I'm trying to create this query to get all complete date on range and data with nulls if the date is not exist on the table
For example this is my tbl_example
Original data:
id | userid(str) | comment(str) | mydate(date)
1 0001 sample1 2019-06-20T16:00:00.000Z
2 0002 sample2 2019-06-21T16:00:00.000Z
3 0003 sample3 2019-06-24T16:00:00.000Z
4 0004 sample4 2019-06-25T16:00:00.000Z
5 0005 sample5 2019-06-26T16:00:00.000Z
Then:
select * from tbl_example where mydate between '2019-06-20' AND
DATE('2019-06-20') + interval '5 day')
how to output all the dates on range with possible null like this
Expected output:
id | userid(str) | comment(str) | mydate(date)
1 0001 sample1 2019-06-20T16:00:00.000Z
2 0002 sample2 2019-06-21T16:00:00.000Z
null null null 2019-06-22T16:00:00.000Z
null null null 2019-06-23T16:00:00.000Z
4 0003 sample3 2019-06-24T16:00:00.000Z
5 0004 sample4 2019-06-25T16:00:00.000Z
This is my sample test environment: http://www.sqlfiddle.com/#!17/f5285/2
OK, just see my SQL as below:
with all_dates as (
select generate_series(min(mydate),max(mydate),'1 day'::interval) as dates from tbl_example
)
,null_dates as (
select
a.dates
from
all_dates a
left join
tbl_example t on a.dates = t.mydate
where
t.mydate is null
)
select null as id, null as userid, null as comment, dates as mydate from null_dates
union
select * from tbl_example order by mydate;
id | userid | comment | mydate
----+--------+---------+---------------------
1 | 0001 | sample1 | 2019-06-20 16:00:00
2 | 0002 | sample1 | 2019-06-21 16:00:00
| | | 2019-06-22 16:00:00
| | | 2019-06-23 16:00:00
3 | 0003 | sample1 | 2019-06-24 16:00:00
4 | 0004 | sample1 | 2019-06-25 16:00:00
5 | 0005 | sample1 | 2019-06-26 16:00:00
(7 rows)
Or the generate_series clause you can just write the date arguments you want ,as below:
select generate_series('2019-06-20 16:00:00','2019-06-20 16:00:00'::timestamp + '5 days'::interval,'1 day'::interval) as dates
SELECT id, userid, "comment", d.mydate
FROM generate_series('2019-06-20'::date, '2019-06-25'::date, INTERVAL '1 day') d (mydate)
LEFT JOIN tbl_example ON d.mydate = tbl_example.mydate
Result
Related
I'm on Postgres 13 and have a table like this
| key | from | to
-------------------------------------------
| A | 2022-11-27T08:00 | 2022-11-27T09:00
| B | 2022-11-27T09:00 | 2022-11-27T10:00
| C | 2022-11-27T08:30 | 2022-11-27T10:30
I want to calculate the duration of each record, but without overlaps. So the desired result would be
| key | from | to | duration
----------------------------------------------------------
| A | 2022-11-27T08:00 | 2022-11-27T09:00 | '1 hour'
| B | 2022-11-27T09:00 | 2022-11-27T09:45 | '45 minutes'
| C | 2022-11-27T08:30 | 2022-11-27T10:00 | '15 minutes'
I guess, I need a subquery and subtract the overlap somehow, but how would I factor in multiple overlaps? In the example above C overlaps A and B, so I must subtract 30 minutes from A and then 45 minute from B... But I'm stuck here:
SELECT key, (("to" - "from")::interval - s.overlap) as duration
FROM time_entries, (
SELECT (???) as overlap
) s
select
key,
fromDT,
toDT,
(toDT-fromDT)::interval -
COALESCE((SELECT SUM(LEAST(te2.toDT,te1.toDT)-GREATEST(te2.fromDT,te1.fromDT))::interval
FROM time_entries te2
WHERE (te2.fromDT<te1.toDT or te2.toDT>te1.fromDT)
AND te2.key<te1.key),'0 minutes') as duration
from time_entries te1;
output:
key
fromdt
todt
duration
A
2022-11-27 08:00:00
2022-11-27 09:00:00
01:00:00
B
2022-11-27 09:00:00
2022-11-27 10:00:00
01:00:00
C
2022-11-27 08:30:00
2022-11-27 10:30:00
00:30:00
I renamed the columns from and to to fromDT and toDT to avoid using reserved words.
a, step by step, explanation is in the DBFIDDLE
Another approach.
