I have a table with timestamp and someother metrics like riskscore and current of a machine.Here plant shift starts # 08:00 am and ends # next day 08:00am.
i want to group the data by day(shift: 08:00am to nextday 08:00am) of timetamp and label it as shift start date.i have a 6months of data.)
expected output:
machine | date | avg_riskscore | avg_current
2 | 2020-12-02 | 25.5 | 10
here this record is group of data between '2020-12-02 08:00:00' and '2020-12-03 08:00:00' and should insert with date '2020-12-02'
here i need to aggregate the 6 months of data like this.
DB Fiddle
You can just offset the timestamp by 8 hours, then truncate to date and aggregate. Based on your fiddle, that would be:
select
equipment_id,
(telemetry_time - interval '8 hour')::date as date,
avg(riskscore) as avg_riskscore,
avg(i_rms) as avg_i_rms
from telemetry_test
group by equipment_id, date
Related
I have a database with a tbl_registration with rows that look like
ID | start_date_time | end_date_time | ...
1 | 2021-01-01 14:00:15 | 2021-01-01 14:00:15
2 | 2021-02-01 14:00:15 | null
4 | 2021-05-15 14:00:15 | 2024-01-01 14:00:15
5 | 2019--15 14:00:15 | 2024-01-01 14:00:15
endDate can be null
It contains 500.000 - 1.000.000 of records
We want to create an overview of year grouped by month that shows the amount of records that are active in that month. So a registration is counted per month if it lies (partially) in that month based on start and end date.
I can do a query per month like this
select count (id)
from tbl_registration
where
(r.end_date_time >= to_timestamp('01/01/2021 00:00:00', 'DD/MM/YYYY HH24:MI:SS') or r.end_date_time is null )
and r.start_date_time < to_timestamp('01/02/2021 00:00:00', 'DD/MM/YYYY HH24:MI:SS');
But that forces me to repeat this query 12 times.
I don't see a creative way to solve this in one query that would give me as a result 12 rows, one for each month
I've been looking at the generate_series function, but I don't see how I can group on the comparison of those start- and end dates
Postgres supports generate_series() . . . so generate the dates you want then then construct the query. One method is:
select gs.mon, x.cnt
from generate_series('2021-01-01'::date, '2021-12-01'::date, interval '1 month') gs(mon) left join lateral
(select count(*) as cnt
from tbl_registration
where r.end_date_time >= gs.mon or r.end_date_time is null) and
r.start_date_time < gs.mon + interval '1 month'
) x
on 1=1;
I'm very new to SQL and time series database. I'm using crate database. I want to aggregate the data by day. But the I want to start each day start time is 9 AM not 12AM..
Time interval is 9 AM to 11.59 PM.
Unix time stamp is used to store the data. following is my sample database.
|sensorid | reading | timestamp|
====================================
|1 | 1616457600 | 10 |
|1 | 1616461200 | 100 |
|2 | 1616493600 | 1 |
|2 | 1616493601 | 10 |
Currently i grouped using following command. But it gives the start time as 12 AM.
select date_trunc('day', v.timestamp) as day,sum(reading)
from sensor1 v(timestamp)
group by (DAY)
From the above table. i want sum of 1616493600 and 1616493601 data (11 is result). because 1616457600 and 1616461200 are less than 9 am data.
You want to add nine hours to midnight:
date_trunc('day', v.timestamp) + interval '9' hour
Edit: If you want to exclude hours before 9:00 from the data you add up, you must add a WHERE clause:
where extract(hour from v.timestamp) >= 9
Here is a complete query with all relevant data:
select
date_trunc('day', v.timestamp) as day,
date_trunc('day', v.timestamp) + interval '9' hour as day_start,
min(v.timestamp) as first_data,
max(v.timestamp) as last_data,
sum(reading) as total_reading
from sensor1 v(timestamp)
where extract(hour from v.timestamp) >= 9
group by day
order by day;
I'm very new to SQL and time series database. I'm using crate database ( it think which is used PostgreSQL).i want to aggregate the data by hour,day ,week and month. Unix time stamp is used to store the data. following is my sample database.
|sensorid | reading | timestamp|
====================================
|1 | 1604192522 | 10 |
|1 | 1604192702 | 9.65 |
|2 | 1605783723 | 8.1 |
|2 | 1601514122 | 9.6 |
|2 | 1602292210 | 10 |
|2 | 1602291611 | 12 |
|2 | 1602291615 | 10 |
i tried the sql query using FROM_UNIXTIME not supported .
please help me?
im looking the answer for hourly data as follows.
