I have a table with below data
EMPID | DEVICE | EVENTTIME
-----------------------------------------
112 | READ_IN | 2018-11-02 07:00:00.000
112 | READ_IN | 2018-11-02 08:00:00.000
112 | READ_OUT | 2018-11-02 12:00:00.000
112 | READ_IN | 2018-11-02 13:00:00.000
112 | READ_OUT | 2018-11-02 16:00:00.000
I need a select query to achieve below data:
ID_Emp |Date |TimeIn |TimeOut|Hours
112 |02/11/2018 |8:00 |16:00 |7:00
In my table, the employee came at 7:00 but he didn't do his work then after one hour he came back and work. He took his lunch break at 12:00-13:00 and left his work at 16:00. So his total working hours will be 7 hours.
At first you need to eliminate time between 12 and 1, I wrote simple where clause for this. After that
I used PIVOT for transposing rows to columns by max EVENTTIME.
And finally, I wrote outermost SELECT query for converting columns to your intended format.
here is the fiddler link: http://sqlfiddle.com/#!4/f1189/10
here is the code:
SELECT
EMPID,
TO_CHAR(READ_IN, 'HH24:MI') READ_IN,
TO_CHAR(READ_OUT, 'HH24:MI') READ_OUT,
EXTRACT(HOUR FROM READ_OUT - READ_IN) HOUR
FROM (
select * from (
select * from Table1
WHERE
extract(hour from eventtime) not between '12' and '13'
)
PIVOT (
MAX(EVENTTIME)
for DEVICE in ( 'READ_IN' READ_IN, 'READ_OUT' READ_OUT )
)
)
please note that this example only works for oracle.
Related
The right answer on the following question:
That is a bug that was fixed in 11.2.0.3 or later if I recall correctly. (11.2.0.1 is no longer supported anyway. 11.2.0.4 is the only 11.2 release that is still supported) – #a_horse_with_no_name
The bug number is 11840579 and it was fixed in 11.2.0.3 and 12.1.0.1
– #a_horse_with_no_name
Question
I have a table
CREATE TABLE test(
from_date date,
to_date date
);
INSERT INTO test(from_date,to_date)
--VALUES('20171101','20171115');
VALUES(TO_DATE('20171101','YYYYMMDD'),TO_DATE('20171115','YYYYMMDD'));
The following query in Oracle return only one row (expected 15 rows)
WITH dateCTE(from_date,to_date,d,i) AS(
SELECT from_date,to_date,from_date AS d,1 AS i
FROM test
UNION ALL
SELECT from_date,to_date,d+INTERVAL '1' DAY,i+1
FROM dateCTE
WHERE d<to_date
)
SELECT d,i
FROM dateCTE
SQL Fiddle - http://sqlfiddle.com/#!4/36907/8
For test I changed the condition to i<10
WITH dateCTE(from_date,to_date,d,i) AS(
SELECT from_date,to_date,from_date AS d,1 AS i
FROM test
UNION ALL
SELECT from_date,to_date,d+INTERVAL '1' DAY,i+1
FROM dateCTE
--WHERE d<to_date
WHERE i<10 -- exit condition
)
SELECT d,i
FROM dateCTE
And get the next result
| D | I |
|------------|----|
| 2017-11-01 | 1 |
| 2017-10-31 | 2 |
| 2017-10-30 | 3 |
| 2017-10-29 | 4 |
| 2017-10-28 | 5 |
| 2017-10-27 | 6 |
| 2017-10-26 | 7 |
| 2017-10-25 | 8 |
| 2017-10-24 | 9 |
| 2017-10-23 | 10 |
Why do this recursive query returned bad result in Oracle?
SQL Fiddle - http://sqlfiddle.com/#!4/36907/5
I ran a similar query in SQLServer and I get the right result
WITH dateCTE(from_date,to_date,d,i) AS(
SELECT from_date,to_date,from_date AS d,1 AS i
FROM test
UNION ALL
SELECT from_date,to_date,DATEADD(DAY,1,d),i+1
FROM dateCTE
WHERE d<to_date
)
SELECT d,i
FROM dateCTE
The right result
d i
2017-11-01 1
2017-11-02 2
2017-11-03 3
2017-11-04 4
2017-11-05 5
2017-11-06 6
2017-11-07 7
2017-11-08 8
2017-11-09 9
2017-11-10 10
2017-11-11 11
2017-11-12 12
2017-11-13 13
2017-11-14 14
2017-11-15 15
Why it doesn't work in Oracle? What alternative variants can you suggest? Thank you!