WITH DATA AS
(SELECT KEY,
FROMDT,
TODT,
MIN(FROMDT) OVER(PARTITION BY FROMDT::DATE
ORDER BY KEY) AS START_DATE,
MAX(TODT) OVER(PARTITION BY FROMDT::DATE
ORDER BY KEY) AS END_DATE
FROM TIME_ENTRIES
ORDER BY KEY) ,STAGING_DATA AS
(SELECT KEY,
FROMDT,
TODT,
COALESCE(LAG(START_DATE) OVER (PARTITION BY FROMDT::DATE
ORDER BY KEY),FROMDT) AS T1_DATE,
COALESCE(LAG(END_DATE) OVER (PARTITION BY FROMDT::DATE
ORDER BY KEY),TODT) AS T2_DATE
FROM DATA)
SELECT KEY,
FROMDT,
TODT,
CASE
WHEN FROMDT = T1_DATE
AND TODT = T2_DATE THEN (TODT - FROMDT) ::Interval
WHEN T2_DATE < TODT THEN (TODT - T2_DATE)::Interval
ELSE (T2_DATE - TODT)::interval
END
FROM STAGING_DATA;
everybody!
I have a table t(id, date1, date2):
id date1 date2
1 '2020-01-02' '2020-01-02'
1 '2020-01-12' '2020-01-02'
1 '2020-02-02' '2020-01-02'
1 '2020-03-02' '2020-01-02'
2 '2020-01-12' '2020-01-02'
2 '2020-01-15' '2020-01-02'
1 '2020-05-02' '2020-01-02'
1 '2020-06-02' '2020-01-02'
I need to update it like this:
id date1 date2
1 '2020-01-02' '2020-01-11'
1 '2020-01-12' '2020-02-01'
1 '2020-02-02' '2020-02-01'
1 '2020-03-02' '2020-05-01'
2 '2020-01-12' '2020-01-14'
2 '2020-01-15' '2999-12-31'
1 '2020-05-02' '2020-06-01'
1 '2020-06-02' '2999-12-31'
in rows with equal id:
date2 = date1 [from next row] - 1
and for the last date1 in group of equal id:
date2 = '2999-12-31'
assuming you can order your columns by id and date1 in order to find which is the next row, you could use the LEAD, partitioned by id to get the next item in the list.
I replicate your case with:
create table test (id int, date1 date, date2 date);
insert into test values (1,'2020-01-02','2020-01-02');
insert into test values (1,'2020-01-12','2020-01-02');
insert into test values (1,'2020-02-02','2020-01-02');
insert into test values (1,'2020-03-02','2020-01-02');
insert into test values (2,'2020-01-12','2020-01-02');
insert into test values (2,'2020-01-15','2020-01-02');
insert into test values (1,'2020-05-02','2020-01-02');
insert into test values (1,'2020-06-02','2020-01-02');
And I could fetch the following date1 for each row with
select
id,
date1,
date2,
coalesce(lead(date1, 1) OVER (PARTITION BY id ORDER BY id, date1),'2999-12-31') date2_next
from test;
Result
id | date1 | date2 | date2_next
----+------------+------------+------------
1 | 2020-01-02 | 2020-01-02 | 2020-01-12
1 | 2020-01-12 | 2020-01-02 | 2020-02-02
1 | 2020-02-02 | 2020-01-02 | 2020-03-02
1 | 2020-03-02 | 2020-01-02 | 2020-05-02
1 | 2020-05-02 | 2020-01-02 | 2020-06-02
1 | 2020-06-02 | 2020-01-02 | 2999-12-31
2 | 2020-01-12 | 2020-01-02 | 2020-01-15
2 | 2020-01-15 | 2020-01-02 | 2999-12-31
(8 rows)
If you're looking for the update statement, check the one below
update test set date2=date2_next
from
(select id,
date1,
coalesce(lead(date1, 1) OVER (PARTITION BY id ORDER BY id, date1),'2999-12-31') date2_next
from test) nxt
where test.id = nxt.id and test.date1=nxt.date1;
This is TSQL and I'm trying to calculate repeat purchase rate for last 12 months. This is achieved by looking at sum of customers who have bought more than 1 time last 12 months and the total number of customers last 12 months.
The SQL code below will give me just that; but i would like to dynamically do this for the last 12 months. This is the part where i'm stuck and not should how to best achieve this.
Each month should include data going back 12 months. I.e. June should hold data between June 2018 and June 2018, May should hold data from May 2018 till May 2019.
