SpringBoot 操作 ElasticSearch 详解

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SpringBoot 操作 ElasticSearch 详解

超级小豆丁 SpringForAll社区 2021-05-26

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本文来源：http://www.mydlq.club/article/64/

一、ElasticSearch 简介

. 1、简介

. 2、特性

. 3、使用场景

. 二、ElasticSearch 基础概念

. 1、ElaticSearch 和 DB 的关系

. 2、索引

. 3、文档

. 4、映射

. 三、SpringBoot 项目引入 ElasticSearch 依赖

. 1、Maven 引入相关依赖

. 2、ElasticSearch 连接配置

. 四、索引操作示例

. 1、Restful 操作示例

. 2、Java 代码示例

. 五、文档操作示例

. 1、Restful 操作示例

. 2、Java 代码示例

. 六、插入初始化数据

. 1、单条插入

. 2、批量插入

. 3、查询数据

. 七、查询操作示例

. 1、精确查询(term)

. 2、匹配查询(match)

. 3、模糊查询(fuzzy)

. 4、范围查询(range)

. 5、通配符查询(wildcard)

. 6、布尔查询(bool)

. 八、聚合查询操作示例

. 1、Metric 聚合分析

. 2、Bucket 聚合分析

. 3、Metric 与 Bucket 聚合分析

参考地址：

百度百科
博文示例项目 Github 地址：https://github.com/my-dlq/blog-example/tree/master/springboot/springboot-elasticsearch-example

系统环境：

SpringBoot 版本：2.2.4
ElasticSearch 版本：6.5.3

一、ElasticSearch 简介

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员工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。

2、特性

分布式的文档存储引擎
分布式的搜索引擎和分析引擎
分布式，支持PB级数据

3、使用场景

搜索领域： 如百度、谷歌，全文检索等。
门户网站： 访问统计、文章点赞、留言评论等。
广告推广： 记录员工行为数据、消费趋势、员工群体进行定制推广等。
信息采集： 记录应用的埋点数据、访问日志数据等，方便大数据进行分析。

二、ElasticSearch 基础概念

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。

2、索引

索引基本概念（indices）：

索引是含义相同属性的文档集合，是 ElasticSearch 的一个逻辑存储，可以理解为关系型数据库中的数据库，ElasticSearch 可以把索引数据存放到一台服务器上，也可以 sharding 后存到多台服务器上，每个索引有一个或多个分片，每个分片可以有多个副本。

索引类型（index_type）：

索引可以定义一个或多个类型，文档必须属于一个类型。在 ElasticSearch 中，一个索引对象可以存储多个不同用途的对象，通过索引类型可以区分单个索引中的不同对象，可以理解为关系型数据库中的表。每个索引类型可以有不同的结构，但是不同的索引类型不能为相同的属性设置不同的类型。

3、文档

文档（document）：

文档是可以被索引的基本数据单位。存储在 ElasticSearch 中的主要实体叫文档 document，可以理解为关系型数据库中表的一行记录。每个文档由多个字段构成，ElasticSearch 是一个非结构化的数据库，每个文档可以有不同的字段，并且有一个唯一的标识符。

4、映射

映射（mapping）:

ElasticSearch 的 Mapping 非常类似于静态语言中的数据类型：声明一个变量为 int 类型的变量，以后这个变量都只能存储 int 类型的数据。同样的，一个 number 类型的 mapping 字段只能存储 number 类型的数据。

同语言的数据类型相比，Mapping 还有一些其他的含义，Mapping 不仅告诉 ElasticSearch 一个 Field 中是什么类型的值，它还告诉 ElasticSearch 如何索引数据以及数据是否能被搜索到。

ElaticSearch 默认是动态创建索引和索引类型的 Mapping 的。这就相当于无需定义 Solr 中的 Schema，无需指定各个字段的索引规则就可以索引文件，很方便。但有时方便就代表着不灵活。比如，ElasticSearch 默认一个字段是要做分词的，但我们有时要搜索匹配整个字段却不行。如有统计工作要记录每个城市出现的次数。对于 name 字段，若记录 new york 文本，ElasticSearch 可能会把它拆分成 new 和 york 这两个词，分别计算这个两个单词的次数，而不是我们期望的 new york。

三、SpringBoot 项目引入 ElasticSearch 依赖

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。

示例项目地址：https://github.com/my-dlq/blog-example/tree/master/springboot/springboot-elasticsearch-example

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。

 1<?xml version="1.0" encoding="UTF-8"?>
 2<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
 3         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
 4    <modelVersion>4.0.0</modelVersion>
 5    <parent>
 6        <groupId>org.springframework.boot</groupId>
 7        <artifactId>spring-boot-starter-parent</artifactId>
 8        <version>2.2.4.RELEASE</version>
 9        <relativePath/> <!-- lookup parent from repository -->
10    </parent>
11    <groupId>club.mydlq</groupId>
12    <artifactId>springboot-elasticsearch-example</artifactId>
13    <version>0.0.1-SNAPSHOT</version>
14    <name>springboot-elasticsearch-example</name>
15    <description>Demo project for Spring Boot ElasticSearch</description>
16
17    <properties>
18        <java.version>1.8</java.version>
19    </properties>
20    <dependencies>
21        <!--web-->
22        <dependency>
23            <groupId>org.springframework.boot</groupId>
24            <artifactId>spring-boot-starter-web</artifactId>
25        </dependency>
26        <!--lombok-->
27        <dependency>
28            <groupId>org.projectlombok</groupId>
29            <artifactId>lombok</artifactId>
30            <optional>true</optional>
31        </dependency>
32        <!--fastjson-->
33        <dependency>
34            <groupId>com.alibaba</groupId>
35            <artifactId>fastjson</artifactId>
36            <version>1.2.61</version>
37        </dependency>
38        <!--elasticsearch-->
39        <dependency>
40            <groupId>org.elasticsearch.client</groupId>
41            <artifactId>elasticsearch-rest-high-level-client</artifactId>
42            <version>6.5.4</version>
43        </dependency>
44        <dependency>
45            <groupId>org.elasticsearch</groupId>
46            <artifactId>elasticsearch</artifactId>
47            <version>6.5.4</version>
48        </dependency>
49    </dependencies>
50
51    <build>
52        <plugins>
53            <plugin>
54                <groupId>org.springframework.boot</groupId>
55                <artifactId>spring-boot-maven-plugin</artifactId>
56            </plugin>
57        </plugins>
58    </build>
59
60</project>

2、ElasticSearch 连接配置

(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：

 1#base
 2server:
 3  port: 8080
 4#spring
 5spring:
 6  application:
 7    name: springboot-elasticsearch-example
 8#elasticsearch
 9elasticsearch:
10  schema: http
11  address: 127.0.0.1:9200
12  connectTimeout: 5000
13  socketTimeout: 5000
14  connectionRequestTimeout: 5000
15  maxConnectNum: 100
16  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：

 1import org.apache.http.HttpHost;
 2import org.elasticsearch.client.RestClient;
 3import org.elasticsearch.client.RestClientBuilder;
 4import org.elasticsearch.client.RestHighLevelClient;
 5import org.springframework.beans.factory.annotation.Value;
 6import org.springframework.context.annotation.Bean;
 7import org.springframework.context.annotation.Configuration;
 8import java.util.ArrayList;
 9import java.util.List;
10
11/**
12 * ElasticSearch 配置
13 */
14@Configuration
15public class ElasticSearchConfig {
16
17    /** 协议 */
18    @Value("${elasticsearch.schema:http}")
19    private String schema;
20
21    /** 集群地址，如果有多个用“,”隔开 */
22    @Value("${elasticsearch.address}")
23    private String address;
24
25    /** 连接超时时间 */
26    @Value("${elasticsearch.connectTimeout:5000}")
27    private int connectTimeout;
28
29    /** Socket 连接超时时间 */
30    @Value("${elasticsearch.socketTimeout:10000}")
31    private int socketTimeout;
32
33    /** 获取连接的超时时间 */
34    @Value("${elasticsearch.connectionRequestTimeout:5000}")
35    private int connectionRequestTimeout;
36
37    /** 最大连接数 */
38    @Value("${elasticsearch.maxConnectNum:100}")
39    private int maxConnectNum;
40
41    /** 最大路由连接数 */
42    @Value("${elasticsearch.maxConnectPerRoute:100}")
43    private int maxConnectPerRoute;
44
45    @Bean
46    public RestHighLevelClient restHighLevelClient() {
47        // 拆分地址
48        List<HttpHost> hostLists = new ArrayList<>();
49        String[] hostList = address.split(",");
50        for (String addr : hostList) {
51            String host = addr.split(":")[0];
52            String port = addr.split(":")[1];
53            hostLists.add(new HttpHost(host, Integer.parseInt(port), schema));
54        }
55        // 转换成 HttpHost 数组
56        HttpHost[] httpHost = hostLists.toArray(new HttpHost[]{});
57        // 构建连接对象
58        RestClientBuilder builder = RestClient.builder(httpHost);
59        // 异步连接延时配置
60        builder.setRequestConfigCallback(requestConfigBuilder -> {
61            requestConfigBuilder.setConnectTimeout(connectTimeout);
62            requestConfigBuilder.setSocketTimeout(socketTimeout);
63            requestConfigBuilder.setConnectionRequestTimeout(connectionRequestTimeout);
64            return requestConfigBuilder;
65        });
66        // 异步连接数配置
67        builder.setHttpClientConfigCallback(httpClientBuilder -> {
68            httpClientBuilder.setMaxConnTotal(maxConnectNum);
69            httpClientBuilder.setMaxConnPerRoute(maxConnectPerRoute);
70            return httpClientBuilder;
71        });
72        return new RestHighLevelClient(builder);
73    }
74
75}

