Saul's blog
SaulJWu
2020-11-26

SpringBoot整合Elasticsearch Rest Client

# 前言

前面通过nginx搭建了ik分词器的自定义词库，接下来就用SpringBoot整合Elasticsearch Rest Client。

当在电商商品页面场景时，需要发请求到Spinrgboot，Spirngoobt操作ES，再用ES来检索商品，将处理的结果返回到前端页面。

对于Java来操作ES有两种方式：

  • 9300 TCP。

    （ES集群节点之间通信也是用9300端口）如果使用这种方式，就需要与ES建立一个常链接，而支持这种操作需要用spring-data-elasticsearch-transport-api.jar，包括官方的elasticsearch.jar也支持这种操作。

    但是不建议使用9300 TCP端口来操作，因为Spirngboot版本不同，transport-api.jar不同，不能适配es版本，而且连官方也说，elasticsearch 7.x已经不建议使用，8.x版本以上都要废弃使用spring-data-elasticsearch-transport-api.jar来操作ES

    spring-data-elasticsearch-transport-api.jar目前最多支持到elasticsearch 6.3.8版本

  • 9200 HTTP

就是给ES发送请求，市面上有许多方式：

  1. JestClinet

非官方，更新慢，maven仓库 (opens new window)最近一次更新是2018年的，而且最多支持elasticsearch 6.3.1版本。

  1. RestTemplate

模拟法HTTP请求，ES很多操作需要自己封装，如果自己操作Query DSL就需要自己封装，比较麻烦。

  1. HttpClient

同上

  1. Elasticssearch-Rest-Client

官方的RestClient，封装了ES操作，API层次分明，上手简单。而且还支持Java,Javascript,Go,Ruby,Python,.net,PHP等等各种语言来操作

所以优先选择官方的RestClient。

为什么不用js来给ES发送请求？

因为安全问题，ES一般部署在集群服务器上，端口不对外暴露，一旦保留了容易被人恶意利用。而且如果用JS发送请求给ES，根本不需要用到RestClient，直接发送请求就可以了。

# Java REST Client

The Java REST Client comes in 2 flavors:

  • Java Low Level REST Client (opens new window): the official low-level client for Elasticsearch. It allows to communicate with an Elasticsearch cluster through http. Leaves requests marshalling and responses un-marshalling to users. It is compatible with all Elasticsearch versions.
  • Java High Level REST Client (opens new window): the official high-level client for Elasticsearch. Based on the low-level client, it exposes API specific methods and takes care of requests marshalling and responses un-marshalling.

Elasticssearch-Rest-Client，分高低阶两种：

他们的关系就类似于mybatis（高阶）与JDBC（低阶）的关系一样，mybatis封装jdbc，再来操作数据库就简单了，所以要用Java High Level REST Client (opens new window)。

# 实现方式

现在直接用idea新建一个独立项目来检索ES。

# 创建独立项目

  • new moudle，选择spring初始化向导

image-20201126155130059

image-20201126160059628
  • 组件 选Web下的SpringWeb

# 导入maven依赖

参考官方文档 (opens new window)

<dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-high-level-client</artifactId>
    <version>7.10.0</version>
</dependency>
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这里改为当前ES的版本，不一定是7.10.0

导入依赖完成，查看一下

image-20201126164244395

这里发现，Springboot默认导入的ES版本与我虚拟机中ES版本的不一致。所以需要在search微服务的pom文件指定版本，保持和虚拟机中的一致。

<properties>
    <java.version>1.8</java.version>
    <elasticsearch.version>7.6.2</elasticsearch.version>
</properties>
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改完后，刷新maven，查看ES版本是否一致。

image-20201130110738077

导入成功后，再导入自己微服务的公共common模块。

# 注册到注册中心

elitmall-search/src/main/resources/application.properties

spring.cloud.nacos.discovery.server-addr=127.0.0.1:8848
spring.application.name=elitmall-search
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启动类添加@EnableDiscoveryClient

package com.elite.mall.search;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.cloud.client.discovery.EnableDiscoveryClient;

@EnableDiscoveryClient
@SpringBootApplication
public class ElitmallSearchApplication {

	public static void main(String[] args) {
		SpringApplication.run(ElitmallSearchApplication.class, args);
	}

