受此 great answer 的启发,我编写了以下查询,返回去年根据 5 分钟间隔计算的 AVG。
我想要的是所有 5 分钟的间隔,如果没有行适合特定时间跨度,则设置为 null
。
with intervals as (select
(select min("timestamp") from public.hst_energy_d) + n AS start_timestamp,
(select min("timestamp") from public.hst_energy_d) + n + 299 AS end_timestamp
from generate_series(extract(epoch from now())::BIGINT - 10596096000, extract(epoch from now())::BIGINT, 300) n)
(SELECT AVG(meas."Al1") as "avg", islots.start_timestamp AS "timestamp"
FROM public.hst_energy_d meas
RIGHT OUTER JOIN intervals islots
on meas.timestamp >= islots.start_timestamp and meas.timestamp <= islots.end_timestamp
WHERE
meas.idinstrum = 4
AND
meas.id_device = 122
AND
meas.timestamp > extract(epoch from now()) - 10596096000
GROUP BY islots.start_timestamp, islots.end_timestamp
ORDER BY timestamp);
最佳答案
我想我明白你想做什么了,我想知道自由地使用 interval '5 minutes'
是否会是一种更好、更容易遵循的方法:
with times as ( -- find the first date in the dataset, up to today
select
date_trunc ('minutes', min("timestamp")) -
mod (extract ('minutes' from min("timestamp"))::int, 5) * interval '1 minute' as bt,
date_trunc ('minutes', current_timestamp) -
mod (extract ('minutes' from current_timestamp)::int, 5) * interval '1 minute' as et
from hst_energy_d
where
idinstrum = 4 and
id_device = 122
), -- generate every possible range between these dates
ranges as (
select
generate_series(bt, et, interval '5 minutes') as range_start
from times
), -- normalize your data to which 5-minut interval it belongs to
rounded_hst as (
select
date_trunc ('minutes', "timestamp") -
mod (extract ('minutes' from "timestamp")::int, 5) * interval '1 minute' as round_time,
*
from hst_energy_d
where
idinstrum = 4 and
id_device = 122
)
select
r.range_start, r.range_start + interval '5 minutes' as range_end,
avg (hd."Al1")
from
ranges r
left join rounded_hst hd on
r.range_start = hd.round_time
group by
r.range_start
order by
r.range_start
顺便说一句,眼尖的人可能想知道为什么要为 CTE rounded_hst
而烦恼,为什么不在连接中使用“between”。从我测试和观察到的所有内容来看,数据库将排除所有可能性,然后在相当于 where 子句的条件下测试 between 条件——一个过滤的笛卡尔。对于这么多间隔,这肯定是一个 killer 。
将每个数据截断到最接近的五分钟允许标准 SQL 连接。我鼓励您对两者都进行测试,我想您会明白我的意思。
-- 编辑 2016 年 11 月 17 日 --
考虑到时间的 OP 解决方案是数字,而不是日期:
with times as ( -- find the first date in the dataset, up to today
select
date_trunc('minutes', to_timestamp(min("timestamp"))::timestamp) -
mod(extract ('minutes' from to_timestamp(min("timestamp"))::timestamp)::int, 5) * interval '1 minute' as bt,
date_trunc('minutes', current_timestamp::timestamp) -
mod(extract ('minutes' from (current_timestamp)::timestamp)::int, 5) * interval '1 minute' as et
from hst_energy_d
where
idinstrum = 4 and
id_device = 122
), -- generate every possible range between these dates
ranges as (
select
generate_series(bt, et, interval '5 minutes') as range_start
from times
), -- normalize your data to which 5-minute interval it belongs to
rounded_hst as (
select
date_trunc ('minutes', to_timestamp("timestamp")::timestamp)::timestamp -
mod (extract ('minutes' from (to_timestamp("timestamp")::timestamp))::int, 5) * interval '1 minute' as round_time,
*
from hst_energy_d
where
idinstrum = 4 and
id_device = 122
)
select
extract('epoch' from r.range_start)::bigint, extract('epoch' from r.range_start + interval '5 minutes')::bigint as range_end,
avg (hd."Al1")
from
ranges r
left join rounded_hst hd on
r.range_start = hd.round_time
group by
r.range_start
order by
r.range_start;
关于sql - 如何插入非分组数据,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40636984/