当前位置：首页 > news >正文

Elasticsearch-ES查询单字段去重

news 2025/7/10 11:51:22

ES 语句

整体数据

GET wkl_test/_search
{"query": {"match_all": {}}
}

结果：

{"took" : 123,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "wkl_test","_type" : "_doc","_id" : "aK0tFpABTkLj5j4c34pE","_score" : 1.0,"_source" : {"name" : "zhangsan","aa" : 1}},{"_index" : "wkl_test","_type" : "_doc","_id" : "aa0uFpABTkLj5j4cFYrJ","_score" : 1.0,"_source" : {"name" : "lisi","aa" : 2}},{"_index" : "wkl_test","_type" : "_doc","_id" : "aq0uFpABTkLj5j4cKYqF","_score" : 1.0,"_source" : {"name" : "wangwu","aa" : 2}},{"_index" : "wkl_test","_type" : "_doc","_id" : "a60uFpABTkLj5j4c2IoF","_score" : 1.0,"_source" : {"name" : "maliu","aa" : 2}},{"_index" : "wkl_test","_type" : "_doc","_id" : "bK1IFpABTkLj5j4cqYop","_score" : 1.0,"_source" : {"name" : "gouqi","aa" : 3}}]}
}

1：collapse折叠功能- 查询去重后的数据列表(ES5.3之后支持)

推荐原因：性能高，占内存小
注意：使用此方式去重时，不会去除掉不存在去重字段的数据。
去重字段只能是数字long类型或keyword。
Field Collapsing（字段折叠）不能与scroll、rescore以及search after 结合使用。

GET wkl_test/_search
{"query": {"match_all": {}},"collapse": {"field": "aa"}
}

结果：hits 中total虽然=5，但是只返回了去重后的 3 条数据

{"took" : 2,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "wkl_test","_type" : "_doc","_id" : "aK0tFpABTkLj5j4c34pE","_score" : 1.0,"_source" : {"name" : "zhangsan","aa" : 1},"fields" : {"aa" : [1]}},{"_index" : "wkl_test","_type" : "_doc","_id" : "aa0uFpABTkLj5j4cFYrJ","_score" : 1.0,"_source" : {"name" : "lisi","aa" : 2},"fields" : {"aa" : [2]}},{"_index" : "wkl_test","_type" : "_doc","_id" : "bK1IFpABTkLj5j4cqYop","_score" : 1.0,"_source" : {"name" : "gouqi","aa" : 3},"fields" : {"aa" : [3]}}]}
}

2：cardinality - 查询去重后的数据总数

聚合+cardinality：即去重计算，类似sql中 count（distinct），先去重再求和
注意：使用此方式统计去重后的数量时，会去除掉不存在去重字段的数据。

GET wkl_test/_search
{"query": {"match_all": {}},"size": 0, "aggs": {"distinct_count": {"cardinality": {"field": "aa"}}}
}

结果：distinct_count = 3,说明去重后有3个，既aggregations聚合下，返回了按名字查询去重后的结果数，但是只有去重后的条数，没有具体的数据。

{"took" : 2,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [ ]},"aggregations" : {"distinct_count" : {"value" : 3}}
}

3：整体语句

使用collapse 折叠查询后，虽然返回了去重后的数据，但是total 还是所有的数据量
使用 cardinality 聚合，虽然在aggs 聚合结果中返回了正确的数据量，但是hits中还是全部的数据
所以我们需要两个综合使用，如下：

GET wkl_test/_search
{"query": {"match_all": {}},"collapse": {"field": "aa"}, "aggs": {"distinct_count": {"cardinality": {"field": "aa"}}}
}