Screen shots from a real system:
If you want to have a sequential from-date to to-date, Use such this select:
SELECT DATE '2017-11-01' + LEVEL - 1 AS D, LEVEL AS I
FROM DUAL
CONNECT BY LEVEL <= DATE '2017-11-15' - DATE '2017-11-01' + 1;
It's working for me in Oracle 11.2 Enterprise. Your SQL fiddle, however, plainly shows that it doesn't in every Oracle version.
I remember I had similar problems with dates in recursive queries. So there is a bug, that has been fixed in newer versions. It is very likely, your Oracle version has this bug.
A workaround: Get only the integer offsets from the recursive query and add them to the from_date afterwards:
WITH dateCTE(from_date, i, iend) AS
(
SELECT from_date, 1 AS i, to_date - from_date as iend
FROM test
UNION ALL
SELECT from_date, i + 1, iend
FROM dateCTE
WHERE i <= iend
)
, dates as (select i, from_date + i - 1 as d from dateCTE)
SELECT d, i
FROM dates;
I am trying to write a query to retrieve data from an events query for a simple calendar app.
The table structure is as followed:
table name: events
Column | Type
---------+-----------
id | integer
start | timestamp
end | timestamp
the data inside of the table
id| start | end
--+---------------------+--------------------
1 | 2017-09-01 12:00:00 | 2017-09-01 12:00:00
2 | 2017-09-03 10:00:00 | 2017-09-03 12:00:00
3 | 2017-09-08 12:00:00 | 2017-09-11 12:00:00
4 | 2017-09-11 12:00:00 | 2017-09-11 12:00:00
the expected result is
date | event.id
-----------+---------
2017-09-01 | 1
2017-09-03 | 2
2017-09-08 | 3
2017-09-09 | 3
2017-09-10 | 3
2017-09-11 | 3
2017-09-11 | 4
As you can see, only days with an event (not just start and end, but also the days in between) is retrieved, days without an event are not retrieved at all.
In the second step I would like to be able to limit the amount of distinct days, e.g. "get 4 days with events" what might be more than 4 rows.
Right now I am able to retrieve the events based on start date only using the following query:
SELECT start::date, id FROM events WHERE events.start::date >= '2017-09-01' LIMIT 3
Thinks I already though about are DENSE_RANK and generate_series, but up to now I didn't find a way to fill the gaps between start and end, but not on days where there are no data.
So in short:
What I want to get is: get the next X days where there is an event. A date with an event is a day where start <= date >= end
Any ideas ?
Edit
Thanks to Tim I have now the following query (modified to use generate_series instead of a table and added a limit using dense_rank):
select date, id FROM (
SELECT
DENSE_RANK() OVER (ORDER BY t1.date) as rank,
t1.date,
events.id
FROM
generate_series([DATE]::date, [DATE]::date + interval '365 day', '1 day') as t1
INNER JOIN
events
ON t1.date BETWEEN events.start::date AND events."end"::date
) as t
WHERE rank <= [LIMIT]
This is working really good, even though I am not 100% sure about the performance hit with this kind of limit
I think you really need a calendar table here to cover the full range of dates in which your data may appear. In the first CTE below, I generate a table covering the month of September 2017. Then all we need to do is inner join this calendar table with the events table on the criteria of a given day appearing within a given range.
WITH cte AS (
SELECT CAST('2017-09-01' AS DATE) + (n || ' day')::INTERVAL AS date
FROM generate_series(0, 29) n
)
SELECT
t1.date,
t2.id
FROM cte t1
INNER JOIN events t2
ON t1.date BETWEEN CAST(t2.start AS DATE) AND CAST(t2.end AS DATE);
Output:
date id
1 01.09.2017 00:00:00 1
2 03.09.2017 00:00:00 2
3 08.09.2017 00:00:00 3
4 09.09.2017 00:00:00 3
5 10.09.2017 00:00:00 3
6 11.09.2017 00:00:00 3
7 11.09.2017 00:00:00 4
Demo here:
Rextester
I am trying to calculate a MIN date by Patient_ID for each record in my dataset that dynamically references the last 30 days from the date (Discharge_Dt) on that row. My initial thought was to use a window function, but I opted for a subquery, which is close, but not quite what I need.
Please note, my sample query is also missing logic that limits the MIN Discharge_Dt to the last 30 days, in other words, I do not want a MIN Discharge_Dt that is older than 30 days for any given row.