}
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# 编写ES配置

参考官方文档 (opens new window)

RestHighLevelClient client = new RestHighLevelClient(
        RestClient.builder(
                new HttpHost("localhost", 9200, "http"),
                new HttpHost("localhost", 9201, "http")));
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实际代码：

package com.elite.mall.search.config;

import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class ElasticsearchConfig {

    @Bean
    public RestHighLevelClient esRestClient() {
        RestClientBuilder builder = RestClient.builder(new HttpHost("192.168.56.10", 9200, "http"));
        RestHighLevelClient client = new RestHighLevelClient(builder);
        return client;
    }
}
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# 新建测试案例

package com.elite.mall.search.config;

import org.elasticsearch.client.RestHighLevelClient;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;

class ElasticsearchConfigTest {

    @Autowired
    private RestHighLevelClient esClient;

    @Test
    void esRestClient() {
        System.out.println(esClient);
    }
}
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结果返回null，检查了以前的测试案例，发现缺少@SpringBootTest

package com.elite.mall.search.config;

import org.elasticsearch.client.RestHighLevelClient;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;

@SpringBootTest
class ElasticsearchConfigTest {

    @Autowired
    private RestHighLevelClient esClient;

    @Test
    void esRestClient() {
        System.out.println(esClient);
    }
}
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结果还是报错，没有指定数据源，因为我common模块设置了数据源

Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'scopedTarget.dataSource' defined in class path resource

修改启动类，排除数据源

package com.elite.mall.search;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.cloud.client.discovery.EnableDiscoveryClient;

@EnableDiscoveryClient
@SpringBootApplication(exclude = DataSourceAutoConfiguration.class)
public class ElitmallSearchApplication {

	public static void main(String[] args) {
		SpringApplication.run(ElitmallSearchApplication.class, args);
	}

}
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重新运行测试案例，测试案例返回：

org.elasticsearch.client.RestHighLevelClient@2e62ead7

测试通过，能打印这个对象。接下来就可以通过官方文档操作ES，进行增删改查操作了。。

# 请求设置

All APIs in the RestHighLevelClient accept a RequestOptions which you can use to customize the request in ways that won’t change how Elasticsearch executes the request. For example, this is the place where you’d specify a NodeSelector to control which node receives the request. See the low level client documentation (opens new window) for more examples of customizing the options.

在进行增删改查之前，必须先了解RequestOptions，比如ES添加了安全访问规则，所有请求访问ES，都必须带上一个安全头等一些设置的信息，那么就可以通过RequestOptions来对所有请求来进行一个统一的设置，这个设置设置是来参考低版本客户端的文档 (opens new window)。

The RequestOptions class holds parts of the request that should be shared between many requests in the same application. You can make a singleton instance and share it between all requests:

private static final RequestOptions COMMON_OPTIONS;
static {
    RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
    builder.addHeader("Authorization", "Bearer " + TOKEN); 
    builder.setHttpAsyncResponseConsumerFactory(           
        new HttpAsyncResponseConsumerFactory
            .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));
    COMMON_OPTIONS = builder.build();
}
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官方建议RequestOptions做成一个单实例，所有请求设置共享使用。

比如可以带上自己的令牌，自定义响应的消费者。

@Configuration
public class ElasticsearchConfig {

    public static final RequestOptions COMMON_OPTIONS;
    static {
        RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
//        builder.addHeader("Authorization", "Bearer " + TOKEN);
//        builder.setHttpAsyncResponseConsumerFactory(
//                new HttpAsyncResponseConsumerFactory
//                        .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));
        COMMON_OPTIONS = builder.build();
    }
}
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为了方便我测试增删改查，先把所有请求头，token，令牌时间注释掉，并且改为public。以后有需要再进行修改。

# Index 索引存储数据

参照官方文档 (opens new window)，首先要构造一个请求，posts指的是在这个索引。

IndexRequest request = new IndexRequest("posts");
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然后编写数据，存储数据方式，有很多种：

