTime":"2019-03-15T08:18:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"陈二","address":"北京市昌平区","remark":"中层员工","age":27,"salary":7900,"birthDate":"1992-01-25","createTime":"2019-11-08T11:15:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"张三","address":"北京市房山区","remark":"中层员工","age":28,"salary":8800,"birthDate":"1991-10-05","createTime":"2019-07-22T13:22:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"李四","address":"北京市大兴区","remark":"高层员工","age":26,"salary":9000,"birthDate":"1993-08-18","createTime":"2019-10-17T15:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"王五","address":"北京市密云区","remark":"低层员工","age":31,"salary":4800,"birthDate":"1988-07-20","createTime":"2019-05-29T09:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"赵六","address":"北京市通州区","remark":"中层员工","age":32,"salary":6500,"birthDate":"1987-06-02","createTime":"2019-12-10T18:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"孙七","address":"北京市朝阳区","remark":"中层员工","age":33,"salary":7000,"birthDate":"1986-04-15","createTime":"2019-06-06T13:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"周八","address":"北京市西城区","remark":"低层员工","age":32,"salary":5000,"birthDate":"1987-09-26","createTime":"2019-01-26T14:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"吴九","address":"北京市海淀区","remark":"高层员工","age":30,"salary":11000,"birthDate":"1989-11-25","createTime":"2019-09-07T13:34:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"郑十","address":"北京市东城区","remark":"低层员工","age":29,"salary":5000,"birthDate":"1990-12-25","createTime":"2019-03-06T12:08:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"萧十一","address":"北京市平谷区","remark":"低层员工","age":29,"salary":3300,"birthDate":"1990-11-11","createTime":"2019-03-10T08:17:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"曹十二","address":"北京市怀柔区","remark":"中层员工","age":27,"salary":6800,"birthDate":"1992-01-25","createTime":"2019-12-03T11:09:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"吴十三","address":"北京市延庆区","remark":"中层员工","age":25,"salary":7000,"birthDate":"1994-10-05","createTime":"2019-07-27T14:22:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"冯十四","address":"北京市密云区","remark":"低层员工","age":25,"salary":3000,"birthDate":"1994-08-18","createTime":"2019-04-22T15:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"蒋十五","address":"北京市通州区","remark":"低层员工","age":31,"salary":2800,"birthDate":"1988-07-20","createTime":"2019-06-13T10:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"苗十六","address":"北京市门头沟区","remark":"高层员工","age":32,"salary":11500,"birthDate":"1987-06-02","createTime":"2019-11-11T18:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"鲁十七","address":"北京市石景山区","remark":"高员工","age":33,"salary":9500,"birthDate":"1986-04-15","createTime":"2019-06-06T14:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"沈十八","address":"北京市朝阳区","remark":"中层员工","age":31,"salary":8300,"birthDate":"1988-09-26","createTime":"2019-09-25T14:00:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"吕十九","address":"北京市西城区","remark":"低层员工","age":31,"salary":4500,"birthDate":"1988-11-25","createTime":"2019-09-22T13:34:00.000Z"}{"index":{"_index":"mydlq-user","_type":"doc"}}{"name":"丁二十","address":"北京市东城区","remark":"低层员工","age":33,"salary":2100,"birthDate":"1986-12-25","createTime":"2019-03-07T12:08:00.000Z"}

3、查询数据

插入完成后再查询数据，查看之前插入的数据是否存在：

GET mydlq-user/_search

执行后得到下面记录:

