微服务java 操作elasticsearch详细总结

Posted 2022-12-15 逆风飞翔的小叔

一、前言

上一篇我们通过kibana的可视化界面，对es的索引以及文档的常用操作做了毕竟详细的总结，本篇将介绍如何使用java完成对es的操作，这也是实际开发中将要涉及到的。

二、java操作es的常用模式

目前，开发中使用java操作es，不管是框架集成，还是纯粹的使用es的api，主要通过下面两种方式：

• rest-api，主流的像  RestHighLevelClient ;

• 与springboot集成时的jpa操作，主要是 ElasticsearchRepository 相关的api；

上面两种模式的api在开发中都可以方便的使用，相比之下，RestHighLevelClient相关的api灵活性更高，而ElasticsearchRepository 底层做了较多的封装，学习和使用的成本更低，上手更快。

接下来将对上面的两种操作模式做一个详细的总结，本篇所述的es基于7.6.2版本，配合的kibana也为7.6.2版本。

三、rest-api 操作

1、前置准备

导入依赖

导入核心依赖，主要是es的rest依赖，其他的可以根据自己的需要导入； 

<dependencies>

        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-api</artifactId>
            <version>2.11.2</version>
        </dependency>

        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>2.11.2</version>
        </dependency>

        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>2.8.2</version>
        </dependency>

        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-jcl</artifactId>
            <version>2.11.2</version>
        </dependency>

        <dependency>
            <groupId>commons-logging</groupId>
            <artifactId>commons-logging</artifactId>
            <version>1.2</version>
        </dependency>

        <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch</artifactId>
            <version>7.6.2</version>
        </dependency>

        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-high-level-client</artifactId>
            <version>7.6.2</version>
        </dependency>

        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.9.9</version>
        </dependency>

        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.12</version>
        </dependency>


    </dependencies>

es连接测试

为了确保后续的所有实验能够正常进行，建议先通过下面的程序测试下是否能够连接es服务；

import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;

import java.io.IOException;

public class EsClientTest 

    public static void main(String[] args) throws IOException 
        RestHighLevelClient esClient = new RestHighLevelClient(
                RestClient.builder(new HttpHost("IP",9200,"http"))
        );
        System.out.println("success");
        esClient.close();
    

运行上面的代码，出现下面的效果说明连接成功

2、索引相关操作api的使用

为了减少连接相关的编码，我们将es的client提出到全局的静态变量中，其他方法中就可以直接引用了

    public static RestHighLevelClient esClient;

    static 
        esClient = new RestHighLevelClient(
                RestClient.builder(new HttpHost("IP", 9200, "http"))
        );
    

2.1  创建索引

    /**
     * 创建索引
     * @throws IOException
     */
    public static void createIndex() throws IOException 
        CreateIndexRequest createIndexRequest = new CreateIndexRequest("user");
        CreateIndexResponse indexResponse = esClient.indices().create(createIndexRequest, RequestOptions.DEFAULT);
        boolean acknowledged = indexResponse.isAcknowledged();
        System.out.println("索引创建状态:" + acknowledged);
    

main方法中调用方法即可

public static void main(String[] args) throws IOException 
        System.out.println("connect success");
        createIndex();
        esClient.close();

运行main创建索引

通过kibana查询确认索引是否创建成功

2.2  获取索引

/**
     * 索引信息查询
     * @throws IOException
     */
    public static void getIndex() throws IOException 
        GetIndexRequest getIndexRequest = new GetIndexRequest("user");
        GetIndexResponse getIndexResponse = esClient.indices().get(getIndexRequest, RequestOptions.DEFAULT);
        System.out.println(getIndexResponse.getAliases());
        System.out.println(getIndexResponse.getMappings());
        System.out.println(getIndexResponse.getSettings());
    