四、索引操作示例

这里示例会指出通过 Kibana 的 Restful 工具操作与对应的 Java 代码操作的两个示例。

1、Restful 操作示例

创建索引

创建名为 mydlq-user 的索引与对应 Mapping。

 1PUT /mydlq-user
 2{
 3  "mappings": {
 4    "doc": {
 5      "dynamic": true,
 6      "properties": {
 7        "name": {
 8          "type": "text",
 9          "fields": {
10            "keyword": {
11              "type": "keyword"
12            }
13          }
14        },
15        "address": {
16          "type": "text",
17          "fields": {
18            "keyword": {
19              "type": "keyword"
20            }
21          }
22        },
23        "remark": {
24          "type": "text",
25          "fields": {
26            "keyword": {
27              "type": "keyword"
28            }
29          }
30        },
31        "age": {
32          "type": "integer"
33        },
34        "salary": {
35          "type": "float"
36        },
37        "birthDate": {
38          "type": "date",
39          "format": "yyyy-MM-dd"
40        },
41        "createTime": {
42          "type": "date"
43        }
44      }
45    }
46  }
47}

删除索引

删除 mydlq-user 索引。

1DELETE /mydlq-user

2、Java 代码示例

  1import lombok.extern.slf4j.Slf4j;
  2import org.elasticsearch.action.admin.indices.create.CreateIndexRequest;
  3import org.elasticsearch.action.admin.indices.create.CreateIndexResponse;
  4import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
  5import org.elasticsearch.action.support.master.AcknowledgedResponse;
  6import org.elasticsearch.client.RequestOptions;
  7import org.elasticsearch.client.RestHighLevelClient;
  8import org.elasticsearch.common.settings.Settings;
  9import org.elasticsearch.common.xcontent.XContentBuilder;
 10import org.elasticsearch.common.xcontent.XContentFactory;
 11import org.springframework.beans.factory.annotation.Autowired;
 12import org.springframework.stereotype.Service;
 13import java.io.IOException;
 14
 15@Slf4j
 16@Service
 17public class IndexService2 {
 18
 19    @Autowired
 20    private RestHighLevelClient restHighLevelClient;
 21
 22    /**
 23     * 创建索引
 24     */
 25    public void createIndex() {
 26        try {
 27            // 创建 Mapping
 28            XContentBuilder mapping = XContentFactory.jsonBuilder()
 29                .startObject()
 30                    .field("dynamic", true)
 31                    .startObject("properties")
 32                        .startObject("name")
 33                            .field("type","text")
 34                            .startObject("fields")
 35                                .startObject("keyword")
 36                                    .field("type","keyword")
 37                                .endObject()
 38                            .endObject()
 39                        .endObject()
 40                        .startObject("address")
 41                            .field("type","text")
 42                            .startObject("fields")
 43                                .startObject("keyword")
 44                                    .field("type","keyword")
 45                                .endObject()
 46                            .endObject()
 47                        .endObject()
 48                        .startObject("remark")
 49                            .field("type","text")
 50                            .startObject("fields")
 51                                .startObject("keyword")
 52                                    .field("type","keyword")
 53                                .endObject()
 54                            .endObject()
 55                        .endObject()
 56                        .startObject("age")
 57                            .field("type","integer")
 58                        .endObject()
 59                        .startObject("salary")
 60                            .field("type","float")
 61                        .endObject()
 62                        .startObject("birthDate")
 63                            .field("type","date")
 64                            .field("format", "yyyy-MM-dd")
 65                        .endObject()
 66                        .startObject("createTime")
 67                            .field("type","date")
 68                        .endObject()
 69                    .endObject()
 70                .endObject();
 71            // 创建索引配置信息，配置
 72            Settings settings = Settings.builder()
 73                    .put("index.number_of_shards", 1)
 74                    .put("index.number_of_replicas", 0)
 75                    .build();
 76            // 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
 77            CreateIndexRequest request = new CreateIndexRequest("mydlq-user", settings);
 78            request.mapping("doc", mapping);
 79            // RestHighLevelClient 执行创建索引
 80            CreateIndexResponse createIndexResponse = restHighLevelClient.indices().create(request, RequestOptions.DEFAULT);
 81            // 判断是否创建成功
 82            boolean isCreated = createIndexResponse.isAcknowledged();
 83            log.info("是否创建成功：{}", isCreated);
 84        } catch (IOException e) {
 85            log.error("", e);
 86        }
 87    }
 88
 89    /**
 90     * 删除索引
 91     */
 92    public void deleteIndex() {
 93        try {
 94            // 新建删除索引请求对象
 95            DeleteIndexRequest request = new DeleteIndexRequest("mydlq-user");
 96            // 执行删除索引
 97            AcknowledgedResponse acknowledgedResponse = restHighLevelClient.indices().delete(request, RequestOptions.DEFAULT);
 98            // 判断是否删除成功
 99            boolean siDeleted = acknowledgedResponse.isAcknowledged();
100            log.info("是否删除成功：{}", siDeleted);
101        } catch (IOException e) {
102            log.error("", e);
103        }
104    }
105
106}

五、文档操作示例

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。

 1POST /mydlq-user/doc
 2{
 3    "address": "北京市",
 4    "age": 29,
 5    "birthDate": "1990-01-10",
 6    "createTime": 1579530727699,
 7    "name": "张三",
 8    "remark": "来自北京市的张先生",
 9    "salary": 100
10}

获取文档信息

获取 mydlq-user 的索引 id=1 的文档信息。

1GET /mydlq-user/doc/1

更新文档信息

更新之前创建的 id=1 的文档信息。

 1PUT /mydlq-user/doc/1
 2{
 3    "address": "北京市海淀区",
 4    "age": 29,
 5    "birthDate": "1990-01-10",
 6    "createTime": 1579530727699,
 7    "name": "张三",
 8    "remark": "来自北京市的张先生",
 9    "salary": 100
10}

删除文档信息

删除之前创建的 id=1 的文档信息。

1DELETE /mydlq-user/doc/1

2、Java 代码示例

  1import club.mydlq.elasticsearch.model.entity.UserInfo;
  2import com.alibaba.fastjson.JSON;
  3import lombok.extern.slf4j.Slf4j;
  4import org.elasticsearch.action.delete.DeleteRequest;
  5import org.elasticsearch.action.delete.DeleteResponse;
  6import org.elasticsearch.action.get.GetRequest;
  7import org.elasticsearch.action.get.GetResponse;
  8import org.elasticsearch.action.index.IndexRequest;
  9import org.elasticsearch.action.index.IndexResponse;
 10import org.elasticsearch.action.update.UpdateRequest;
 11import org.elasticsearch.action.update.UpdateResponse;
 12import org.elasticsearch.client.RequestOptions;
 13import org.elasticsearch.client.RestHighLevelClient;
 14import org.elasticsearch.common.xcontent.XContentType;
 15import org.springframework.beans.factory.annotation.Autowired;
 16import org.springframework.stereotype.Service;
 17import java.io.IOException;
 18import java.util.Date;
 19
 20@Slf4j
 21@Service
 22public class IndexService {
 23
 24    @Autowired
 25    private RestHighLevelClient restHighLevelClient;
 26
 27    /**
 28     * 增加文档信息
 29     */
 30    public void addDocument() {
 31        try {
 32            // 创建索引请求对象
 33            IndexRequest indexRequest = new IndexRequest("mydlq-user", "doc", "1");
 34            // 创建员工信息
 35            UserInfo userInfo = new UserInfo();
 36            userInfo.setName("张三");
 37            userInfo.setAge(29);
 38            userInfo.setSalary(100.00f);
 39            userInfo.setAddress("北京市");
 40            userInfo.setRemark("来自北京市的张先生");
 41            userInfo.setCreateTime(new Date());
 42            userInfo.setBirthDate("1990-01-10");
 43            // 将对象转换为 byte 数组
 44            byte[] json = JSON.toJSONBytes(userInfo);
 45            // 设置文档内容
 46            indexRequest.source(json, XContentType.JSON);
 47            // 执行增加文档
 48            IndexResponse response = restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
 49            log.info("创建状态：{}", response.status());
 50        } catch (Exception e) {
 51            log.error("", e);
 52        }
 53    }
 54
 55    /**
 56     * 获取文档信息
 57     */
 58    public void getDocument() {
 59        try {
 60            // 获取请求对象
 61            GetRequest getRequest = new GetRequest("mydlq-user", "doc", "1");
 62            // 获取文档信息
 63            GetResponse getResponse = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);
 64            // 将 JSON 转换成对象
 65            if (getResponse.isExists()) {
 66                UserInfo userInfo = JSON.parseObject(getResponse.getSourceAsBytes(), UserInfo.class);
 67                log.info("员工信息：{}", userInfo);
 68            }
 69        } catch (IOException e) {
 70            log.error("", e);
 71        }
 72    }
 73
 74    /**
 75     * 更新文档信息
 76     */
 77    public void updateDocument() {
 78        try {
 79            // 创建索引请求对象
 80            UpdateRequest updateRequest = new UpdateRequest("mydlq-user", "doc", "1");
 81            // 设置员工更新信息
 82            UserInfo userInfo = new UserInfo();
 83            userInfo.setSalary(200.00f);
 84            userInfo.setAddress("北京市海淀区");
 85            // 将对象转换为 byte 数组
 86            byte[] json = JSON.toJSONBytes(userInfo);
 87            // 设置更新文档内容
 88            updateRequest.doc(json, XContentType.JSON);
 89            // 执行更新文档
 90            UpdateResponse response = restHighLevelClient.update(updateRequest, RequestOptions.DEFAULT);
 91            log.info("创建状态：{}", response.status());
 92        } catch (Exception e) {
 93            log.error("", e);
 94        }
 95    }
 96
 97    /**
 98     * 删除文档信息
 99     */
100    public void deleteDocument() {
101        try {
102            // 创建删除请求对象
103            DeleteRequest deleteRequest = new DeleteRequest("mydlq-user", "doc", "1");
104            // 执行删除文档
105            DeleteResponse response = restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT);
106            log.info("删除状态：{}", response.status());
107        } catch (IOException e) {
108            log.error("", e);
109        }
110    }
111
112}