Sample Query:
SELECT Patient_ID,
Discharge_Dt,
/* Calculating the MIN Discharge_Dt by Patient_ID for the last 30
days based upon the Discharge_Dt for that row */
(SELECT MIN(Discharge_Dt)
FROM admissions_ds AS b
WHERE a.Patient_ID = b.Patient_ID AND
a.Discharge_Dt >= DATEADD('D', -30, GETDATE())) AS MIN_Dt
FROM admissions_ds AS a
Desired Output Table:
Patient_ID | Discharge_Dt | MIN_Dt
10 | 2017-08-15 | 2017-08-15
10 | 2017-08-31 | 2017-08-15
10 | 2017-09-21 | 2017-08-31
15 | 2017-07-01 | 2017-07-01
15 | 2017-07-18 | 2017-07-01
20 | 2017-05-05 | 2017-05-05
25 | 2017-09-24 | 2017-09-24
Here you go,
Just a simple join required.
drop TABLE if EXISTS admissions_ds;
create table admissions_ds (Patient_ID int,Discharge_Dt date);
insert into admissions_ds
values
(10,'2017-08-15'),
(10,'2017-08-31'),
(10,'2017-09-21'),
(15,'2017-07-01'),
(15,'2017-07-18'),
(20,'2017-05-05'),
(25,'2017-09-24');
select t1.Patient_ID,t1.Discharge_Dt,min(t2.Discharge_Dt) as min_dt
from admissions_ds as t1
join admissions_ds as t2 on t1.Patient_ID=t2.Patient_ID and t2.Discharge_Dt > t1.Discharge_Dt - interval '30 days'
group by 1,2
order by 1,2
;
I am trying to track the usage of material with my SQL. There is no way in our database to link when a part is used to the order it originally came from. A part simply ends up in a bin after an order arrives, and then usage of parts basically just creates a record for the number of parts used at a time of transaction. I am attempting to, as best I can, link usage to an order number by summing over the data and sequentially assigning it to order numbers.
My sub queries have gotten me this far. Each order number is received on a date. I then join the usage table records based on the USEDATE needing to be equal to or greater than the RECEIVEDATE of the order. The data produced by this is as such:
| ORDERNUM | PARTNUM | RECEIVEDATE | ORDERQTY | USEQTY | USEDATE |
|----------|----------|-------------------------|-----------|---------|------------------------|
| 4412 | E1125 | 10/26/2016 1:32:25 PM | 1 | 1 | 11/18/2016 1:40:55 PM |
| 4412 | E1125 | 10/26/2016 1:32:25 PM | 1 | 3 | 12/26/2016 2:19:32 PM |
| 4412 | E1125 | 10/26/2016 1:32:25 PM | 1 | 1 | 1/3/2017 8:31:21 AM |
| 4111 | E1125 | 10/28/2016 2:54:13 PM | 1 | 1 | 11/18/2016 1:40:55 PM |
| 4111 | E1125 | 10/28/2016 2:54:13 PM | 1 | 3 | 12/26/2016 2:19:32 PM |
| 4111 | E1125 | 10/28/2016 2:54:13 PM | 1 | 1 | 1/3/2017 8:31:21 AM |
| 0393 | E1125 | 12/22/2016 11:52:04 AM | 3 | 3 | 12/26/2016 2:19:32 PM |
| 0393 | E1125 | 12/22/2016 11:52:04 AM | 3 | 1 | 1/3/2017 8:31:21 AM |
| 7812 | E1125 | 12/27/2016 10:56:01 AM | 1 | 1 | 1/3/2017 8:31:21 AM |
| 1191 | E1125 | 1/5/2017 1:12:01 PM | 2 | 0 | null |
The query for the above section looks as such:
SELECT
B.*,
NVL(B2.QTY, ‘0’) USEQTY
B2.USEDATE USEDATE
FROM <<Sub Query B>>
LEFT JOIN USETABLE B2 ON B.PARTNUM = B2.PARTNUM AND B2.USEDATE >= B.RECEIVEDATE
My ultimate goal here is to join USEQTY records sequentially until they have filled enough ORDERQTY’s. I also need to add an ORDERUSE column that represents what QTY from the USEQTY column was actually applied to that record. Not really sure how to word this any better so here is example of what I need to happen based on the table above:
| ORDERNUM | PARTNUM | RECEIVEDATE | ORDERQTY | USEQTY | USEDATE | ORDERUSE |
|----------|----------|-------------------------|-----------|---------|------------------------|-----------|
| 4412 | E1125 | 10/26/2016 1:32:25 PM | 1 | 1 | 11/18/2016 1:40:55 PM | 1 |
| 4111 | E1125 | 10/28/2016 2:54:13 PM | 1 | 3 | 12/26/2016 2:19:32 PM | 1 |
| 0393 | E1125 | 12/22/2016 11:52:04 AM | 3 | 2 | 12/26/2016 2:19:32 PM | 2 |
| 0393 | E1125 | 12/22/2016 11:52:04 AM | 3 | 1 | 1/3/2017 8:31:21 AM | 1 |
| 7812 | E1125 | 12/27/2016 10:56:01 AM | 1 | 0 | null | 0 |
| 1191 | E1125 | 1/5/2017 1:12:01 PM | 2 | 0 | null | 0 |
If I can get the query to pull the information like above, I will then be able to group the records together and sum the ORDERUSE column which would get me the information I need to know what orders have been used and which have not been fully used. So in the example above, if I were to sum the ORDERUSE column for each of the ORDERNUMs, orders 4412, 4111, 0393 would all show full usage. Orders 7812, 1191 would show not being fully used.
