导数聚合 derivative
Derivative Aggregation
父管道聚合,用于计算父直方图(或date_histogram)聚合中指定度量的导数。指定的度量必须是数字,封闭直方图的min_doc_count必须设置为0(直方图聚合的默认值)。
语法
"derivative": {
"buckets_path": "the_sum"
}
derivative
参数定义
参数名 | 描述 | 是否必须 | 默认值 |
---|---|---|---|
buckets_path | 我们希望为其查找派生的Bucket的路径 | 必选 | |
gap_policy | 在数据中发现差距时应用的策略 | 可选 | skip |
format | 应用于此聚合的输出值的格式 | 可选 | null |
First Order Derivative
以下代码段计算每月总销售额的导数:
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"interval" : "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales"
}
}
}
}
}
}
buckets_path
指定了 derivative
为sales aggregation
的输出的派生
返回
{
"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
}
}
]
}
}
}
Second Order Derivative
Second Derivative可以通过 derivative agg 链接到另一个 derivative agg 的结果上来计算,如以下示例所示,该示例将计算每月总销售额的一阶导数和二阶导数:
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"interval" : "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales"
}
},
"sales_2nd_deriv": {
"derivative": {
"buckets_path": "sales_deriv"
}
}
}
}
}
}
二阶导数的buckets_path
指向一阶导数的名称
返回
{
"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
导数聚合允许指定导数值的单位。这将在响应normalized_value中返回一个额外字段,该字段以所需的x轴单位报告导数值。在下例中,我们计算每月总销售额的导数,但要求以每天的销售额为单位计算销售额的导数:
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"interval" : "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
},
"sales_deriv": {
"derivative": {
"buckets_path": "sales",
"unit": "day"
}
}
}
}
}
}
unit
指定用于导数计算的x轴的单位
返回
{
"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
}
}
]
}
}
}
value
以每月的原始单位报告normalized_value
以每天所需的单位报告