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
}
}
]
}
}
]
}
}
}