GET /jzt_study_detail/content/_search { "size": 0, "aggs": { "group_by_channelids": { "terms": { "field": "channelIds", "size": 5, "order": { "sum_views": "desc" } }, "aggs": { "avg_views": { "avg": { "field": "views" } }, "sum_views": { "sum": { "field": "views" } } } } } }
使用terms进行分组操作，用于分组操作字段应该设置成不分词，然后通过内部包含aggs的max以及avg去进行数据聚合以及字段排序。
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buck aggs方式分为两种，一种是range（按照数据区间分组），另一种是term（按照指定的字段分组，多个字段可嵌套分组），上面的json为按照term分组
按照range分组如下：
POST /index_test_1/type_test_1/_search { "size": 0, "aggs": { "group_by_views": { "range": { "field": "views", "ranges": [ { "key": "<2", "to": 2 }, { "to": 3, "from": 2 }, { "to": 4, "from": 3 } , { "key": ">4", "from": 4 } ] }, "aggs":{ "sum_views":{ "sum":{ "field": "views" } }, "avg_views":{ "avg": { "field": "views" } } } } } }
分组操作后，可以使用top_hit方式求组内某一指标的排序topN，如下json：
POST /index_test_1/type_test_1/_search { "size": 0, "aggs": { "group_view": { "terms": { "field": "content_type", "size": 10 }, "aggs": { "top_title": { "top_hits": { "size": 10, "sort": [ { "views":{ "order": "desc" } } ] } } } } } }
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PUT /index_test_1 { "mappings": { "type_test_1":{ "properties":{ "title":{ "type":"text", "fielddata":true, "fields": {"raw": {"type": "keyword"}} }, "views":{ "type":"long" }, "content_type":{ "type":"keyword" } } } } } POST /index_test_1/type_test_1/a1 { "title":"我的名字", "views":1, "content_type":"viedo" } POST /index_test_1/type_test_1/a2 { "title":"中国人的名字", "views":2, "content_type":"viedo" } POST /index_test_1/type_test_1/a3 { "title":"中国人是最牛的", "views":3, "content_type":"word" } POST /index_test_1/type_test_1/a4 { "title":"我爱你中国", "views":4, "content_type":"word" } POST /index_test_1/type_test_1/a5 { "title":"在水中的国家", "views":5, "content_type":"word" }
GET /index_test_1/_search { "size": 0, "aggs": { "views_histogram": { "histogram": { "field": "views", "interval": 2, "min_doc_count": 0, "extended_bounds": { "min": 0, "max": 6 }, "order": { "sum_views": "desc" } }, "aggs": { "sum_views": { "sum": { "field": "views" } } } } } }
以上是数据示例，按照区间段进行分组后聚合views并排序入下：
POST /index_test_1/type_test_1/_search { "size": 0, "aggs": { "histogram_views": { "histogram": { "field": "views", 按照该字段进行分区间汇总，比如柱状图 "interval": 2 , 区间窗口间隔为2
"min_doc_count": 0, 空的区间段返回0 "extended_bounds" : { "min" : 0, 分区间的开始位置 "max" : 6 分区间的结束位置 } }, "aggs":{ "group_by_title":{ "terms": { "field": "title.raw", 不能使用分词后的聚合方式，raw已经指定了keyword不分词。 "order": { "sum_views": "asc" } }, "aggs": { "sum_views": { "sum": { "field": "views" } } } } } } } }
如果涉及按照月份或者季度聚合应该使用如下形式：
GET /tvs/sales/_search { "size": 0, "aggs": { "group_by_sold_date": { "date_histogram": { "field": "sold_date", "interval": "quarter", 也可以是month "format": "yyyy-MM-dd", "min_doc_count": 0, 即使为空的区间，也要返回 "extended_bounds" : { "min" : "2016-01-01", "max" : "2017-01-01" } }, "aggs": { "group_by_brand": { "terms": { "field": "brand" }, "aggs": { "sum_price": { "sum": { "field": "price" } } } }, "total_sum_price" : { "sum": { "field": "price" } } } } } }
检索自定义分数计算函数：
GET /index_test_1/type_test_1/_search { "query": { "function_score": { "query": { "bool": { "must": [ { "match": { "title": { "query":"中国", "boost": 0.1 } } } ] } } , "functions": [ { "field_value_factor": { "field": "views" #views字段参与自定义分数计算，获取views的值后乘以weight }, "weight":10 } ] , "score_mode": "sum", "boost_mode": "sum" #搜索分词分值与自定义分值函数计算使用加法，这样整体的分值计算不会出现突增突降问题 } }, "sort": { "_score": { "order": "desc" } } }