  • json字符串
  • 哈希表Mapping
  • XContentBuilder object
  • key-pairs，String键值对

数据的id，可以不设置，不设置就会默认自动生成。

在实际场景中，显然是json字符串是最常用的。

存储完数据后，可以设置版本、超时时间等等，最后通过同步执行或异步执行来执行保存。

  • 同步保存
IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);
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  • 异步保存
client.indexAsync(request, RequestOptions.DEFAULT, listener);
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# 测试案例

@Test
void indexData() throws IOException {
    IndexRequest indexRequest = new IndexRequest("user");
    indexRequest.id("1");
    //indexRequest.source("username", "zhangsan", "age", 18, "gender", "男");
    User user = new User();
    user.setUsername("zhangsan");
    user.setAge(18);
    user.setGender("男");
    String jsonString = JSON.toJSONString(user);
    // 要保存的内容
    indexRequest.source(jsonString, XContentType.JSON);
    // 执行保存操作
    IndexResponse index = esClient.index(indexRequest, ElasticsearchConfig.COMMON_OPTIONS);
    // 提取有用的响应数据
    System.out.println(index);
}
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# 最后输出
IndexResponse[index=user,type=_doc,id=1,version=1,result=created,seqNo=0,primaryTerm=1,shards={"total":2,"successful":1,"failed":0}]
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# kibana 查询
GET user/_search
# 返回
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "user",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "age" : 18,
          "gender" : "男",
          "username" : "zhangsan"
        }
      }
    ]
  }
}
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当我把username改为lisi时，发现测试案例也可以通过，这次就变成更新操作了。

# 输出结果
IndexResponse[index=user,type=_doc,id=1,version=2,result=updated,seqNo=1,primaryTerm=1,shards={"total":2,"successful":1,"failed":0}]

# Kibana查询返回
{
  "took" : 262,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "user",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "age" : 18,
          "gender" : "男",
          "username" : "lisi"
        }
      }
    ]
  }
}
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其他增删改查操作，这里就不展开了，可以参考官方文档 (opens new window)。

参照官方文档 (opens new window)，有一个检索示例：

SearchRequest searchRequest = new SearchRequest(); 
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); 
searchSourceBuilder.query(QueryBuilders.matchAllQuery()); 
searchRequest.source(searchSourceBuilder);
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  1. 构造一个检索请求

  2. 构建Query DSL

但是上面的操作，并不会执行检索，执行检索需要手动进行。

执行检索也分同步和异步操作：

  • 同步：
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
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  • 异步：
client.searchAsync(searchRequest, RequestOptions.DEFAULT, listener);
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# 测试案例1

@Test
void searchData() throws IOException {
    // 创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    // 指定索引
    searchRequest.indices("bank");
    // 指定DSL，检索条件
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.matchQuery("address", "mill"));
    System.out.println(searchSourceBuilder);
    //        searchSourceBuilder.from();
    //        searchSourceBuilder.size();
    //        searchSourceBuilder.aggregation();
    searchRequest.source(searchSourceBuilder);
    // 执行检索
    SearchResponse searchResponse = esClient.search(searchRequest, RequestOptions.DEFAULT);
    // 分析结果
    System.out.println(searchResponse.toString());
}
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  • 条件构造
{
	"query": {
		"match": {
			"address": {
				"query": "mill",
				"operator": "OR",
				"prefix_length": 0,
				"max_expansions": 50,
				"fuzzy_transpositions": true,
				"lenient": false,
				"zero_terms_query": "NONE",
				"auto_generate_synonyms_phrase_query": true,
				"boost": 1.0
			}
		}
	}
}
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其中boost是来表示关联相关性得分，具体可以参照官方文档 (opens new window)。

