最小桶聚合
编辑最小桶聚合
编辑一个同级管道聚合，用于识别同级聚合中指定指标的最小值所在的桶，并输出桶的值和键。指定的指标必须是数值型，且同级聚合必须是多桶聚合。
语法
编辑一个 min_bucket 聚合的单独形式如下所示：
{
"min_bucket": {
"buckets_path": "the_sum"
}
}
表 65. min_bucket 参数
| 参数名称 | 描述 | 必需 | 默认值 |
|---|---|---|---|
|
要查找最小值的桶的路径（有关详细信息，请参阅 |
必需 |
|
|
在数据中发现缺口时应用的策略（有关详细信息，请参阅 处理数据中的缺口） |
可选 |
|
|
输出值的 DecimalFormat 模式。如果指定，格式化的值将返回到聚合的 |
可选 |
|
以下代码片段计算每月总 sales 的最小值
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
}
}
},
"min_monthly_sales": {
"min_bucket": {
"buckets_path": "sales_per_month>sales"
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
body: {
size: 0,
aggregations: {
sales_per_month: {
date_histogram: {
field: 'date',
calendar_interval: 'month'
},
aggregations: {
sales: {
sum: {
field: 'price'
}
}
}
},
min_monthly_sales: {
min_bucket: {
buckets_path: 'sales_per_month>sales'
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
aggs: {
sales_per_month: {
date_histogram: {
field: "date",
calendar_interval: "month",
},
aggs: {
sales: {
sum: {
field: "price",
},
},
},
},
min_monthly_sales: {
min_bucket: {
buckets_path: "sales_per_month>sales",
},
},
},
});
console.log(response);
POST /sales/_search
{
"size": 0,
"aggs": {
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
}
}
},
"min_monthly_sales": {
"min_bucket": {
"buckets_path": "sales_per_month>sales"
}
}
}
}
以下可能是响应：
{
"took": 11,
"timed_out": false,
"_shards": ...,
"hits": ...,
"aggregations": {
"sales_per_month": {
"buckets": [
{
"key_as_string": "2015/01/01 00:00:00",
"key": 1420070400000,
"doc_count": 3,
"sales": {
"value": 550.0
}
},
{
"key_as_string": "2015/02/01 00:00:00",
"key": 1422748800000,
"doc_count": 2,
"sales": {
"value": 60.0
}
},
{
"key_as_string": "2015/03/01 00:00:00",
"key": 1425168000000,
"doc_count": 2,
"sales": {
"value": 375.0
}
}
]
},
"min_monthly_sales": {
"keys": ["2015/02/01 00:00:00"],
"value": 60.0
}
}
}