I have a table "Product" as :
| ProductId | ProductCatId | Price | Date | Deadline |
--------------------------------------------------------------------
| 1 | 1 | 10.00 | 2016-01-01 | 2016-01-27 |
| 2 | 2 | 10.00 | 2016-02-01 | 2016-02-27 |
| 3 | 3 | 10.00 | 2016-03-01 | 2016-03-27 |
| 4 | 1 | 10.00 | 2016-04-01 | 2016-04-27 |
| 5 | 3 | 10.00 | 2016-05-01 | 2016-05-27 |
| 6 | 3 | 10.00 | 2016-06-01 | 2016-06-27 |
| 7 | 1 | 20.00 | 2016-01-01 | 2016-01-27 |
| 8 | 2 | 30.00 | 2016-02-01 | 2016-02-27 |
| 9 | 1 | 40.00 | 2016-03-01 | 2016-03-27 |
| 10 | 4 | 15.00 | 2016-04-01 | 2016-04-27 |
| 11 | 1 | 25.00 | 2016-05-01 | 2016-05-27 |
| 12 | 5 | 55.00 | 2016-06-01 | 2016-06-27 |
| 13 | 5 | 55.00 | 2016-06-01 | 2016-01-27 |
| 14 | 5 | 55.00 | 2016-06-01 | 2016-02-27 |
| 15 | 5 | 55.00 | 2016-06-01 | 2016-03-27 |
I want to create SP count rows of Product each month with condition Year = CurrentYear , like :
| Month| SumProducts | SumExpiredProducts |
-------------------------------------------
| 1 | 3 | 3 |
| 2 | 3 | 3 |
| 3 | 3 | 3 |
| 4 | 2 | 2 |
| 5 | 2 | 2 |
| 6 | 2 | 2 |
What should i do ?
You can use a query like the following:
SELECT MONTH([Date]),
COUNT(*) AS SumProducts ,
COUNT(CASE WHEN [Date] > Deadline THEN 1 END) AS SumExpiredProducts
FROM mytable
WHERE YEAR([Date]) = YEAR(GETDATE())
GROUP BY MONTH([Date])
Related
I am solving the following Hard Leetcode SQL Question.
Link to Question: https://leetcode.com/problems/trips-and-users/
(You can directly look at the solution and understand the problem)
Question:
Trips table:
+----+-----------+-----------+---------+---------------------+------------+
| id | client_id | driver_id | city_id | status | request_at |
+----+-----------+-----------+---------+---------------------+------------+
| 1 | 1 | 10 | 1 | completed | 2013-10-01 |
| 2 | 2 | 11 | 1 | cancelled_by_driver | 2013-10-01 |
| 3 | 3 | 12 | 6 | completed | 2013-10-01 |
| 4 | 4 | 13 | 6 | cancelled_by_client | 2013-10-01 |
| 5 | 1 | 10 | 1 | completed | 2013-10-02 |
| 6 | 2 | 11 | 6 | completed | 2013-10-02 |
| 7 | 3 | 12 | 6 | completed | 2013-10-02 |
| 8 | 2 | 12 | 12 | completed | 2013-10-03 |
| 9 | 3 | 10 | 12 | completed | 2013-10-03 |
| 10 | 4 | 13 | 12 | cancelled_by_driver | 2013-10-03 |
+----+-----------+-----------+---------+---------------------+------------+
Users table:
+----------+--------+--------+
| users_id | banned | role |
+----------+--------+--------+
| 1 | No | client |
| 2 | Yes | client |
| 3 | No | client |
| 4 | No | client |
| 10 | No | driver |
| 11 | No | driver |
| 12 | No | driver |
| 13 | No | driver |
+----------+--------+--------+
Output:
+------------+-------------------+
| Day | Cancellation Rate |
+------------+-------------------+
| 2013-10-01 | 0.33 |
| 2013-10-02 | 0.00 |
| 2013-10-03 | 0.50 |
+------------+-------------------+
Here's my code:
SELECT request_at,
count(*) c,
sum(case when status='cancelled_by_driver' or status='cancelled_by_client' then 1 else 0 end) s,
round(sum(case when status='cancelled_by_client' or status='cancelled_by_client' then 1 else 0 end)/count(*),2) as Cancellation_rate
FROM trips
WHERE
client_id not in (select users_id from users where banned = 'Yes')
AND
driver_id not in (select users_id from users where banned = 'Yes')
GROUP BY request_at;
And the output is:
request_at | c | s | cancellation_rate
------------+---+---+-------------------
2013-10-01 | 3 | 1 | 0.00
2013-10-03 | 2 | 1 | 0.00
2013-10-02 | 2 | 0 | 0.00
How is the cancellation_rate is 0.00 when it is clear by looking at previous columns(s/c) that it should be 0.33,0.50, 0.00.
