累计求和聚合
编辑累计求和聚合
编辑一个父管道聚合，它计算父直方图（或 date_histogram）聚合中指定指标的累积总和。指定的指标必须是数值型的，并且封闭的直方图必须将 min_doc_count 设置为 0 ( histogram 聚合的默认值)。
语法
编辑一个独立的 cumulative_sum 聚合看起来像这样
{
"cumulative_sum": {
"buckets_path": "the_sum"
}
}
表 60. cumulative_sum 参数
| 参数名称 | 描述 | 必需 | 默认值 |
|---|---|---|---|
|
我们要计算累积和的桶的路径（有关详细信息，请参阅 |
必需 |
|
|
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 的累积和
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"cumulative_sales": {
"cumulative_sum": {
"buckets_path": "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'
}
},
cumulative_sales: {
cumulative_sum: {
buckets_path: '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",
},
},
cumulative_sales: {
cumulative_sum: {
buckets_path: "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"
}
},
"cumulative_sales": {
"cumulative_sum": {
"buckets_path": "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
},
"cumulative_sales": {
"value": 550.0
}
},
{
"key_as_string": "2015/02/01 00:00:00",
"key": 1422748800000,
"doc_count": 2,
"sales": {
"value": 60.0
},
"cumulative_sales": {
"value": 610.0
}
},
{
"key_as_string": "2015/03/01 00:00:00",
"key": 1425168000000,
"doc_count": 2,
"sales": {
"value": 375.0
},
"cumulative_sales": {
"value": 985.0
}
}
]
}
}
}