i have table like this:
| ID | id_number | a | b |
| 1 | 1 | 0 | 215 |
| 2 | 2 | 28 | 8952 |
| 3 | 3 | 10 | 2000 |
| 4 | 1 | 0 | 215 |
| 5 | 1 | 0 |10000 |
| 6 | 3 | 10 | 5000 |
| 7 | 2 | 3 |90933 |
I want to sum a*b where id_number is same, what the query to get all value for every id_number? for example the result is like this :
| ID | id_number | result |
| 1 | 1 | 0 |
| 2 | 2 | 523455 |
| 3 | 3 | 70000 |
This is a simple aggregation query:
select id_number, sum(a*b)
from t
group by id_number
I'm not sure what the first column is for.
Related
I have the following sql to calculate a % total:
SELECT tblTourns_atp.ID_Ti,
Sum([FS_1]/(SELECT Sum(FSOF_1)
FROM stat_atp
WHERE stat_atp.ID_T = tblTourns_atp.ID_T)) AS S1_IP
FROM stat_atp
INNER JOIN tblTourns_atp ON stat_atp.ID_T = tblTourns_atp.ID_T
GROUP BY tblTourns_atp.ID_Ti
I'm getting the 'aggregate error' because it wants the ID_T fields either grouped or in an aggregate function. I've read loads of examples but none of them seem to apply when the offending field is the subject of 'WHERE'.
Tables and output as follows:
+----------+------+--------+--+---------------+-------+--+--------+--------+
| stat_atp | | | | tblTourns_atp | | | Output | |
+----------+------+--------+--+---------------+-------+--+--------+--------+
| ID_T | FS_1 | FSOF_1 | | ID_T | ID_Ti | | ID_Ti | S1_IP |
| 1 | 20 | 40 | | 1 | 1 | | 1 | 31.03% |
| 2 | 30 | 100 | | 2 | 1 | | 2 | 28.57% |
| 3 | 40 | 150 | | 3 | 1 | | 3 | 33.33% |
| 4 | 30 | 100 | | 4 | 2 | | | |
| 5 | 30 | 100 | | 5 | 2 | | | |
| 6 | 40 | 150 | | 6 | 2 | | | |
| 7 | 20 | 40 | | 7 | 3 | | | |
| 8 | 30 | 100 | | 8 | 3 | | | |
| 9 | 40 | 150 | | 9 | 3 | | | |
| 10 | 20 | 40 | | 10 | 3 | | | |
+----------+------+--------+--+---------------+-------+--+--------+--------+
Since you already have an inner join between the two tables, a separate subquery isn't required:
select t.id_ti, sum(s.fs_1)/sum(s.fsof_1) as pct
from tbltourns_atp t inner join stat_atp s on t.id_t = s.id_t
group by t.id_ti
So I have an accounts table in witch row may or may not have a parent account (0 means it doesn't have a parent):
+----+-----------+
| id | parent_id |
+----+-----------+
| 1 | 2 |
| 2 | 0 |
| 3 | 1 |
| 4 | 3 |
| 5 | 4 |
+----+-----------+
I was trying to add the top 3 parents for each row, so I would get something like this:
+----+-----------+----------+----------+----------+
| id | parent_id | parent_1 | parent_2 | parent_3 |
+----+-----------+----------+----------+----------+
| 1 | 2 | 2 | null | null |
| 2 | 0 | null | null | null |
| 3 | 1 | 2 | 1 | null |
| 4 | 3 | 2 | 1 | 3 |
| 5 | 4 | 2 | 1 | 3 |
+----+-----------+----------+----------+----------+
I figured I can do it with recursive queries, but I haven't managed to build a working query.
Any help would be appreciated.
Consider the following table T
------------------------------
| CountryID | Obs | Event |
------------------------------
| 1 | 1 | 10 |
| 1 | 2 | 20 |
| 1 | 3 | 30 |
| 2 | 1 | 20 |
| 2 | 2 | 30 |
| 2 | 3 | 10 |
| 3 | 1 | 30 |
| 3 | 2 | 10 |
| 3 | 3 | 20 |
------------------------------
I would like to delete all rows such that Event = 20 however I would then like to update the Obs so that they were still in incremental order from 1 with a difference of 1.
For example if I run SELECT * FROM T WHERE Event != 20, I would get
------------------------------
| CountryID | Obs | Event |
------------------------------
| 1 | 1 | 10 |
| 1 | 3 | 30 |
| 2 | 2 | 30 |
| 2 | 3 | 10 |
| 3 | 1 | 30 |
| 3 | 2 | 10 |
------------------------------
but instead I want
------------------------------
| CountryID | Obs | Event |
------------------------------
| 1 | 1 | 10 |
| 1 | 2 | 30 |
| 2 | 1 | 30 |
| 2 | 2 | 10 |
| 3 | 1 | 30 |
| 3 | 2 | 10 |
------------------------------
what query do I need to achieve this?
