Springboot整合Elasticsearch(查询数据的方式)
参考文档地址:
Elasticsearch 官方文档地址:点击链接
Spring Data Elasticsearch 官方文档地址:点击链接
添加maven依赖：
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
1.初始化Elasticsearch
- 在yml配置文件中配置es的连接参数(略)
- 新建一个config类，配置es(如下)
@Configuration public class ElasticsearchConfig { @Bean public RestHighLevelClient restHighLevelClient() { // 这个是springboot的文档推荐写法 // ClientConfiguration clientConfiguration = ClientConfiguration.builder() // .connectedTo("192.168.203.129:9200").build(); // // return RestClients.create(clientConfiguration).rest(); // es官方文档推荐写法 RestHighLevelClient client = new RestHighLevelClient( RestClient.builder( new HttpHost("192.168.203.129", 9200, "http"))); return client; } }
2.简单查询
Spring Data Elasticsearch提供了一个ElasticsearchRepository接口，可以很方便的自定义简单的查询方法。
public interface MyRepository extends ElasticsearchRepository<User, Long> { /** * 根据id或者年龄或者名字查询 * @param id * @param age * @param name * @return */ User findByIdOrAgeOrName(Long id, Integer age, String name); /** * 删除年龄大于或等于给定值的数据 * @param age */ void deleteByAgeGreaterThanEqual(Integer age); /** * 搜索指定年龄段的user * @param start 开始年龄 * @param end 结束年龄 * @return */ User findAllByAgeBetween(int start,int end); }
这里要注意，自定义方法的名字是有规则的，idea会自动提示，根据提示，以及自己想要的操作，书写方法名和对应参数即可。在Spring Data Elasticsearch的文档里也有相关说明：
1.1测试代码
@Autowired private MyRepository myRepository; // 查询年龄为27岁的用户数据 @Test void myTest6() { User rico = myRepository.findByIdOrAgeOrName(null, 27, null); System.out.println(rico); } // 插入一条user数据 @Test void myTest7() throws IOException { User user = User.builder() .name("rico3") .age(35) .id(3L) .birthday(new Date()) .build(); User save = myRepository.save(user); System.out.println(save); restHighLevelClient.close(); } // 删除年龄大于或等于29岁的用户的数据 @Test void myTest8() throws IOException { myRepository.deleteByAgeGreaterThanEqual(29); restHighLevelClient.close(); }
3.复杂查询
3.1使用ElasticsearchRestTemplate
先看测试代码
@Autowired private ElasticsearchRestTemplate elasticsearchRestTemplate; // 使用elasticsearchRestTemplate来查询数据 @Test void myTest9() { // 创建一个query，QueryBuilders下可以选择查询方式 NativeSearchQuery nativeSearchQuery = new NativeSearchQuery(QueryBuilders.matchAllQuery()); SearchHits<User> search = elasticsearchRestTemplate.search(nativeSearchQuery, User.class); for (org.springframework.data.elasticsearch.core.SearchHit<User> userSearchHit : search) { User content = userSearchHit.getContent(); System.out.println(content); } } @Test void myTest11() { NativeSearchQueryBuilder builder = new NativeSearchQueryBuilder(); builder.withQuery(QueryBuilders.matchAllQuery()); // 搜索age大于27的user数据,这里的写法其实和json查询语句的写法一样的，如下 /* GET /bank/_search { "query": { "bool": { "must": { "match_all": {} }, "filter": { "range": { "balance": { "gte": 20000, "lte": 30000 } } } } } } */ builder.withQuery(QueryBuilders.boolQuery() .must(QueryBuilders.matchAllQuery()) .filter(QueryBuilders.rangeQuery("age").gte(27))); NativeSearchQuery query = builder.build(); SearchHits<User> searchHits = elasticsearchRestTemplate.search(query, User.class); for (org.springframework.data.elasticsearch.core.SearchHit<User> searchHit : searchHits) { System.out.println(searchHit.getContent()); } } // 查询年龄大于10岁的用户的数量 @Test public void myTest14() { NativeSearchQueryBuilder builder = new NativeSearchQueryBuilder(); builder.addAggregation(AggregationBuilders .filter("age_gt_10", QueryBuilders.rangeQuery("age").gt(10)) .subAggregation(AggregationBuilders.count("group_by_count").field("name"))); NativeSearchQuery searchQuery = builder.build(); SearchHits<User> search = elasticsearchRestTemplate.search(searchQuery, User.class); Filter age_gt_10 = search.getAggregations().get("age_gt_10"); Aggregations aggregations = age_gt_10.getAggregations(); ValueCount count = aggregations.get("group_by_count"); System.out.println(count.getValue()); }
