_score为null,因为它并没有用于排序。 date 字段的值表示为自 epoch (January 1, 1970 00:00:00 UTC)以来的毫秒数,通过 sort 字段的值进行返回。 多级排序 很多时候,我们的排序都是需要多级的。如下,先按照date的值逆序排序,date相同的按_score逆序排序。(_score是搜索的匹配度) GET /_search { "query" :...
默认的,返回的结 果中关联性最大的文档排在首位;这意味着,它是按照 _score 降序排列的 空搜索的情况下,我们没有指定任何查询,所以所有 文档的相关性是一样的,因此所有结果的 _score 都是取得一个中间值 1 max_score 指的是所有文档匹配查询中 _score 的最大值。 2.2 took took 告诉我们整个搜索请求花费的...
{ "took" : 1, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 1000, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "avg_balance" : { "...
{"took":396,"timed_out":false,"_shards": {"total":3,"successful":3,"skipped":0,"failed":0},"hits": {"total": {"value":7,"relation":"eq"},"max_score":null,"hits": [ ] },"aggregations": {"type_bucket": {"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buc...
{"took":2,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":10000,"relation":"gte"},"max_score":null,"hits":[]},"aggregations":{"dest":{"doc_count_error_upper_bound":0,"sum_other_doc_count":7605,"buckets":[{"key...
"value": 0, "relation": "eq" }, "max_score": null, "hits": [] } } 并没有搜索出结果,说明在进行分词时,西瓜是作为一个词出现的,并没有拆分成每一个字,这也是符合我们预期的。 好了~ 这一节的IK中文分词器就给大家介绍到这里了~~
1{2"took" : 2,3"timed_out" :false,4"_shards" :{5"total" : 9,6"successful" : 9,7"skipped" : 0,8"failed" : 09},10"hits" :{11"total" :{12"value" : 620,13"relation" : "eq"14},15"max_score" :null,16"hits" :[ ]17},18"aggregations" :{19"target" :{20"doc_count...
{"took":1,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":1000,"relation":"eq"},"max_score":null,"hits":[]},"aggregations":{"avg_balance":{"value":25714.837}}} ...
}, "hits": { "total": 84, "max_score": null, "hits": [] } } 优化scroll查询 在一般场景下,scroll通常用来取得需要排序过后的大笔数据,但是有时候数据之间的排序性对我们而言是没有关系的,只要所有数据都能取出来就好,这时能够对scroll进行优化 ...
{"took":2,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":5,// 这里的值是折叠前的文档个数"relation":"eq"},"max_score":null,"hits":[{"_index":"product","_id":"1","_score":null,"_source":{"name":"xiaomi pho...