I am trying to figure out the offset that should be applied to a meeting with start and end date time.
Timezone table below stores the utc offset in minutes and when the utc offset became active.
Timezone Table
TimezoneCode StartDate EndDate UtcOffSetInMinute
Antarctica/Casey 2020-04-05 02:00:00 2020-09-26 02:00:00 720
Antarctica/Casey 2020-09-27 05:00:00 2020-05-03 05:00:00 780
Meeting table which stores all the meetings
Meeting Table
|Id | StartDateTime | EndDateTime
+----+---------------------+----------------------
|1 | 2020-04-06 23:00:00 | 2020-09-26 05:00:00
|2 | 2020-10-21 10:00:00 | 2020-10-21 11:00:00
Using the above timezone table I am struggling to figure local time of meeting.
How can we join the timezone table with meeting table and get the utcoffset for meeting based on date range?
Expected output
|Id | StartDateTime | EndDateTime | OffsetInMins
+----+---------------------+----------------------
|1 | 2020-04-06 23:00:00 | 2020-09-26 05:00:00 | 720
|2 | 2020-09-27 23:00:00 | 2020-09-29 05:00:00 | 780
Related
Purpose: I work in Hospitality Industry. I want to understand at what time the Restaurant is full and what time it is less busy. I have the opening and closing times, I want to split it 30 minute interval period.
I would really appreciate if you could ease help me.
Thanking you in advance
Table
Check# Open CloseTime
25484 17:34 18:06
25488 18:04 21:22
Output
Check# Open Close Duration
25484 17:34 18:00 0:25
25484 18:00 18:30 0:30
25488 18:08 18:30 0:21
25488 18:30 19:00 0:30
25488 19:00 19:30 0:30
25488 19:30 20:00 0:30
25488 20:00 20:30 0:30
25488 20:30 21:00 0:30
25488 21:00 21:30 0:30
I am new to SQL. I am good at Excel, but due to its limitations i want to use SQL. I just know the basics in SQL.
I have tried on the google, but could not find solution to it. All i can see use of Date Keywords, but not the Field name in the code, hence i am unable to use them.
Could you try this, it works in MySQL 8.0:
WITH RECURSIVE times AS (
SELECT time '0:00' AS `Open`, time '0:30' as `Close`
UNION ALL
SELECT addtime(`Open`, '0:30'), addtime(`Close`, '0:30')
FROM times
WHERE `Open` < time '23:30'
)
SELECT c.`Check`,
greatest(t.`Open`, c.`Open`) `Open`,
least(t.`Close`, c.`CloseTime`) `Close`,
timediff(least(t.`Close`, c.`CloseTime`), greatest(t.`Open`, c.`Open`)) `Duration`
FROM times t
JOIN checks c ON (c.`Open` < t.`Close` AND c.`CloseTime` > t.`Open`);
| Check | Open | Close | Duration |
| ----- | -------- | -------- | -------- |
| 25484 | 17:34:00 | 18:00:00 | 00:26:00 |
| 25484 | 18:00:00 | 18:06:00 | 00:06:00 |
| 25488 | 18:04:00 | 18:30:00 | 00:26:00 |
| 25488 | 18:30:00 | 19:00:00 | 00:30:00 |
| 25488 | 19:00:00 | 19:30:00 | 00:30:00 |
| 25488 | 19:30:00 | 20:00:00 | 00:30:00 |
| 25488 | 20:00:00 | 20:30:00 | 00:30:00 |
| 25488 | 20:30:00 | 21:00:00 | 00:30:00 |
| 25488 | 21:00:00 | 21:22:00 | 00:22:00 |
->Fiddle
This works for SQL Server 2019:
WITH times([Open], [Close]) AS (
SELECT cast({t'00:00:00'} as time) as "Open",
cast({t'00:30:00'} as time) as "Close"
UNION ALL
SELECT dateadd(minute, 30, [Open]), dateadd(minute, 30, [Close])
FROM times
WHERE [Open] < cast({t'23:30:00'} as time)
)