2.3  删除索引

    /**
     * 删除索引
     * @throws IOException
     */
    public static void deleteIndex() throws IOException 
        DeleteIndexRequest getIndexRequest = new DeleteIndexRequest("user");
        AcknowledgedResponse delete = esClient.indices().delete(getIndexRequest, RequestOptions.DEFAULT);
        System.out.println("索引删除状态:" + delete.isAcknowledged());
    

3、文档常用操作api的使用

在实际开发过程中，对于文档的操作更为的频繁，接下来演示与es文档相关的操作api。

前置准备

public static ObjectMapper objectMapper = new ObjectMapper();

    public static RestHighLevelClient esClient;
    static 
        esClient = new RestHighLevelClient(
                RestClient.builder(new HttpHost("IP", 9200, "http"))
        );
    

用于测试使用的对象

public class User 

    private String name;
    private String sex;
    private Integer age;

    private Integer salary;

    public User() 
    

    public User(String name, String sex, Integer age, Integer salary) 
        this.name = name;
        this.sex = sex;
        this.age = age;
        this.salary = salary;
    

    public Integer getSalary() 
        return salary;
    

    public void setSalary(Integer salary) 
        this.salary = salary;
    

    public String getName() 
        return name;
    

    public void setName(String name) 
        this.name = name;
    

    public String getSex() 
        return sex;
    

    public void setSex(String sex) 
        this.sex = sex;
    

    public Integer getAge() 
        return age;
    

    public void setAge(Integer age) 
        this.age = age;
    

3.1  索引添加文档

注意：实际开发中，user对象应该作为参数传入【可以基于此做进一步的封装】

    /**
     * 添加数据
     * @throws Exception
     */
    public static void add() throws Exception
        IndexRequest indexRequest = new IndexRequest();
        indexRequest.index("user").id("1008");
        User user = new User();
        user.setName("孙二娘");
        user.setAge(23);
        user.setSex("女");
        user.setSalary(7000);

        String userData = objectMapper.writeValueAsString(user);
        indexRequest.source(userData,XContentType.JSON);
        //插入数据
        IndexResponse response = esClient.index(indexRequest, RequestOptions.DEFAULT);
        System.out.println(response.status());
        System.out.println(response.getResult());
    

在main方法调用执行下该方法

public static void main(String[] args) throws Exception 
        add();
        esClient.close();

可以通过kibana查询检查下数据是否添加成功

3.2  修改文档

    /**
     * 修改数据
     * @throws Exception
     */
    public static void update() throws Exception
        UpdateRequest request = new UpdateRequest();
        request.index("user").id("1008");
        request.doc(XContentType.JSON,"name","母夜叉");
        //插入数据
        UpdateResponse response = esClient.update(request, RequestOptions.DEFAULT);
        System.out.println(response.getResult());
    

3.3  删除文档

    /**
     * 删除
     * @throws Exception
     */
    public static void delete() throws Exception
        DeleteRequest request = new DeleteRequest();
        request.index("user").id("1008");
        //插入数据
        DeleteResponse delete = esClient.delete(request, RequestOptions.DEFAULT);
        System.out.println(delete.getResult());
    

 3.4  批量添加文档

有些情况下，单条插入效率太低，可以使用es的批量插入功能一次性添加多条数据

    /**
     * 批量添加
     * @throws Exception
     */
    public static void batchInsert() throws Exception

        BulkRequest bulkRequest = new BulkRequest();

        User user1 = new User("关羽","男",33,5500);
        String userData1 = objectMapper.writeValueAsString(user1);
        IndexRequest indexRequest1 = new IndexRequest().index("user").id("1002").source(userData1, XContentType.JSON);

        bulkRequest.add(indexRequest1);

        User user2 = new User("黄忠","男",50,8000);
        String userData2 = objectMapper.writeValueAsString(user2);
        IndexRequest indexRequest2 = new IndexRequest().index("user").id("1003").source(userData2, XContentType.JSON);
        bulkRequest.add(indexRequest2);