  • 返回
{
	"took": 4,
	"timed_out": false,
	"_shards": {
		"total": 1,
		"successful": 1,
		"skipped": 0,
		"failed": 0
	},
	"hits": {
		"total": {
			"value": 4,
			"relation": "eq"
		},
		"max_score": 5.4032025,
		"hits": [{
			"_index": "bank",
			"_type": "account",
			"_id": "970",
			"_score": 5.4032025,
			"_source": {
				"account_number": 970,
				"balance": 19648,
				"firstname": "Forbes",
				"lastname": "Wallace",
				"age": 28,
				"gender": "M",
				"address": "990 Mill Road",
				"employer": "Pheast",
				"email": "forbeswallace@pheast.com",
				"city": "Lopezo",
				"state": "AK"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "136",
			"_score": 5.4032025,
			"_source": {
				"account_number": 136,
				"balance": 45801,
				"firstname": "Winnie",
				"lastname": "Holland",
				"age": 38,
				"gender": "M",
				"address": "198 Mill Lane",
				"employer": "Neteria",
				"email": "winnieholland@neteria.com",
				"city": "Urie",
				"state": "IL"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "345",
			"_score": 5.4032025,
			"_source": {
				"account_number": 345,
				"balance": 9812,
				"firstname": "Parker",
				"lastname": "Hines",
				"age": 38,
				"gender": "M",
				"address": "715 Mill Avenue",
				"employer": "Baluba",
				"email": "parkerhines@baluba.com",
				"city": "Blackgum",
				"state": "KY"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "472",
			"_score": 5.4032025,
			"_source": {
				"account_number": 472,
				"balance": 25571,
				"firstname": "Lee",
				"lastname": "Long",
				"age": 32,
				"gender": "F",
				"address": "288 Mill Street",
				"employer": "Comverges",
				"email": "leelong@comverges.com",
				"city": "Movico",
				"state": "MT"
			}
		}]
	}
}
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# 测试案例2

@Test
void searchData() throws IOException {
    // 创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    // 指定索引
    searchRequest.indices("bank");
    // 指定DSL，检索条件
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.matchQuery("address", "mill"));

    //        searchSourceBuilder.from();
    //        searchSourceBuilder.size();
    // 按照年龄的值分布聚合
    TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg")
        .field("age").size(10);
    searchSourceBuilder.aggregation(ageAgg);
    // 按照年龄平均值聚合
    AvgAggregationBuilder ageAvg = AggregationBuilders.avg("ageAvg").field("age");
    searchSourceBuilder.aggregation(ageAvg);
    // 按照薪资平均值聚合
    AvgAggregationBuilder balanceAvg = AggregationBuilders.avg("balanceAvg").field("balance");
    searchSourceBuilder.aggregation(balanceAvg);

    System.out.println(searchSourceBuilder);
    searchRequest.source(searchSourceBuilder);
    // 执行检索
    SearchResponse searchResponse = esClient.search(searchRequest, RequestOptions.DEFAULT);
    // 分析结果
    System.out.println(searchResponse.toString());
}
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  • 条件构造
{
	"query": {
		"match": {
			"address": {
				"query": "mill",
				"operator": "OR",
				"prefix_length": 0,
				"max_expansions": 50,
				"fuzzy_transpositions": true,
				"lenient": false,
				"zero_terms_query": "NONE",
				"auto_generate_synonyms_phrase_query": true,
				"boost": 1.0
			}
		}
	},
	"aggregations": {
		"ageAgg": {
			"terms": {
				"field": "age",
				"size": 10,
				"min_doc_count": 1,
				"shard_min_doc_count": 0,
				"show_term_doc_count_error": false,
				"order": [{
					"_count": "desc"
				}, {
					"_key": "asc"
				}]
			}
		},
		"ageAvg": {
			"avg": {
				"field": "age"
			}
		},
		"balanceAvg": {
			"avg": {
				"field": "balance"
			}
		}
	}
}
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发现检索条件和自己写Query DSL很类似

