导数聚合
编辑导数聚合
编辑一个父级管道聚合，用于计算父级直方图（或 date_histogram）聚合中指定指标的导数。指定的指标必须是数字，并且封闭的直方图的 min_doc_count 必须设置为 0（histogram 聚合的默认值）。
语法
编辑一个 derivative 聚合单独使用时看起来像这样
"derivative": {
"buckets_path": "the_sum"
}
表 61. derivative 参数
| 参数名称 | 描述 | 必需 | 默认值 |
|---|---|---|---|
|
我们希望查找导数的桶的路径（有关详细信息，请参阅 |
必需 |
|
|
在数据中发现间隙时应用的策略（有关详细信息，请参阅 处理数据中的间隙） |
可选 |
|
|
用于输出值的 DecimalFormat 模式。如果指定，格式化的值将在聚合的 |
可选 |
|
一阶导数
编辑以下代码片段计算每月总 sales 的导数
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"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'
}
},
sales_deriv: {
derivative: {
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",
},
},
sales_deriv: {
derivative: {
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"
}
},
"sales_deriv": {
"derivative": {
"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
}
},
{
"key_as_string": "2015/02/01 00:00:00",
"key": 1422748800000,
"doc_count": 2,
"sales": {
"value": 60.0
},
"sales_deriv": {
"value": -490.0
}
},
{
"key_as_string": "2015/03/01 00:00:00",
"key": 1425168000000,
"doc_count": 2,
"sales": {
"value": 375.0
},
"sales_deriv": {
"value": 315.0
}
}
]
}
}
}
二阶导数
编辑可以通过将导数管道聚合链接到另一个导数管道聚合的结果来计算二阶导数，如下例所示，它将计算每月总销售额的一阶导数和二阶导数
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales"
}
},
"sales_2nd_deriv": {
"derivative": {
"buckets_path": "sales_deriv"
}
}
}
}
},
)
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'
}
},
sales_deriv: {
derivative: {
buckets_path: 'sales'
}
},
"sales_2nd_deriv": {
derivative: {
buckets_path: 'sales_deriv'
}
}
}
}
}
}
)
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",
},
},
sales_deriv: {
derivative: {
buckets_path: "sales",
},
},
sales_2nd_deriv: {
derivative: {
buckets_path: "sales_deriv",
},
},
},
},
},
});
console.log(response);
POST /sales/_search
{
"size": 0,
"aggs": {
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales"
}
},
"sales_2nd_deriv": {
"derivative": {
"buckets_path": "sales_deriv"
}
}
}
}
}
}
以下可能是响应
{
"took": 50,
"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
},
"sales_deriv": {
"value": -490.0
}
},
{
"key_as_string": "2015/03/01 00:00:00",
"key": 1425168000000,
"doc_count": 2,
"sales": {
"value": 375.0
},
"sales_deriv": {
"value": 315.0
},
"sales_2nd_deriv": {
"value": 805.0
}
}
]
}
}
}
单位
编辑导数聚合允许指定导数值的单位。这会在响应中返回一个额外的字段 normalized_value，它以所需的 x 轴单位报告导数值。在下面的示例中，我们计算每月总销售额的导数，但要求销售额的导数以每天的销售额为单位
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales",
"unit": "day"
}
}
}
}
},
)
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'
}
},
sales_deriv: {
derivative: {
buckets_path: 'sales',
unit: 'day'
}
}
}
}
}
}
)
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",
},
},
sales_deriv: {
derivative: {
buckets_path: "sales",
unit: "day",
},
},
},
},
},
});
console.log(response);
POST /sales/_search
{
"size": 0,
"aggs": {
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales",
"unit": "day"
}
}
}
}
}
}
以下可能是响应
{
"took": 50,
"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
},
"sales_deriv": {
"value": -490.0,
"normalized_value": -15.806451612903226
}
},
{
"key_as_string": "2015/03/01 00:00:00",
"key": 1425168000000,
"doc_count": 2,
"sales": {
"value": 375.0
},
"sales_deriv": {
"value": 315.0,
"normalized_value": 11.25
}
}
]
}
}
}