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

1{"name":"零零","address":"北京市丰台区","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

 1{"index":{"_index":"mydlq-user","_type":"doc"}}
 2{"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"}
 3{"index":{"_index":"mydlq-user","_type":"doc"}}
 4{"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"}
 5{"index":{"_index":"mydlq-user","_type":"doc"}}
 6{"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"}
 7{"index":{"_index":"mydlq-user","_type":"doc"}}
 8{"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"}
 9{"index":{"_index":"mydlq-user","_type":"doc"}}
10{"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"}
11{"index":{"_index":"mydlq-user","_type":"doc"}}
12{"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"}
13{"index":{"_index":"mydlq-user","_type":"doc"}}
14{"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"}
15{"index":{"_index":"mydlq-user","_type":"doc"}}
16{"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"}
17{"index":{"_index":"mydlq-user","_type":"doc"}}
18{"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"}
19{"index":{"_index":"mydlq-user","_type":"doc"}}
20{"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"}
21{"index":{"_index":"mydlq-user","_type":"doc"}}
22{"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"}
23{"index":{"_index":"mydlq-user","_type":"doc"}}
24{"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"}
25{"index":{"_index":"mydlq-user","_type":"doc"}}
26{"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"}
27{"index":{"_index":"mydlq-user","_type":"doc"}}
28{"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"}
29{"index":{"_index":"mydlq-user","_type":"doc"}}
30{"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"}
31{"index":{"_index":"mydlq-user","_type":"doc"}}
32{"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"}
33{"index":{"_index":"mydlq-user","_type":"doc"}}
34{"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"}
35{"index":{"_index":"mydlq-user","_type":"doc"}}
36{"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"}
37{"index":{"_index":"mydlq-user","_type":"doc"}}
38{"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"}
39{"index":{"_index":"mydlq-user","_type":"doc"}}
40{"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：

1GET mydlq-user/_search

执行后得到下面记录:

  1{
  2  "took": 2,
  3  "timed_out": false,
  4  "_shards": {
  5    "total": 1,
  6    "successful": 1,
  7    "skipped": 0,
  8    "failed": 0
  9  },
 10  "hits": {
 11    "total": 20,
 12    "max_score": 1,
 13    "hits": [
 14      {
 15        "_index": "mydlq-user",
 16        "_type": "_doc",
 17        "_id": "BeN0BW8B7BNodGwRFTRj",
 18        "_score": 1,
 19        "_source": {
 20          "name": "刘一",
 21          "address": "北京市丰台区",
 22          "remark": "低层员工",
 23          "age": 30,
 24          "salary": 3000,
 25          "birthDate": "1989-11-11",
 26          "createTime": "2019-03-15T08:18:00.000Z"
 27        }
 28      },
 29      {
 30        "_index": "mydlq-user",
 31        "_type": "_doc",
 32        "_id": "BuN0BW8B7BNodGwRFTRj",
 33        "_score": 1,
 34        "_source": {
 35          "name": "陈二",
 36          "address": "北京市昌平区",
 37          "remark": "中层员工",
 38          "age": 27,
 39          "salary": 7900,
 40          "birthDate": "1992-01-25",
 41          "createTime": "2019-11-08T11:15:00.000Z"
 42        }
 43      },
 44      {
 45        "_index": "mydlq-user",
 46        "_type": "_doc",
 47        "_id": "B-N0BW8B7BNodGwRFTRj",
 48        "_score": 1,
 49        "_source": {
 50          "name": "张三",
 51          "address": "北京市房山区",
 52          "remark": "中层员工",
 53          "age": 28,
 54          "salary": 8800,
 55          "birthDate": "1991-10-05",
 56          "createTime": "2019-07-22T13:22:00.000Z"
 57        }
 58      },
 59      {
 60        "_index": "mydlq-user",
 61        "_type": "_doc",
 62        "_id": "CON0BW8B7BNodGwRFTRj",
 63        "_score": 1,
 64        "_source": {
 65          "name": "李四",
 66          "address": "北京市大兴区",
 67          "remark": "高层员工",
 68          "age": 26,
 69          "salary": 9000,
 70          "birthDate": "1993-08-18",
 71          "createTime": "2019-10-17T15:00:00.000Z"
 72        }
 73      },
 74      {
 75        "_index": "mydlq-user",
 76        "_type": "_doc",
 77        "_id": "CeN0BW8B7BNodGwRFTRj",
 78        "_score": 1,
 79        "_source": {
 80          "name": "王五",
 81          "address": "北京市密云区",
 82          "remark": "低层员工",
 83          "age": 31,
 84          "salary": 4800,
 85          "birthDate": "1988-07-20",
 86          "createTime": "2019-05-29T09:00:00.000Z"
 87        }
 88      },
 89      {
 90        "_index": "mydlq-user",
 91        "_type": "_doc",
 92        "_id": "CuN0BW8B7BNodGwRFTRj",
 93        "_score": 1,
 94        "_source": {
 95          "name": "赵六",
 96          "address": "北京市通州区",
 97          "remark": "中层员工",
 98          "age": 32,
 99          "salary": 6500,
100          "birthDate": "1987-06-02",
101          "createTime": "2019-12-10T18:00:00.000Z"
102        }
103      },
104      {
105        "_index": "mydlq-user",
106        "_type": "_doc",
107        "_id": "C-N0BW8B7BNodGwRFTRj",
108        "_score": 1,
109        "_source": {
110          "name": "孙七",
111          "address": "北京市朝阳区",
112          "remark": "中层员工",
113          "age": 33,
114          "salary": 7000,
115          "birthDate": "1986-04-15",
116          "createTime": "2019-06-06T13:00:00.000Z"
117        }
118      },
119      {
120        "_index": "mydlq-user",
121        "_type": "_doc",
122        "_id": "DON0BW8B7BNodGwRFTRj",
123        "_score": 1,
124        "_source": {
125          "name": "周八",
126          "address": "北京市西城区",
127          "remark": "低层员工",
128          "age": 32,
129          "salary": 5000,
130          "birthDate": "1987-09-26",
131          "createTime": "2019-01-26T14:00:00.000Z"
132        }
133      },
134      {
135        "_index": "mydlq-user",
136        "_type": "_doc",
137        "_id": "DeN0BW8B7BNodGwRFTRj",
138        "_score": 1,
139        "_source": {
140          "name": "吴九",
141          "address": "北京市海淀区",
142          "remark": "高层员工",
143          "age": 30,
144          "salary": 11000,
145          "birthDate": "1989-11-25",
146          "createTime": "2019-09-07T13:34:00.000Z"
147        }
148      },
149      {
150        "_index": "mydlq-user",
151        "_type": "_doc",
152        "_id": "DuN0BW8B7BNodGwRFTRj",
153        "_score": 1,
154        "_source": {
155          "name": "郑十",
156          "address": "北京市东城区",
157          "remark": "低层员工",
158          "age": 29,
159          "salary": 5000,
160          "birthDate": "1990-12-25",
161          "createTime": "2019-03-06T12:08:00.000Z"
162        }
163      }
164    ]
165  }
166}

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。

 1GET mydlq-user/_search
 2{
 3  "query": {
 4    "term": {
 5      "address.keyword": {
 6        "value": "北京市通州区"
 7      }
 8    }
 9  }
10}

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：

 1GET mydlq-user/_search
 2{
 3  "query": {
 4    "terms": {
 5      "address.keyword": [
 6        "北京市丰台区",
 7        "北京市昌平区",
 8        "北京市大兴区"
 9      ]
10    }
11  }
12}