If i am reading this correctly you want to determine how many parts have been used. In your example it looks like you have 5 usages and with 5 orders coming to a total of 8 parts with the following orders having been used.
4412 - one part - one used
4111 - one part - one used
7812 - one part - one used
0393 - three
parts - two used
After a bit of hacking away I came up with the following SQL. Not sure if this works outside of your sample data since thats the only thing I used to test and I am no expert.
WITH data
AS (SELECT *
FROM (SELECT *
FROM sub_b1
join (SELECT ROWNUM rn
FROM dual
CONNECT BY LEVEL < 15) a
ON a.rn <= sub_b1.orderqty
ORDER BY receivedate)
WHERE ROWNUM <= (SELECT SUM(useqty)
FROM sub_b2))
SELECT sub_b1.ordernum,
partnum,
receivedate,
orderqty,
usage
FROM sub_b1
join (SELECT ordernum,
Max(rn) AS usage
FROM data
GROUP BY ordernum) b
ON sub_b1.ordernum = b.ordernum
You are looking for "FIFO" inventory accounting.
The proper data model should have two tables, one for "received" parts and the other for "delivered" or "used". Each table should show an order number, a part number and quantity (received or used) for that order, and a timestamp or date-time. I model both in CTE's in my query below, but in your business they should be two separate table. Also, a trigger or similar should enforce the constraint that a part cannot be used until it is available in stock (that is: for each part id, the total quantity used since inception, at any point in time, should not exceed the total quantity received since inception, also at the same point in time). I assume that the two input tables do, in fact, satisfy this condition, and I don't check it in the solution.
The output shows a timeline of quantity used, by timestamp, matching "received" and "delivered" (used) quantities for each part_id. In the sample data I illustrate a single part_id, but the query will work with multiple part_id's, and orders (both for received and for delivered or used) that include multiple parts (part id's) with different quantities.
with
received ( order_id, part_id, ts, qty ) as (
select '0030', '11A4', timestamp '2015-03-18 15:00:33', 20 from dual union all
select '0032', '11A4', timestamp '2015-03-22 15:00:33', 13 from dual union all
select '0034', '11A4', timestamp '2015-03-24 10:00:33', 18 from dual union all
select '0036', '11A4', timestamp '2015-04-01 15:00:33', 25 from dual
),
delivered ( order_id, part_id, ts, qty ) as (
select '1200', '11A4', timestamp '2015-03-18 16:30:00', 14 from dual union all
select '1210', '11A4', timestamp '2015-03-23 10:30:00', 8 from dual union all
select '1220', '11A4', timestamp '2015-03-23 11:30:00', 7 from dual union all
select '1230', '11A4', timestamp '2015-03-23 11:30:00', 4 from dual union all
select '1240', '11A4', timestamp '2015-03-26 15:00:33', 1 from dual union all
select '1250', '11A4', timestamp '2015-03-26 16:45:11', 3 from dual union all
select '1260', '11A4', timestamp '2015-03-27 10:00:33', 2 from dual union all
select '1270', '11A4', timestamp '2015-04-03 15:00:33', 16 from dual
),
(end of test data; the SQL query begins below - just add the word WITH at the top)
-- with
combined ( part_id, rec_ord, rec_ts, rec_sum, del_ord, del_ts, del_sum) as (
select part_id, order_id, ts,
sum(qty) over (partition by part_id order by ts, order_id),
null, cast(null as date), cast(null as number)
from received
union all
select part_id, null, cast(null as date), cast(null as number),
order_id, ts,
sum(qty) over (partition by part_id order by ts, order_id)
from delivered
),
prep ( part_id, rec_ord, del_ord, del_ts, qty_sum ) as (
select part_id, rec_ord, del_ord, del_ts, coalesce(rec_sum, del_sum)
from combined
)
select part_id,
last_value(rec_ord ignore nulls) over (partition by part_id
order by qty_sum desc) as rec_ord,
last_value(del_ord ignore nulls) over (partition by part_id
order by qty_sum desc) as del_ord,
