Data example:
id visiting_time
1 13.01.2001 02:34
1 14.01.2001 02:36
1 15.01.2001 02:36
1 16.01.2001 02:37
1 17.01.2001 02:38
1 18.01.2001 02:39
1 19.01.2001 02:40
2 13.01.2001 02:35
2 15.01.2001 02:36
2 16.01.2001 02:37
2 17.01.2001 02:38
2 18.01.2001 02:39
2 19.01.2001 02:40
I want to get all users which were online everyday for the last week, f.e. from 13th january 00:00 till 20th january 00:00.
For my data sample the answer is:
id
1
Considered
everyday for the last week, f.e. from 13th january 00:00 till 20th
january 00:00
and
I point it out myself. In general, I can choose any number of days I
want.
I guess it works only as a filter so the task is "find users online everyday during selected interval
SELECT id,
count(DISTINCT toDate(visiting_time)) AS number_of_days_visited
FROM user_visits
WHERE visiting_time BETWEEN '2001-01-13 00:00:00' AND '2001-01-20 00:00:00'
GROUP BY id
HAVING number_of_days_visited =
round((toUInt32(toDateTime('2001-01-20 00:00:00')) - toUInt32(toDateTime('2001-01-13 00:00:00'))) / 60 / 60 / 24)
In HAVING I computed number of days from the WHERE filter.
The below code will work only if the visiting_time column format is YYYY-MM-DD HH:MM, otherwise the dates are not comparable:
SELECT t.id FROM (SELECT id, COUNT(DISTINCT substr(visiting_time, 1, 10)) AS counter From table1 WHERE ((visiting_time >= '2001-01-13 00:00' AND visiting_time < '2001-01-20 00:00')) GROUP BY id) AS t WHERE t.counter=7
Related
I need to pull all records from 6 months ago up to present.
At first I hardcoded the date for today (Sep 2, 2021) and got the result I expected:
select case_no, closed_dt from table1
where closed_dt >= add_months(TO_DATE('09/02/2021', 'mm/dd/yyyy'), -6)
order by closed_dt
This gave me the results I wanted, a list of records from Mar 2, 2021, up through today:
CASE_NO | CLOSED_DT
-------------------
94 | 03/02/2021
57 | 03/03/2021
29 | 07/26/2021
04 | 09/02/2021
However, this query will be in an automatic script and so I cannot hardcode the date, I need it to dynamically change to always be 6 months in the past. So I tried to use sysdate, and got this result instead:
select case_no, closed_dt from table1
where closed_dt >= add_months(sysdate, -6)
order by closed_dt
Result:
CASE_NO | CLOSED_DT
-------------------
57 | 03/03/2021
29 | 07/26/2021
04 | 09/02/2021
As you can see, the record from Mar 2 is now not getting returned, even though it should be.
Even more confusingly, when I do
select add_months(sysdate, -6) from dual
It returns 03/02/2021 as expected.
Can anyone explain what is happening, and provide the correct solution to return records from 6 months ago by using sysdate?
An Oracle date always has a day and a time component. TO_DATE('09/02/2021', 'mm/dd/yyyy') returns a date of 2 September 2021 at midnight. On the other hand sysdate returns the current day and time (2 September 2021 13:51:00 on my local machine). Assuming the data in your table has a value of 2 March 2021 at midnight, the first query would return the row while the second query would not because of the time.
I'd expect that you want to use the trunc function to set the time component to midnight
where closed_dt >= add_months(trunc(sysdate), -6)
I have a data table something similar to having a customer ID and an item purchase date as shown below. As a filter, I want to return customer ID IFF a given Customer ID has at least 1 purchase in the last 30 rolling days.
Is this something that can be done with a simple WHERE clause ? For my purposes, this data table has many records where a customer ID might have hundreds of transactions
Customer ID Item Date Purchased
233 2021-05-27
111 2021-05-27
111 2021-05-21
23 2021-05-12
412 2021-03-11
111 2021-03-03
Desired output:
Customer ID
233
111
23
Originally thought to use a CTE to initially filter out any users that don't have at least 1 item purchase within the last 30 days. Tried the following two different where statements but both didn't work returning incorrect date timeframes.