[Order Date] is a normal datefield (yyyy-mm-dd hh:mm:ss)
DECLARE #startdate1 DATETIME
DECLARE #enddate1 DATETIME
SET #enddate1 = DATEADD(MONTH, DATEDIFF(MONTH, 0, GETDATE())-1, 0) -- Starting June 2018
SET #startdate1 = DATEADD(mm,DATEDIFF(mm,0,GETDATE())-13,0) -- Ending June 2019
;
with dataset as (
select [Phone No_] as who_identifier,
count(distinct([Order No_])) as mycount
from [MyCompany$Sales Invoice Header]
where [Order Date] between #startdate1 and #enddate1
group by [Phone No_]
),
frequentbuyers as (
select who_identifier, sum(mycount) as frequentbuyerscount
from dataset
where mycount > 1
group by who_identifier),
allpurchases as (
select who_identifier, sum(mycount) as allpurchasescount
from dataset
group by who_identifier
)
select sum(frequentbuyerscount) as frequentbuyercount, (select sum(allpurchasescount) from allpurchases) as allpurchasecount
from frequentbuyers
I'm hoping to achieve end result looking something like this:
...Dec, Jan, Feb, March, April, May, June each month holding both values for frequentbuyercount and allpurchasescount.
Here is the code. I made a little modification for the frequentbuyerscount and allpurchasescount. If you use a sumif like expression you don't need a second cte.
if object_id('tempdb.dbo.#tmpMonths') is not null drop table #tmpMonths
create table #tmpMonths ( MonthID datetime, StartDate datetime, EndDate datetime)
declare #MonthCount int = 12
declare #Month datetime = DATEADD(MONTH, DATEDIFF(MONTH, 0, GETDATE()), 0)
while #MonthCount > 0 begin
insert into #tmpMonths( MonthID, StartDate, EndDate )
select #Month, dateadd(month, -12, #Month), #Month
set #Month = dateadd(month, -1, #Month)
set #MonthCount = #MonthCount - 1
end
;with dataset as (
select m.MonthID as MonthID, [Phone No_] as who_identifier,
count(distinct([Order No_])) as mycount
from [MyCompany$Sales Invoice Header]
inner join #tmpMonths m on [Order Date] between m.StartDate and m.EndDate
group by m.MonthID, [Phone No_]
),
buyers as (
select MonthID, who_identifier
, sum(iif(mycount > 1, mycount, 0)) as frequentbuyerscount --sum only if count > 1
, sum(mycount) as allpurchasescount
from dataset
group by MonthID, who_identifier
)
select
b.MonthID
, max(tm.StartDate) StartDate, max(tm.EndDate) EndDate
, sum(b.frequentbuyerscount) as frequentbuyercount
, sum(b.allpurchasescount) as allpurchasecount
from buyers b inner join #tmpMonths tm on tm.MonthID = b.MonthID
group by b.MonthID
Be aware, that the code was tested only syntax-wise.
After the test data, this is the result:
MonthID | StartDate | EndDate | frequentbuyercount | allpurchasecount
-----------------------------------------------------------------------------
2018-08-01 | 2017-08-01 | 2018-08-01 | 340 | 3702
2018-09-01 | 2017-09-01 | 2018-09-01 | 340 | 3702
2018-10-01 | 2017-10-01 | 2018-10-01 | 340 | 3702
2018-11-01 | 2017-11-01 | 2018-11-01 | 340 | 3702
2018-12-01 | 2017-12-01 | 2018-12-01 | 340 | 3703
2019-01-01 | 2018-01-01 | 2019-01-01 | 340 | 3703
2019-02-01 | 2018-02-01 | 2019-02-01 | 2 | 8
2019-03-01 | 2018-03-01 | 2019-03-01 | 2 | 3
2019-04-01 | 2018-04-01 | 2019-04-01 | 2 | 3
2019-05-01 | 2018-05-01 | 2019-05-01 | 2 | 3
2019-06-01 | 2018-06-01 | 2019-06-01 | 2 | 3
2019-07-01 | 2018-07-01 | 2019-07-01 | 2 | 3
I have a table in PostgreSQL 10. The table has the following structure
| date | entity | col1 | col2 |
|------+--------+------+------|
Every row represents an event that happens to an entity in a given date. The event has attributes represented by col1 and col2.
I want to add a new column that indicates if with respect to the current row there are events in which the column col2 fulfills a given condition (in the following example the condition is col2 > 20) in a given interval (say 1 month) .
| date | entity | col1 | col2 | fulfill |
|------+--------+------+------+---------|
| t1 | A | a1 | 10 | F |
| t1 | B | b | 9 | F |
| t2 | A | a2 | 10 | T |
| t3 | A | a3 | 25 | F |
| t3 | B | b2 | 8 | F |
t3 is a date inside t2 + interval 1 month.
What is the most efficient way to acomplish this?