last_value(del_ts ignore nulls) over (partition by part_id
order by qty_sum desc) as used_date,
qty_sum - lag(qty_sum, 1, 0) over (partition by part_id
order by qty_sum, del_ts) as used_qty
from prep
order by qty_sum
;
Output:
PART_ID REC_ORD DEL_ORD USED_DATE USED_QTY
------- ------- ------- ----------------------------------- ----------
11A4 0030 1200 18-MAR-15 04.30.00.000000000 PM 14
11A4 0030 1210 23-MAR-15 10.30.00.000000000 AM 6
11A4 0032 1210 23-MAR-15 10.30.00.000000000 AM 2
11A4 0032 1220 23-MAR-15 11.30.00.000000000 AM 7
11A4 0032 1230 23-MAR-15 11.30.00.000000000 AM 4
11A4 0032 1230 23-MAR-15 11.30.00.000000000 AM 0
11A4 0034 1240 26-MAR-15 03.00.33.000000000 PM 1
11A4 0034 1250 26-MAR-15 04.45.11.000000000 PM 3
11A4 0034 1260 27-MAR-15 10.00.33.000000000 AM 2
11A4 0034 1270 03-APR-15 03.00.33.000000000 PM 12
11A4 0036 1270 03-APR-15 03.00.33.000000000 PM 4
11A4 0036 21
12 rows selected.
Notes: (1) One needs to be careful if at one moment the cumulative used quantity exactly matches cumulative received quantity. All rows must be include in all the intermediate results, otherwise there will be bad data in the output; but this may result (as you can see in the output above) in a few rows with a "used quantity" of 0. Depending on how this output is consumed (for further processing, for reporting, etc.) these rows may be left as they are, or they may be discarded in a further outer-query with the condition where used_qty > 0.
(2) The last row shows a quantity of 21 with no used_date and no del_ord. This is, in fact, the "current" quantity in stock for that part_id as of the last date in both tables - available for future use. Again, if this is not needed, it can be removed in an outer query. There may be one or more rows like this at the end of the table.
In simplest terms, I want to pull aggregate data from a table over a 4 week period but group by each week. It is safe to assume we can "force" a specific date or time (although it would be nice to allow any date entered and have the query run based on the date entered).
For example, the resulting data from a query would look like this:
start_date | end_date | count_of_sales
---------------------------------------------------------------
2014-03-03 04:00:00 | 2014-03-10 03:59:59 | 375
2014-03-10 04:00:00 | 2014-03-17 03:59:59 | 375
2014-03-17 04:00:00 | 2014-03-24 03:59:59 | 375
2014-03-24 04:00:00 | 2014-03-31 04:00:00 | 200
This would stem from unaggregated data that simply had a date (and of course other data but that is irrelevant):
saleDate | repID | productID
---------------------------------------------------------------
2014-03-04 12:36:33 | 1235 | 443
2014-03-09 07:08:12 | 1235 | 493
2014-03-09 10:12:44 | 3948 | 472
2014-03-21 23:33:01 | 2957 | 479
In my head the query would look SOMETHING (although accurate) like this:
SELECT start_date, end_date, COUNT(*) FROM table WHERE date < '2014-03-31 04:00:00' GROUP BY date
I understand the query above however does not understand how far back to look (ideally the customer enters the final date and perhaps how many weeks prior of data they want to pull) which is why I left out a date BETWEEN clause (they may not know the exact 'start' date.
Sorry if this is confusing but hopefully the sample SQL (albeit wrong) and desired results will give a clearer picture
If I got your question correctly, then following code should help you,
For clarification: Code which I have given is of SQL Server.
With CTE as
(
Select 1 as pID,'2014-03-03 04:00:00' as startDate,'2014-03-10 03:59:59' as endDate
Union All
Select 2,'2014-03-10 04:00:00','2014-03-17 03:59:59'
Union All
Select 3,'2014-03-17 04:00:00','2014-03-24 03:59:59'
Union All
Select 4,'2014-03-24 04:00:00','2014-03-31 04:00:00'
)
select a.pID,a.startDate,a.endDate,count(*) from CTE as a
inner join MyTable on myDateCol between a.startDate and a.endDate
group by a.pID,a.startDate,a.endDate
for demo SQL Fiddle