我想在SQLite表中计算数据的移动平均值。我在MySQL中发现了几种方法,但在SQLite中找不到有效的方法。
在SQL中,我认为这样的事情应该这样做(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:
实际上,我希望计算每个日期的“价值”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一个解决方案:
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);
我不知道它是否是最有效的方式,但似乎有效
编辑:应用于包含20 000行的真实数据库,超过两个参数的每周移动平均值需要大约1分钟才能计算出来。
我看到两个选择:
一种方法是创建一个中间表,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;
你得到的例子,
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'2018-02-02'到'2018-02-08'组。如果日期属于某个组,则数据的值将加入该组的移动平均值的计算。
有了这个,计算移动平均线变得简单:
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,中间表的行数是原始表的7倍,它随着窗口的增大而成比例增长。这应该是可以接受的,除非你有更大的表。
我还试验了20 000行。插入查询花了1.5秒,选择查询花了0.5秒在我的笔记本电脑上。
一种不需要中间表的替代方案。下面的查询将表与自身合并,以允许3天滞后的方式,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
;