  • 结果
{
	"took": 6,
	"timed_out": false,
	"_shards": {
		"total": 1,
		"successful": 1,
		"skipped": 0,
		"failed": 0
	},
	"hits": {
		"total": {
			"value": 4,
			"relation": "eq"
		},
		"max_score": 5.4032025,
		"hits": [{
			"_index": "bank",
			"_type": "account",
			"_id": "970",
			"_score": 5.4032025,
			"_source": {
				"account_number": 970,
				"balance": 19648,
				"firstname": "Forbes",
				"lastname": "Wallace",
				"age": 28,
				"gender": "M",
				"address": "990 Mill Road",
				"employer": "Pheast",
				"email": "forbeswallace@pheast.com",
				"city": "Lopezo",
				"state": "AK"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "136",
			"_score": 5.4032025,
			"_source": {
				"account_number": 136,
				"balance": 45801,
				"firstname": "Winnie",
				"lastname": "Holland",
				"age": 38,
				"gender": "M",
				"address": "198 Mill Lane",
				"employer": "Neteria",
				"email": "winnieholland@neteria.com",
				"city": "Urie",
				"state": "IL"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "345",
			"_score": 5.4032025,
			"_source": {
				"account_number": 345,
				"balance": 9812,
				"firstname": "Parker",
				"lastname": "Hines",
				"age": 38,
				"gender": "M",
				"address": "715 Mill Avenue",
				"employer": "Baluba",
				"email": "parkerhines@baluba.com",
				"city": "Blackgum",
				"state": "KY"
			}
		}, {
			"_index": "bank",
			"_type": "account",
			"_id": "472",
			"_score": 5.4032025,
			"_source": {
				"account_number": 472,
				"balance": 25571,
				"firstname": "Lee",
				"lastname": "Long",
				"age": 32,
				"gender": "F",
				"address": "288 Mill Street",
				"employer": "Comverges",
				"email": "leelong@comverges.com",
				"city": "Movico",
				"state": "MT"
			}
		}]
	},
	"aggregations": {
		"lterms#ageAgg": {
			"doc_count_error_upper_bound": 0,
			"sum_other_doc_count": 0,
			"buckets": [{
				"key": 38,
				"doc_count": 2
			}, {
				"key": 28,
				"doc_count": 1
			}, {
				"key": 32,
				"doc_count": 1
			}]
		},
		"avg#ageAvg": {
			"value": 34.0
		},
		"avg#balanceAvg": {
			"value": 25208.0
		}
	}
}
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# 返回结果封装JavaBean

在实际场景中，是需要返回到前端的，ES官方 (opens new window)也提供了方法，方便返回。

RestStatus status = searchResponse.status();
TimeValue took = searchResponse.getTook();
Boolean terminatedEarly = searchResponse.isTerminatedEarly();
boolean timedOut = searchResponse.isTimedOut();
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TotalHits totalHits = hits.getTotalHits();
// the total number of hits, must be interpreted in the context of totalHits.relation
long numHits = totalHits.value;
// whether the number of hits is accurate (EQUAL_TO) or a lower bound of the total (GREATER_THAN_OR_EQUAL_TO)
TotalHits.Relation relation = totalHits.relation;
float maxScore = hits.getMaxScore();
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返回结果封装：

Map map = JSON.parseObject(searchResponse.toString(), Map.class);
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这样显然是不行的，因为从测试案例2中，发现里面封装了很多层，需要获取真实数据要很多层，而且返回到前端也是需要封装成JavaBean，所幸，可以使用官方文档提供的解决方法。

