聚合可以實現對文檔數據的統計，分析，運算，聚合常見有三類（聚合的值一定不能是text類型的）：

桶（Bucket）聚合：用來對文檔做分組。

度量（Metric）聚合：用以計算一些值，比方說最大值，最小值，平均值等。

管道（pipeline）聚合：其它聚合的結果為基礎進行聚合。

參與聚合的字段類型：keyword，數值，日期，布爾。

DSL實現Bucket聚合

lasticsearch 的 Bucket 聚合（桶聚合）是將文檔分組到 "桶" 中的強大工具，類似于 SQL 中的GROUP BY。每個桶關聯一個條件，符合條件的文檔會被分到對應的桶中。

Terms聚合

• 場景：統計博客文章中每個標簽的文檔數量。

• GET /blog/_search
  {"size": 0, ?// 不返回原始文檔，只返回聚合結果"aggs": {"tags": {"terms": {"field": "tags.keyword", ?// 使用keyword類型避免分詞"size": 10, ?// 返回前10個最常見的標簽"order": {"_count": "desc" ?// 按文檔數量降序排序}}}}
  }
  結果示例
  {"aggregations": {"tags": {"doc_count_error_upper_bound": 0,"sum_other_doc_count": 15,"buckets": [{"key": "elasticsearch","doc_count": 25},{"key": "java","doc_count": 18}]}}
  }
  //大多數 Bucket 聚合默認按文檔數量（_count）降序排序。
  //按文檔數量排序DSL演示
  GET /products/_search
  {"size": 0,"aggs": {"by_category": {"terms": {"field": "category.keyword","order": {"_count": "desc" ?// 按文檔數量降序（默認）}}}}
  }
  //結果演示
  {"aggregations": {"by_category": {"buckets": [{ "key": "electronics", "doc_count": 120 },{ "key": "clothing", "doc_count": 80 },{ "key": "books", "doc_count": 50 }]}}
  }
  //場景：只對價格大于 100 的商品進行類別聚合
  //DSL示例
  GET /products/_search
  {"query": {"range": {"price": {"gt": 100}}},"size": 0,"aggs": {"by_category": {"terms": {"field": "category.keyword"}}}
  }
  //結果顯示
  {"aggregations": {"by_category": {"buckets": [{"key": "electronics","doc_count": 100,"expensive_products": {"doc_count": 75, ?// 價格>100的電子產品數量"count": {"value": 75}}}]}}
  }

• aggs代表聚合，與query同級，此時query的作用是限定聚合的的文檔范圍

• 聚合必須的三要素

  • 聚合名稱

  • 聚合類型

  • 聚合字段

• 聚合可配置的屬性有：size：指定聚合結果數量，order指定聚合結果排序方式，field指定聚合字段。

DSL實現Metric聚合

計算所有產品的平均價格

GET /products/_search
{"size": 0, ?// 不返回原始文檔"aggs": {"avg_price": {"avg": {"field": "price"}}}
}
//結果顯示
{"aggregations": {"avg_price": {"value": 125.5 ?// 平均價格}}
}

嵌套聚合metric聚合的組合使用

//按類別分組，計算每個類別的平均價格、最高價格和最低價格。
GET /products/_search
{"size": 0,"aggs": {"by_category": {"terms": {"field": "category.keyword"},"aggs": {"avg_price": { "avg": { "field": "price" } },"max_price": { "max": { "field": "price" } },"min_price": { "min": { "field": "price" } },"price_stats": { "stats": { "field": "price" } }}}}
}

在java中進行聚合

import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.aggregations.AggregationBuilders;
import org.elasticsearch.search.aggregations.bucket.filter.Filter;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.builder.SearchSourceBuilder;
?
import java.io.IOException;
?
public class FilterAggregationExample {private final RestHighLevelClient client;public FilterAggregationExample(RestHighLevelClient client) {this.client = client;}public void filterAggregation() throws IOException {SearchRequest searchRequest = new SearchRequest("products");SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();// 構建按類別分組的聚合，在每個類別中過濾價格>100的商品searchSourceBuilder.aggregation(AggregationBuilders.terms("by_category").field("category.keyword").subAggregation(AggregationBuilders.filter("expensive_products",QueryBuilders.rangeQuery("price").gt(100)).subAggregation(AggregationBuilders.valueCount("count").field("id"))));searchRequest.source(searchSourceBuilder);SearchResponse response = client.search(searchRequest, RequestOptions.DEFAULT);// 處理聚合結果Terms byCategory = response.getAggregations().get("by_category");for (Terms.Bucket bucket : byCategory.getBuckets()) {String category = bucket.getKeyAsString();long totalCount = bucket.getDocCount();Filter expensiveProducts = bucket.getAggregations().get("expensive_products");long expensiveCount = expensiveProducts.getDocCount();System.out.println("Category: " + category + ", Total: " + totalCount + ", Expensive: " + expensiveCount);}}
}