1.1 bucket
有如下数据
| city | name |
| 北京 | 张三 |
| 北京 | 李四 |
| 天津 | 王五 |
| 天津 | 赵六 |
| 天津 | 王麻子 |
划分出来两个bucket，一个是北京bucket，一个是天津bucket
北京bucket：包含了2个人，张三，李四
上海bucket：包含了3个人，王五，赵六，王麻子
1.2 metric
metric，就是对一个bucket执行的某种聚合分析的操作，比如说求平均值，求最大值，求最小值
比如下面的一个sql语句
select count(*) from book group studymodelbucket：group by studymodel --> 那些studymodel相同的数据，就会被划分到一个bucket中
metric：count(*)，对每个bucket中所有的数据，计算一个数量。例如avg()，sum()，max()，min()
二、聚合示例
2.1 数据准备
首先创建book索引
PUT /book/ { "settings": { "number_of_shards": 1, "number_of_replicas": 0 }, "mappings": { "properties": { "name": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart" }, "description": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart" }, "studymodel": { "type": "keyword" }, "price": { "type": "double" }, "timestamp": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis" }, "pic": { "type": "text", "index": false } } } }添加测试数据
PUT /book/_doc/1 { "name": "Bootstrap开发", "description": "Bootstrap是一个非常流行的开发框架。此开发框架可以帮助不擅长css页面开发的程序人员轻松的实现一个css，不受浏览器限制的精美界面css效果。", "studymodel": "201002", "price": 38.6, "timestamp": "2019-08-25 19:11:35", "pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg", "tags": [ "bootstrap", "dev" ] } PUT /book/_doc/2 { "name": "java编程思想", "description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。", "studymodel": "201001", "price": 68.6, "timestamp": "2019-08-25 19:11:35", "pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg", "tags": [ "java", "dev" ] } PUT /book/_doc/3 { "name": "spring开发基础", "description": "spring 在java领域非常流行，java程序员都在用。", "studymodel": "201001", "price": 88.6, "timestamp": "2019-08-24 19:11:35", "pic": "group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg", "tags": [ "spring", "java" ] }2.2 计算每个studymodel下的商品数量
sql语句： select studymodel，count(*) from book group by studymodel
"size": 0, ==> 作用 ：只需要聚合的数据，不需要查询的数据
GET /book/_search { "size": 0, "query": { "match_all": {} }, "aggs": { "group_by_model": { "terms": { "field": "studymodel" } } } }结果：
{ "took" : 2, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 3, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_model" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "201001", "doc_count" : 2 }, { "key" : "201002", "doc_count" : 1 } ] } } }2.3 计算每个tags下的商品数量
设置字段"fielddata": true，不设置会报错
PUT /book/_mapping/ { "properties": { "tags": { "type": "text", "fielddata": true } } }查询
GET /book/_search { "size": 0, "query": { "match_all": {} }, "aggs": { "group_by_tags": { "terms": { "field": "tags" } } } }结果：
{ "took" : 2, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 3, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "dev", "doc_count" : 2 }, { "key" : "java", "doc_count" : 2 }, { "key" : "bootstrap", "doc_count" : 1 }, { "key" : "spring", "doc_count" : 1 } ] } } }2.4 加上搜索条件，计算每个tags下的商品数量
GET /book/_search { "size": 0, "query": { "match": { "description": "java程序员" } }, "aggs": { "group_by_tags": { "terms": { "field": "tags" } } } }结果：
{ "took" : 70, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 2, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "java", "doc_count" : 2 }, { "key" : "dev", "doc_count" : 1 }, { "key" : "spring", "doc_count" : 1 } ] } } }2.5 计算每个tag下的商品的平均价格
子聚合
GET /book/_search { "size": 0, "aggs": { "group_by_tags": { "terms": { "field": "tags" }, "aggs": { "avg_price": { "avg": { "field": "price" } } } } } }结果：
{ "took" : 0, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 3, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "dev", "doc_count" : 2, "avg_price" : { "value" : 53.599999999999994 } }, { "key" : "java", "doc_count" : 2, "avg_price" : { "value" : 78.6 } }, { "key" : "bootstrap", "doc_count" : 1, "avg_price" : { "value" : 38.6 } }, { "key" : "spring", "doc_count" : 1, "avg_price" : { "value" : 88.6 } } ] } } }2.6 计算每个tag下的商品的平均价格，按照平均价格降序排序
小技巧，如果是查询全部，match_all可省略
GET /book/_search { "size": 0, "aggs": { "group_by_tags": { "terms": { "field": "tags", "order": { "avg_price": "desc" } }, "aggs": { "avg_price": { "avg": { "field": "price" } } } } } }结果：
{ "took" : 4, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 3, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "spring", "doc_count" : 1, "avg_price" : { "value" : 88.6 } }, { "key" : "java", "doc_count" : 2, "avg_price" : { "value" : 78.6 } }, { "key" : "dev", "doc_count" : 2, "avg_price" : { "value" : 53.599999999999994 } }, { "key" : "bootstrap", "doc_count" : 1, "avg_price" : { "value" : 38.6 } } ] } } }2.7 按照指定的价格范围区间进行分组，然后在每组内再按照tag进行分组，最后再计算每组的平均价格
GET /book/_search { "size": 0, "aggs": { "group_by_price": { "range": { "field": "price", "ranges": [ { "from": 0, "to": 40 }, { "from": 40, "to": 60 }, { "from": 60, "to": 80 } ] }, "aggs": { "group_by_tags": { "terms": { "field": "tags" }, "aggs": { "average_price": { "avg": { "field": "price" } } } } } } } }结果：
{ "took" : 5, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 3, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "aggregations" : { "group_by_price" : { "buckets" : [ { "key" : "0.0-40.0", "from" : 0.0, "to" : 40.0, "doc_count" : 1, "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "bootstrap", "doc_count" : 1, "average_price" : { "value" : 38.6 } }, { "key" : "dev", "doc_count" : 1, "average_price" : { "value" : 38.6 } } ] } }, { "key" : "40.0-60.0", "from" : 40.0, "to" : 60.0, "doc_count" : 0, "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ ] } }, { "key" : "60.0-80.0", "from" : 60.0, "to" : 80.0, "doc_count" : 1, "group_by_tags" : { "doc_count_error_upper_bound" : 0, "sum_other_doc_count" : 0, "buckets" : [ { "key" : "dev", "doc_count" : 1, "average_price" : { "value" : 68.6 } }, { "key" : "java", "doc_count" : 1, "average_price" : { "value" : 68.6 } } ] } } ] } } }