I am not sure if I got your problem correctly. My case is 'T if there is a value >= 10 between now an the next month'
I have the following data:
val event_date
--- ----------
22 2016-12-31 -- should be T because val >= 10
8 2017-03-20 -- should be F because in [event_date, eventdate + 1 month no val >= 10]
6 2017-03-22 -- F
42 2017-12-31 -- T because there are 2 values >= 10 in next month
25 2018-01-24 -- T val >= 10
9 2018-02-11 -- F
1 2018-03-01 -- T because in month there is 1 val >= 10
2 2018-03-10 -- T same
20 2018-04-01 -- T
7 2018-04-01 -- T because an same day val >= 10
1 2018-07-24 -- F
22 2019-01-01 -- T
4 2020-10-22 -- T
123 2020-11-04 -- T
The query:
SELECT DISTINCT
e1.val,
e1.event_date,
CASE
WHEN MAX(e2.val) over (partition BY e1.event_date) >= 10
THEN 'T'
ELSE 'F'
END AS fulfilled
FROM
testdata.events e1
JOIN
testdata.events e2
ON
e1.event_date <= e2.event_date
AND e2.event_date <=(e1.event_date + interval '1 month') ::DATE
ORDER BY
e1.event_date
The result:
val event_date fulfilled
--- ---------- ---------
22 2016-12-31 T
8 2017-03-20 F
6 2017-03-22 F
42 2017-12-31 T
25 2018-01-24 T
9 2018-02-11 F
1 2018-03-01 T
2 2018-03-10 T
20 2018-04-01 T
7 2018-04-01 T
1 2018-07-24 F
22 2019-01-01 T
4 2020-10-22 T
123 2020-11-04 T
Currently I am not finding a solution without joining the same table which seems not very stylish to me.
I have specific task, and don't know how to realize it. I hope someone can help me =)
I have stock_move table:
product_id |location_id |location_dest_id |product_qty |date_expected |
-----------|------------|-----------------|------------|--------------------|
327 |80 |84 |10 |2014-05-28 00:00:00 |
327 |80 |84 |10 |2014-05-23 00:00:00 |
327 |80 |84 |10 |2014-02-26 00:00:00 |
327 |80 |85 |10 |2014-02-21 00:00:00 |
327 |80 |84 |10 |2014-02-12 00:00:00 |
327 |84 |85 |20 |2014-02-06 00:00:00 |
322 |84 |80 |120 |2015-12-16 00:00:00 |
322 |80 |84 |30 |2015-12-10 00:00:00 |
322 |80 |84 |30 |2015-12-04 00:00:00 |
322 |80 |84 |15 |2015-11-26 00:00:00 |
i.e. it's table of product moves from one warehouse to second.
I can calculate stock at custom date if I use something like this:
select
coalesce(si.product_id, so.product_id) as "Product",
(coalesce(si.stock, 0) - coalesce(so.stock, 0)) as "Stock"
from
(
select
product_id
,sum(product_qty * price_unit) as stock
from stock_move
where
location_dest_id = 80
and date_expected < now()
group by product_id
) as si
full outer join (
select
product_id
,sum(product_qty * price_unit) as stock
from stock_move
where
location_id = 80
and date_expected < now()
group by product_id
) as so
on si.product_id = so.product_id
Result I have current stock:
Product |Stock |
--------|------|
325 |1058 |
313 |34862 |
304 |2364 |
BUT what to do if I need stock per month?
something like this?
Month |Total Stock |
--------|------------|
Jan |130238 |
Feb |348262 |
Mar |2323364 |
How can I sum product qty from start period to end of each month?
I have just one idea - it's use 24 sub queries for get stock per each month (ex. below)
Jan |Feb | Mar |
----|----|-----|
123 |234 |345 |
End after this rotate rows and columns?
I think this's stupid, but I don't know another way... Help me pls =)
Something like this could give you monthly "ending" inventory snapshots. The trick is your data may omit certain months for certain parts, but that part will still have a balance (ie 50 received in January, nothing happened in February, but you still want to show February with a running total of 50).
One way to handle this is to come up with all possible combinations part/dates. I assumed 1/1/14 + 24 months in this example, but that's easily changed in the all_months subquery. For example, you may only want to start with the minimum date from the stock_move table.
with all_months as (
select '2014-01-01'::date + interval '1 month' * generate_series(0, 23) as month_begin
),
stock_calc as (
select
product_id, date_expected,
date_trunc ('month', date_expected)::date as month_expected,
case
when location_id = 80 then -product_qty * price_unit
when location_dest_id = 80 then product_qty * price_unit
else 0
end as qty
from stock_move
union all
select distinct
s.product_id, m.month_begin::date, m.month_begin::date, 0
from
stock_move s
cross join all_months m
),
running_totals as (
select
product_id, date_expected, month_expected,
sum (qty) over (partition by product_id order by date_expected) as end_qty,
row_number() over (partition by product_id, month_expected
order by date_expected desc) as rn
from stock_calc
)
select
product_id, month_expected, end_qty
from running_totals
where
rn = 1