SQLite 中的移动平均线

Moving average in SQLite

我想计算 SQLite table 中数据的移动平均值。我在 MySQL 中找到了几种方法,但在 SQLite.

中找不到有效的方法

在SQL中,我认为应该这样做(但是,我无法尝试...):

SELECT date, value, 
avg(value) OVER (ORDER BY date ROWS BETWEEN 3 PRECEDING AND 3 FOLLOWING) as MovingAverageWindow7
FROM t ORDER BY date;

但是,我看到两个缺点:

的确,我希望它计算每个日期 'value' 的平均值,超过 +/-3 天(每周移动平均值)或 +/-15 天(每月移动平均值)

这是一个示例数据集:

CREATE TABLE t ( date DATE, value INTEGER );

INSERT INTO t (date, value) VALUES ('2018-02-01', 8);
INSERT INTO t (date, value) VALUES ('2018-02-02', 2);
INSERT INTO t (date, value) VALUES ('2018-02-05', 5);
INSERT INTO t (date, value) VALUES ('2018-02-06', 4);
INSERT INTO t (date, value) VALUES ('2018-02-07', 1);
INSERT INTO t (date, value) VALUES ('2018-02-10', 6);
INSERT INTO t (date, value) VALUES ('2018-02-11', 0);
INSERT INTO t (date, value) VALUES ('2018-02-12', 2);
INSERT INTO t (date, value) VALUES ('2018-02-13', 1);
INSERT INTO t (date, value) VALUES ('2018-02-14', 3);
INSERT INTO t (date, value) VALUES ('2018-02-15', 11);
INSERT INTO t (date, value) VALUES ('2018-02-18', 4);
INSERT INTO t (date, value) VALUES ('2018-02-20', 1);
INSERT INTO t (date, value) VALUES ('2018-02-21', 5);
INSERT INTO t (date, value) VALUES ('2018-02-28', 10);
INSERT INTO t (date, value) VALUES ('2018-03-02', 6);
INSERT INTO t (date, value) VALUES ('2018-03-03', 7);
INSERT INTO t (date, value) VALUES ('2018-03-04', 3);
INSERT INTO t (date, value) VALUES ('2018-03-08', 5);
INSERT INTO t (date, value) VALUES ('2018-03-09', 6);
INSERT INTO t (date, value) VALUES ('2018-03-15', 1);
INSERT INTO t (date, value) VALUES ('2018-03-16', 3);
INSERT INTO t (date, value) VALUES ('2018-03-25', 5);
INSERT INTO t (date, value) VALUES ('2018-03-31', 1);

我想我实际上找到了解决方案:

SELECT date, value, 
  (SELECT AVG(value) FROM t t2 
   WHERE datetime(t1.date, '-3 days') <= datetime(t2.date) AND datetime(t1.date, '+3 days') >= datetime(t2.date)
   ) AS MAVG
FROM t t1
GROUP BY strftime('%Y-%m-%d', date); 

我不知道这是否是最有效的方法,但它似乎有效

编辑: 应用于包含 20,000 行的真实数据库,计算两个参数的每周移动平均值大约需要 1 分钟。

我看到有两个选项:

  • 有一种更有效的方法可以使用 SQLite 进行计算
  • 从 SQLite
  • 中提取数据后,我在 Python 中计算移动平均值

一种方法是创建一个中间 table 将每个日期映射到它所属的组。

CREATE TABLE groups (date DATE, daygroup DATE);
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '-1 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '-2 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '-3 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '+1 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '+2 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, strftime('%Y-%m-%d', datetime(date, '+3 days')) AS daygroup
  FROM t;  
INSERT INTO groups 
  SELECT date, date AS daygroup FROM t;

你得到例如,

SELECT * FROM groups WHERE date = '2018-02-05'

    date        daygroup
    2018-02-05  2018-02-04
    2018-02-05  2018-02-03
    2018-02-05  2018-02-02
    2018-02-05  2018-02-06
    2018-02-05  2018-02-07
    2018-02-05  2018-02-08
    2018-02-05  2018-02-05

表示'2018-02-05'属于组'2018-02-02'到'2018-02-08'。如果一个日期属于一个组,则数据的值加入该组的移动平均计算。

有了这个,计算移动平均线就变得简单了:

SELECT
  d.date, d.value, c.ma
FROM
  t AS d
INNER JOIN 
  (SELECT 
    b.daygroup,
    avg(a.value) AS ma
  FROM 
    t AS a 
  INNER JOIN
    groups AS b
  ON a.date = b.date
  GROUP BY b.daygroup) AS c
ON
  d.date = c.daygroup

请注意,中间table的行数是原始table行数的7倍,它随着window宽度的增加而按比例增长。这应该是 acceptable 除非你有更大的 table.

我还试验了 20 000 行。 插入查询用了 1.5 秒,select 查询在我的笔记本电脑上用了 0.5 秒。

已添加,也许更好。

不需要中间的替代方案table。 下面的查询将 table 与其自身合并,允许 3 天的延迟,然后取平均值。

SELECT
  t1.date, avg(t2.value) AS MVG
FROM 
  t AS t1
INNER JOIN
  t AS t2
ON
  datetime(t1.date, '-3 days') <= datetime(t2.date) 
  AND 
  datetime(t1.date, '+3 days') >= datetime(t2.date)
GROUP BY
  t1.date
;

Window 功能已在 3.25.0 (2018-09-15) 版本中添加。随着版本 3.28.0 (2019-04-16) 中添加的 RANGE 帧类型,您现在可以:

SELECT date, value, 
avg(value) OVER (
    ORDER BY CAST (strftime('%s', date) AS INT)
    RANGE BETWEEN 3 * 24 * 60 * 60 PRECEDING
        AND 3 * 24 * 60 * 60 FOLLOWING
) AS MovingAverageWindow7
FROM t ORDER BY date;