Firstly, I'm rather new to SQL and I've run into a roadblock. I'm using the Mimer SQL system.
I have three tables: "Transactions", roughly equivalent with a receipt total, which I want to update with data from a selection and the tables "item", containing prices and "sale", containing number of items and item IDs for a given transaction, which I have to join in order to get the data to update Transaction with.
SELECT sale.T_ID, SUM(sale.quantity * item.price) as total
FROM sale
INNER JOIN item
ON sale.I_ID = item.I_ID
GROUP BY T_ID
Gives me the desired data selection with the transaction IDs and the sum total for that transaction:
T_ID Amount
1 100
2 150
etc...
I want to update the Transaction table, which contains columns "T_ID" and "Total". I want to match the T_IDs and update the Total with the data from the corresponding Amount in the selection. The query:
UPDATE transaction SET total = (
SELECT total FROM (
SELECT sale.T_ID, SUM(sale.quantity * item.price) as total
FROM sale
INNER JOIN item
ON sale.I_ID = item.I_ID
GROUP BY T_ID)
WHERE transaction.T_ID=T_ID);
I can sense that the above statement is faulty, but unable to discern the problem. How should I construct the query?
Only select the SUM(sale.quantity * item.price) in your subquery and remove the select total one.
update Transaction
set total = (
select SUM(sale.quantity * Item.price)
from Sale
inner join Item on Sale.I_ID = Item.I_ID
where Sale.T_ID = Transaction.T_ID
)
That is what I would try out in SQL Server.
I would have prefered to have some sample data so that I can test it against my local SQL Server database in order to verify whether this statement does what is expected, though you're not using SQL Server, the idea is still the same.
EDIT #1
Though I do not fully understand why it does not overwrite values in the transaction.total column when a transaction is composed of several different items, your suggested query works.
The behaviour of the SUM function is to sum all targeted records resulting in only one scalar value for each Sale and Item rows. There can be only one sum, can it not?
That said, it multipies each resulting rows from the constraint, that is, for a particular transaction.
It selects both Sale and Item rows for this very transaction;
It then iterates through each of the resulting rows and multiply Sale.Quantity and Item.Price together, which is worth a value for each row;
Once a row is multiplied, its total is then added to a total which is stored somewhere in memory;
Once it has processed all the rows for that transaction, it comes out with a scalar value, which is the sum of all the rows in Sale and Item for that given transaction;
This SUM ends up to be this transaction's total.
In other words, the subquery "knows" for which transaction to sum which is filtered in the subquery itself. The Transaction table is accessible in the subquery as part of the main SQL statement. So, putting it in the where clause filters the rows from Sale and Item that will be later multiplied and additioned for the total.
Does this help you better understand this update statement?
Please feel free to ask your questions. =)
Related
I am working on a database to track staff productivity. Two of the ways we do that is by monitoring the number of orders they fulfil and by tracking their error rate.
Each order they finish is recorded in a table. In one day they can complete many orders.
It is also possible for a single order to have multiple errors.
I am trying to create a query that provides a summary of their results. This query should have one column with "TotalOrders" and another with "TotalErrors".
I connect the two tables with a LEFT/RIGHT join since not all orders will have errors.
The problem comes when I want to total the number of orders. If someone made multiple mistakes on an order, that order gets counted multiple times; once for each error.
I want to modify my query so that when counting the number of orders it only counts records with distinct OrderID's; yet, in the same query, also count the total errors without losing any.
Is this possible?
Here is my SQL
SELECT Count(tblTickets.TicketID) AS TotalOrders,
Count(tblErrors.ErrorID) AS TotalErrors
FROM tblTickets
LEFT JOIN tblErrors ON tblTickets.TicketID = tblErrors.TicketID;
I have played around with SELECT DISTINCT and UNION but am struggling with the correct syntax in Access. Also, a lot of the examples I have seen are trying to total a single field rather than two fields in different ways.
To be clear when totalling the OrderCount field I want to only count records with DISTINCT TicketID's. When totalling the ErrorCount field I want to count ALL errors.
Ticket = Order.
Query Result: Order Count Too High
Ticket/Order Table: Total of 14 records
Error Table: You can see two errors for the same order on 8th
do a query that counts orders by staff from Orders table and a query that counts errors by staff from Errors table then join those two queries to Staff table (queries can be nested for one long SQL statement)
correlated subqueries
SELECT Staff.*,
(SELECT Count(*) FROM Orders WHERE StaffID = Staff.ID) AS CntOrders,
(SELECT Count(*) FROM Errors WHERE StaffID = Staff.ID) AS CntErrors
FROM Staff;
use DCount() domain aggregate function
Option 1 is probably the most efficient and option 3 the least.
Good Evening Stackoverflow team/members
Oracle version: 11g Release 11.1.0.6.0 - 64bit Production
I have two Tables: ORDERS and ITEMS.
ORDERS looks like this
ORDERS
ITEMS looks like this
enter image description here
Table ORDERS has 1 or more Order_Number each assigned to at least one depot or more. the column Total_Value SHOULD store exactly the sum of the item values associated to an order number. the table ITEMS in fact stores via parcel_code items values for a specific order_number/s.
my db has a bug for orders that have more than one depot assigned to an order number (e.g. order number 1 and 4) do not store the actual total value correctly.
in my case I cannot figure out the UPDATE statement that would select order numbers that would take the sum from the table ITEMS and link it via parcel_code and update the column total_value in the table ORDERS.
the result of my update should give this back:
for table orders i should get back for
order number 1:
for both rows total value 1120
order number 4
for both rows total value: 350
order number 2 and 3 as they are single depot order remain the same:
50 and 20
pseudo-code :
update ORDERS
set total_value = (select sum(I.item_value) from ITEMS I, ORDERS O where O.parcel_code = I.parcel_code)
i would update also those orders which have on e depot assigned as they will exactly the same.
i was looking at MERGE statements or INNER select queries. the problem i am facing is that my update must be dynamic. this means not driven by values but by columns joins as i may have to create a process that update this every day.
can someone help me?