        User user3 = new User("黄忠2","男",49,10000);
        String userData3 = objectMapper.writeValueAsString(user3);
        IndexRequest indexRequest3 = new IndexRequest().index("user").id("1004").source(userData3, XContentType.JSON);
        bulkRequest.add(indexRequest3);

        User user4 = new User("赵云","男",33,12000);
        String userData4 = objectMapper.writeValueAsString(user4);
        IndexRequest indexRequest4 = new IndexRequest().index("user").id("1005").source(userData4, XContentType.JSON);
        bulkRequest.add(indexRequest4);

        User user5 = new User("马超","男",38,20000);
        String userData5 = objectMapper.writeValueAsString(user5);
        IndexRequest indexRequest5 = new IndexRequest().index("user").id("1006").source(userData5, XContentType.JSON);
        bulkRequest.add(indexRequest5);

        User user6 = new User("关羽","男",41,27000);
        String userData6 = objectMapper.writeValueAsString(user6);
        IndexRequest indexRequest6 = new IndexRequest().index("user").id("1007").source(userData6, XContentType.JSON);
        bulkRequest.add(indexRequest6);

        BulkResponse bulkResponse = esClient.bulk(bulkRequest, RequestOptions.DEFAULT);
        System.out.println(bulkResponse.status());
        System.out.println(bulkResponse.getItems());
    

 

3.5  批量删除

可以通过批量操作一次性删除多条数据

    /**
     * 批量删除
     * @throws Exception
     */
    public static void batchDelete() throws Exception
        BulkRequest bulkRequest = new BulkRequest();
        DeleteRequest indexRequest1 = new DeleteRequest().index("user").id("1002");
        DeleteRequest indexRequest2 = new DeleteRequest().index("user").id("1003");
        DeleteRequest indexRequest3 = new DeleteRequest().index("user").id("1004");
        DeleteRequest indexRequest4 = new DeleteRequest().index("user").id("1005");
        DeleteRequest indexRequest5 = new DeleteRequest().index("user").id("1006");
        DeleteRequest indexRequest6 = new DeleteRequest().index("user").id("1007");

        bulkRequest.add(indexRequest1);
        bulkRequest.add(indexRequest2);
        bulkRequest.add(indexRequest3);
        bulkRequest.add(indexRequest4);
        bulkRequest.add(indexRequest5);
        bulkRequest.add(indexRequest6);

        BulkResponse bulkResponse = esClient.bulk(bulkRequest, RequestOptions.DEFAULT);
        System.out.println(bulkResponse.status());
        System.out.println(bulkResponse.getItems());
    

 4、文档搜索相关api的使用

我们知道es最强大的功能就是文档检索了，接下来演示下与es文档查询相关的常用API的操作；

4.1  查询某个索引下的所有数据

    /**
     * 查询某个索引下的所有数据
     * @throws Exception
     */
    public static void searchIndexAll() throws Exception
        SearchRequest request = new SearchRequest();
        request.indices("user");
        // 索引中的全部数据查询
        SearchSourceBuilder query = new SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
        request.source(query);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        
    

执行一下对该方法的调用

这个效果和在kibana中下面的操作效果是一样的

4.2  批量查询多条数据

针对那种需要一次性查出多条数据的场景可以考虑使用

        MultiGetRequest multiGetRequest = new MultiGetRequest();
        multiGetRequest.add("user", "1002");
        multiGetRequest.add("user", "1003");
        MultiGetResponse responses = esClient
                .mget(multiGetRequest, RequestOptions.DEFAULT);

        Iterator<MultiGetItemResponse> iterator = responses.iterator();
        while (iterator.hasNext())
            MultiGetItemResponse next = iterator.next();
            System.out.println(next.getResponse().getSourceAsString());
        