{  "took": 2,  "timed_out": false,  "_shards": {    "total": 1,    "successful": 1,    "skipped": 0,    "failed": 0  },  "hits": {    "total": 20,    "max_score": 1,    "hits": [      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "BeN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "刘一",          "address": "北京市丰台区",          "remark": "低层员工",          "age": 30,          "salary": 3000,          "birthDate": "1989-11-11",          "createTime": "2019-03-15T08:18:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "BuN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "陈二",          "address": "北京市昌平区",          "remark": "中层员工",          "age": 27,          "salary": 7900,          "birthDate": "1992-01-25",          "createTime": "2019-11-08T11:15:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "B-N0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "张三",          "address": "北京市房山区",          "remark": "中层员工",          "age": 28,          "salary": 8800,          "birthDate": "1991-10-05",          "createTime": "2019-07-22T13:22:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "CON0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "李四",          "address": "北京市大兴区",          "remark": "高层员工",          "age": 26,          "salary": 9000,          "birthDate": "1993-08-18",          "createTime": "2019-10-17T15:00:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "CeN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "王五",          "address": "北京市密云区",          "remark": "低层员工",          "age": 31,          "salary": 4800,          "birthDate": "1988-07-20",          "createTime": "2019-05-29T09:00:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "CuN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "赵六",          "address": "北京市通州区",          "remark": "中层员工",          "age": 32,          "salary": 6500,          "birthDate": "1987-06-02",          "createTime": "2019-12-10T18:00:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "C-N0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "孙七",          "address": "北京市朝阳区",          "remark": "中层员工",          "age": 33,          "salary": 7000,          "birthDate": "1986-04-15",          "createTime": "2019-06-06T13:00:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "DON0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "周八",          "address": "北京市西城区",          "remark": "低层员工",          "age": 32,          "salary": 5000,          "birthDate": "1987-09-26",          "createTime": "2019-01-26T14:00:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "DeN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "吴九",          "address": "北京市海淀区",          "remark": "高层员工",          "age": 30,          "salary": 11000,          "birthDate": "1989-11-25",          "createTime": "2019-09-07T13:34:00.000Z"        }      },      {        "_index": "mydlq-user",        "_type": "_doc",        "_id": "DuN0BW8B7BNodGwRFTRj",        "_score": 1,        "_source": {          "name": "郑十",          "address": "北京市东城区",          "remark": "低层员工",          "age": 29,          "salary": 5000,          "birthDate": "1990-12-25",          "createTime": "2019-03-06T12:08:00.000Z"        }      }    ]  }}

七、查询操作示例

1、精确查询(term)

(1)、Restful 操作示例

精确查询

精确查询，查询地址为 北京市通州区 的人员信息：

查询条件不会进行分词，但是查询内容可能会分词，导致查询不到。之前在创建索引时设置 Mapping 中 address 字段存在 keyword 字段是专门用于不分词查询的子字段。

GET mydlq-user/_search{  "query": {    "term": {      "address.keyword": {        "value": "北京市通州区"      }    }  }}

精确查询-多内容查询

精确查询，查询地址为 北京市丰台区、北京市昌平区 或 北京市大兴区 的人员信息：

GET mydlq-user/_search{  "query": {    "terms": {      "address.keyword": [        "北京市丰台区",        "北京市昌平区",        "北京市大兴区"      ]    }  }}

(2)、Java 代码示例

import cloud.spiritmark.elasticsearch.model.entity.UserInfo;import com.alibaba.fastjson.JSON;import lombok.extern.slf4j.Slf4j;import org.elasticsearch.action.search.SearchRequest;import org.elasticsearch.action.search.SearchResponse;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.index.query.QueryBuilders;import org.elasticsearch.rest.RestStatus;import org.elasticsearch.search.SearchHit;import org.elasticsearch.search.SearchHits;import org.elasticsearch.search.builder.SearchSourceBuilder;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import java.io.IOException;@Slf4j@Servicepublic class TermQueryService {    @Autowired    private RestHighLevelClient restHighLevelClient;    /**     * 精确查询(查询条件不会进行分词，但是查询内容可能会分词，导致查询不到)     */    public void termQuery() {        try {            // 构建查询条件(注意：termQuery 支持多种格式查询，如 boolean、int、double、string 等，这里使用的是 string 的查询)            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.termQuery("address.keyword", "北京市通州区"));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }    /**     * 多个内容在一个字段中进行查询     */    public void termsQuery() {        try {            // 构建查询条件(注意：termsQuery 支持多种格式查询，如 boolean、int、double、string 等，这里使用的是 string 的查询)            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.termsQuery("address.keyword", "北京市丰台区", "北京市昌平区", "北京市大兴区"));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }}

2、匹配查询(match)

(1)、Restful 操作示例

匹配查询全部数据与分页

匹配查询符合条件的所有数据，并且设置以 salary 字段升序排序，并设置分页：

GET mydlq-user/_search{  "query": {    "match_all": {}  },  "from": 0,  "size": 10,  "sort": [    {      "salary": {        "order": "asc"      }    }  ]}

