MySQL calculate moving average of N rows - mysql

Question

I'm trying to calculate the moving average of N rows, for all rows in a single query. In the example case, I am attempting to calculate the moving average of 50 rows.
SELECT
h1.date,
h1.security_id,
( SELECT
AVG(last50.close)
FROM (
SELECT h.close
FROM history as h
WHERE h.date <= h1.date AND h.security_id = h1.security_id
ORDER BY h.date DESC
LIMIT 50
) as last50
) as avg50
FROM history as h1
However, MySQL gives me an error when running this query:
Unknown column 'h1.date' in 'where clause'
I'm trying this method because the other solutions listed don't really seem to work for my use case. There are solutions for a moving average of N days, but since all dates are not accounted for in my data set, I need the average of N rows.
This solution, shown below, doesn't work because AVG (also SUM and COUNT) doesn't account for LIMIT:
SELECT
t1.data_date
( SELECT SUM(t2.price) / COUNT(t2.price)
FROM t as t2
WHERE t2.data_date <= t1.data_date
ORDER BY t2.data_date DESC
LIMIT 5
) AS 'five_row_moving_average_price'
FROM t AS t1
ORDER BY t1.data_date;
This question looks promising, but is somewhat indecipherable to me.
Any suggestions? Here's an SQLFiddle to play around in.

Answer 1

plan
self join history on last 50 days
take average grouping by date and security id ( of current )
query
select curr.date, curr.security_id, avg(prev.close)
from history curr
inner join history prev
on prev.`date` between date_sub(curr.`date`, interval 49 day) and curr.`date`
and curr.security_id = prev.security_id
group by 1, 2
order by 2, 1
;
output
+---------------------------+-------------+--------------------+
| date | security_id | avg(prev.close) |
+---------------------------+-------------+--------------------+
| January, 04 2016 00:00:00 | 1 | 10.770000457763672 |
| January, 05 2016 00:00:00 | 1 | 10.800000190734863 |
| January, 06 2016 00:00:00 | 1 | 10.673333485921225 |
| January, 07 2016 00:00:00 | 1 | 10.59250020980835 |
| January, 08 2016 00:00:00 | 1 | 10.432000160217285 |
| January, 11 2016 00:00:00 | 1 | 10.40166680018107 |
| January, 12 2016 00:00:00 | 1 | 10.344285828726631 |
| January, 13 2016 00:00:00 | 1 | 10.297500133514404 |
| January, 14 2016 00:00:00 | 1 | 10.2877779006958 |
| January, 04 2016 00:00:00 | 2 | 56.15999984741211 |
| January, 05 2016 00:00:00 | 2 | 56.18499946594238 |
| .. | .. | .. |
+---------------------------+-------------+--------------------+
sqlfiddle
reference
sql rolling averages
modified to use last 50 rows
select
rnk_curr.`date`, rnk_curr.security_id, avg(rnk_prev50.close)
from
(
select `date`, security_id,
#row_num := if(#lag = security_id, #row_num + 1,
if(#lag := security_id, 1, 1)) as row_num
from history
cross join ( select #row_num := 1, #lag := null ) params
order by security_id, `date`
) rnk_curr
inner join
(
select date, security_id, close,
#row_num := if(#lag = security_id, #row_num + 1,
if(#lag := security_id, 1, 1)) as row_num
from history
cross join ( select #row_num := 1, #lag := null ) params
order by security_id, `date`
) rnk_prev50
on rnk_curr.security_id = rnk_prev50.security_id
and rnk_prev50.row_num between rnk_curr.row_num - 49 and rnk_curr.row_num
group by 1,2
order by 2,1
;
sqlfiddle
note
the if function is to force the correct order of evaluation of variables.

Answer 2

In mysql 8 window function frame can be used to obtain the averages.
SELECT date, security_id, AVG(close) OVER (PARTITION BY security_id ORDER BY date ROWS 49 PRECEDING) as ma
FROM history
ORDER BY date DESC
This calculates the average of the current row and 49 preceding rows.