执行聚合 · my-elasticsearch-cn

# 执行聚合聚合提供了分组并统计数据的能力。理解聚合的最简单的方式是将其粗略地等同为SQL的GROUP BY和SQL聚合函数。在Elasticsearch中，你可以在一个响应中同时返回命中的数据和聚合结果。你可以使用简单的API同时运行查询和多个聚合并一次返回，这避免了来回的网络通信，是非常强大和高效的。首先，这个例子演示了根据账户所在的州来统计各个州的账户数，并返回账户数最多的前10个州（默认大小为10）： ``` GET /bank/_search { "size": 0, "aggs": { "group_by_state": { "terms": { "field": "state.keyword" } } } } ``` 在SQL中，上面的聚合在概念上类似于： ``` SELECT COUNT(*) from bank GROUP BY state ORDER BY COUNT(*) DESC ``` 响应（其中一部分）是： ``` { "took": 29, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits" : { "total" : 1000, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "group_by_state" : { "doc_count_error_upper_bound": 20, "sum_other_doc_count": 770, "buckets" : [ { "key" : "ID", "doc_count" : 27 }, { "key" : "TX", "doc_count" : 27 }, { "key" : "AL", "doc_count" : 25 }, { "key" : "MD", "doc_count" : 25 }, { "key" : "TN", "doc_count" : 23 }, { "key" : "MA", "doc_count" : 21 }, { "key" : "NC", "doc_count" : 21 }, { "key" : "ND", "doc_count" : 21 }, { "key" : "ME", "doc_count" : 20 }, { "key" : "MO", "doc_count" : 20 } ] } } } ``` 我们可以看到`ID`（Idaho）州有27个账户，紧跟着`TX`（Texas）州有27个账户、`AL`（Alabama）有25个账户，依此类推。注意我们将`size`设置成 0，这样我们就可以只看到聚合结果了，而不会显示命中的文档的详细结果。在先前聚合的基础上，现在这个例子计算了每个州的账户的平均存款（还是按照账户数量倒序排序的前10个州）： ``` GET /bank/_search { "size": 0, "aggs": { "group_by_state": { "terms": { "field": "state.keyword" }, "aggs": { "average_balance": { "avg": { "field": "balance" } } } } } } ``` 注意，我们把`average_balance`聚合嵌套在了`group_by_state`聚合之中。这是所有聚合的一个常用模式。你可以在任意的聚合之中嵌套聚合，这样就可以从你的数据中抽取出想要的结果。在前面的聚合的基础上，现在让我们按照平均余额进行排序： ``` GET /bank/_search { "size": 0, "aggs": { "group_by_state": { "terms": { "field": "state.keyword", "order": { "average_balance": "desc" } }, "aggs": { "average_balance": { "avg": { "field": "balance" } } } } } } ``` 下面的例子显示了如何使用年龄段（20-29，30-39，40-49）分组，然后再用性别分组，最后为每一个年龄段的每组性别计算平均账户余额。 ``` GET /bank/_search { "size": 0, "aggs": { "group_by_age": { "range": { "field": "age", "ranges": [ { "from": 20, "to": 30 }, { "from": 30, "to": 40 }, { "from": 40, "to": 50 } ] }, "aggs": { "group_by_gender": { "terms": { "field": "gender.keyword" }, "aggs": { "average_balance": { "avg": { "field": "balance" } } } } } } } } ``` There are many other aggregations capabilities that we won’t go into detail here. The [aggregations reference guide](https://www.elastic.co/guide/en/elasticsearch/reference/6.0/search-aggregations.html) is a great starting point if you want to do further experimentation.