(2)、Java 代码示例

 1import club.mydlq.elasticsearch.model.entity.UserInfo;
 2import com.alibaba.fastjson.JSON;
 3import lombok.extern.slf4j.Slf4j;
 4import org.elasticsearch.action.search.SearchRequest;
 5import org.elasticsearch.action.search.SearchResponse;
 6import org.elasticsearch.client.RequestOptions;
 7import org.elasticsearch.client.RestHighLevelClient;
 8import org.elasticsearch.index.query.QueryBuilders;
 9import org.elasticsearch.rest.RestStatus;
10import org.elasticsearch.search.SearchHit;
11import org.elasticsearch.search.SearchHits;
12import org.elasticsearch.search.builder.SearchSourceBuilder;
13import org.springframework.beans.factory.annotation.Autowired;
14import org.springframework.stereotype.Service;
15import java.io.IOException;
16
17@Slf4j
18@Service
19public class TermQueryService {
20
21    @Autowired
22    private RestHighLevelClient restHighLevelClient;
23
24    /**
25     * 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）
26     */
27    public void termQuery() {
28        try {
29            // 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）
30            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
31            searchSourceBuilder.query(QueryBuilders.termQuery("address.keyword", "北京市通州区"));
32            // 创建查询请求对象，将查询对象配置到其中
33            SearchRequest searchRequest = new SearchRequest("mydlq-user");
34            searchRequest.source(searchSourceBuilder);
35            // 执行查询，然后处理响应结果
36            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
37            // 根据状态和数据条数验证是否返回了数据
38            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
39                SearchHits hits = searchResponse.getHits();
40                for (SearchHit hit : hits) {
41                    // 将 JSON 转换成对象
42                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
43                    // 输出查询信息
44                    log.info(userInfo.toString());
45                }
46            }
47        } catch (IOException e) {
48            log.error("", e);
49        }
50    }
51
52    /**
53     * 多个内容在一个字段中进行查询
54     */
55    public void termsQuery() {
56        try {
57            // 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）
58            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
59            searchSourceBuilder.query(QueryBuilders.termsQuery("address.keyword", "北京市丰台区", "北京市昌平区", "北京市大兴区"));
60            // 创建查询请求对象，将查询对象配置到其中
61            SearchRequest searchRequest = new SearchRequest("mydlq-user");
62            searchRequest.source(searchSourceBuilder);
63            // 执行查询，然后处理响应结果
64            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
65            // 根据状态和数据条数验证是否返回了数据
66            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
67                SearchHits hits = searchResponse.getHits();
68                for (SearchHit hit : hits) {
69                    // 将 JSON 转换成对象
70                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
71                    // 输出查询信息
72                    log.info(userInfo.toString());
73                }
74            }
75        } catch (IOException e) {
76            log.error("", e);
77        }
78    }
79
80}

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：

 1GET mydlq-user/_search
 2{
 3  "query": {
 4    "match_all": {}
 5  },
 6  "from": 0,
 7  "size": 10,
 8  "sort": [
 9    {
10      "salary": {
11        "order": "asc"
12      }
13    }
14  ]
15}

匹配查询数据

匹配查询地址为 通州区 的数据：

1GET mydlq-user/_search
2{
3  "query": {
4    "match": {
5      "address": "通州区"
6    }
7  }
8}

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：

1GET mydlq-user/_search
2{
3  "query": {
4    "match_phrase": {
5      "address": "北京市通州区"
6    }
7  }
8}

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：

1GET mydlq-user/_search
2{
3  "query": {
4    "multi_match": {
5      "query": "北京",
6      "fields": ["address","remark"]
7    }
8  }
9}

(2)、Java 代码示例

  1import club.mydlq.elasticsearch.model.entity.UserInfo;
  2import com.alibaba.fastjson.JSON;
  3import lombok.extern.slf4j.Slf4j;
  4import org.elasticsearch.action.search.SearchRequest;
  5import org.elasticsearch.action.search.SearchResponse;
  6import org.elasticsearch.client.RequestOptions;
  7import org.elasticsearch.client.RestHighLevelClient;
  8import org.elasticsearch.index.query.MatchAllQueryBuilder;
  9import org.elasticsearch.index.query.QueryBuilders;
 10import org.elasticsearch.rest.RestStatus;
 11import org.elasticsearch.search.SearchHit;
 12import org.elasticsearch.search.SearchHits;
 13import org.elasticsearch.search.builder.SearchSourceBuilder;
 14import org.elasticsearch.search.sort.SortOrder;
 15import org.springframework.beans.factory.annotation.Autowired;
 16import org.springframework.stereotype.Service;
 17import java.io.IOException;
 18
 19@Slf4j
 20@Service
 21public class MatchQueryService {
 22
 23    @Autowired
 24    private RestHighLevelClient restHighLevelClient;
 25
 26    /**
 27     * 匹配查询符合条件的所有数据，并设置分页
 28     */
 29    public Object matchAllQuery() {
 30        try {
 31            // 构建查询条件
 32            MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
 33            // 创建查询源构造器
 34            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 35            searchSourceBuilder.query(matchAllQueryBuilder);
 36            // 设置分页
 37            searchSourceBuilder.from(0);
 38            searchSourceBuilder.size(3);
 39            // 设置排序
 40            searchSourceBuilder.sort("salary", SortOrder.ASC);
 41            // 创建查询请求对象，将查询对象配置到其中
 42            SearchRequest searchRequest = new SearchRequest("mydlq-user");
 43            searchRequest.source(searchSourceBuilder);
 44            // 执行查询，然后处理响应结果
 45            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
 46            // 根据状态和数据条数验证是否返回了数据
 47            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
 48                SearchHits hits = searchResponse.getHits();
 49                for (SearchHit hit : hits) {
 50                    // 将 JSON 转换成对象
 51                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
 52                    // 输出查询信息
 53                    log.info(userInfo.toString());
 54                }
 55            }
 56        } catch (IOException e) {
 57            log.error("", e);
 58        }
 59    }
 60
 61    /**
 62     * 匹配查询数据
 63     */
 64    public Object matchQuery() {
 65        try {
 66            // 构建查询条件
 67            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 68            searchSourceBuilder.query(QueryBuilders.matchQuery("address", "*通州区"));
 69            // 创建查询请求对象，将查询对象配置到其中
 70            SearchRequest searchRequest = new SearchRequest("mydlq-user");
 71            searchRequest.source(searchSourceBuilder);
 72            // 执行查询，然后处理响应结果
 73            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
 74            // 根据状态和数据条数验证是否返回了数据
 75            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
 76                SearchHits hits = searchResponse.getHits();
 77                for (SearchHit hit : hits) {
 78                    // 将 JSON 转换成对象
 79                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
 80                    // 输出查询信息
 81                    log.info(userInfo.toString());
 82                }
 83            }
 84        } catch (IOException e) {
 85            log.error("", e);
 86        }
 87    }
 88
 89    /**
 90     * 词语匹配查询
 91     */
 92    public Object matchPhraseQuery() {
 93        try {
 94            // 构建查询条件
 95            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 96            searchSourceBuilder.query(QueryBuilders.matchPhraseQuery("address", "北京市通州区"));
 97            // 创建查询请求对象，将查询对象配置到其中
 98            SearchRequest searchRequest = new SearchRequest("mydlq-user");
 99            searchRequest.source(searchSourceBuilder);
100            // 执行查询，然后处理响应结果
101            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
102            // 根据状态和数据条数验证是否返回了数据
103            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
104                SearchHits hits = searchResponse.getHits();
105                for (SearchHit hit : hits) {
106                    // 将 JSON 转换成对象
107                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
108                    // 输出查询信息
109                    log.info(userInfo.toString());
110                }
111            }
112        } catch (IOException e) {
113            log.error("", e);
114        }
115    }
116
117    /**
118     * 内容在多字段中进行查询
119     */
120    public Object matchMultiQuery() {
121        try {
122            // 构建查询条件
123            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
124            searchSourceBuilder.query(QueryBuilders.multiMatchQuery("北京市", "address", "remark"));
125            // 创建查询请求对象，将查询对象配置到其中
126            SearchRequest searchRequest = new SearchRequest("mydlq-user");
127            searchRequest.source(searchSourceBuilder);
128            // 执行查询，然后处理响应结果
129            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
130            // 根据状态和数据条数验证是否返回了数据
131            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
132                SearchHits hits = searchResponse.getHits();
133                for (SearchHit hit : hits) {
134                    // 将 JSON 转换成对象
135                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
136                    // 输出查询信息
137                    log.info(userInfo.toString());
138                }
139            }
140        } catch (IOException e) {
141            log.error("", e);
142        }
143    }
144
145}

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

1GET mydlq-user/_search
2{
3  "query": {
4    "fuzzy": {
5      "name": "三"
6    }
7  }
8}

