I want to plot my_values with some lower resolution on the time axis than I have in the database. I use something like the following SQL to get the average values per time interval (e.g., an hour):
SELECT DATE_TRUNC('hour', my_timestamps) AS my_time_lowres
, AVG(my_values)
FROM my_table
GROUP BY my_time_lowres
Using date_trunc() it is possible to reduce the resolution of the timestamp to a certain degree (according to the docs):
select date_trunc('hour', timestamp '2001-02-16 20:38:40')
-- the output is: 2001-02-16 20:00:00
This way, I can do this for the following interval sizes (and some larger/smaller sizes):
...
second
minute
hour
day
week
...
Is there a way to achieve this for other time intervals as well, e.g., 3 hours, 6 hours?
Consider this demo to bring timestamps down to a resolution of 15 minutes and aggregate resulting dupes:
WITH tbl(id, ts) AS ( VALUES
(1::int, '2012-10-04 00:00:00'::timestamp)
,(2, '2012-10-04 18:23:01')
,(3, '2012-10-04 18:30:00')
,(4, '2012-10-04 18:52:33')
,(5, '2012-10-04 18:55:01')
,(6, '2012-10-04 18:59:59')
,(7, '2012-10-05 11:01:01')
)
SELECT to_timestamp((extract(epoch FROM ts)::bigint / 900)*900)::timestamp
AS lower_bound
, to_timestamp(avg(extract(epoch FROM ts)))::timestamp AS avg_ts
, count(*) AS ct
FROM tbl
GROUP BY 1
ORDER BY 1;
Result:
lower_bound | avg_ts | ct
---------------------+---------------------+----
2012-10-04 00:00:00 | 2012-10-04 00:00:00 | 1
2012-10-04 18:15:00 | 2012-10-04 18:23:01 | 1
2012-10-04 18:30:00 | 2012-10-04 18:30:00 | 1
2012-10-04 18:45:00 | 2012-10-04 18:55:51 | 3
2012-10-05 11:00:00 | 2012-10-05 11:01:01 | 1
The trick is to extract a unix epoch like @Michael already posted. Integer division lumps them together in buckets of the chosen resolution, because fractional digits are truncated.
I divide by 900, because 15 minutes = 900 seconds.
Multiply by the same number to get the resulting lower_bound.
Convert the unix epoch back to a timestamp with to_timestamp().
This works great for intervals that can be represented without fractional digits in the decimal system. For even more versatility use the often overlooked function width_bucket() like I demonstrate in this recent, closely related answer. More explanation, links and an sqlfiddle demo over there.
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