4.3  根据条件精准查询

根据性别查询，有点类似于mysql 中的 where sex='女' 这样的效果

        TermQueryBuilder ageQueryBuilder = QueryBuilders.termQuery("sex", "女");
        SearchSourceBuilder query = new SearchSourceBuilder().query(ageQueryBuilder);
        request.source(query);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.4  分页查询

考察from + size的使用

        SearchSourceBuilder sourceBuilder = new                         
        SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
        sourceBuilder.from(0).size(3);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.5  查询结果按照某个字段进行排序

将查询结果按照age进行排序

        SearchSourceBuilder sourceBuilder = new     
        SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
        sourceBuilder.sort("age",SortOrder.ASC);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.6  查询结果过滤某些字段

类似于mysql中只查询某个表的部分字段

        SearchSourceBuilder sourceBuilder = new         
        SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
        request.source(sourceBuilder);
        String[] includes = "name","sex";
        String[] excludes = "age";
        sourceBuilder.fetchSource(includes,excludes);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.7  多条件查询

es可以像mysql那样组合多个条件进行查询，考察对BoolQuery的使用，如下：查询性别为难男，年龄在35到45之间的用户；

        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        boolQueryBuilder.must(QueryBuilders.matchQuery("sex","男"));
        boolQueryBuilder.must(QueryBuilders.rangeQuery("age").lt(45).gt(35));
        sourceBuilder.query(boolQueryBuilder);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.8  范围查询

        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        RangeQueryBuilder rangeQueryBuilder =     
        QueryBuilders.rangeQuery("age").gte(35).lte(45);
        sourceBuilder.query(rangeQueryBuilder);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.9  模糊查询

        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        FuzzyQueryBuilder fuzzyQueryBuilder =
                QueryBuilders.fuzzyQuery("name", "黄忠")
                        .fuzziness(Fuzziness.ONE);
        sourceBuilder.query(fuzzyQueryBuilder);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.10   高亮查询

        SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
        TermQueryBuilder ageQueryBuilder = QueryBuilders.termQuery("age", 33);
        HighlightBuilder highlightBuilder = new HighlightBuilder();
        highlightBuilder.preTags("<font color='red'>");
        highlightBuilder.postTags("</font>");
        highlightBuilder.field("name");
        sourceBuilder.highlighter(highlightBuilder);
        sourceBuilder.query(ageQueryBuilder);
        request.source(sourceBuilder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.11  多字段查询multi_match

这个用法表示从多个字段中匹配某个关键字

        SearchSourceBuilder builder = new SearchSourceBuilder();
        MultiMatchQueryBuilder multiMatchQuery = QueryBuilders.multiMatchQuery("黄忠","name", "sex");
        multiMatchQuery.operator(Operator.OR);
        builder.query(multiMatchQuery);
        request.source(builder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.12  聚合查询

        SearchSourceBuilder builder = new SearchSourceBuilder();
        AggregationBuilder aggregationBuilder = AggregationBuilders.max("maxAge").field("age");
        builder.aggregation(aggregationBuilder);
        request.source(builder);
        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

4.13  分组查询

        SearchSourceBuilder builder = new SearchSourceBuilder();
        AggregationBuilder aggregationBuilder = AggregationBuilders.terms("ageGroup").field("age");
        builder.aggregation(aggregationBuilder);
        request.source(builder);

        SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);
        System.out.println(response.getHits().getHits());
        System.out.println(response.getHits().getTotalHits());
        SearchHits hits = response.getHits();
        for (SearchHit searchHit : hits)
            System.out.println(searchHit.getSourceAsString());
        

四、与springboot 整合

es提供了与spring，springboot快速整合的第三方SDK，接下来以spring-data为例进行说明；

spring-boot-starter-data-elasticsearch 与spring其他相关的jpa方式使用类似，封装了丰富的API接口，客户只需要继承其提供的接口，就能方便的使用内置的API

前置准备

本地创建一个maven工程

1、导入核心依赖

    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.3.6.RELEASE</version>
        <relativePath/>
    </parent>