The good news is you're only off by a typo.
In your example you are using cancelled_by_client or cancelled_by_client
round(sum(case when status='cancelled_by_client' or status='cancelled_by_client' then 1 else 0 end)/count(*),2) as Cancellation_rate
rather than:
.. when status='cancelled_by_driver' or status='cancelled_by_client' then ..
which would return:
request_at
c
s
cancellation_rate
2013-10-01
3
1
0.33
2013-10-02
2
0
0.00
2013-10-03
2
1
0.50
I have a table that looks like this:
| id | date_start | gap_7_days |
| -- | ------------------- | --------------- |
| 1 | 2021-06-10 00:00:00 | 0 |
| 1 | 2021-06-13 00:00:00 | 0 |
| 1 | 2021-06-19 00:00:00 | 0 |
| 1 | 2021-06-27 00:00:00 | 0 |
| 2 | 2021-07-04 00:00:00 | 1 |
| 2 | 2021-07-11 00:00:00 | 1 |
| 2 | 2021-07-18 00:00:00 | 1 |
| 2 | 2021-07-25 00:00:00 | 1 |
| 2 | 2021-08-01 00:00:00 | 1 |
| 2 | 2021-08-08 00:00:00 | 1 |
| 2 | 2021-08-09 00:00:00 | 0 |
| 2 | 2021-08-16 00:00:00 | 1 |
| 2 | 2021-08-23 00:00:00 | 1 |
| 2 | 2021-08-30 00:00:00 | 1 |
| 2 | 2021-08-31 00:00:00 | 0 |
| 2 | 2021-09-01 00:00:00 | 0 |
| 2 | 2021-08-08 00:00:00 | 1 |
| 2 | 2021-08-15 00:00:00 | 1 |
| 2 | 2021-08-22 00:00:00 | 1 |
| 2 | 2021-08-23 00:00:00 | 1 |
For each ID, I check whether consecutive date_start values are 7 days apart, and put a 1 or 0 in gap_7_days accordingly.
I want to do the following (using Redshift SQL only):
Get the length of each sequence of consecutive 1s in gap_7_days for each ID
Expected output:
| id | date_start | gap_7_days | sequence_length |
| -- | ------------------- | --------------- | --------------- |
| 1 | 2021-06-10 00:00:00 | 0 | |
| 1 | 2021-06-13 00:00:00 | 0 | |
| 1 | 2021-06-19 00:00:00 | 0 | |
| 1 | 2021-06-27 00:00:00 | 0 | |
| 2 | 2021-07-04 00:00:00 | 1 | 6 |
| 2 | 2021-07-11 00:00:00 | 1 | 6 |
| 2 | 2021-07-18 00:00:00 | 1 | 6 |
| 2 | 2021-07-25 00:00:00 | 1 | 6 |
| 2 | 2021-08-01 00:00:00 | 1 | 6 |
| 2 | 2021-08-08 00:00:00 | 1 | 6 |
| 2 | 2021-08-09 00:00:00 | 0 | |
| 2 | 2021-08-16 00:00:00 | 1 | 3 |
| 2 | 2021-08-23 00:00:00 | 1 | 3 |
| 2 | 2021-08-30 00:00:00 | 1 | 3 |
| 2 | 2021-08-31 00:00:00 | 0 | |
| 2 | 2021-09-01 00:00:00 | 0 | |
| 2 | 2021-08-08 00:00:00 | 1 | 4 |
| 2 | 2021-08-15 00:00:00 | 1 | 4 |
| 2 | 2021-08-22 00:00:00 | 1 | 4 |
| 2 | 2021-08-23 00:00:00 | 1 | 4 |
Get the number of sequences for each ID
Expected output:
| id | num_sequences |
| -- | ------------------- |
| 1 | 0 |
| 2 | 3 |
How can I achieve this?
If you want the number of sequences, just look at the previous value. When the current value is "1" and the previous is NULL or 0, then you have a new sequence.
So:
select id,
sum( (gap_7_days = 1 and coalesce(prev_gap_7_days, 0) = 0)::int ) as num_sequences
from (select t.*,
lag(gap_7_days) over (partition by id order by date_start) as prev_gap_7_days
from t
) t
group by id;
If you actually want the lengths of the sequences, as in the intermediate results, then ask a new question. That information is not needed for this question.
