谷粒商城微服务分布式高级篇ElasticSearch四——Java使用ElasticSearch

ElasticSearch-Rest-Client

Java使用ElasticSearch

1)、9300,TCP
spring-data-elasticsearch:transport-apl.jar;
spfingboot版本不同，transport-api.jar不同，不能适配es版本
7.x已经不建议使用，8以后就要废弃

2)、9200.HTTP
JestClient:非官方,更新慢
Resttemplate： 模拟发HTTP请求,ES很多操作需要自己封装,麻烦
Httpclent:同上
ElasticSearch-Rest-Client：官方RestClient，封装了ES操作，API层次分明，上手简单

最终选择 ElasticSearch-Rest-Clent(elasticSearch-rest-high-level-client)
官方文档

开始整合
1）、创建SpringBoot ES 搜索服务 导入依赖

<dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-high-level-client</artifactId>
    <version>7.4.2</version>
</dependency>

ElasticSearch-Rest-Client Java High Level REST Client的版本必须小于等于你的elasticsearch版本，建议版本一致

springboot有管理es版本，所以得手动改成当前es版本

<properties>
    <java.version>1.8</java.version>
    <elasticsearch.version>7.4.2</elasticsearch.version>
</properties>

2）、注册到nacos

可见 nacos得注册与发现

3）、编写配置，将客户端注入spring容器

/**
 * @program: MyMall
 * @description: ES配置类
 * @author: DAIHAO
 * @created: 2020/05/09 22:53
 */
@Configuration
public class EsConfig {

    @Bean
    public RestHighLevelClient esRestClient() {
        RestClientBuilder builder = null;
        HttpHost host = new HttpHost("192.168.175.130",9200,"http");
        builder = RestClient.builder(host);
        RestHighLevelClient client = new RestHighLevelClient(builder);
        return client;
    }

}

4)、测试

@RunWith(SpringRunner.class)
@SpringBootTest
public class MallSearchApplicationTests {

    @Autowired
    RestHighLevelClient client;

    @Test
    public void contextLoads() {
        System.out.println(client);
        //org.elasticsearch.client.RestHighLevelClient@f438904 
    }

}

5）、使用单实例RestHighLevelClient
RestHighLevelClient中的所有API都接受一个RequestOptions，您可以使用它们以不会改变Elasticsearch执行请求的方式自定义请求。例如，在这里您可以指定NodeSelector来控制哪个节点接收请求

    public static final RequestOptions COMMON_OPTIONS;

    static {
        RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
//暂时不使用
        //        builder.addHeader("Authorization", "Bearer " + TOKEN);
//        builder.setHttpAsyncResponseConsumerFactory(
//                new HttpAsyncResponseConsumerFactory
//                        .HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));
        COMMON_OPTIONS = builder.build();
    }

存储数据到ES

    /**
     * 测试存储数据到es
     */
    @Test
    public void index() throws IOException {
        //指定索引
        IndexRequest indexRequest = new IndexRequest("users");
        //指定ID 如果不设置自动生成
        indexRequest.id("1");
        //1、使用kv结构
        //index.source("userName","daihao","age","18");

        //2、使用json
        User user = new User();
        user.setName("DAIHAO");
        user.setAge(18);
        user.setGender("男");
        String json = JSON.toJSONString(user);
        indexRequest.source(json, XContentType.JSON);

        //执行同步存储 RequestOptions.DEFAULT:请求设置项
        IndexResponse index = client.index(indexRequest, RequestOptions.DEFAULT);

        //提取有用得响应数据
        System.out.println(index);
        //IndexResponse[index=users,type=_doc,id=1,version=1,result=created,seqNo=0,primaryTerm=1,shards={"total":2,"successful":1,"failed":0}]


        //java.lang.IllegalArgumentException: The number of object passed must be even but was [1]
        //错误 没有设置传递的内容格式 XContentType.JSON

    }
    @Data
    class User {
        private String name;
        private String gender;
        private Integer age;
    }

从ES检索数据

    /**
     * 复杂查询
     */
    @Test
    public 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 sourceBuilder = new SearchSourceBuilder();
        sourceBuilder.query(QueryBuilders.matchQuery("address", "mill"));

        //按照年龄的值分布聚合
        TermsAggregationBuilder ageAgg = AggregationBuilders.terms("ageAgg")
                .field("age").size(10);
        sourceBuilder.aggregation(ageAgg);

        //计算平均薪资
        AvgAggregationBuilder balanceVag = AggregationBuilders.avg("balanceVag")
                .field("balance");
        sourceBuilder.aggregation(balanceVag);

        //System.out.println(sourceBuilder.toString());
        searchRequest.source(sourceBuilder);

        //执行
        SearchResponse searchResponse = client.search(searchRequest, EsConfig.COMMON_OPTIONS);

        //获取命中数据
        SearchHits searchHits = searchResponse.getHits();
        SearchHit[] hits = searchHits.getHits();
        for (SearchHit hit : hits) {
            String str = hit.getSourceAsString();
            Account account = JSON.parseObject(str, Account.class);
            System.out.println("account:" + account);
            //account_number=970, balance=19648, firstname=Forbes, lastname=Wallace, age=28, gender=M,
            //address=990 Mill Road, employer=Pheast, [email protected], city=Lopezo, state=AK)
        }

        //获取这次检索的到的分析信息
        Aggregations aggregations = searchResponse.getAggregations();
        for (Aggregation aggregation : aggregations.asList()) {
            System.out.println("当前聚合：" + aggregation.getName());
            //当前聚合：ageAgg
            //当前聚合：balanceVag
        }

        Terms ageAgg1 = aggregations.get("ageAgg");
        for (Terms.Bucket bucket : ageAgg1.getBuckets()) {
            String str = bucket.getKeyAsString();
            System.out.println("年龄:" + str + "===>" + bucket.getDocCount());
//            年龄:38===>2
//            年龄:28===>1
//            年龄:32===>1
        }

        Avg balanceVag1 = aggregations.get("balanceVag");
        System.out.println("平均薪资：" + balanceVag1.getValueAsString());
        //平均薪资：25208.0

    }

    @ToString
    @Data
    static class Account {
        private int account_number;
        private int balance;
        private String firstname;
        private String lastname;
        private int age;
        private String gender;
        private String address;
        private String employer;
        private String email;
        private String city;
        private String state;
    }

项目使用ES

1、 提供按关键字查询的全文搜索功能。
2、 著名的ELK框架(ElasticSearch,Logstash,Kibana)，实现企业海量日志的处理分析的解决方案。大数据领域的重要一份子