    <dependencies>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-devtools</artifactId>
            <scope>runtime</scope>
            <optional>true</optional>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-test</artifactId>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework</groupId>
            <artifactId>spring-test</artifactId>
        </dependency>
    </dependencies>

2、核心配置文件

# es 服务地址
elasticsearch.host=IP
# es 服务端口
elasticsearch.port=9200
# 配置日志级别,开启 debug 日志
logging.level.com.congge=debug

整合过程

1、创建一个实体类

该实体类属于连接es文档与客户端的一个中间转换层，使用过jpa或者mybatis-plus的同学对这个应该不陌生；

import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.ToString;
import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.Document;
import org.springframework.data.elasticsearch.annotations.Field;
import org.springframework.data.elasticsearch.annotations.FieldType;

@Data
@NoArgsConstructor
@AllArgsConstructor
@ToString
@Document(indexName = "shopping", shards = 3, replicas = 1)
public class Product 
    //必须有 id,这里的 id 是全局唯一的标识，等同于 es 中的"_id"
    @Id
    private Long id;//商品唯一标识

    /**
     * type : 字段数据类型
     * analyzer : 分词器类型
     * index : 是否索引(默认:true)
     * Keyword : 短语,不进行分词
     */
    @Field(type = FieldType.Text, analyzer = "ik_max_word")
    private String title;//商品名称

    @Field(type = FieldType.Keyword)
    private String category;//分类名称

    @Field(type = FieldType.Double)
    private Double price;//商品价格

    @Field(type = FieldType.Keyword, index = false)
    private String images;//图片地址

2、提供一个接口，继承ElasticsearchRepository

import com.congge.entity.Product;
import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;
import org.springframework.stereotype.Repository;

@Repository
public interface ProductDao extends ElasticsearchRepository<Product, Long>

3、核心配置类

import lombok.Data;
import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Configuration;
//import org.springframework.data.elasticsearch.config.AbstractElasticsearchConfiguration;

@ConfigurationProperties(prefix = "elasticsearch")
@Configuration
@Data
public class EsConfig extends com.congge.config.AbstractElasticsearchConfiguration 

    private String host ;
    private Integer port ;

    //重写父类方法
    @Override
    public RestHighLevelClient elasticsearchClient() 
        RestClientBuilder builder = RestClient.builder(new HttpHost(host, port));
        RestHighLevelClient restHighLevelClient = new
                RestHighLevelClient(builder);
        return restHighLevelClient;
    

import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.context.annotation.Bean;
import org.springframework.data.elasticsearch.config.ElasticsearchConfigurationSupport;
import org.springframework.data.elasticsearch.core.ElasticsearchOperations;
import org.springframework.data.elasticsearch.core.ElasticsearchRestTemplate;
import org.springframework.data.elasticsearch.core.convert.ElasticsearchConverter;

public abstract class AbstractElasticsearchConfiguration extends ElasticsearchConfigurationSupport 

    //需重写本方法
    public abstract RestHighLevelClient elasticsearchClient();

    @Bean(name =  "elasticsearchOperations", "elasticsearchTemplate" )
    public ElasticsearchOperations elasticsearchOperations(ElasticsearchConverter elasticsearchConverter) 
        return new ElasticsearchRestTemplate(elasticsearchClient(), elasticsearchConverter);
    

模拟测试

接下来通过junit的方式进行测试

1、索引相关的操作测试

import com.congge.entity.Product;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.data.elasticsearch.core.ElasticsearchRestTemplate;
import org.springframework.test.context.junit4.SpringRunner;

@RunWith(SpringRunner.class)
@SpringBootTest
public class EsIndexTest 

    //注入 ElasticsearchRestTemplate
    @Autowired
    private ElasticsearchRestTemplate elasticsearchRestTemplate;

    //创建索引并增加映射配置
    @Test
    public void createIndex()
        //创建索引，系统初始化会自动创建索引
        System.out.println("创建索引");
    