In sql I have a history table for each item we have and they can have a record of in or out with a quantity for each action. I'm trying to get a running count of how many of an item we have based on whether it's an activity of out or in. Here is my final sql:
SELECT itemid,
activitydate,
activitycode,
SUM(quantity) AS quantity,
SUM(CASE WHEN activitycode = 'IN'
THEN quantity
WHEN activitycode = 'OUT'
THEN -quantity
ELSE 0 END) OVER (PARTITION BY itemid ORDER BY activitydate rows unbounded preceding) AS runningcount
FROM itemhistory
GROUP BY itemid,
activitydate,
activitycode
This results in:
+--------+-------------------------+--------------+----------+--------------+
| itemid | activitydate | activitycode | quantity | runningcount |
+--------+-------------------------+--------------+----------+--------------+
| 1 | 2017-06-08 13:58:00.000 | IN | 1 | 1 |
| 1 | 2017-06-08 16:02:00.000 | IN | 6 | 2 |
| 1 | 2017-06-15 11:43:00.000 | OUT | 3 | 1 |
| 1 | 2017-06-19 12:36:00.000 | IN | 1 | 2 |
| 2 | 2017-06-08 13:50:00.000 | IN | 5 | 1 |
| 2 | 2017-06-12 12:41:00.000 | IN | 4 | 2 |
| 2 | 2017-06-15 11:38:00.000 | OUT | 2 | 1 |
| 2 | 2017-06-20 12:54:00.000 | IN | 15 | 2 |
| 2 | 2017-06-08 13:52:00.000 | IN | 5 | 3 |
| 2 | 2017-06-12 13:09:00.000 | IN | 1 | 4 |
| 2 | 2017-06-15 11:47:00.000 | OUT | 1 | 3 |
| 2 | 2017-06-20 13:14:00.000 | IN | 1 | 4 |
+--------+-------------------------+--------------+----------+--------------+
I want the end result to look like this:
+--------+-------------------------+--------------+----------+--------------+
| itemid | activitydate | activitycode | quantity | runningcount |
+--------+-------------------------+--------------+----------+--------------+
| 1 | 2017-06-08 13:58:00.000 | IN | 1 | 1 |
| 1 | 2017-06-08 16:02:00.000 | IN | 6 | 7 |
| 1 | 2017-06-15 11:43:00.000 | OUT | 3 | 4 |
| 1 | 2017-06-19 12:36:00.000 | IN | 1 | 5 |
| 2 | 2017-06-08 13:50:00.000 | IN | 5 | 5 |
| 2 | 2017-06-12 12:41:00.000 | IN | 4 | 9 |
| 2 | 2017-06-15 11:38:00.000 | OUT | 2 | 7 |
| 2 | 2017-06-20 12:54:00.000 | IN | 15 | 22 |
| 2 | 2017-06-08 13:52:00.000 | IN | 5 | 27 |
| 2 | 2017-06-12 13:09:00.000 | IN | 1 | 28 |
| 2 | 2017-06-15 11:47:00.000 | OUT | 1 | 27 |
| 2 | 2017-06-20 13:14:00.000 | IN | 1 | 28 |
+--------+-------------------------+--------------+----------+--------------+
You want sum(sum()), because this is an aggregation query:
SELECT itemid, activitydate, activitycode,
SUM(quantity) AS quantity,
SUM(SUM(CASE WHEN activitycode = 'IN' THEN quantity
WHEN activitycode = 'OUT' THEN -quantity
ELSE 0
END)
) OVER (PARTITION BY itemid ORDER BY activitydate ) AS runningcount
FROM itemhistory
GROUP BY itemid, activitydate, activitycode
I would geatly appreciate if someone could help me with the
problem. I have the following fact table:
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| EntryNo | ItemNo | CompanyId | BranchId | LocationId | ValuationDate | ValuatedQty | ValuatedAmount |
+=========+========+===========+==========+============+===============+=============+================+
| 1 | Item1 | 1 | 1 | 1 | 2016-03-01 | 0 | 0 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 2 | Item1 | 1 | 2 | 1 | 2016-03-01 | 4 | 400 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 3 | Item1 | 1 | 1 | 1 | 2016-03-02 | 10 | 1000 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 4 | Item2 | 1 | 1 | 2 | 2016-03-02 | 4 | 200 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 5 | Item2 | 2 | 2 | 2 | 2016-03-02 | 6 | 300 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 6 | Item1 | 2 | 2 | 1 | 2016-03-03 | 0 | 0 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 7 | Item3 | 1 | 2 | 3 | 2016-03-03 | 0 | 0 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
| 8 | Item1 | 2 | 2 | 3 | 2016-03-03 | 9 | 450 |
+---------+--------+-----------+----------+------------+---------------+-------------+----------------+
There are two measures that represent "overstocked" items on a particular day.
Is it possible to create a calculated member that will allow for slicing data
on the all linked dimensions (Items, Companies, etc.) ? I guess the LastNonEmpty agregration
would be useful here except it is not available in the standard edition.