SELECT c.[Check],
iif(t.[Open] > c.[Open], t.[Open], c.[Open]) as [Open],
iif(t.[Close] < c.[CloseTime], t.[Close], c.[CloseTime]) as [Close],
datediff(minute,
iif(t.[Open] > c.[Open], t.[Open], c.[Open]),
iif(t.[Close] < c.[CloseTime], t.[Close], c.[CloseTime])) Duration
FROM times t
JOIN checks c ON (c.[Open] < t.[Close] AND c.[CloseTime] > t.[Open]);
Check | Open | Close | Duration
25484 | 17:34:00.0000000 | 18:00:00.0000000 | 26
25484 | 18:00:00.0000000 | 18:06:00.0000000 | 6
25488 | 18:04:00.0000000 | 18:30:00.0000000 | 26
25488 | 18:30:00.0000000 | 19:00:00.0000000 | 30
25488 | 19:00:00.0000000 | 19:30:00.0000000 | 30
25488 | 19:30:00.0000000 | 20:00:00.0000000 | 30
25488 | 20:00:00.0000000 | 20:30:00.0000000 | 30
25488 | 20:30:00.0000000 | 21:00:00.0000000 | 30
25488 | 21:00:00.0000000 | 21:22:00.0000000 | 22
->Fiddle
How can I generate the following table in BigQuery:
+---------------------+
| mydate |
+---------------------+
| 2010-01-01 00:00:00 |
| 2010-01-01 01:00:00 |
| 2010-01-01 02:00:00 |
| 2010-01-01 03:00:00 |
| 2010-01-01 04:00:00 |
| 2010-01-01 05:00:00 |
+---------------------+
Use below
select ts
from unnest(generate_timestamp_array('2010-01-01 00:00:00', '2010-01-01 05:00:00', interval 1 hour)) ts
with output
Another option (based on #Daniel's comment and #Khilesh's answer)
select timestamp('2010-01-01 00:00:00') + make_interval(hour => hours_to_add)
from unnest(generate_array(0,5)) AS hours_to_add
obviously with same output as above
You can try this as well
SELECT
TIMESTAMP_ADD(TIMESTAMP("2010-01-01 00:00:00", INTERVAL hours_to_add HOURS) as mydate
from
(SELECT num1 as hours_to_add FROM UNNEST(GENERATE_ARRAY(0,2400)) AS num1)
Output :
+---------------------+
| mydate |
+---------------------+
| 2010-01-01 00:00:00 |
| 2010-01-01 01:00:00 |
| 2010-01-01 02:00:00 |
| 2010-01-01 03:00:00 |
| 2010-01-01 04:00:00 |
| 2010-01-01 05:00:00 |
+---------------------+
In Postgres below query is working using generate_series function
SELECT dates
FROM generate_series(CAST('2019-03-01' as TIMESTAMP), CAST('2019-04-01' as TIMESTAMP), interval '30 mins') AS dates
Below query is also working in Oracle but only for date interval
select to_date('2019-03-01','YYYY-MM-DD') + rownum -1 as dates
from all_objects
where rownum <= to_date('2019-03-06','YYYY-MM-DD')-to_date('2019-03-01','YYYY-MM-DD')+1
SELECT dates
FROM generate_series(CAST('2019-03-01' as TIMESTAMP), CAST('2019-04-01' as TIMESTAMP), interval '30 mins') AS dates
I want same result in Oracle for below query
SELECT dates
FROM generate_series(CAST('2019-03-01' as TIMESTAMP), CAST('2019-04-01' as TIMESTAMP), interval '30 mins') AS dates
Use a hierarchical query:
SELECT DATE '2019-03-01' + ( LEVEL - 1 ) * INTERVAL '30' MINUTE AS dates
FROM DUAL
CONNECT BY DATE '2019-03-01' + ( LEVEL - 1 ) * INTERVAL '30' MINUTE <= DATE '2019-04-01';
Output:
| DATES |
| :------------------ |
| 2019-03-01 00:00:00 |
| 2019-03-01 00:30:00 |
| 2019-03-01 01:00:00 |
| 2019-03-01 01:30:00 |
| 2019-03-01 02:00:00 |
| 2019-03-01 02:30:00 |
| 2019-03-01 03:00:00 |
| 2019-03-01 03:30:00 |
| 2019-03-01 04:00:00 |
| 2019-03-01 04:30:00 |
| 2019-03-01 05:00:00 |
| 2019-03-01 05:30:00 |
...