sensorid ,reading , timestamp
1 19.65(10+9.65) 1604192400(starting hour unixt time)
2 8.1 1605783600(starting hour unix time)
2 9.6 1601514000(starting hour unix time)
2 32 (10+12+10) 1602291600(starting hour unix time)
im looking the answer for monthly data is like
sensorid , reading , timestamp
1 24.61(10+9.65+8.1) 1604192400(starting month unix time)
2 41.6(9.6+10+12+10) 1601510400(starting month unix time)
A straight-forward approach is:
SELECT
(date '1970-01-01' + unixtime * interval '1 second')::date as date,
extract(hour from date '1970-01-01' + unixtime * interval '1 second') AS hour,
count(c.user) AS count
FROM core c
GROUP BY 1,2
If you are content with having the date and time in the same column (which would seem more helpful to me), you can use date_trunc():
select
date_trunc('hour', date '1970-01-01' + unixtime * interval '1 second') as date_hour,
count(c.user) AS count
FROM core c
GROUP BY 1,2
You can convert a unix timestamp to a date/time value using to_timestamp(). You can aggregate along multiple dimensions at the same time using grouping sets. So, you might want:
select date_trunc('year', v.ts) as year,
date_trunc('month', v.ts) as month,
date_trunc('week', v.ts) as week,
date_trunc('day', v.ts) as day,
date_trunc('hour', v.ts) as hour,
count(*), avg(reading), sum(reading)
from t cross join lateral
(values (to_timestamp(timestamp))) v(ts)
group by grouping sets ( (year), (month), (week), (day), (hour) );
I have a SQLite database with start and stop datetimes
With the following SQL query I get the difference hours between start and stop:
SELECT starttime, stoptime, cast((strftime('%s',stoptime)-strftime('%s',starttime)) AS real)/60/60 AS diffHours FROM tracktime;
I need a SQL query, which delivers the sum of multiple timestamps, grouped by every day (also whole dates between timestamps).
The result should be something like this:
2018-08-01: 12 hours
2018-08-02: 24 hours
2018-08-03: 12 hours
2018-08-04: 0 hours
2018-08-05: 1 hours
2018-08-06: 14 hours
2018-08-07: 8 hours
You can try this, use CTE RECURSIVE make a calendar table for every date start time and end time, and do some calculation.
Schema (SQLite v3.18)
CREATE TABLE tracktime(
id int,
starttime timestamp,
stoptime timestamp
);
insert into tracktime values
(11,'2018-08-01 12:00:00','2018-08-03 12:00:00');
insert into tracktime values
(12,'2018-09-05 18:00:00','2018-09-05 19:00:00');
Query #1
WITH RECURSIVE cte AS (
select id,starttime,date(starttime,'+1 day') totime,stoptime
from tracktime
UNION ALL
SELECT id,
date(starttime,'+1 day'),
date(totime,'+1 day'),
stoptime
FROM cte
WHERE date(starttime,'+1 day') < stoptime
)
SELECT strftime('%Y-%m-%d', starttime),(strftime('%s',CASE
WHEN totime > stoptime THEN stoptime
ELSE totime
END) -strftime('%s',starttime))/3600 diffHour
FROM cte;
| strftime('%Y-%m-%d', starttime) | diffHour |
| ------------------------------- | -------- |
| 2018-08-01 | 12 |
| 2018-09-05 | 1 |
| 2018-08-02 | 24 |
| 2018-08-03 | 12 |
View on DB Fiddle
To extract the week of a given year we can use:
SELECT EXTRACT(WEEK FROM timestamp '2014-02-16 20:38:40');
However, I am trying to group weeks together in a bit of an odd format. My start of a week would begin on Mondays at 4am and would conclude the following Monday at 3:59:59am.
Ideally, I would like to create a query that provides a start and end date, then groups the total sales for that period by the weeks laid out above.
Example:
SELECT
(some custom week date),
SUM(sales)
FROM salesTable
WHERE
startDate BETWEEN 'DATE 1' AND 'DATE 2'
I am not looking to change the EXTRACT() function, rather create a query that would pull from the following sample table and output the sample results.
If 'DATE 1' in query was '2014-07-01' AND 'DATE 2' was '2014-08-18':
Sample Table:
itemID | timeSold | price
------------------------------------
1 | 2014-08-13 09:13:00 | 12.45
2 | 2014-08-15 12:33:00 | 20.00
3 | 2014-08-05 18:33:00 | 10.00
4 | 2014-07-31 04:00:00 | 30.00
Desired result:
weekBegin | priceTotal
----------------------------------
2014-07-28 04:00:00 | 30.00
2014-08-04 04:00:00 | 10.00
2014-08-11 04:00:00 | 32.45
Produces your desired output:
SELECT date_trunc('week', time_sold - interval '4h')
+ interval '4h' AS week_begin
, sum(price) AS price_total
FROM tbl
WHERE time_sold >= '2014-07-01 0:0'::timestamp
AND time_sold < '2014-08-19 0:0'::timestamp -- start of next day
GROUP BY 1
ORDER BY 1;
db<>fiddle here (extended with a row that actually shows the difference)
Old sqlfiddle
Explanation
date_trunc() is the superior tool here. You are not interested in week numbers, but in actual timestamps.
The "trick" is to subtract 4 hours from selected timestamps before extracting the week - thereby shifting the time frame towards the earlier bound of the ISO week. To produce the desired display, add the same 4 hours back to the truncated timestamps.
But apply the WHERE condition on unmodified timestamps. Also, never use BETWEEN with timestamps, which have fractional digits. Use the WHERE conditions like presented above. See:
Unexpected results from SQL query with BETWEEN timestamps
Operating with data type timestamp, i.e. with (shifted) "weeks" according to the current time zone. You might want to work with timestamptz instead. See:
Ignoring time zones altogether in Rails and PostgreSQL