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。
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