1. 按照 tags 字段 进行分组
GET /ecommerce/product/_search
{ "size": 0,
"aggs": {
"group_by_tag": {
"terms": {
"field": "tags",
"size": 10
}
}
}
}
(注意: "size": 0 的作用是不需要获得所有匹配的 document 的信息,只返回聚合的结果)
此时如果抛出了下面的错误:
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [tags] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
]
需要对 tags 这个字段需要进行下面的处理
PUT /ecommerce/_mapping/product
{
"properties": {
"tags": {
"type": "text",
"fielddata": true
}
}
}
2. 对名称中包含yagao的商品,计算每个tag下的商品数量
GET /ecommerce/product/_search
{
"size": 0,
"query": {
"match": {
"name": "yagao"
}
},
"aggs": {
"all_tags": {
"terms": {
"field": "tags"
}
}
}
}
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" : { "field" : "tags" },
"aggs" : {
"avg_price" : {
"avg" : { "field" : "price" }
}
}
}
}
}
4. 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/product/_search
{
"size": 0,
"aggs" : {
"all_tags" : {
"terms" : { "field" : "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,然后在每组内再按照tag进行分组,最后再计算每组的平均价格
{
"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": {
"average_price": {
"avg": {
"field": "price"
}
}
}
}
}
}
}
}