SELECT *
FROM data d
WHERE 30 <= datediff(days, d.ITEM_PURCHASE_DATE, current_date) X
WHERE t.DATE_CREATED <= current_date + interval '30 days' X
To get the customers that have made at least one purchase in the last 30 days you can do this:
select distinct
customer_id
from sample_table
where item_date_purchased > dateadd(day, -30, current_date());
the dateadd function shown above returns a date 30 days prior to the current date.
The approach with INTERVAL was almost correct.
SELECT *
FROM data d
WHERE d.DATE_CREATED <= current_date + interval '30 days'
-- this date is from the future instead of the past
=>
SELECT *
FROM data d
WHERE d.DATE_CREATED >= current_date - interval '30 days'
I have the following sql Code (where clause just to limit rows currently)
select
month,
monthname,
year,
count(distinct case when a.dim_service_type_id_desc like '%Direct Payment%' then a.DIM_PERSON_ID else null end) as No_dp,
count(distinct a.DIM_PERSON_ID) as no_ppl
from
SERVICE_PROVISIONS a
inner join date_tbl d on CONVERT(VARCHAR(35),a.start_dttm,112) = d.dim_date_id
where
a.dim_person_id >0
and year = 2018
group by
month,
monthname,
year
my output is this
month monthname year No_dp no_ppl
1 January 2018 142 1604
2 February 2018 111 1526
3 March 2018 133 1636
4 April 2018 1107 3829
5 May 2018 140 1575
6 June 2018 131 1389
7 July 2018 200 893
8 August 2018 2 73
9 September 2018 1 32
10 October 2018 2 21
11 November 2018 2 21
12 December 2018 2 19
So my question is - the customer wants to see how many services were open (using start date and end date) during the previous 12 months (not how many were started, but how many were current and not ended). This is fine when using the current month, however they want to show this also for the previous 12 months as a rolling dynamic figure.
So for example this month in July they want to see how many services were open during the last 12 months. Last month June, they want to see how many services were open during the 12 months previous to June and so on for the previous 12 months.
The table needs to have the month name for the last 12 months and in a column show the number of services that were open in the previous 12 months next to that month.
I hope that makes sense, sorry if it doesn't, feel free to ask questions and I will try to clarify.
The output needs to look something like the current output table, but it is currently only showing how many services were started within that month, which isn't what we want.
The date table is a reference table which has different date formats etc. It can be used or added to if needed.
I've had to make several assumptions about your data. Hopefully the query I'll show in a minute will be easy for you to adjust if any of these are wrong:
I am guessing by its name that start_dttm is a datetime or datetime2 column.
I assume there is a corresponding column called end_dttm that gives the end date/time of a service, and that a null in this column would indicate that a service has not yet ended.
My best guess as to what it means for a service to be "open" in a given month is that it began sometime either within or prior to that month, and has not ended by the time that month is over.
I assume from your original query that multiple services having the same dim_person_id do not represent distinct services.
Since I don't know what's in your date_tbl, I'll show an example that doesn't require it. Consider the following query:
select
BeginDate = dateadd(month, -1, dateadd(day, 1, eomonth(getdate(), -Offset.X))),
EndDate = dateadd(day, 1, eomonth(getdate(), -Offset.X))
from
(values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11)) Offset(X)
This will give you 12 records, representing the current month and each of the 11 preceding months. Note that my EndDate here is not actually the last day of the month, but the first day of the following month. I've done this because of assumption 1 above; since your service dates may have time components, I'll determine whether they fall in a given month by checking if their dates are strictly earlier than the start of the following month. Here's what that query gives me:
BeginDate EndDate
2018-07-01 2018-08-01
2018-06-01 2018-07-01
2018-05-01 2018-06-01
2018-04-01 2018-05-01
2018-03-01 2018-04-01
2018-02-01 2018-03-01
2018-01-01 2018-02-01
2017-12-01 2018-01-01
2017-11-01 2017-12-01
2017-10-01 2017-11-01
2017-09-01 2017-10-01
2017-08-01 2017-09-01
Now I'll join the above result set to your SERVICE_PROVISIONS data, looking for records in each month that have dim_person_id > 0 (from your original query) and which satisfy assumption 3 above.
