I have an input table as below:
name
time
price
one
2022-11-22 19:00:00 UTC
12
one
2022-11-23 7:00:00 UTC
24
one
2022-11-23 19:00:00 UTC
10
one
2022-11-24 7:00:00 UTC
20
My expected output is:
name
time
price
one
2022-11-22
36
one
2022-11-23
30
Explanation:
I have to group-by 2 consecutive timestamps, the prev date 19:00:00 UTC and the next date 7:00:00 UTC and name the row with the prev date.
Sum the price for each 2 consecutive rows.
Approach:
As I understand, I have to use partition by on the time column, but I cannot figure out how to combine with exact timestamps.
with cte as (
select name,
time,
price,
(row_number() over (partition by name order by time)+1) div 2 as group_no
from consec_data)
select name,
min(time) as time,
sum(price) as price
from cte
group by name, group_no;
Related
Say I have two tables:
a:
timestamp
precipitation
2015-08-03 21:00:00 UTC
3
2015-08-03 22:00:00 UTC
3
2015-08-04 3:00:00 UTC
4
2016-02-04 18:00:00 UTC
4
and b:
timestamp
loc
2015-08-03 21:23:00 UTC
San Francisco
2016-02-04 16:04:00 UTC
New York
I want to join to get a table who has fuzzy joined entries where every row in b tries to get joined to a row in a. Criteria:
The time is within 60 minutes. If a match does not exist within 60 minutes, do not include that row in the output.
In the case of a tie where some row in b could join onto two rows in a, pick the closest one in terms of time.
Example Output:
timestamp
loc
precipitation
2015-08-03 21:00:00 UTC
San Francisco
3
What you need is an ASOF join. I don't think there is an easy way to do this with BigQuery. Other databases like Kinetica (and I think Clickhouse) support ASOF functions that can be used to perform 'fuzzy' joins.
The syntax for Kinetica would be something like the following.
SELECT *
FROM a
LEFT JOIN b
ON ASOF(a.timestamp, b.timestamp, INTERVAL '0' MINUTES, INTERVAL '60' MINUTES, MIN)
The ASOF function above sets up an interval of 60 minutes within which to look for matches on the right side table. When there are multiple matches, it selects the one that is closest (MAX would pick the one that is farthest away).
As per my understanding and based on the data you provided I think the below query should work for your use case.
create temporary table a as(
select TIMESTAMP('2015-08-03 21:00:00 UTC') as ts, 3 as precipitation union all
select TIMESTAMP('2015-08-03 22:00:00 UTC'), 3 union all
select TIMESTAMP('2015-08-04 3:00:00 UTC'), 4 union all
select TIMESTAMP('2016-02-04 18:00:00 UTC'), 4
);
create temporary table b as(
select TIMESTAMP('2015-08-03 21:23:00 UTC') as ts,'San Francisco ' as loc union all
select TIMESTAMP('2016-02-04 14:04:00 UTC') as ts,'New York ' as loc
);
select b_ts,a_ts,loc,precipitation,diff_time_sec
from(
select b.ts b_ts,a.ts a_ts,
ABS(TIMESTAMP_DIFF(b.ts,a.ts, SECOND)) as diff_time_sec,
*
from b
inner join a on b.ts between date_sub(a.ts, interval 60 MINUTE) and date_add(a.ts, interval 60 MINUTE)
)
qualify RANK() OVER(partition by b_ts ORDER BY diff_time_sec) = 1
I have two tables. One defines time intervals (beginning and end). Time intervals are not equal in length. Another contains product ID, start and end date of the product.
TableOne:
Interval StartDateTime EndDateTime
202020201 2020-01-01 00:00:00 2020-02-10 00:00:00
202020202 2020-02-10 00:00:00 2020-02-20 00:00:00
TableTwo
ProductID ProductStartDateTime ProductEndDateTime
ASSDWE1 2018-01-04 00:12:00 2020-04-10 20:00:30
ADFGHER 2020-01-05 00:11:30 2020-01-19 00:00:00
ASDFVBN 2017-10-10 00:12:10 2020-02-23 00:23:23
I need to compute the average length of the products from TableTwo that existed during time intervals defined in TableOne. If the product existed throughout the time interval from TableOne, then the length of the product during this time interval is defined as it length since its start date till the end of the time interval.