    @Test
    public void deleteIndex()
        //创建索引，系统初始化会自动创建索引
        boolean flg = elasticsearchRestTemplate.deleteIndex(Product.class);
        System.out.println("删除索引 = " + flg);
    

基于spring-data的方式，在工程启动的时候，会自动读取实体类相关的注解，自动完成索引的创建，运行下创建索引的测试方法；

然后去到kibana上面确认下是否创建成功；

2、文档相关的操作测试

该测试类中列举了常用的增删改查操作

import com.congge.dao.ProductDao;
import com.congge.entity.Product;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.TermQueryBuilder;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.data.domain.Page;
import org.springframework.data.domain.PageRequest;
import org.springframework.data.domain.Sort;
import org.springframework.test.context.junit4.SpringRunner;

import java.util.ArrayList;
import java.util.List;

@RunWith(SpringRunner.class)
@SpringBootTest
public class EsDocTest 


    @Autowired
    private ProductDao productDao;

    /**
     * 新增
     */
    @Test
    public void save() 
        Product product = new Product();
        product.setId(2L);
        product.setTitle("ipad mini");
        product.setCategory("ipad");
        product.setPrice(1998.0);
        product.setImages("http://ipad.jpg");
        productDao.save(product);
    


    //修改
    @Test
    public void update()
        Product product = new Product();
        product.setId(2L);
        product.setTitle("iphone");
        product.setCategory("mobile");
        product.setPrice(6999.0);
        product.setImages("http://www.phone.jpg");
        productDao.save(product);
    

    //根据 id 查询
    @Test
    public void findById()
        Product product = productDao.findById(2L).get();
        System.out.println(product);
    

    //查询所有
    @Test
    public void findAll()
        Iterable<Product> products = productDao.findAll();
        for (Product product : products) 
            System.out.println(product);
        
    

    //删除
    @Test
    public void delete()
        Product product = new Product();
        product.setId(2L);
        productDao.delete(product);
    

    //批量新增
    @Test
    public void saveAll()
        List<Product> productList = new ArrayList<>();
        for (int i = 0; i < 10; i++) 
            Product product = new Product();
            product.setId(Long.valueOf(i));
            product.setTitle("iphone" + i);
            product.setCategory("mobile");
            product.setPrice(5999.0 + i);
            product.setImages("http://www.phone.jpg");
            productList.add(product);
        
        productDao.saveAll(productList);
    

    //分页查询
    @Test
    public void findByPageable()
        //设置排序(排序方式，正序还是倒序，排序的 id)
        Sort sort = Sort.by(Sort.Direction.DESC,"id");
        int currentPage=0;//当前页，第一页从 0 开始， 1 表示第二页
        int pageSize = 5;//每页显示多少条
        //设置查询分页
        PageRequest pageRequest = PageRequest.of(currentPage, pageSize,sort);
        //分页查询
        Page<Product> productPage = productDao.findAll(pageRequest);
        for (Product Product : productPage.getContent()) 
            System.out.println(Product);
        
    

    /**
     * term 查询
     * search(termQueryBuilder) 调用搜索方法，参数查询构建器对象
     */
    @Test
    public void termQuery()
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("title", "iphone");
        Iterable<Product> products = productDao.search(termQueryBuilder);
        for (Product product : products) 
            System.out.println(product);
        
    

    /**
     * term 查询加分页
     */
    @Test
    public void termQueryByPage()
        int currentPage= 0 ;
        int pageSize = 5;
        //设置查询分页
        PageRequest pageRequest = PageRequest.of(currentPage, pageSize);
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("title", "phone");
        Iterable<Product> products =
                productDao.search(termQueryBuilder,pageRequest);
        for (Product product : products) 
            System.out.println(product);
        
    

测试其中批量新增的方法

更多丰富的API接口的使用有兴趣的同学可以基于此继续深入的研究学习。