- 折叠+取 inner_hits 分两阶段执行（组合聚合的方式只有一个阶段），所以 top hits 永远是精确的。
- 字段折叠只在 top hits 层执行，不需要每次都在完整的结果集上对为每个折叠主键计算实际的 doc values 值，只对 top hits 这小部分数据操作就可以，和 term agg 相比要节省很多内存。
- 因为只在 top hits 上进行折叠，所以相比组合聚合的方式，速度要快很多。
- 折叠 top docs 不需要使用全局序列（global ordinals）来转换 string，相比 agg 这也节省了很多内存。
- 分页成为可能，和常规搜索一样，具有相同的局限，先获取 from+size 的内容，再合并。
- search_after 和 scroll 暂未实现，不过具备可行性。
- 折叠只影响搜索结果，不影响聚合，搜索结果的 total 是所有的命中纪录数，去重的结果数未知（无法计算）。
下面来看看具体的例子，就知道怎么回事了，使用起来很简单。
- 先准备索引和数据，这里以菜谱为例，name：菜谱名，type 为菜系，rating 为用户的累积平均评分
DELETE recipesPUT recipesPOST recipes/type/_mapping{ "properties": { "name":{ "type": "text" }, "rating":{ "type": "float" },"type":{ "type": "keyword" } }}POST recipes/type/{ "name":"清蒸鱼头","rating":1,"type":"湘菜"}POST recipes/type/{ "name":"剁椒鱼头","rating":2,"type":"湘菜"}POST recipes/type/{ "name":"红烧鲫鱼","rating":3,"type":"湘菜"}POST recipes/type/{ "name":"鲫鱼汤（辣）","rating":3,"type":"湘菜"}POST recipes/type/{ "name":"鲫鱼汤（微辣）","rating":4,"type":"湘菜"}POST recipes/type/{ "name":"鲫鱼汤（变态辣）","rating":5,"type":"湘菜"}POST recipes/type/{ "name":"广式鲫鱼汤","rating":5,"type":"粤菜"}POST recipes/type/{ "name":"鱼香肉丝","rating":2,"type":"川菜"}POST recipes/type/{ "name":"奶油鲍鱼汤","rating":2,"type":"西菜"}
- 现在我们看看普通的查询效果是怎么样的，搜索关键字带“鱼”的菜，返回3条数据
POST recipes/type/_search{ "query": {"match": { "name": "鱼" }},"size": 3} 全是湘菜，我的天，最近上火不想吃辣，这个第一页的结果对我来说就是垃圾，如下：
{ "took": 2, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": 0.26742277, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYF_OA-dG63Txsd", "_score": 0.26742277, "_source": { "name": "鲫鱼汤（变态辣）", "rating": 5, "type": "湘菜" } }, { "_index": "recipes", "_type": "type", "_id": "AVoESHXO_OA-dG63Txsa", "_score": 0.19100356, "_source": { "name": "红烧鲫鱼", "rating": 3, "type": "湘菜" } }, { "_index": "recipes", "_type": "type", "_id": "AVoESHWy_OA-dG63TxsZ", "_score": 0.19100356, "_source": { "name": "剁椒鱼头", "rating": 2, "type": "湘菜" } } ] }} 我们再看看，这次我想加个评分排序，大家都喜欢的是那些，看看有没有喜欢吃的，执行查询：
POST recipes/type/_search{ "query": {"match": { "name": "鱼" }},"sort": [ { "rating": { "order": "desc" } } ],"size": 3} 结果稍微好点了，不过3个里面2个是湘菜，还是有点不合适，结果如下：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYF_OA-dG63Txsd", "_score": null, "_source": { "name": "鲫鱼汤（变态辣）", "rating": 5, "type": "湘菜" }, "sort": [ 5 ] }, { "_index": "recipes", "_type": "type", "_id": "AVoESHYW_OA-dG63Txse", "_score": null, "_source": { "name": "广式鲫鱼汤", "rating": 5, "type": "粤菜" }, "sort": [ 5 ] }, { "_index": "recipes", "_type": "type", "_id": "AVoESHX7_OA-dG63Txsc", "_score": null, "_source": { "name": "鲫鱼汤（微辣）", "rating": 4, "type": "湘菜" }, "sort": [ 4 ] } ] }} 现在我知道了，我要看看其他菜系，这家不是还有西餐、广东菜等各种菜系的么，来来，帮我每个菜系来一个菜看看，换 terms agg 先得到唯一的 term 的 bucket，再组合 top_hits agg，返回按评分排序的第一个 top hits，有点复杂，没关系，看下面的查询就知道了：
GET recipes/type/_search{ "query": { "match": { "name": "鱼" } }, "sort": [ { "rating": { "order": "desc" } } ],"aggs": { "type": { "terms": { "field": "type", "size": 10 },"aggs": { "rated": { "top_hits": { "sort": [{ "rating": {"order": "desc"} }], "size": 1 } } } } }, "size": 0, "from": 0} 看下面的结果，虽然 json 结构有点复杂，不过总算是我们想要的结果了，湘菜、粤菜、川菜、西菜都出来了，每样一个，不重样：
