php - elasticsearch中将content字段设置为ik分词器后再使用 terms 聚合生成类似热门词汇的功能

索引的msg2017-04中201038447的mapping

{"msg2017-04":{"mappings":{"201038447":{"properties":{"@timestamp":{"type":"date"},"content":{"type":"text","boost":8,"analyzer":"ik_smart","include_in_all":true},"createTime":{"type":"date"}}}}}}

索引的settings

{"msg2017-04":{"settings":{"index":{"creation_date":"1492398234434","number_of_shards":"5","number_of_replicas":"1","uuid":"yiGoDhL1T3WLexG79e5uQg","version":{"created":"5020299"},"provided_name":"msg2017-04"}}}}

环境：

• linux

• elasticsearch5.2.2

• 已安装ik分词

分词结果

//requestGET/msg2017-04/_search?pretty{"size":1,"aggs":{"fenci":{"terms":{"field":"content.ik_smart"}}}}//response{"took":2,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":105,"max_score":1,"hits":[{"_index":"msg2017-04","_type":"7510570179@chatroom","_id":"5067959408840553063","_score":1,"_source":{"wxid":"wxid_1idf7gf5jgh822","msgId":"69","msgSvrId":"5067959408840553063","type":0,"isSend":"1","status":"2","speakerId":"","content":"rhh","imei":"867464024215618","room":"7510570179@chatroom","roomName":"和湖光山色hzhzh","roomOwner":"mikezhangsky","roomMembers":"mikezhangsky;wxid_1idf7gf5jgh822;wxid_j56srpxywn5n22;wxid_90uy0wlz229e22;sun461629376","roomSize":"5","createTime":"2017-04-07T03:08:37","@timestamp":"2017-04-17T03:14:15"}}]},"aggregations":{"fenci":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[]}}}

我想通过中文分词后再聚合，这样就可以实时的统计出一段时间内的热词，类似微博的热搜。

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