Elasticsearch7.3教程中，第二十七章具体讲解了哪些内容？

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一、两个核心概念：bucket 和 metric 1.1 bucket。数据示例：北京、张三、北京、李四、天津、王五、天津、赵六、天津、王麻子、划分出两个 bucket，一个是北京 bucket，一个是天津 bucket。北京 bucket：包含北京相关的数据。

一、两个核心概念：bucket和metric 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 studymodel

bucket：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 } } ] } } ] } } }