{ "took": 4, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": 0, "hits": [] }, "aggregations": { "type": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": "湘菜", "doc_count": 6, "rated": { "hits": { "total": 6, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYF_OA-dG63Txsd", "_score": null, "_source": { "name": "鲫鱼汤（变态辣）", "rating": 5, "type": "湘菜" }, "sort": [ 5 ] } ] } } }, { "key": "川菜", "doc_count": 1, "rated": { "hits": { "total": 1, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYr_OA-dG63Txsf", "_score": null, "_source": { "name": "鱼香肉丝", "rating": 2, "type": "川菜" }, "sort": [ 2 ] } ] } } }, { "key": "粤菜", "doc_count": 1, "rated": { "hits": { "total": 1, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYW_OA-dG63Txse", "_score": null, "_source": { "name": "广式鲫鱼汤", "rating": 5, "type": "粤菜" }, "sort": [ 5 ] } ] } } }, { "key": "西菜", "doc_count": 1, "rated": { "hits": { "total": 1, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHY3_OA-dG63Txsg", "_score": null, "_source": { "name": "奶油鲍鱼汤", "rating": 2, "type": "西菜" }, "sort": [ 2 ] } ] } } } ] } }} 上面的实现方法，前面已经说了，可以做，有局限性，那看看新的字段折叠法如何做到呢，查询如下，加一个 collapse 参数，指定对那个字段去重就行了，这里当然对菜系“type”字段进行去重了：
GET recipes/type/_search{ "query": { "match": { "name": "鱼" } }, "collapse": { "field": "type" }, "size": 3, "from": 0} 结果很理想嘛，命中结果还是熟悉的那个味道（和查询结果长的一样嘛），如下：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoDNlRJ_OA-dG63TxpW", "_score": 0.018980097, "_source": { "name": "鲫鱼汤（微辣）", "rating": 4, "type": "湘菜" }, "fields": { "type": [ "湘菜" ] } }, { "_index": "recipes", "_type": "type", "_id": "AVoDNlRk_OA-dG63TxpZ", "_score": 0.013813315, "_source": { "name": "鱼香肉丝", "rating": 2, "type": "川菜" }, "fields": { "type": [ "川菜" ] } }, { "_index": "recipes", "_type": "type", "_id": "AVoDNlRb_OA-dG63TxpY", "_score": 0.0125863515, "_source": { "name": "广式鲫鱼汤", "rating": 5, "type": "粤菜" }, "fields": { "type": [ "粤菜" ] } } ] }} 我再试试翻页，把 from 改一下，现在返回了3条数据，from 改成3，新的查询如下：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoDNlRw_OA-dG63Txpa", "_score": 0.012546891, "_source": { "name": "奶油鲍鱼汤", "rating": 2, "type": "西菜" }, "fields": { "type": [ "西菜" ] } } ] }} 上面的结果只有一条了，去重之后本来就只有4条数据，上面的工作正常，每个菜系只有一个菜啊，那我不乐意了，帮我每个菜系里面多返回几条，我好选菜啊，加上参数 inner_hits 来控制返回的条数，这里返回2条，按 rating 也排个序，新的查询构造如下：
GET recipes/type/_search{ "query": { "match": { "name": "鱼" } }, "collapse": { "field": "type", "inner_hits": { "name": "top_rated", "size": 2, "sort": [ { "rating": "desc" } ] } }, "sort": [ { "rating": { "order": "desc" } } ], "size": 2, "from": 0} 查询结果如下，完美：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 9, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYF_OA-dG63Txsd", "_score": null, "_source": { "name": "鲫鱼汤（变态辣）", "rating": 5, "type": "湘菜" }, "fields": { "type": [ "湘菜" ] }, "sort": [ 5 ], "inner_hits": { "top_rated": { "hits": { "total": 6, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYF_OA-dG63Txsd", "_score": null, "_source": { "name": "鲫鱼汤（变态辣）", "rating": 5, "type": "湘菜" }, "sort": [ 5 ] }, { "_index": "recipes", "_type": "type", "_id": "AVoESHX7_OA-dG63Txsc", "_score": null, "_source": { "name": "鲫鱼汤（微辣）", "rating": 4, "type": "湘菜" }, "sort": [ 4 ] } ] } } } }, { "_index": "recipes", "_type": "type", "_id": "AVoESHYW_OA-dG63Txse", "_score": null, "_source": { "name": "广式鲫鱼汤", "rating": 5, "type": "粤菜" }, "fields": { "type": [ "粤菜" ] }, "sort": [ 5 ], "inner_hits": { "top_rated": { "hits": { "total": 1, "max_score": null, "hits": [ { "_index": "recipes", "_type": "type", "_id": "AVoESHYW_OA-dG63Txse", "_score": null, "_source": { "name": "广式鲫鱼汤", "rating": 5, "type": "粤菜" }, "sort": [ 5 ] } ] } } } } ] }} 好了，字段折叠介绍就到这里。