First, in SQLite, there is a pseudo-column called rowid that uniquely identifies each row. You can do what you want by using a correlated subquery:
update t
set obs = (select count(*)
from t t2
where t2.countryid = t.countryid and t2.rowid <= t.rowid
);
That said, this is quite inefficient and shouldn't be run on anything other than baby tables. If this is an operation that you regularly want to do, you might consider a more powerful database than SQLite.
I have this table
+----+--------+------------+-----------+
| Id | day_id | subject_id | period_Id |
+----+--------+------------+-----------+
| 1 | 1 | 1 | 1 |
| 2 | 1 | 2 | 2 |
| 8 | 2 | 6 | 1 |
| 9 | 2 | 7 | 2 |
| 15 | 3 | 3 | 1 |
| 16 | 3 | 4 | 2 |
| 22 | 4 | 5 | 1 |
| 23 | 4 | 5 | 2 |
| 24 | 4 | 6 | 3 |
| 29 | 5 | 8 | 1 |
| 30 | 5 | 1 | 2 |
to something like this
| Id | day_id | subject_id | period_Id |
| 1 | 1 | 1 | 1 |
| 8 | 2 | 6 | 1 |
| 15 | 3 | 3 | 1 |
| 22 | 4 | 5 | 1 |
| 29 | 5 | 8 | 1 |
| 2 | 1 | 2 | 2 |
| 2 | 1 | 2 | 2 |
| 16 | 3 | 4 | 2 |
| 23 | 4 | 5 | 2 |
| 30 | 5 | 1 | 2 |
+----+--------+------------+-----------+
SO, I want to choose one period with a different subject each day and doing this for number of weeks. so first subject dose not come until all subject have been chosen.
You can ORDER BY period_id first and then by day_id:
SELECT *
FROM your_table
ORDER BY period_Id, day_Id
LiveDemo
I have a table structure for SalesItems, and Sales.
SalesItems is setup something like this
| SaleItemID | SaleID | ProductID | ProductType |
| 1 | 1 | 1 | 1 |
| 2 | 1 | 2 | 2 |
| 3 | 1 | 15 | 1 |
| 4 | 2 | 5 | 2 |
| 5 | 3 | 1 | 1 |
| 6 | 3 | 8 | 5 |
And Sales is setup something like this
| Sale | Cash |
| 1 | 1.00 |
| 2 | 10.00 |
| 3 | 28.50 |
I am trying to export a basic 'Daily History' that uses joins to spit out the information like this.
| Date | StoreID | Type1Sales | Type2Sales | ... | Cash Taken |
| 5/2 | 50 | 50 | 40 | ... | 39.50 |
| 5/3 | 50 | 10 | 32.50 | ... | 48.50 |
The issue I'm having is if I do an inner join From Sales to Sales Items, I'll end up with this.
| SaleItemID | SaleID | ProductID | ProductType | Sale | Cash |
| 1 | 1 | 1 | 1 | 1 | 1.00 |
| 2 | 1 | 2 | 2 | 1 | 1.00 |
| 3 | 1 | 15 | 1 | 1 | 1.00 |
| 4 | 2 | 5 | 2 | 2 | 10.00 |
| 5 | 3 | 1 | 1 | 3 | 28.50 |
| 6 | 3 | 8 | 5 | 3 | 28.50 |
So if I do a SUM(Cash), then I'll end up returning $70.00, instead of the correct $39.50. I'm not the best with joins, so I've been researching outer joins and such, but none of those seem to work as it's still matching up. Is there a way to only match on the FIRST instance, and return NULL for the rest? For example, something like this
| SaleItemID | SaleID | ProductID | ProductType | Sale | Cash |
| 1 | 1 | 1 | 1 | 1 | 1.00 |
| 2 | 1 | 2 | 2 | 1 | NULL |
| 3 | 1 | 15 | 1 | 1 | NULL |
| 4 | 2 | 5 | 2 | 2 | 10.00 |
| 5 | 3 | 1 | 1 | 3 | 28.50 |
| 6 | 3 | 8 | 5 | 3 | NULL |
Or do you have any other suggestions for returning back the correct amount of Cash for each particular day?
Use DISTINCT(SaleID) in your SELECT to return a single row for each Sale ID.