第一个分析需求：计算每个tag下的商品数量
将文本field的fielddata属性设置为true
ES 7.X 命令：
PUT /ecommerce/_mapping/{"properties": {"tags": {"type": "text","fielddata": true}}}
在执行：
GET /ecommerce/_search
{
"aggs": {
"group_by_tags": { # group_by_tags 只是一个名字, 随意定义
"terms": { "field":"tags"}
}
},
"size": 0
}
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "fangzhu",
"doc_count" : 2
},
{
"key" : "meibai",
"doc_count" : 2
},
{
"key" : "qingxin",
"doc_count" : 2
}
]
}
}
}
第二个聚合分析的需求：对名称中包含yagao的商品，计算每个tag下的商品数量
ES 7.x 命令, 其实 ES7.X 处理没有type 之外，整体的查询方式是和ES 5.X 是差不多的：
GET /ecommerce/_search
{
"query": {
"match": {
"name": "yagao"
}
},
"aggs": {
"group_by_tags": {
"terms": { "field":"tags"}
}
},
"size": 0
}
结果：
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "fangzhu",
"doc_count" : 2
},
{
"key" : "meibai",
"doc_count" : 2
},
{
"key" : "qingxin",
"doc_count" : 2
}
]
}
}
}
第三个聚合分析的需求：先分组，再算每组的平均值，计算每个tag下的商品的平均价格
GET /ecommerce/_search
{
"size": 0,
"aggs" : {
"group_by_tags" : {
"terms" : { "field" : "tags" },
"aggs" : {
"avg_price" : {
"avg" : { "field" : "price" }
}
}
}
}
}
结果集：
{
"took" : 22,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "fangzhu",
"doc_count" : 2,
"avg_price" : {
"value" : 27.5
}
},
{
"key" : "meibai",
"doc_count" : 2,
"avg_price" : {
"value" : 40.0
}
},
{
"key" : "qingxin",
"doc_count" : 2,
"avg_price" : {
"value" : 45.0
}
}
]
}
}
}
第四个数据分析需求：计算每个tag下的商品的平均价格，并且按照平均价格降序排序
GET /ecommerce/_search
{
"size": 0,
"aggs": {
"group_by_tags": {
"terms": {
"field": "tags",
"order": {
"avg_price": "desc"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
}
}
结果集：
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "qingxin",
"doc_count" : 2,
"avg_price" : {
"value" : 45.0
}
},
{
"key" : "meibai",
"doc_count" : 2,
"avg_price" : {
"value" : 40.0
}
},
{
"key" : "fangzhu",
"doc_count" : 2,
"avg_price" : {
"value" : 27.5
}
}
]
}
}
}
我们现在全部都是用es的restful api在学习和讲解es的所欲知识点和功能点，但是没有使用一些编程语言去讲解（比如java），原因有以下：
1、es最重要的api，让我们进行各种尝试、学习甚至在某些环境下进行使用的api，就是restful api。如果你学习不用es restful api，比如我上来就用java api来讲es，也是可以的，但是你根本就漏掉了es知识的一大块，你都不知道它最重要的restful api是怎么用的
2、讲知识点，用es restful api，更加方便，快捷，不用每次都写大量的java代码，能加快讲课的效率和速度，更加易于同学们关注es本身的知识和功能的学习
3、我们通常会讲完es知识点后，开始详细讲解java api，如何用java api执行各种操作
4、我们每个篇章都会搭配一个项目实战，项目实战是完全基于java去开发的真实项目和系统
第五个数据分析需求：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 /ecommerce/_search
{
"size": 0,
"aggs": {
"group_by_price": {
"range": {
"field": "price",
"ranges": [
{
"from": 0,
"to": 20
},
{
"from": 20,
"to": 40
},
{
"from": 40,
"to": 50
}
]
},
"aggs": {
"group_by_tags": {
"terms": {
"field": "tags"
},
"aggs": {
"averge_price": {
"avg": {
"field": "price"
}
}
}
}
}
}
}
}
结果集：
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_price" : {
"buckets" : [
{
"key" : "0.0-20.0",
"from" : 0.0,
"to" : 20.0,
"doc_count" : 0,
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [ ]
}
},
{
"key" : "20.0-40.0",
"from" : 20.0,
"to" : 40.0,
"doc_count" : 2,
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "fangzhu",
"doc_count" : 2,
"averge_price" : {
"value" : 27.5
}
},
{
"key" : "meibai",
"doc_count" : 1,
"averge_price" : {
"value" : 30.0
}
}
]
}
},
{
"key" : "40.0-50.0",
"from" : 40.0,
"to" : 50.0,
"doc_count" : 1,
"group_by_tags" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "qingxin",
"doc_count" : 1,
"averge_price" : {
"value" : 40.0
}
}
]
}
}
]
}
}
}
https://www.cnblogs.com/haixiang/p/12040272.html
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