influxDB 变换类函数

4、MOVING_AVERAGE()函数

作用：返回一个连续字段值的移动平均值，字段类型必须是长整形或者float64类型。

例子1：

下面的例子water_level在表 h2o_feet，location 为santa_monica，时间段2015 - 08 - 18 - t00:00:00z和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_level
2015-08-18T00:00:00Z	  2.064
2015-08-18T00:06:00Z	  2.116
2015-08-18T00:12:00Z	  2.028
2015-08-18T00:18:00Z	  2.126
2015-08-18T00:24:00Z	  2.041
2015-08-18T00:30:00Z	  2.051
2015-08-18T00:36:00Z	  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_average
2015-08-18T00:06:00Z	  2.09
2015-08-18T00:12:00Z	  2.072
2015-08-18T00:18:00Z	  2.077
2015-08-18T00:24:00Z	  2.0835
2015-08-18T00:30:00Z	  2.0460000000000003
2015-08-18T00:36:00Z	  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

• 选择最低值water_level每隔12分钟和计算移动平均每2字段值:

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_average
2015-08-18T00:12:00Z	  2.0460000000000003
2015-08-18T00:24:00Z	  2.0345000000000004
2015-08-18T00:36:00Z	  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			   min
2015-08-18T00:00:00Z	  2.064
2015-08-18T00:12:00Z	  2.028
2015-08-18T00:24:00Z	  2.041
2015-08-18T00:36:00Z	  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。