You need to join the items and orders tables together, then select the sum of all item_values where your order_number is equal to the row which you are updating (in table o1).
update
Orders o1
set o1.total_value = (
select sum(i.item_value) from Items i
join Orders o2 on o2.parcel_code = i.parcel_code
where o2.Order_number = o1.Order_number
)
I have an app (its ruby on rails but it shouldn't matter) where I am bulk loading items and quantities per branch.
The database is sqlite.
Say I have a two tables: items and quantities.
items columns:
id
quantity
quantities columns:
id
item_id
branch_id
value
I need to be able to loop through all records in the items table set the item.quantity to the sum of all quantity.value where item_id matches item.id
I would like to know if there is a way to do this all within a sql query (the select and update) so that I don't have to pull the data out of the database, do the calculation and then write the updated quantity back to each item, instead I would like to have it all occur in the database using sql statements and functions.
Is this possible in a sql query function db side?
example:
item[1] = {id=>1,quantity=>0}
quantity[1] = {id=>1,item_id=>1,value=>100,branch_id=>1}
quantity[2] = {id=>2,item_id=>1,value=>200,branch_id=>2}
quantity[3] = {id=>3,item_id=>1,value=>300,branch_id=>3}
item[1].quantity = quantity[1].value + quantity[2].value + quantity[3].value
You can do this with an update query. In this case, you can use a correlated subquery to calculate the sum of the quantities for a given item:
update item
set quantity = (select sum(value) from quantities where item.id = quantities.item_id);
EDIT:
If you want to speed it up putting an index on quantities(item_id, value).
You could also summarize quantities in a temporary table and use this instead. The index, however, however, should be sufficient for performance.
You are duplicating your data! Which means you must always keeping everything in sync.
I would prefer to create a view and get total quantities from there:
CREATE TABLE items(id, ...);
CREATE TABLE quantities(id, item_id, branch_id, value, ...);
CREATE VIEW items_sum AS SELECT items.*, SUM(quantities.value) AS quantity FROM items LEFT JOIN quantities ON items.id=quantities.item_id GROUP BY items.id;
As items_sum is a query, you don't have to update it. SELECT * FROM items_sum;will return desired results for total quantities.
Given scenario:
table fd
(cust_id, fd_id) primary-key and amount
table loan
(cust_id, l_id) primary-key and amount
I want to list all customers who have a fixed deposit with an amount less than the sum of all their loans.
Query:
SELECT cust_id
FROM fd
WHERE amount
<
(SELECT sum(amount)
FROM loan
WHERE fd.cust_id = loan.cust_id);
OR should we use
SELECT cust_id
FROM fd
WHERE amount
<
(SELECT sum(amount)
FROM loan
WHERE fd.cust_id = loan.cust_id group by cust_id);
A customer can have multiple loans but one FD is considered at a time.
GROUP BY can be omitted in this case, because there is only (one) aggregate function(s) in the SELECT list and all rows are guaranteed to belong to the same group of cust_id ( by the WHERE clause).
The aggregation will be over all rows with matching cust_id in both cases. So both queries are correct.
This would be a cleaner another way to implement the same thing:
SELECT fd.cust_id
FROM fd
JOIN loan USING (cust_id)
GROUP BY fd.cust_id, fd.amount
HAVING fd.amount < sum(loan.amount)
There is one difference: rows with identical (cust_id, amount) in fd only appear once in the result of my query, while they would appear multiple times in the original.
Either way, if there is no matching row with a non-null amount in table loan, you get no rows at all. I assume you are aware of that.
There are no need for GROUP BY since you filtered data by cust_id. In any case inner query will return the same result.
No, it isn't, because you calculate sum(amount) for customer with id = fd.cust_id, so for a single customer.
However, if somehow your subquery calculate sum for more than one customer, the group by would cause the subquery to generate more than one row and this will cause the condition(<) to fail, and thus, the query to fail.
A query with an aggregate like sum but without a group by will output one group. The aggregates will be computed over all matching rows.
A subquery in a condition clause is only allowed to return one row. If the subquery returned multiple rows, what would the following expression mean?
where 1 > (... subquery ...)
So the group by must be omitted; you would even get an error for your second query.
N.B. When you specify all, any, or some a subquery can return multiple rows:
where 1 > ALL (... subquery ...)
But it's easy to see why that doesn't make sense in your case; you'd compare one customer's data to that of another.
Basically, I have a table of data with plenty of records (10,000+)
They all have 4 fields in common which must have data entered. The unique data is TIME.
I have already done a group sort query which has identified the group's of data based on these 4 fields, and then calculated an average time for each group.
I'm now needing to re-insert the average time against the real time in a table so each individual record's time can be evaluated against the average of its type.
For instance, one group from the query would have the result
Process1, Week2, Operator3, Shift4, AvgOfTIME = 120.70
It would then need to re-insert that average time into all records that match those criteria, but do it for every group result and record.
Is this even possible?
you need to update table use subquery
update t1 set t1.timefield = s2.AvgOfTIME
from yourtable t1
inner join
(
-- you query for calculating avg time
)
as t2
on t1.Process1 = t2.Process1 and t1.Week2 = t2.Week2 and t1.Operator3 = t2.Operator3 and t1.Shift4 = t2.Shift4