1. Calculate the number of items in each tag
GET /ecommerce/product/_search
{
“aggs”:{
“group_by_tags”:{
“terms”:{“field”:”tags”}
}
}
}
The text field of fielddate property is set to true
PUT /ecommerce/_mapping/product
{
“properties”:{
“tags”:{
“type”:”text”,
“fielddata”:true
}
}
}
Re-execute the command packet
“size”:0
The results may not display information about the analysis of the data, return only after polymerization Analysis
2. a name which includes yagao goods, quantity of goods calculated at each tag
GET /ecommerce/product/_search
{
"size": 0,
"query": {
"match": {
"name": "yagao"
}
},
"aggs": {
"group_by_tags": {
"terms": {
"field": "tags"
}
}
}
}
结果一样，因为每个商品name中都包含有yagao
3.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/product/_search
{
“size”:0,
“aggs”:{
“group_by_tags”:{
“terms”:{“fiedd”:”tags”},
“aggs”:{
“avg_price”:{
“avg”:{“field”:”price”}
}
}
}
}
}
4.在3的基础上，按照平均价格进行排序
GET /ecommerce/product/_search
{
“size”:0,
“aggs”:{
“group_by_tags”:{
“terms”:{“fiedd”:”tags”，“order”:{“avg_price”:”desc”}},
“aggs”:{
“avg_price”:{
“avg”:{“field”:”price”}
}
}
}
}
}
5.按照指定的价格范围区间进行分组，然后在每组内按照tag进行分组，最后再计算每组的平均价格
GET /ecommerce/product/_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_tag": {
"terms": {
"field": "tags",
"order": {
"avg_by_price": "desc"
}
},
"aggs": {
"avg_by_price": {
"avg": {
"field": "price"
}
}
}
}
}
}
}
}