(2)、Java 代码示例

 1import club.mydlq.elasticsearch.model.entity.UserInfo;
 2import com.alibaba.fastjson.JSON;
 3import lombok.extern.slf4j.Slf4j;
 4import org.elasticsearch.action.search.SearchRequest;
 5import org.elasticsearch.action.search.SearchResponse;
 6import org.elasticsearch.client.RequestOptions;
 7import org.elasticsearch.client.RestHighLevelClient;
 8import org.elasticsearch.common.unit.Fuzziness;
 9import org.elasticsearch.index.query.QueryBuilders;
10import org.elasticsearch.rest.RestStatus;
11import org.elasticsearch.search.SearchHit;
12import org.elasticsearch.search.SearchHits;
13import org.elasticsearch.search.builder.SearchSourceBuilder;
14import org.springframework.beans.factory.annotation.Autowired;
15import org.springframework.stereotype.Service;
16import java.io.IOException;
17
18@Slf4j
19@Service
20public class FuzzyQueryService {
21
22    @Autowired
23    private RestHighLevelClient restHighLevelClient;
24
25    /**
26     * 模糊查询所有以 “三” 结尾的姓名
27     */
28    public Object fuzzyQuery() {
29        try {
30            // 构建查询条件
31            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
32            searchSourceBuilder.query(QueryBuilders.fuzzyQuery("name", "三").fuzziness(Fuzziness.AUTO));
33            // 创建查询请求对象，将查询对象配置到其中
34            SearchRequest searchRequest = new SearchRequest("mydlq-user");
35            searchRequest.source(searchSourceBuilder);
36            // 执行查询，然后处理响应结果
37            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
38            // 根据状态和数据条数验证是否返回了数据
39            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
40                SearchHits hits = searchResponse.getHits();
41                for (SearchHit hit : hits) {
42                    // 将 JSON 转换成对象
43                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
44                    // 输出查询信息
45                    log.info(userInfo.toString());
46                }
47            }
48        } catch (IOException e) {
49            log.error("", e);
50        }
51    }
52
53}

4、范围查询(range)

(1)、Restful 操作示例

查询岁数 ≥ 30 岁的员工数据：

 1GET /mydlq-user/_search
 2{
 3  "query": {
 4    "range": {
 5      "age": {
 6        "gte": 30
 7      }
 8    }
 9  }
10}

查询生日距离现在 30 年间的员工数据：

 1GET mydlq-user/_search
 2{
 3  "query": {
 4    "range": {
 5      "birthDate": {
 6        "gte": "now-30y"
 7      }
 8    }
 9  }
10}

(2)、Java 代码示例

 1import club.mydlq.elasticsearch.model.entity.UserInfo;
 2import com.alibaba.fastjson.JSON;
 3import lombok.extern.slf4j.Slf4j;
 4import org.elasticsearch.action.search.SearchRequest;
 5import org.elasticsearch.action.search.SearchResponse;
 6import org.elasticsearch.client.RequestOptions;
 7import org.elasticsearch.client.RestHighLevelClient;
 8import org.elasticsearch.index.query.QueryBuilders;
 9import org.elasticsearch.rest.RestStatus;
10import org.elasticsearch.search.SearchHit;
11import org.elasticsearch.search.SearchHits;
12import org.elasticsearch.search.builder.SearchSourceBuilder;
13import org.springframework.beans.factory.annotation.Autowired;
14import org.springframework.stereotype.Service;
15import java.io.IOException;
16
17@Slf4j
18@Service
19public class RangeQueryService {
20
21    @Autowired
22    private RestHighLevelClient restHighLevelClient;
23
24    /**
25     * 查询岁数 ≥ 30 岁的员工数据
26     */
27    public void rangeQuery() {
28        try {
29            // 构建查询条件
30            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
31            searchSourceBuilder.query(QueryBuilders.rangeQuery("age").gte(30));
32            // 创建查询请求对象，将查询对象配置到其中
33            SearchRequest searchRequest = new SearchRequest("mydlq-user");
34            searchRequest.source(searchSourceBuilder);
35            // 执行查询，然后处理响应结果
36            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
37            // 根据状态和数据条数验证是否返回了数据
38            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
39                SearchHits hits = searchResponse.getHits();
40                for (SearchHit hit : hits) {
41                    // 将 JSON 转换成对象
42                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
43                    // 输出查询信息
44                    log.info(userInfo.toString());
45                }
46            }
47        } catch (IOException e) {
48            log.error("", e);
49        }
50    }
51
52    /**
53     * 查询距离现在 30 年间的员工数据
54     * [年(y)、月(M)、星期(w)、天(d)、小时(h)、分钟(m)、秒(s)]
55     * 例如：
56     * now-1h 查询一小时内范围
57     * now-1d 查询一天内时间范围
58     * now-1y 查询最近一年内的时间范围
59     */
60    public void dateRangeQuery() {
61        try {
62            // 构建查询条件
63            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
64            // includeLower（是否包含下边界）、includeUpper（是否包含上边界）
65            searchSourceBuilder.query(QueryBuilders.rangeQuery("birthDate")
66                    .gte("now-30y").includeLower(true).includeUpper(true));
67            // 创建查询请求对象，将查询对象配置到其中
68            SearchRequest searchRequest = new SearchRequest("mydlq-user");
69            searchRequest.source(searchSourceBuilder);
70            // 执行查询，然后处理响应结果
71            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
72            // 根据状态和数据条数验证是否返回了数据
73            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
74                SearchHits hits = searchResponse.getHits();
75                for (SearchHit hit : hits) {
76                    // 将 JSON 转换成对象
77                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
78                    // 输出查询信息
79                    log.info(userInfo.toString());
80                }
81            }
82        } catch (IOException e) {
83            log.error("", e);
84        }
85    }
86
87}

5、通配符查询(wildcard)

(1)、Restful 操作示例

查询所有以 “三” 结尾的姓名：

 1GET mydlq-user/_search
 2{
 3  "query": {
 4    "wildcard": {
 5      "name.keyword": {
 6        "value": "*三"
 7      }
 8    }
 9  }
10}

(2)、Java 代码示例

 1import club.mydlq.elasticsearch.model.entity.UserInfo;
 2import com.alibaba.fastjson.JSON;
 3import lombok.extern.slf4j.Slf4j;
 4import org.elasticsearch.action.search.SearchRequest;
 5import org.elasticsearch.action.search.SearchResponse;
 6import org.elasticsearch.client.RequestOptions;
 7import org.elasticsearch.client.RestHighLevelClient;
 8import org.elasticsearch.index.query.QueryBuilders;
 9import org.elasticsearch.rest.RestStatus;
10import org.elasticsearch.search.SearchHit;
11import org.elasticsearch.search.SearchHits;
12import org.elasticsearch.search.builder.SearchSourceBuilder;
13import org.springframework.beans.factory.annotation.Autowired;
14import org.springframework.stereotype.Service;
15import java.io.IOException;
16
17@Slf4j
18@Service
19public class WildcardQueryService {
20
21    @Autowired
22    private RestHighLevelClient restHighLevelClient;
23
24    /**
25     * 查询所有以 “三” 结尾的姓名
26     *
27     * *：表示多个字符（0个或多个字符）
28     * ?：表示单个字符
29     */
30    public Object wildcardQuery() {
31        try {
32            // 构建查询条件
33            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
34            searchSourceBuilder.query(QueryBuilders.wildcardQuery("name.keyword", "*三"));
35            // 创建查询请求对象，将查询对象配置到其中
36            SearchRequest searchRequest = new SearchRequest("mydlq-user");
37            searchRequest.source(searchSourceBuilder);
38            // 执行查询，然后处理响应结果
39            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
40            // 根据状态和数据条数验证是否返回了数据
41            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
42                SearchHits hits = searchResponse.getHits();
43                for (SearchHit hit : hits) {
44                    // 将 JSON 转换成对象
45                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
46                    // 输出查询信息
47                    log.info(userInfo.toString());
48                }
49            }
50        } catch (IOException e) {
51            log.error("", e);
52        }
53    }
54
55}

6、布尔查询(bool)

(1)、Restful 操作示例

查询出生在 1990-1995 年期间，且地址在 北京市昌平区、北京市大兴区、北京市房山区 的员工信息：

 1GET /mydlq-user/_search
 2{
 3  "query": {
 4    "bool": {
 5      "filter": {
 6        "range": {
 7          "birthDate": {
 8            "format": "yyyy", 
 9            "gte": 1990,
10            "lte": 1995
11          }
12        }
13      },
14      "must": [
15        {
16          "terms": {
17            "address.keyword": [
18              "北京市昌平区",
19              "北京市大兴区",
20              "北京市房山区"
21            ]
22          }
23        }
24      ]
25    }
26  }
27}