结果：

{"took" : 3,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "wkl_test","_type" : "_doc","_id" : "aK0tFpABTkLj5j4c34pE","_score" : 1.0,"_source" : {"name" : "zhangsan","aa" : 1},"fields" : {"aa" : [1]}},{"_index" : "wkl_test","_type" : "_doc","_id" : "aa0uFpABTkLj5j4cFYrJ","_score" : 1.0,"_source" : {"name" : "lisi","aa" : 2},"fields" : {"aa" : [2]}},{"_index" : "wkl_test","_type" : "_doc","_id" : "bK1IFpABTkLj5j4cqYop","_score" : 1.0,"_source" : {"name" : "gouqi","aa" : 3},"fields" : {"aa" : [3]}}]},"aggregations" : {"distinct_count" : {"value" : 3}}
}

注：我们使用cardinality聚合后的distinct_count 作为去重后的总数，用 collapse 折叠后的列表作为数据结果集

分页使用解释说明：

1.hits中total的总条数实际上是去重前的总条数，原数据条数，这里我们知道就行，分页中我们并不使用它。hits中数组的大小刚好等于courseAgg聚合的值，数组中的数据就是去重后的数据。
2.aggregations中的courseAgg条数，这个才是去重后的实际条数，也是分页用的总条数。
3.from 查询的偏移量，也就是从哪里开始查。
4.size 查询条数，一次查几条。
接下来，你就可以把它当做一个简单分页查询来用了，传入from和size就ok啦~

JAVA API使用

1：collapse 查询去重的结果集

// 使用collapse来指定去重的字段，例如"your_distinct_field"CollapseBuilder collapseBuilder = new CollapseBuilder("your_distinct_field");searchSourceBuilder.collapse(collapseBuilder);

2：cardinality - 查询去重后的数据总数

		// 添加一个cardinality聚合来计算去重字段的唯一值数量CardinalityAggregationBuilder aggregation = AggregationBuilders.cardinality("distinct_count")//这里是聚合结果的字段名.field("your_distinct_field")//这里是需要聚合的字段.precisionThreshold(40000); // 根据需要调整精度阈值searchSourceBuilder.aggregation(aggregation);

3：整体使用

package com.wenge.system.utils;import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.metrics.CardinalityAggregationBuilder;
import org.elasticsearch.search.aggregations.metrics.ParsedCardinality;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.collapse.CollapseBuilder;import java.io.IOException;
import java.util.Map;/*** @author wangkanglu* @version 1.0* @description* @date 2024-06-17 16:48*/
public class TestES {public static void main(String[] args) throws IOException {//创建ES客户端RestHighLevelClient esClient = new RestHighLevelClient(RestClient.builder(new HttpHost("localhost",9200,"http")));try {// 创建一个搜索请求并设置索引名SearchRequest searchRequest = new SearchRequest("your_index");// 构建搜索源构建器SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();// 设置查询条件，例如匹配所有文档，这里根据业务自己修改searchSourceBuilder.query(QueryBuilders.matchAllQuery());// 使用collapse来指定去重的字段，例如"your_distinct_field"CollapseBuilder collapseBuilder = new CollapseBuilder("your_distinct_field");searchSourceBuilder.collapse(collapseBuilder);// 添加一个cardinality聚合来计算去重字段的唯一值数量CardinalityAggregationBuilder aggregation = AggregationBuilders.cardinality("distinct_count")//这里是聚合结果的字段名.field("your_distinct_field")//这里是需要聚合的字段.precisionThreshold(40000); // 根据需要调整精度阈值searchSourceBuilder.aggregation(aggregation);// 设置搜索源searchRequest.source(searchSourceBuilder);// 执行搜索SearchResponse searchResponse = esClient.search(searchRequest, RequestOptions.DEFAULT);SearchHit[] hits = searchResponse.getHits().getHits();for (SearchHit hit : hits) {Map<String, Object> sourceAsMap = hit.getSourceAsMap();System.out.println("去重结果: " + sourceAsMap);}// 处理搜索结果，获取去重数量ParsedCardinality parsedCardinality = searchResponse.getAggregations().get("distinct_count");long distinctCount = parsedCardinality.getValue();System.out.println("去重结果数量:" + distinctCount);} finally {// 关闭clientesClient.close();}}
}