  • 在测试案例2，添加实例代码：
// 分析结果
System.out.println("返回结果：");
System.out.println(searchResponse.toString());
//        Map map = JSON.parseObject(searchResponse.toString(), Map.class);
// 获取素有查到的数据
SearchHits searchHits = searchResponse.getHits();
SearchHit[] hits = searchHits.getHits();
for (SearchHit hit : hits) {
    String sourceAsString = hit.getSourceAsString();
    Account account = JSON.parseObject(sourceAsString, Account.class);
    System.out.println("account:"+account);
}
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# 检索条件：
{"query":{"match":{"address":{"query":"mill","operator":"OR","prefix_length":0,"max_expansions":50,"fuzzy_transpositions":true,"lenient":false,"zero_terms_query":"NONE","auto_generate_synonyms_phrase_query":true,"boost":1.0}}},"aggregations":{"ageAgg":{"terms":{"field":"age","size":10,"min_doc_count":1,"shard_min_doc_count":0,"show_term_doc_count_error":false,"order":[{"_count":"desc"},{"_key":"asc"}]}},"ageAvg":{"avg":{"field":"age"}},"balanceAvg":{"avg":{"field":"balance"}}}}
# 返回结果：
{"took":3,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":4,"relation":"eq"},"max_score":5.4032025,"hits":[{"_index":"bank","_type":"account","_id":"970","_score":5.4032025,"_source":{"account_number":970,"balance":19648,"firstname":"Forbes","lastname":"Wallace","age":28,"gender":"M","address":"990 Mill Road","employer":"Pheast","email":"forbeswallace@pheast.com","city":"Lopezo","state":"AK"}},{"_index":"bank","_type":"account","_id":"136","_score":5.4032025,"_source":{"account_number":136,"balance":45801,"firstname":"Winnie","lastname":"Holland","age":38,"gender":"M","address":"198 Mill Lane","employer":"Neteria","email":"winnieholland@neteria.com","city":"Urie","state":"IL"}},{"_index":"bank","_type":"account","_id":"345","_score":5.4032025,"_source":{"account_number":345,"balance":9812,"firstname":"Parker","lastname":"Hines","age":38,"gender":"M","address":"715 Mill Avenue","employer":"Baluba","email":"parkerhines@baluba.com","city":"Blackgum","state":"KY"}},{"_index":"bank","_type":"account","_id":"472","_score":5.4032025,"_source":{"account_number":472,"balance":25571,"firstname":"Lee","lastname":"Long","age":32,"gender":"F","address":"288 Mill Street","employer":"Comverges","email":"leelong@comverges.com","city":"Movico","state":"MT"}}]},"aggregations":{"lterms#ageAgg":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":38,"doc_count":2},{"key":28,"doc_count":1},{"key":32,"doc_count":1}]},"avg#ageAvg":{"value":34.0},"avg#balanceAvg":{"value":25208.0}}}
account:ElasticsearchConfigTest.Account(account_number=970, balance=19648, firstname=Forbes, lastname=Wallace, age=28, gender=M, address=990 Mill Road, employer=Pheast, email=forbeswallace@pheast.com, city=Lopezo, state=AK)
account:ElasticsearchConfigTest.Account(account_number=136, balance=45801, firstname=Winnie, lastname=Holland, age=38, gender=M, address=198 Mill Lane, employer=Neteria, email=winnieholland@neteria.com, city=Urie, state=IL)
account:ElasticsearchConfigTest.Account(account_number=345, balance=9812, firstname=Parker, lastname=Hines, age=38, gender=M, address=715 Mill Avenue, employer=Baluba, email=parkerhines@baluba.com, city=Blackgum, state=KY)
account:ElasticsearchConfigTest.Account(account_number=472, balance=25571, firstname=Lee, lastname=Long, age=32, gender=F, address=288 Mill Street, employer=Comverges, email=leelong@comverges.com, city=Movico, state=MT)
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# 返回结果分析信息

也可以，将这次检索到的分析信息，再进行遍历。

  • 官方实例
Aggregations aggregations = searchResponse.getAggregations();
Terms byCompanyAggregation = aggregations.get("by_company"); 
Bucket elasticBucket = byCompanyAggregation.getBucketByKey("Elastic"); 
Avg averageAge = elasticBucket.getAggregations().get("average_age"); 
double avg = averageAge.getValue();
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在返回的JSON数据中，可以看到某个聚合都是类似类型+聚合名字的格式，比如：lterms#ageAgg，avg#ageAvg，在Java中，可以直接获取聚合名字。

  • 测试案例2，添加实例代码：
// 获取这次检索到的分析信息
// 年龄分布
Aggregations aggregations = searchResponse.getAggregations();
Terms ageAgg1 = aggregations.get("ageAgg");
for (Terms.Bucket bucket : ageAgg1.getBuckets()) {
    String keyAsString = bucket.getKeyAsString();
    System.out.println("年龄分布:" + keyAsString);
}
// 平均年龄
Avg ageAvg1 = aggregations.get("ageAvg");
System.out.println("平均年龄：" + ageAvg1.getValue());
// 平均薪资
Avg balanceAvg1 = aggregations.get("balanceAvg");
System.out.println("平均薪资：" + balanceAvg1.getValue());
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  • 输出结果

年龄分布:38 年龄分布:28 年龄分布:32 平均年龄：34.0 平均薪资：25208.0

# 总结

至此，对SpringBoot整合ES的操作，也初步掌握了，以后只要参照文档或者笔记，提高熟练度就可以得心应手了。如果有新的API需要去学习，只需要参照官方文档使用就行了。

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上次更新: 2020/12/17, 08:38:35
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