聚合查询是es除搜索功能外提供的针对es数据做统计分析的功能。聚合有助于根据搜索查询提供聚合数据。聚合查询是数据库中重要的功能特性，ES作为搜索引擎兼数据库，同样提供了强大的聚合分析能力。它基于查询条件来对数据进行分桶、计算的方法。有点类似于 SQL 中的 group by 再加一些函数方法的操作。

注意：text类型是不支持聚合的。

测试数据

# 创建索引 index 和映射 mapping
PUT /fruit
{
  "mappings": {
    "properties": {
      "title":{
        "type": "keyword"
      },
      "price":{
        "type":"double"
      },
      "description":{
        "type": "text",
        "analyzer": "ik_max_word"
      }
    }
  }
}
# 放入测试数据
PUT /fruit/_bulk
{"index":{}}
  {"title" : "面包","price" : 19.9,"description" : "小面包非常好吃"}
{"index":{}}
  {"title" : "旺仔牛奶","price" : 29.9,"description" : "非常好喝"}
{"index":{}}
  {"title" : "日本豆","price" : 19.9,"description" : "日本豆非常好吃"}
{"index":{}}
  {"title" : "小馒头","price" : 19.9,"description" : "小馒头非常好吃"}
{"index":{}}
  {"title" : "大辣片","price" : 39.9,"description" : "大辣片非常好吃"}
{"index":{}}
  {"title" : "透心凉","price" : 9.9,"description" : "透心凉非常好喝"}
{"index":{}}
  {"title" : "小浣熊","price" : 19.9,"description" : "童年的味道"}
{"index":{}}
  {"title" : "海苔","price" : 19.9,"description" : "海的味道"}

使用

根据某个字段分组

GET /fruit/_search
{
  "query": {
    "term": {
      "description": {
        "value": "好吃"
      }
    }
  }, 
  "aggs": {
    "price_group": {
      "terms": {
        "field": "price"
      }
    }
  }
}

求最大值

GET /fruit/_search
{
  "aggs": {
    "price_max": {
      "max": {
        "field": "price"
      }
    }
  }
}

求最小值

GET /fruit/_search
{
  "aggs": {
    "price_min": {
      "min": {
        "field": "price"
      }
    }
  }
}

求平均值

GET /fruit/_search
{
  "aggs": {
    "price_agv": {
      "avg": {
        "field": "price"
      }
    }
  }
}

求和

GET /fruit/_search
{
  "aggs": {
    "price_sum": {
      "sum": {
        "field": "price"
      }
    }
  }
}

整合应用

@Test
public void testAggsPrice() throws IOException {
  SearchRequest searchRequest = new SearchRequest("fruit");
  SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
  sourceBuilder.aggregation(AggregationBuilders.terms("group_price").field("price"));
  searchRequest.source(sourceBuilder);
  SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
  Aggregations aggregations = searchResponse.getAggregations();
  ParsedDoubleTerms terms = aggregations.get("group_price");
  List<? extends Terms.Bucket> buckets = terms.getBuckets();
  for (Terms.Bucket bucket : buckets) {
    System.out.println(bucket.getKey() + ", "+ bucket.getDocCount());
  }
}

// 求不同名称的数量
@Test
public void testAggsTitle() throws IOException {
  SearchRequest searchRequest = new SearchRequest("fruit");
  SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
  sourceBuilder.aggregation(AggregationBuilders.terms("group_title").field("title"));
  searchRequest.source(sourceBuilder);
  SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
  Aggregations aggregations = searchResponse.getAggregations();
  ParsedStringTerms terms = aggregations.get("group_title");
  List<? extends Terms.Bucket> buckets = terms.getBuckets();
  for (Terms.Bucket bucket : buckets) {
  	System.out.println(bucket.getKey() + ", "+ bucket.getDocCount());
  }
}

// 求和
@Test
public void testAggsSum() throws IOException {
  SearchRequest searchRequest = new SearchRequest("fruit");
  SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
  sourceBuilder.aggregation(AggregationBuilders.sum("sum_price").field("price"));
  searchRequest.source(sourceBuilder);
  SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
  ParsedSum parsedSum = searchResponse.getAggregations().get("sum_price");
  System.out.println(parsedSum.getValue());
}