ElasticsearchRestTemplate适合做一些复杂的搜索操作，比如聚合搜索等。需要注意的是，ElasticsearchRestTemplate查询返回的结果需要传入我们的数据实体类User.class。
@Data @Document(indexName = "users") // 将此类标记为Document，索引是users，对应es里的数据 @Builder public class User { @Id private Long id; @Field(type = FieldType.Keyword) private String name; @Field(type = FieldType.Long) private Integer age; @Field(type = FieldType.Date,format= DateFormat.basic_date) private Date birthday; }
还有一个需要注意：在上面的代码myTest14函数中，builder的写法需要基本是和es的json查询语句一样的，如下：
输出结果是：
3.2使用RestHighLevelClient
@Autowired private RestHighLevelClient restHighLevelClient; @Test void myTest() throws IOException { // 创建一个索引，并设置了id为1的文档数据 IndexRequest request = new IndexRequest("spring-data3") .id("1") .opType(DocWriteRequest.OpType.CREATE) .source("name", "rico2") .setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE); IndexResponse response = restHighLevelClient.index(request, RequestOptions.DEFAULT); System.out.println(response.toString()); restHighLevelClient.close(); // 获取文档内容 @Test void myTest4() throws IOException { GetRequest getRequest = new GetRequest("users", "1"); boolean exists = restHighLevelClient.indices().exists(new GetIndexRequest(getRequest.index()), RequestOptions.DEFAULT); if (exists) { GetResponse getResponse = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT); System.out.println(getResponse.getSourceAsString()); } else { System.out.println("索引不存在!"); } restHighLevelClient.close(); } // 搜索index为users下的所有文档 @Test void myTest5() throws IOException { SearchRequest searchRequest = new SearchRequest("users"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.matchAllQuery()); searchRequest.source(searchSourceBuilder); SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); SearchHit[] hits = search.getHits().getHits(); for (SearchHit hit : hits) { System.out.println(hit.getSourceAsString()); System.out.println("================================="); } } // 查询users下所有用户的年龄平均值 @Test public void myTest12() throws IOException { SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); AvgAggregationBuilder avgAggregationBuilder = AggregationBuilders.avg("average_age").field("age"); searchSourceBuilder.aggregation(avgAggregationBuilder); SearchRequest request = new SearchRequest("users"); request.source(searchSourceBuilder); SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT); Aggregations aggregations = response.getAggregations(); Avg average_age = aggregations.get("average_age"); System.out.println(average_age.getValue()); } // 查询年龄大于10岁的用户的数量，使用restHighLevelClient @Test public void myTest13() throws IOException { SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); FilterAggregationBuilder filter = AggregationBuilders .filter("age_gt_10", QueryBuilders.rangeQuery("age").gt(10)); filter.subAggregation(AggregationBuilders.count("group_by_count").field("name")); searchSourceBuilder.aggregation(filter); SearchRequest request = new SearchRequest("users"); request.source(searchSourceBuilder); SearchResponse response = restHighLevelClient.search(request, RequestOptions.DEFAULT); Aggregations aggregations = response.getAggregations(); Filter age_gt_10 = aggregations.get("age_gt_10"); Aggregations aggregations1 = age_gt_10.getAggregations(); ValueCount group_by_count = aggregations1.get("group_by_count"); System.out.println(group_by_count.getValue()); }
可以看出，RestHighLevelClient既可以做简单的查询，也可以做复杂的查询。如果只需要做简单的数据操作，还是建议用ElasticsearchRepository，代码更简单。和ElasticsearchRestTemplate一样，建立查询条件的代码要参照es的json查询语句的写法，比如这里的myTest13用的就是嵌套查询。