(2)、Java 代码示例

 1import club.mydlq.elasticsearch.model.entity.UserInfo;
 2import com.alibaba.fastjson.JSON;
 3import lombok.extern.slf4j.Slf4j;
 4import org.elasticsearch.action.search.SearchRequest;
 5import org.elasticsearch.action.search.SearchResponse;
 6import org.elasticsearch.client.RequestOptions;
 7import org.elasticsearch.client.RestHighLevelClient;
 8import org.elasticsearch.index.query.BoolQueryBuilder;
 9import org.elasticsearch.index.query.QueryBuilders;
10import org.elasticsearch.rest.RestStatus;
11import org.elasticsearch.search.SearchHit;
12import org.elasticsearch.search.SearchHits;
13import org.elasticsearch.search.builder.SearchSourceBuilder;
14import org.springframework.beans.factory.annotation.Autowired;
15import org.springframework.stereotype.Service;
16import java.io.IOException;
17
18@Slf4j
19@Service
20public class BoolQueryService {
21
22    @Autowired
23    private RestHighLevelClient restHighLevelClient;
24
25    public Object boolQuery() {
26        try {
27            // 创建 Bool 查询构建器
28            BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
29            // 构建查询条件
30            boolQueryBuilder.must(QueryBuilders.termsQuery("address.keyword", "北京市昌平区", "北京市大兴区", "北京市房山区"))
31                    .filter().add(QueryBuilders.rangeQuery("birthDate").format("yyyy").gte("1990").lte("1995"));
32            // 构建查询源构建器
33            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
34            searchSourceBuilder.query(boolQueryBuilder);
35            // 创建查询请求对象，将查询对象配置到其中
36            SearchRequest searchRequest = new SearchRequest("mydlq-user");
37            searchRequest.source(searchSourceBuilder);
38            // 执行查询，然后处理响应结果
39            SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
40            // 根据状态和数据条数验证是否返回了数据
41            if (RestStatus.OK.equals(searchResponse.status()) && searchResponse.getHits().totalHits > 0) {
42                SearchHits hits = searchResponse.getHits();
43                for (SearchHit hit : hits) {
44                    // 将 JSON 转换成对象
45                    UserInfo userInfo = JSON.parseObject(hit.getSourceAsString(), UserInfo.class);
46                    // 输出查询信息
47                    log.info(userInfo.toString());
48                }
49            }
50        }catch (IOException e){
51            log.error("",e);
52        }
53    }
54
55}

八、聚合查询操作示例

1、Metric 聚合分析

(1)、Restful 操作示例

统计员工总数、工资最高值、工资最低值、工资平均工资、工资总和：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_stats": {
 6      "stats": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工工资最低值：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_min": {
 6      "min": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工工资最高值：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_max": {
 6      "max": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工工资平均值：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_avg": {
 6      "avg": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工工资总值：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_sum": {
 6      "sum": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工总数：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "employee_count": {
 6      "value_count": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

统计员工工资百分位：

 1GET /mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_percentiles": {
 6      "percentiles": {
 7        "field": "salary"
 8      }
 9    }
10  }
11}

(2)、Java 代码示例

  1import lombok.extern.slf4j.Slf4j;
  2import org.elasticsearch.action.search.SearchRequest;
  3import org.elasticsearch.action.search.SearchResponse;
  4import org.elasticsearch.client.RequestOptions;
  5import org.elasticsearch.client.RestHighLevelClient;
  6import org.elasticsearch.rest.RestStatus;
  7import org.elasticsearch.search.aggregations.AggregationBuilder;
  8import org.elasticsearch.search.aggregations.AggregationBuilders;
  9import org.elasticsearch.search.aggregations.Aggregations;
 10import org.elasticsearch.search.aggregations.metrics.avg.ParsedAvg;
 11import org.elasticsearch.search.aggregations.metrics.max.ParsedMax;
 12import org.elasticsearch.search.aggregations.metrics.min.ParsedMin;
 13import org.elasticsearch.search.aggregations.metrics.percentiles.ParsedPercentiles;
 14import org.elasticsearch.search.aggregations.metrics.percentiles.Percentile;
 15import org.elasticsearch.search.aggregations.metrics.stats.ParsedStats;
 16import org.elasticsearch.search.aggregations.metrics.sum.ParsedSum;
 17import org.elasticsearch.search.aggregations.metrics.sum.SumAggregationBuilder;
 18import org.elasticsearch.search.aggregations.metrics.valuecount.ParsedValueCount;
 19import org.elasticsearch.search.builder.SearchSourceBuilder;
 20import org.springframework.beans.factory.annotation.Autowired;
 21import org.springframework.stereotype.Service;
 22import java.io.IOException;
 23
 24@Slf4j
 25@Service
 26public class AggrMetricService {
 27
 28    @Autowired
 29    private RestHighLevelClient restHighLevelClient;
 30
 31    /**
 32     * stats 统计员工总数、员工工资最高值、员工工资最低值、员工平均工资、员工工资总和
 33     */
 34    public Object aggregationStats() {
 35        String responseResult = "";
 36        try {
 37            // 设置聚合条件
 38            AggregationBuilder aggr = AggregationBuilders.stats("salary_stats").field("salary");
 39            // 查询源构建器
 40            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 41            searchSourceBuilder.aggregation(aggr);
 42            // 设置查询结果不返回，只返回聚合结果
 43            searchSourceBuilder.size(0);
 44            // 创建查询请求对象，将查询条件配置到其中
 45            SearchRequest request = new SearchRequest("mydlq-user");
 46            request.source(searchSourceBuilder);
 47            // 执行请求
 48            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
 49            // 获取响应中的聚合信息
 50            Aggregations aggregations = response.getAggregations();
 51            // 输出内容
 52            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
 53                // 转换为 Stats 对象
 54                ParsedStats aggregation = aggregations.get("salary_stats");
 55                log.info("-------------------------------------------");
 56                log.info("聚合信息:");
 57                log.info("count：{}", aggregation.getCount());
 58                log.info("avg：{}", aggregation.getAvg());
 59                log.info("max：{}", aggregation.getMax());
 60                log.info("min：{}", aggregation.getMin());
 61                log.info("sum：{}", aggregation.getSum());
 62                log.info("-------------------------------------------");
 63            }
 64            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
 65            responseResult = response.toString();
 66        } catch (IOException e) {
 67            log.error("", e);
 68        }
 69        return responseResult;
 70    }
 71
 72    /**
 73     * min 统计员工工资最低值
 74     */
 75    public Object aggregationMin() {
 76        String responseResult = "";
 77        try {
 78            // 设置聚合条件
 79            AggregationBuilder aggr = AggregationBuilders.min("salary_min").field("salary");
 80            // 查询源构建器
 81            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 82            searchSourceBuilder.aggregation(aggr);
 83            searchSourceBuilder.size(0);
 84            // 创建查询请求对象，将查询条件配置到其中
 85            SearchRequest request = new SearchRequest("mydlq-user");
 86            request.source(searchSourceBuilder);
 87            // 执行请求
 88            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
 89            // 获取响应中的聚合信息
 90            Aggregations aggregations = response.getAggregations();
 91            // 输出内容
 92            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
 93                // 转换为 Min 对象
 94                ParsedMin aggregation = aggregations.get("salary_min");
 95                log.info("-------------------------------------------");
 96                log.info("聚合信息:");
 97                log.info("min：{}", aggregation.getValue());
 98                log.info("-------------------------------------------");
 99            }
100            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
101            responseResult = response.toString();
102        } catch (IOException e) {
103            log.error("", e);
104        }
105        return responseResult;
106    }
107
108    /**
109     * max 统计员工工资最高值
110     */
111    public Object aggregationMax() {
112        String responseResult = "";
113        try {
114            // 设置聚合条件
115            AggregationBuilder aggr = AggregationBuilders.max("salary_max").field("salary");
116            // 查询源构建器
117            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
118            searchSourceBuilder.aggregation(aggr);
119            searchSourceBuilder.size(0);
120            // 创建查询请求对象，将查询条件配置到其中
121            SearchRequest request = new SearchRequest("mydlq-user");
122            request.source(searchSourceBuilder);
123            // 执行请求
124            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
125            // 获取响应中的聚合信息
126            Aggregations aggregations = response.getAggregations();
127            // 输出内容
128            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
129                // 转换为 Max 对象
130                ParsedMax aggregation = aggregations.get("salary_max");
131                log.info("-------------------------------------------");
132                log.info("聚合信息:");
133                log.info("max：{}", aggregation.getValue());
134                log.info("-------------------------------------------");
135            }
136            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
137            responseResult = response.toString();
138        } catch (IOException e) {
139            log.error("", e);
140        }
141        return responseResult;
142    }
143
144    /**
145     * avg 统计员工工资平均值
146     */
147    public Object aggregationAvg() {
148        String responseResult = "";
149        try {
150            // 设置聚合条件
151            AggregationBuilder aggr = AggregationBuilders.avg("salary_avg").field("salary");
152            // 查询源构建器
153            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
154            searchSourceBuilder.aggregation(aggr);
155            searchSourceBuilder.size(0);
156            // 创建查询请求对象，将查询条件配置到其中
157            SearchRequest request = new SearchRequest("mydlq-user");
158            request.source(searchSourceBuilder);
159            // 执行请求
160            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
161            // 获取响应中的聚合信息
162            Aggregations aggregations = response.getAggregations();
163            // 输出内容
164            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
165                // 转换为 Avg 对象
166                ParsedAvg aggregation = aggregations.get("salary_avg");
167                log.info("-------------------------------------------");
168                log.info("聚合信息:");
169                log.info("avg：{}", aggregation.getValue());
170                log.info("-------------------------------------------");
171            }
172            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
173            responseResult = response.toString();
174        } catch (IOException e) {
175            log.error("", e);
176        }
177        return responseResult;
178    }
179
180    /**
181     * sum 统计员工工资总值
182     */
183    public Object aggregationSum() {
184        String responseResult = "";
185        try {
186            // 设置聚合条件
187            SumAggregationBuilder aggr = AggregationBuilders.sum("salary_sum").field("salary");
188            // 查询源构建器
189            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
190            searchSourceBuilder.aggregation(aggr);
191            searchSourceBuilder.size(0);
192            // 创建查询请求对象，将查询条件配置到其中
193            SearchRequest request = new SearchRequest("mydlq-user");
194            request.source(searchSourceBuilder);
195            // 执行请求
196            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
197            // 获取响应中的聚合信息
198            Aggregations aggregations = response.getAggregations();
199            // 输出内容
200            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
201                // 转换为 Sum 对象
202                ParsedSum aggregation = aggregations.get("salary_sum");
203                log.info("-------------------------------------------");
204                log.info("聚合信息:");
205                log.info("sum：{}", String.valueOf((aggregation.getValue())));
206                log.info("-------------------------------------------");
207            }
208            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
209            responseResult = response.toString();
210        } catch (IOException e) {
211            log.error("", e);
212        }
213        return responseResult;
214    }
215
216    /**
217     * count 统计员工总数
218     */
219    public Object aggregationCount() {
220        String responseResult = "";
221        try {
222            // 设置聚合条件
223            AggregationBuilder aggr = AggregationBuilders.count("employee_count").field("salary");
224            // 查询源构建器
225            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
226            searchSourceBuilder.aggregation(aggr);
227            searchSourceBuilder.size(0);
228            // 创建查询请求对象，将查询条件配置到其中
229            SearchRequest request = new SearchRequest("mydlq-user");
230            request.source(searchSourceBuilder);
231            // 执行请求
232            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
233            // 获取响应中的聚合信息
234            Aggregations aggregations = response.getAggregations();
235            // 输出内容
236            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
237                // 转换为 ValueCount 对象
238                ParsedValueCount aggregation = aggregations.get("employee_count");
239                log.info("-------------------------------------------");
240                log.info("聚合信息:");
241                log.info("count：{}", aggregation.getValue());
242                log.info("-------------------------------------------");
243            }
244            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
245            responseResult = response.toString();
246        } catch (IOException e) {
247            log.error("", e);
248        }
249        return responseResult;
250    }
251
252    /**
253     * percentiles 统计员工工资百分位
254     */
255    public Object aggregationPercentiles() {
256        String responseResult = "";
257        try {
258            // 设置聚合条件
259            AggregationBuilder aggr = AggregationBuilders.percentiles("salary_percentiles").field("salary");
260            // 查询源构建器
261            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
262            searchSourceBuilder.aggregation(aggr);
263            searchSourceBuilder.size(0);
264            // 创建查询请求对象，将查询条件配置到其中
265            SearchRequest request = new SearchRequest("mydlq-user");
266            request.source(searchSourceBuilder);
267            // 执行请求
268            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
269            // 获取响应中的聚合信息
270            Aggregations aggregations = response.getAggregations();
271            // 输出内容
272            if (RestStatus.OK.equals(response.status()) || aggregations != null) {
273                // 转换为 Percentiles 对象
274                ParsedPercentiles aggregation = aggregations.get("salary_percentiles");
275                log.info("-------------------------------------------");
276                log.info("聚合信息:");
277                for (Percentile percentile : aggregation) {
278                    log.info("百分位：{}：{}", percentile.getPercent(), percentile.getValue());
279                }
280                log.info("-------------------------------------------");
281            }
282            // 根据具体业务逻辑返回不同结果，这里为了方便直接将返回响应对象Json串
283            responseResult = response.toString();
284        } catch (IOException e) {
285            log.error("", e);
286        }
287        return responseResult;
288    }
289
290}