-- Some sample data (assumptions 1 & 2)
declare #SERVICE_PROVISIONS table (dim_person_id bigint, start_dttm datetime, end_dttm datetime);
insert #SERVICE_PROVISIONS values
(1, '20180101', '20180315'),
(1, '20180101', '20180315'),
(2, '20171215', '20180520');
-- The CTE defines the months we'll report on, as described earlier.
with MonthsCTE as
(
select
BeginDate = dateadd(month, -1, dateadd(day, 1, eomonth(getdate(), -Offset.X))),
EndDate = dateadd(day, 1, eomonth(getdate(), -Offset.X))
from
(values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11)) Offset(X)
)
-- This query matches the months from the CTE against the applicable services.
select
[Month] = datepart(month, M.BeginDate),
[MonthName] = datename(month, M.BeginDate),
[Year] = datepart(year, M.BeginDate),
ServicesOpen = count(distinct S.dim_person_id) -- Assumption 4
from
MonthsCTE M
left join #SERVICE_PROVISIONS S on
S.dim_person_id > 0 and
S.start_dttm < M.EndDate and -- Assumption 3
(
S.end_dttm >= M.EndDate or
S.end_dttm is null -- Assumption 2
)
group by
M.BeginDate,
M.EndDate
order by
M.BeginDate;
Note that I moved the dim_person_id > 0 from the WHERE clause to the JOIN so that each of the 12 months will still appear in the result set even if there were no services open during that time. Results:
Month MonthName Year ServicesOpen
8 August 2017 0
9 September 2017 0
10 October 2017 0
11 November 2017 0
12 December 2017 1
1 January 2018 2
2 February 2018 2
3 March 2018 1
4 April 2018 1
5 May 2018 0
6 June 2018 0
7 July 2018 0
something a bit like this - if you can write a query to get the value you want for a row in your ootput, then use cross apply to link to that query. Counting records that have an open record before the month, but no close record before the month seems feasible
SELECT IQ. *, OA.SERVICE_PROVISIONS FROM (select
month,
monthname,
year,
a.dim_person_id dim_person_id,
count(distinct case when a.dim_service_type_id_desc like '%Direct Payment%' then a.DIM_PERSON_ID else null end) as No_dp,
count(distinct a.DIM_PERSON_ID) as no_ppl
from
SERVICE_PROVISIONS a
inner join date_tbl d on CONVERT(VARCHAR(35),a.start_dttm,112) = d.dim_date_id
where
a.dim_person_id >0
and year = 2018
group by
month,
monthname,
year) IQ
CROSS APPLY
(SELECT count(0) OpenThings FROM SERVICE_PROVISIONS SP1 WHERE
(sp1.startdate < DATEFROMPARTS(IQ.year,iq.month,1)
AND
sp1.enddate is null or sp1.enddate > DATEFROMPARTS(IQ.year,iq.month,1)) and sp1.dim_person_id = iq.dim_person_id
) AS OA
I have some data that I am trying to get some counts on. There are dates for when the record was entered and when it was closed, if it has been closed yet. I want to be able to get a count of how many records were still open from the previous month as of the first of the month. Here is an example. First table is the data, second table is the results I am looking for. In the second table, ignore the parenthesis, they are just the IDs of the records that make up that count.
Position DateEntered DateClosed
1 12/15/2017 12/20/2017
11 12/20/2017 1/7/2018
2 1/23/2018 2/3/2018
3 1/24/2018
4 2/15/2018
5 2/20/2018 5/16/2018
6 3/3/2018 3/15/2018
7 3/23/2018 4/12/2018
8 4/11/2018 5/10/2018
9 4/12/2018 4/25/2018
10 5/4/2018
Year Month Carried Over
2018 January 1 (11)
2018 February 2 (2,3)
2018 March 3 (3,4,5)
2018 April 4 (3,4,5,7)
2018 May 4 (3,4,5,8)
2018 June 3 (3,4,10)
2018 July 3 (3,4,10)
2018 August 3 (3,4,10)
Is this possible, and if so, how? Been racking my brain on this one for a few hours.