匹配查询数据

匹配查询地址为 通州区 的数据：

GET mydlq-user/_search{  "query": {    "match": {      "address": "通州区"    }  }}

词语匹配查询

词语匹配进行查询，匹配 address 中为 北京市通州区 的员工信息：

GET mydlq-user/_search{  "query": {    "match_phrase": {      "address": "北京市通州区"    }  }}

内容多字段查询

查询在字段 address、remark 中存在 北京 内容的员工信息：

GET mydlq-user/_search{  "query": {    "multi_match": {      "query": "北京",      "fields": ["address","remark"]    }  }}

(2)、Java 代码示例

import cloud.spiritmark.elasticsearch.model.entity.UserInfo;import com.alibaba.fastjson.JSON;import lombok.extern.slf4j.Slf4j;import org.elasticsearch.action.search.SearchRequest;import org.elasticsearch.action.search.SearchResponse;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.index.query.MatchAllQueryBuilder;import org.elasticsearch.index.query.QueryBuilders;import org.elasticsearch.rest.RestStatus;import org.elasticsearch.search.SearchHit;import org.elasticsearch.search.SearchHits;import org.elasticsearch.search.builder.SearchSourceBuilder;import org.elasticsearch.search.sort.SortOrder;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import java.io.IOException;@Slf4j@Servicepublic class MatchQueryService {    @Autowired    private RestHighLevelClient restHighLevelClient;    /**     * 匹配查询符合条件的所有数据，并设置分页     */    public Object matchAllQuery() {        try {            // 构建查询条件            MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();            // 创建查询源构造器            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(matchAllQueryBuilder);            // 设置分页            searchSourceBuilder.from(0);            searchSourceBuilder.size(3);            // 设置排序            searchSourceBuilder.sort("salary", SortOrder.ASC);            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }    /**     * 匹配查询数据     */    public Object matchQuery() {        try {            // 构建查询条件            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.matchQuery("address", "*通州区"));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }    /**     * 词语匹配查询     */    public Object matchPhraseQuery() {        try {            // 构建查询条件            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.matchPhraseQuery("address", "北京市通州区"));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }    /**     * 内容在多字段中进行查询     */    public Object matchMultiQuery() {        try {            // 构建查询条件            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.multiMatchQuery("北京市", "address", "remark"));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }}

3、模糊查询(fuzzy)

(1)、Restful 操作示例

模糊查询所有以 三 结尾的姓名

GET mydlq-user/_search{  "query": {    "fuzzy": {      "name": "三"    }  }}

(2)、Java 代码示例

import cloud.spiritmark.elasticsearch.model.entity.UserInfo;import com.alibaba.fastjson.JSON;import lombok.extern.slf4j.Slf4j;import org.elasticsearch.action.search.SearchRequest;import org.elasticsearch.action.search.SearchResponse;import org.elasticsearch.client.RequestOptions;import org.elasticsearch.client.RestHighLevelClient;import org.elasticsearch.common.unit.Fuzziness;import org.elasticsearch.index.query.QueryBuilders;import org.elasticsearch.rest.RestStatus;import org.elasticsearch.search.SearchHit;import org.elasticsearch.search.SearchHits;import org.elasticsearch.search.builder.SearchSourceBuilder;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import java.io.IOException;@Slf4j@Servicepublic class FuzzyQueryService {    @Autowired    private RestHighLevelClient restHighLevelClient;    /**     * 模糊查询所有以 “三” 结尾的姓名     */    public Object fuzzyQuery() {        try {            // 构建查询条件            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();            searchSourceBuilder.query(QueryBuilders.fuzzyQuery("name", "三").fuzziness(Fuzziness.AUTO));            // 创建查询请求对象，将查询对象配置到其中            SearchRequest searchRequest = new SearchRequest("mydlq-user");            searchRequest.source(searchSourceBuilder);            // 执行查询，然后处理响应结果            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);            // 根据状态和数据条数验证是否返回了数据            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {                SearchHits hits = searchResponse.getHits();                for (SearchHit hit : hits) {                    // 将 JSON 转换成对象                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);                    // 输出查询信息                    log.info(userInfo.toString());                }            }        } catch (IOException e) {            log.error("", e);        }    }}