2、Bucket 聚合分析

(1)、Restful 操作示例

按岁数进行聚合分桶，统计各个岁数员工的人数：

 1GET mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "age_bucket": {
 6      "terms": {
 7        "field": "age",
 8        "size": "10"
 9      }
10    }
11  }
12}

按工资范围进行聚合分桶，统计工资在 3000-5000、5000-9000 和 9000 以上的员工信息：

 1GET mydlq-user/_search
 2{
 3  "aggs": {
 4    "salary_range_bucket": {
 5      "range": {
 6        "field": "salary",
 7        "ranges": [
 8          {
 9            "key": "低级员工", 
10            "to": 3000
11          },{
12            "key": "中级员工",
13            "from": 5000,
14            "to": 9000
15          },{
16            "key": "高级员工",
17            "from": 9000
18          }
19        ]
20      }
21    }
22  }
23}

按照时间范围进行分桶，统计 1985-1990 年和 1990-1995 年出生的员工信息：

 1GET mydlq-user/_search
 2{
 3  "size": 10,
 4  "aggs": {
 5    "date_range_bucket": {
 6      "date_range": {
 7        "field": "birthDate",
 8        "format": "yyyy", 
 9        "ranges": [
10          {
11            "key": "出生日期1985-1990的员工", 
12            "from": "1985",
13            "to": "1990"
14          },{
15            "key": "出生日期1990-1995的员工", 
16            "from": "1990",
17            "to": "1995"
18          }
19        ]
20      }
21    }
22  }
23}

按工资多少进行聚合分桶，设置统计的最小值为 0，最大值为 12000，区段间隔为 3000：

 1GET mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_histogram": {
 6      "histogram": {
 7        "field": "salary",
 8        "extended_bounds": {
 9          "min": 0,
10          "max": 12000
11        }, 
12        "interval": 3000
13      }
14    }
15  }
16}

按出生日期进行分桶：

 1GET mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "birthday_histogram": {
 6      "date_histogram": {
 7        "format": "yyyy", 
 8        "field": "birthDate",
 9        "interval": "year"
10      }
11    }
12  }
13}

