InfluxDB Transform class functions

4. Moving_average () function

Function: Returns the moving average of a continuous field value, which must be a long or float64 type.

Example 1:

The following examples water_level are shown in tables  h2o_feet， location 为 santa_monica， 时间段 2015-08-18-t00:00:00z and 2015-08-18-t00:36:00z:

> SELECT water_level FROM h2o_feet WHERE location = ‘santa_monica‘ AND time >= ‘2015-08-18T00:00:00Z‘ and time <= ‘2015-08-18T00:36:00Z‘name: h2o_feet--------------time  water_level2015-08-18T00:00:00Z  2.0642015-08-18T00:06:00Z  2.1162015-08-18T00:12:00Z  2.0282015-08-18T00:18:00Z  2.1262015-08-18T00:24:00Z  2.0412015-08-18T00:30:00Z  2.0512015-08-18T00:36:00Z  2.067

计算移动平均在每2字段值:

SELECT MOVING_AVERAGE(water_level,2) FROM h2o_feet WHERE location = ‘santa_monica‘ AND time >= ‘2015-08-18T00:00:00Z‘ and time <= ‘2015-08-18T00:36:00Z‘

结果：

name: h2o_feet--------------time moving_average2015-08-18T00:06:00Z  2.092015-08-18T00:12:00Z  2.0722015-08-18T00:18:00Z  2.0772015-08-18T00:24:00Z  2.08352015-08-18T00:30:00Z  2.04600000000000032015-08-18T00:36:00Z  2.059

解释
移动平均线列中的第一个值的平均值是2.064和2.116,第二个移动平均线列中的值是2.116和2.028的平均水平。

例子2

• Select the lowest value water_level every 12 minutes and calculate the moving average per 2 field value:

SELECT MOVING_AVERAGE(MIN(water_level),2) FROM h2o_feet WHERE location = ‘santa_monica‘ AND time >= ‘2015-08-18T00:00:00Z‘ and time <= ‘2015-08-18T00:36:00Z‘ GROUP BY time(12m)

结果：

name: h2o_feet--------------time                moving_average2015-08-18T00:12:00Z  2.04600000000000032015-08-18T00:24:00Z  2.03450000000000042015-08-18T00:36:00Z  2.0540000000000003

解释：
这些结果,InfluxDB首先选择MIN() water_level每12分钟间隔:

name: h2o_feet--------------time   min2015-08-18T00:00:00Z  2.0642015-08-18T00:12:00Z  2.0282015-08-18T00:24:00Z  2.0412015-08-18T00:36:00Z  2.067

然后使用这些值来计算移动平均在每2字段值,移动平均线列中的第一个结果的平均值2.064和2.028,第二个结果是2.028和2.041的平均水平。

InfluxDB Transform class functions