I tried the following
select
a.*,
(select
AVG(datediff(day, b.ProductStartDateTime, IIF (b.ProductEndDateTime> a.EndDateTime, a.EndDateTime
,b.ProductEndDateTime))) --compute average length of the products
FROM #TableTwo b
WHERE ( not (b.ProductEndDateTime <= a.StartDateTime ) and not (b.ProductStartDateTime >= a.EndDateTime) )
-- select products that existed during interval from #TableOne
) as AverageProductLength
from #TableOne a
I get the mistake "Multiple columns are specified in an aggregated expression containing an outer reference. If an expression being aggregated contains an outer reference, then that outer reference must be the only column referenced in the expression."
The result I want:
Interval StartDateTime EndDateTime AverageProductLength
202020201 2020-01-01 00:00:00 2020-02-10 00:00:00 23
202020202 2020-02-10 00:00:00 2020-02-20 00:00:00 34.5
Is there a way I can do the averaging?
I have a table where I store all status changes and the time that it has been made. So, when I search the order number on the table of times I get all the dates of my changes, but what I realy want is the time (hours/minutes) that the order was in each status.
The table of time seems like this
ID_ORDER | Status | Date
1 Waiting 27/09/2017 12:00:00
1 Late 27/09/2017 14:00:00
1 In progress 28/09/2017 08:00:00
1 Validating 30/09/2017 14:00:00
1 Completed 30/09/2017 14:00:00
Thanks!
Use lead():
select t.*,
(lead(date) over (partition by id_order order by date) - date) as time_in_order
from t;
I have a database table named availableTimeslot with fields pk, startDate, endDate, e.g.
PK startDate endDate
1. 2017-03-07 09:00:00 2017-03-07 18:00:00
2. 2017-03-07 18:00:00 2017-03-07 21:00:00
3. 2017-03-08 09:00:00 2017-03-08 18:00:00
records starting from 09:00:00 to 18:00:00 indicate it is a morning time slot, while 18:00:00 to 23:00:00 indicating it is a afternoon time slot
storing available timeslot dates (e.g. 2017-03-06, 2017-03-08) which are available for the customer to choose one.
Can I use one query to get exactly 10 available time slots dates starting on the day after the order date?
e.g. if I order a product on 2016-03-07, then the query returns
2017-03-08 09:00:00
2017-03-08 18:00:00
2017-03-09 09:00:00
2017-03-09 18:00:00
2017-03-10 ...
2017-03-11 ...
2017-03-13 ...
as 12 is a public holiday and not in the table.
In short, it returns 10 dates (5 days with each day having am and pm sessions)
remark: the available time slot dates are in order, but may not be consecutive
select available_date
from ( select available_date, row_number() over (order by available_date) as rn
from your_table
where available_date > :order_date
)
where rn <= 5;
:order_date is a bind variable - the date entered by the user/customer through the interface.
Do you want 5 for a single customer?
select ts.*
from (select ts.*
from customer c join
timeslots ts
on ts.date > c.orderdate
where c.customerid = v_customerid
order by ts.date asc
) ts
where rownum <= 5
Is is possible to select a datetime field from a MySQL table and group by the date only?
I'm trying to output a list of events that happen at multiple times, grouped by the date it happened on.
My table/data looks like this: (the timestamp is a datetime field)
1. 2010-03-21 18:00:00 Event1
2. 2010-03-21 18:30:00 Event2
3. 2010-03-30 13:00:00 Event3
4. 2010-03-30 14:00:00 Event4
I want to output something like this:
March 21st
1800 - Event 1
1830 - Event 2
March 30th
1300 - Event 3
1400 - Event 4
Thanks!
select date_format(created_at, "%Y-m-%d") as date from tablename GROUP BY date
OR
SELECT DATE_FORMAT(date_column, '%H%i') as time, event FROM table ORDER BY DATE_FORMAT(date_column, '%Y-%m-%d'), time
SELECT DATE_FORMAT(date_column, '%H%i'), DATE_FORMAT(date_column, '%M %D'), event FROM table ORDER BY date_column
%H%i - 1830
%M%D - March 21st