(2)、Java 代码示例

  1import lombok.extern.slf4j.Slf4j;
  2import org.elasticsearch.action.search.SearchRequest;
  3import org.elasticsearch.action.search.SearchResponse;
  4import org.elasticsearch.client.RequestOptions;
  5import org.elasticsearch.client.RestHighLevelClient;
  6import org.elasticsearch.rest.RestStatus;
  7import org.elasticsearch.search.aggregations.AggregationBuilder;
  8import org.elasticsearch.search.aggregations.AggregationBuilders;
  9import org.elasticsearch.search.aggregations.Aggregations;
 10import org.elasticsearch.search.aggregations.bucket.histogram.DateHistogramInterval;
 11import org.elasticsearch.search.aggregations.bucket.histogram.Histogram;
 12import org.elasticsearch.search.aggregations.bucket.range.Range;
 13import org.elasticsearch.search.aggregations.bucket.terms.Terms;
 14import org.elasticsearch.search.builder.SearchSourceBuilder;
 15import org.springframework.beans.factory.annotation.Autowired;
 16import org.springframework.stereotype.Service;
 17import java.io.IOException;
 18import java.util.List;
 19
 20@Slf4j
 21@Service
 22public class AggrBucketService {
 23
 24    @Autowired
 25    private RestHighLevelClient restHighLevelClient;
 26
 27    /**
 28     * 按岁数进行聚合分桶
 29     */
 30    public Object aggrBucketTerms() {
 31        try {
 32            AggregationBuilder aggr = AggregationBuilders.terms("age_bucket").field("age");
 33            // 查询源构建器
 34            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 35            searchSourceBuilder.size(10);
 36            searchSourceBuilder.aggregation(aggr);
 37            // 创建查询请求对象，将查询条件配置到其中
 38            SearchRequest request = new SearchRequest("mydlq-user");
 39            request.source(searchSourceBuilder);
 40            // 执行请求
 41            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
 42            // 获取响应中的聚合信息
 43            Aggregations aggregations = response.getAggregations();
 44            // 输出内容
 45            if (RestStatus.OK.equals(response.status())) {
 46                // 分桶
 47                Terms byCompanyAggregation = aggregations.get("age_bucket");
 48                List<? extends Terms.Bucket> buckets = byCompanyAggregation.getBuckets();
 49                // 输出各个桶的内容
 50                log.info("-------------------------------------------");
 51                log.info("聚合信息:");
 52                for (Terms.Bucket bucket : buckets) {
 53                    log.info("桶名：{} | 总数：{}", bucket.getKeyAsString(), bucket.getDocCount());
 54                }
 55                log.info("-------------------------------------------");
 56            }
 57        } catch (IOException e) {
 58            log.error("", e);
 59        }
 60    }
 61
 62    /**
 63     * 按工资范围进行聚合分桶
 64     */
 65    public Object aggrBucketRange() {
 66        try {
 67            AggregationBuilder aggr = AggregationBuilders.range("salary_range_bucket")
 68                    .field("salary")
 69                    .addUnboundedTo("低级员工", 3000)
 70                    .addRange("中级员工", 5000, 9000)
 71                    .addUnboundedFrom("高级员工", 9000);
 72            // 查询源构建器
 73            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
 74            searchSourceBuilder.size(0);
 75            searchSourceBuilder.aggregation(aggr);
 76            // 创建查询请求对象，将查询条件配置到其中
 77            SearchRequest request = new SearchRequest("mydlq-user");
 78            request.source(searchSourceBuilder);
 79            // 执行请求
 80            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
 81            // 获取响应中的聚合信息
 82            Aggregations aggregations = response.getAggregations();
 83            // 输出内容
 84            if (RestStatus.OK.equals(response.status())) {
 85                // 分桶
 86                Range byCompanyAggregation = aggregations.get("salary_range_bucket");
 87                List<? extends Range.Bucket> buckets = byCompanyAggregation.getBuckets();
 88                // 输出各个桶的内容
 89                log.info("-------------------------------------------");
 90                log.info("聚合信息:");
 91                for (Range.Bucket bucket : buckets) {
 92                    log.info("桶名：{} | 总数：{}", bucket.getKeyAsString(), bucket.getDocCount());
 93                }
 94                log.info("-------------------------------------------");
 95            }
 96        } catch (IOException e) {
 97            log.error("", e);
 98        }
 99    }
100
101    /**
102     * 按照时间范围进行分桶
103     */
104    public Object aggrBucketDateRange() {
105        try {
106            AggregationBuilder aggr = AggregationBuilders.dateRange("date_range_bucket")
107                    .field("birthDate")
108                    .format("yyyy")
109                    .addRange("1985-1990", "1985", "1990")
110                    .addRange("1990-1995", "1990", "1995");
111            // 查询源构建器
112            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
113            searchSourceBuilder.size(0);
114            searchSourceBuilder.aggregation(aggr);
115            // 创建查询请求对象，将查询条件配置到其中
116            SearchRequest request = new SearchRequest("mydlq-user");
117            request.source(searchSourceBuilder);
118            // 执行请求
119            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
120            // 获取响应中的聚合信息
121            Aggregations aggregations = response.getAggregations();
122            // 输出内容
123            if (RestStatus.OK.equals(response.status())) {
124                // 分桶
125                Range byCompanyAggregation = aggregations.get("date_range_bucket");
126                List<? extends Range.Bucket> buckets = byCompanyAggregation.getBuckets();
127                // 输出各个桶的内容
128                log.info("-------------------------------------------");
129                log.info("聚合信息:");
130                for (Range.Bucket bucket : buckets) {
131                    log.info("桶名：{} | 总数：{}", bucket.getKeyAsString(), bucket.getDocCount());
132                }
133                log.info("-------------------------------------------");
134            }
135        } catch (IOException e) {
136            log.error("", e);
137        }
138    }
139
140    /**
141     * 按工资多少进行聚合分桶
142     */
143    public Object aggrBucketHistogram() {
144        try {
145            AggregationBuilder aggr = AggregationBuilders.histogram("salary_histogram")
146                    .field("salary")
147                    .extendedBounds(0, 12000)
148                    .interval(3000);
149            // 查询源构建器
150            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
151            searchSourceBuilder.size(0);
152            searchSourceBuilder.aggregation(aggr);
153            // 创建查询请求对象，将查询条件配置到其中
154            SearchRequest request = new SearchRequest("mydlq-user");
155            request.source(searchSourceBuilder);
156            // 执行请求
157            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
158            // 获取响应中的聚合信息
159            Aggregations aggregations = response.getAggregations();
160            // 输出内容
161            if (RestStatus.OK.equals(response.status())) {
162                // 分桶
163                Histogram byCompanyAggregation = aggregations.get("salary_histogram");
164                List<? extends Histogram.Bucket> buckets = byCompanyAggregation.getBuckets();
165                // 输出各个桶的内容
166                log.info("-------------------------------------------");
167                log.info("聚合信息:");
168                for (Histogram.Bucket bucket : buckets) {
169                    log.info("桶名：{} | 总数：{}", bucket.getKeyAsString(), bucket.getDocCount());
170                }
171                log.info("-------------------------------------------");
172            }
173        } catch (IOException e) {
174            log.error("", e);
175        }
176    }
177
178    /**
179     * 按出生日期进行分桶
180     */
181    public Object aggrBucketDateHistogram() {
182        try {
183            AggregationBuilder aggr = AggregationBuilders.dateHistogram("birthday_histogram")
184                    .field("birthDate")
185                    .interval(1)
186                    .dateHistogramInterval(DateHistogramInterval.YEAR)
187                    .format("yyyy");
188            // 查询源构建器
189            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
190            searchSourceBuilder.size(0);
191            searchSourceBuilder.aggregation(aggr);
192            // 创建查询请求对象，将查询条件配置到其中
193            SearchRequest request = new SearchRequest("mydlq-user");
194            request.source(searchSourceBuilder);
195            // 执行请求
196            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
197            // 获取响应中的聚合信息
198            Aggregations aggregations = response.getAggregations();
199            // 输出内容
200            if (RestStatus.OK.equals(response.status())) {
201                // 分桶
202                Histogram byCompanyAggregation = aggregations.get("birthday_histogram");
203
204                List<? extends Histogram.Bucket> buckets = byCompanyAggregation.getBuckets();
205                // 输出各个桶的内容
206                log.info("-------------------------------------------");
207                log.info("聚合信息:");
208                for (Histogram.Bucket bucket : buckets) {
209                    log.info("桶名：{} | 总数：{}", bucket.getKeyAsString(), bucket.getDocCount());
210                }
211                log.info("-------------------------------------------");
212            }
213        } catch (IOException e) {
214            log.error("", e);
215        }
216    }
217
218}

3、Metric 与 Bucket 聚合分析

(1)、Restful 操作示例

按照员工岁数分桶、然后统计每个岁数员工工资最高值:

 1GET mydlq-user/_search
 2{
 3  "size": 0,
 4  "aggs": {
 5    "salary_bucket": {
 6      "terms": {
 7        "field": "age",
 8        "size": "10"
 9      },
10      "aggs": {
11        "salary_max_user": {
12          "top_hits": {
13            "size": 1,
14            "sort": [
15              {
16                "salary": {
17                  "order": "desc"
18                }
19              }
20            ]
21          }
22        }
23      }
24    }
25  }
26}

(2)、Java 代码示例

 1import lombok.extern.slf4j.Slf4j;
 2import org.elasticsearch.action.search.SearchRequest;
 3import org.elasticsearch.action.search.SearchResponse;
 4import org.elasticsearch.client.RequestOptions;
 5import org.elasticsearch.client.RestHighLevelClient;
 6import org.elasticsearch.rest.RestStatus;
 7import org.elasticsearch.search.SearchHit;
 8import org.elasticsearch.search.aggregations.AggregationBuilder;
 9import org.elasticsearch.search.aggregations.AggregationBuilders;
10import org.elasticsearch.search.aggregations.Aggregations;
11import org.elasticsearch.search.aggregations.bucket.terms.Terms;
12import org.elasticsearch.search.aggregations.metrics.tophits.ParsedTopHits;
13import org.elasticsearch.search.builder.SearchSourceBuilder;
14import org.elasticsearch.search.sort.SortOrder;
15import org.springframework.beans.factory.annotation.Autowired;
16import org.springframework.stereotype.Service;
17import java.io.IOException;
18import java.util.List;
19
20@Slf4j
21@Service
22public class AggrBucketMetricService {
23
24    @Autowired
25    private RestHighLevelClient restHighLevelClient;
26
27    /**
28     * topHits 按岁数分桶、然后统计每个员工工资最高值
29     */
30    public Object aggregationTopHits() {
31        try {
32            AggregationBuilder testTop = AggregationBuilders.topHits("salary_max_user")
33                    .size(1)
34                    .sort("salary", SortOrder.DESC);
35            AggregationBuilder salaryBucket = AggregationBuilders.terms("salary_bucket")
36                    .field("age")
37                    .size(10);
38            salaryBucket.subAggregation(testTop);
39            // 查询源构建器
40            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
41            searchSourceBuilder.size(0);
42            searchSourceBuilder.aggregation(salaryBucket);
43            // 创建查询请求对象，将查询条件配置到其中
44            SearchRequest request = new SearchRequest("mydlq-user");
45            request.source(searchSourceBuilder);
46            // 执行请求
47            SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT);
48            // 获取响应中的聚合信息
49            Aggregations aggregations = response.getAggregations();
50            // 输出内容
51            if (RestStatus.OK.equals(response.status())) {
52                // 分桶
53                Terms byCompanyAggregation = aggregations.get("salary_bucket");
54                List<? extends Terms.Bucket> buckets = byCompanyAggregation.getBuckets();
55                // 输出各个桶的内容
56                log.info("-------------------------------------------");
57                log.info("聚合信息:");
58                for (Terms.Bucket bucket : buckets) {
59                    log.info("桶名：{}", bucket.getKeyAsString());
60                    ParsedTopHits topHits = bucket.getAggregations().get("salary_max_user");
61                    for (SearchHit hit:topHits.getHits()){
62                        log.info(hit.getSourceAsString());
63                    }
64                }
65                log.info("-------------------------------------------");
66            }
67        } catch (IOException e) {
68            log.error("", e);
69        }
70    }
71
72}