For each month, you want the number of rows that start before that month and end after. I'm thinking:
with dates as (
select cast('2018-01-01' as date) as dte
union all
select dateadd(month, 1, dte)
from dates
where dte < '2018-08-01'
)
select d.dte,
(select count(*)
from t
where t.dateentered < d.dte and
(t.dateclosed > d.dte or t.dateClosed is null)
) as carriedover
from dates d;
Note that this puts the date in a single column, rather than splitting the year and month into separate columns. That is easily arranged, but I prefer to keep date components together.
I have the following query that works fine, but it is giving me counts for a single, whole day (00:00 to 23:59 UTC). For example, it's giving me counts for all of January 1 2017 (00:00 to 23:59 UTC).
My dataset lends itself to be queried from 12:00 UTC to 12:00 UTC. For example, I'm looking for all counts from Jan 1 2017 12:00 UTC to Jan 2 2017 12:00 UTC.
Here is my query:
SELECT count(DISTINCT ltg_data.lat), cwa, to_char(time, 'MM/DD/YYYY')
FROM counties
JOIN ltg_data on ST_contains(counties.the_geom, ltg_data.ltg_geom)
WHERE cwa = 'MFR'
AND time BETWEEN '1987-06-01'
AND '1992-08-1'
GROUP BY cwa, to_char(time, 'MM/DD/YYYY');
FYI...I'm changing the format of the time so I can use the results more readily in javascript.
And a description of the dataset. It's thousands of point data that occurs within various polygons every second. I'm determining if the points are occurring withing the polygon "cwa = MFR" and then counting them.
Thanks for any help!
I see two approaches here.
first, join generate_series(start_date::timestamp,end_date,'12 hours'::interval) to get count in those generate_series. this would be more correct I believe. But it has a major minus - you have to lateral join it against existing data set to use min(time) and max(time)...
second, a monkey hack itself, but much less coding and less querying. Use different time zone to make 12:00 a start of the day, eg (you did not give the sample, so I generate content of counties with generate_series with 2 hours interval as sample data):
t=# with counties as (select generate_series('2017-09-01'::timestamptz,'2017-09-04'::timestamptz,'2 hours'::interval)
g)
select count(1),to_char(g,'MM/DD/YYYY') from counties
group by to_char(g,'MM/DD/YYYY')
order by 2;
count | to_char
-------+------------
12 | 09/01/2017
12 | 09/02/2017
12 | 09/03/2017
1 | 09/04/2017
(4 rows)
so for UTC time zone there are 12 two hours interval rows for days above, due to inclusive nature of generate_series in my sample, 1 row for last days. in general: 37 rows.
Now a monkey hack:
t=# with counties as (select generate_series('2017-09-01'::timestamptz,'2017-09-04'::timestamptz,'2 hours'::interval)
g)
select count(1),to_char(g at time zone 'utc+12','MM/DD/YYYY') from counties
group by to_char(g at time zone 'utc+12','MM/DD/YYYY')
order by 2;
count | to_char
-------+------------
6 | 08/31/2017
12 | 09/01/2017
12 | 09/02/2017
7 | 09/03/2017
(4 rows)
I select same dates for different time zone, switching it exactly 12 hours, getting first day starting at 31 Aug middday, not 1 Sep midnight, and the count changes, still totalling 37 rows, but grouping your requested way...
update
for your query I'd try smth like:
SELECT count(DISTINCT ltg_data.lat), cwa, to_char(time at time zone 'utc+12', 'MM/DD/YYYY')
FROM counties
JOIN ltg_data on ST_contains(counties.the_geom, ltg_data.ltg_geom)
WHERE cwa = 'MFR'
AND time BETWEEN '1987-06-01'
AND '1992-08-1'
GROUP BY cwa, to_char(time at time zone 'utc+12', 'MM/DD/YYYY');
also if you want to apply +12 hours logic to where clause - add at time zone 'utc+12' to "time" comparison as well