Given the example the results should be as follows:
By Company:
+---------+-------------+----------------+
| Company | ValuatedQty | ValuatedAmount |
+=========+=============+================+
| 1 | 14 | 1200 |
+---------+-------------+----------------+
| 2 | 15 | 750 |
+---------+-------------+----------------+
By Date:
+------------+-------------+----------------+
| Date | ValuatedQty | ValuatedAmount |
+============+=============+================+
| 2016-03-01 | 4 | 400 |
+------------+-------------+----------------+
| 2016-03-02 | 16 | 1300 |
+------------+-------------+----------------+
| 2016-03-03 | 9 | 450 |
+------------+-------------+----------------+
By Item:
+-------+-------------+----------------+
| Item | ValuatedQty | ValuatedAmount |
+=======+=============+================+
| Item1 | 9 | 450 |
+-------+-------------+----------------+
| Item2 | 6 | 300 |
+-------+-------------+----------------+
| Item3 | 0 | 0 |
+-------+-------------+----------------+
Two functions that come to mind for your requirements are:
Tail: https://msdn.microsoft.com/en-us/library/ms146056.aspx
Bottomcount: https://msdn.microsoft.com/en-us/library/ms144864.aspx
So with Tail something like the following is possible:
WITH SET [LastYearPerSubCat] AS
GENERATE(
[Product].[Product Categories].[SubCategory].members AS S,
S.CURRENTMEMBER
*
TAIL(
NONEMPTY(
[Date].[Calendar Year].[Calendar Year].MEMBERS,
S.CURRENTMEMBER
)
)
)
SELECT
[Measures].[Reseller Gross Profit] ON 0
,[LastYearPerSubCat] ON 1
FROM [Adventure Works];
I have 2 tables,
table 1 is transaction table
+----------+-----------+---------+------------+-----+
| IDOutlet | IDProduct | TrxType | TrxDate | Qty |
+----------+-----------+---------+------------+-----+
| 101 | ASD11 | 2 | 11/11/2015 | 15 |
| 101 | ASD11 | 3 | 11/14/2015 | -3 |
| 101 | ASD11 | 3 | 11/17/2015 | -6 |
| 101 | ASD11 | 2 | 11/22/2015 | 7 |
| 101 | ASD11 | 3 | 11/26/2015 | -2 |
| 101 | ASD11 | 2 | 12/3/2015 | 1 |
| 101 | ASD11 | 3 | 12/9/2015 | -3 |
| 101 | ASD11 | 3 | 12/11/2015 | -2 |
| 101 | ASD11 | 2 | 12/12/2015 | 5 |
| 101 | FFD34 | 2 | 11/11/2015 | 9 |
| 101 | FFD34 | 3 | 11/14/2015 | -3 |
| 101 | FFD34 | 2 | 11/16/2015 | 3 |
| 101 | FFD34 | 3 | 11/19/2015 | -4 |
| 101 | FFD34 | 3 | 11/23/2015 | -3 |
| 102 | FFD34 | 2 | 11/26/2015 | 2 |
| 102 | FFD34 | 2 | 11/28/2015 | 4 |
| 102 | FFD34 | 3 | 11/29/2015 | -5 |
| 102 | FFD34 | 3 | 12/1/2015 | -1 |
+----------+-----------+---------+------------+-----+
Table 2 is opnametable
+----------+-----------+------------+-----------+
| IDOutlet | IDProduct | OpnameDate | QtyOpname |
+----------+-----------+------------+-----------+
| 101 | ASD11 | 11/20/2015 | 5 |
| 101 | FFD34 | 11/30/2015 | 5 |
| 102 | FFD34 | 11/30/2015 | 1 |
+----------+-----------+------------+-----------+
And I want the result like this
+----------+-----------+------------+---------+
| IDOutlet | IDProduct | OpnameDate | Sum Qty |
+----------+-----------+------------+---------+
| 101 | ASD11 | 11/20/2015 | 6 |
| 101 | FFD34 | 11/20/2015 | 5 |
| 102 | FFD34 | 11/30/2015 | 1 |
+----------+-----------+------------+---------+
You can use a date comparison in your JOIN criteria:
SELECT T2.IDOutlet,T2.IDProduct,T2.OpnameDate,SUM(T1.Qty) AS Sum_Qty
FROM opnametable T2
LEFT JOIN transaction T1
ON T2.IDOUtlet = T1.IDOutlet
AND T2.IDProduct = T1.IDProduct
AND T1.TrxDate <= T2.OpnameDate
GROUP BY T2.IDOutlet,T2.IDProduct,T2.OpnameDate
I'm assuming the dates are stored in an appropriate date datatype, and that you want to include OpnameDate.
Try this
select o.IDOutlet,o.IDProduct,sum(t.Qty) as [Sum Qty]
from opnametable o left outer join transaction1 t on o.IDOutlet=t.IDOutlet
and o.IDProduct=t.IDProduct and t.trxdate<o.OpnameDate
group by o.IDOutlet,o.IDProduct