| 2019-03-31 19:30:00 |
| 2019-03-31 20:00:00 |
| 2019-03-31 20:30:00 |
| 2019-03-31 21:00:00 |
| 2019-03-31 21:30:00 |
| 2019-03-31 22:00:00 |
| 2019-03-31 22:30:00 |
| 2019-03-31 23:00:00 |
| 2019-03-31 23:30:00 |
| 2019-04-01 00:00:00 |
db<>fiddle here
I have a PostgreSQL table containing start timestamp and duration time.
timestamp | interval
------------------------------
2018-01-01 15:00:00 | 06:00:00
2018-01-02 23:00:00 | 04:00:00
2018-01-04 09:00:00 | 2 days 16 hours
What I would like is to have the interval splitted into every day like this:
timestamp | interval
------------------------------
2018-01-01 15:00:00 | 06:00:00
2018-01-02 23:00:00 | 01:00:00
2018-01-03 00:00:00 | 03:00:00
2018-01-04 09:00:00 | 15:00:00
2018-01-05 00:00:00 | 24:00:00
2018-01-06 00:00:00 | 24:00:00
2018-01-07 00:00:00 | 01:00:00
I am playing with generate_series(), width_bucket(), range functions, but I still can't find plausible solution. Is there any existing or working solution?
not sure about all edge cases, but this seems working:
t=# with c as (select *,min(t) over (), max(t+i) over (), tsrange(date_trunc('day',t),t+i) tr from t)
, mid as (
select distinct t,i,g,tr
, case when g < t then t else g end tt
from c
right outer join (select generate_series(date_trunc('day',min),date_trunc('day',max),'1 day') g from c) e on g <# tr order by 3,1
)
select
tt
, i
, case when tt+'1 day' > upper(tr) and t < g then upper(tr)::time::interval when upper(tr) - lower(tr) < '1 day' then i else g+'1 day' - tt end
from mid
order by tt;
tt | i | case
---------------------+-----------------+----------
2018-01-01 15:00:00 | 06:00:00 | 06:00:00
2018-01-02 23:00:00 | 04:00:00 | 01:00:00
2018-01-03 00:00:00 | 04:00:00 | 03:00:00
2018-01-04 09:00:00 | 2 days 16:00:00 | 15:00:00
2018-01-05 00:00:00 | 2 days 16:00:00 | 1 day
2018-01-06 00:00:00 | 2 days 16:00:00 | 1 day
2018-01-07 00:00:00 | 2 days 16:00:00 | 01:00:00
(7 rows)
also please mind that timestamp without time zone can fail you when comparing timestamps...
In my Postgres database, I have the following table:
SELECT start_at, end_at FROM schedules;
+---------------------+---------------------+
| start_at | end_at |
|---------------------+---------------------|
| 2016-09-05 16:30:00 | 2016-09-05 17:30:00 |
| 2016-09-05 17:30:00 | 2016-09-05 18:30:00 |
| 2017-08-13 03:00:00 | 2017-08-13 07:00:00 |
| 2017-08-13 03:00:00 | 2017-08-13 07:00:00 |
| 2017-08-13 18:42:26 | 2017-08-13 21:30:46 |
| 2017-08-10 00:00:00 | 2017-08-10 03:30:00 |
| 2017-08-09 18:00:00 | 2017-08-10 03:00:00 |
| 2017-08-06 23:00:00 | 2017-08-07 03:00:00 |
| 2017-08-07 01:00:00 | 2017-08-07 03:48:20 |
| 2017-08-07 01:00:00 | 2017-08-07 03:48:20 |
| 2017-08-07 18:05:00 | 2017-08-07 20:53:20 |
| 2017-08-07 14:00:00 | 2017-08-08 01:00:00 |
| 2017-08-07 18:00:00 | 2017-08-07 20:48:20 |
| 2017-08-08 08:00:00 | 2017-08-09 00:00:00 |
| 2017-08-09 21:30:00 | 2017-08-10 00:18:20 |
| 2017-08-13 03:53:26 | 2017-08-13 06:41:46 |
+---------------------+---------------------+
Assume I also have an ID column, what I want to do is update all the start and end times to be for today (now), what is the most efficient SQL to accomplish this? My table could have millions of rows.
the best I can think of is this:
update schedules
set start_at = current_date + start_at::time
, end_at = current_date + end_at::time
WHERE start_at::date <> current_date
or end_at::date <> current_date;
The arithmetic is fast compared to accessing the rows.
if not all rows need updating, the where clause will help efficiency. Updates are expensive.