I'm looking to filter out rows in the database (PostgreSQL) if one of the values in the status column occurs. The idea is to sum the amount column if the unique reference only has a status equals to 1. The query should not SELECT the reference at all if it has also a status of 2 or any other status for that matter. status refers to the state of the transaction.
Current data table:
reference | amount | status
1 100 1
2 120 1
2 -120 2
3 200 1
3 -200 2
4 450 1
Result:
amount | status
550 1
I've simplified the data example but I think it gives a good idea of what I'm looking for.
I'm unsuccessful in selecting only references that only have status 1.
I've tried sub-queries, using the HAVING clause and other methods without success.
Thanks
Here's a way using not exists to sum all rows where the status is 1 and other rows with the same reference and a non 1 status do not exist.
select sum(amount) from mytable t1
where status = 1
and not exists (
select 1 from mytable t2
where t2.reference = t1.reference
and t2.status <> 1
)
SELECT SUM(amount)
FROM table
WHERE reference NOT IN (
SELECT reference
FROM table
WHERE status<>1
)
The subquery SELECTs all references that must be excluded, then the main query sums everything except them
select sum (amount) as amount
from (
select sum(amount) as amount
from t
group by reference
having not bool_or(status <> 1)
) s;
amount
--------
550
You could use windowed functions to count occurences of status different than 1 per each group:
SELECT SUM(amount) AS amount
FROM (SELECT *,COUNT(*) FILTER(WHERE status<>1) OVER(PARTITION BY reference) cnt
FROM tc) AS sub
WHERE cnt = 0;
Rextester Demo
Related
My goal is something like following table:
Key | Count since date X | Count total
1 | 4 | 28
With two simple selects I could gain this values: (the key of the table consists of 3 columns [t$ncmp, t$trav, t$seqn])
1. SELECT COUNT(*) FROM db.table WHERE t$date >= sysdate-2 GROUP BY t$ncmp, t$trav, t$seqn
2. SELECT COUNT(*) FROM db.table GROUP BY t$ncmp, t$trav, t$seqn
How can I join these statements?
What I tried:
SELECT n.t$trav, COUNT(n.t$trav), m.total FROM db.table n
LEFT JOIN (SELECT t$ncmp, t$trav, t$seqn, COUNT(*) as total FROM db.table
GROUP BY t$ncmp, t$trav, t$seqn) m
ON (n.t$ncmp = m.t$ncmp AND n.t$trav = m.t$trav AND n.t$seqn = m.t$seqn)
WHERE n.t$date >= sysdate-2
GROUP BY n.t$ncmp, n.t$trav, n.t$seqn
I tried different variantes, but always got errors like 'group by is missing' or 'unknown qualifier'.
Now this at least executes, but total is always 2.
T$TRAV COUNT(N.T$TRAV) TOTAL
4 2 2
29 3 2
51 1 2
62 2 2
16 1 2
....
If it matter, I will run this as an OPENQUERY from MSSQLSERVER to Oracle-DB.
I'd try
GROUP BY n.t$trav, m.total
You typically GROUP BY the same columns as you SELECT - except those who are arguments to set functions.
My goal is something like following table:
If so, you seem to want conditional aggregation:
select key, count(*) as total,
sum(case when datecol >= date 'xxxx-xx-xx' then 1 else 0 end) as total_since_x
from t
group by key;
I'm not sure how this relates to your sample queries. I simply don't see the relationship between that code and your question.
I wrote a query to count the amount of item with some conditions. But the query looks complex and take a long time to run. Is there a better way to get the same result?
My table looks like this.
timestamp uid action item state
------------------------------------------------
2010 1 switch null on
2100 1 move A null
2300 1 move A null
2700 1 move B null
2013 2 switch null off
2213 2 move C null
2513 2 move A null
2200 3 switch null off
2350 3 move A null
2513 3 switch null on
2700 3 move A null
Basically, I want to get the number of each item with a condition that state is on before and within a period of time.
My query is
WITH action_move (
SELECT timestamp, uid, item
FROM table
WHERE action=move AND item IS NOT NULL
)
SELECT item, count(*)
FROM action_move
WHERE EXISTS (
SELECT timestamp
FROM table
WHERE
uid=action_move.uid
action=switch
AND state=on
AND (action_move.timestamp - timestamp) < 1000
)
GROUP BY item;
My result
item count
-------------
A 3
B 1
C 0
You can do what you want with window functions. I think the logic is:
select item, count(*)
from (select t.*,
max(timestamp) filter (where state = 'on') over (order by timestamp) as prev_on
from t
) t
where item is not null prev_on >= timestamp - 1000
group by item;
Often times when you could use window functions, in modern postgres you should use LATERAL. A LATERAL subclause allows you to reference columns from the parent clause. So try something like:
SELECT item, sum(counts.count) AS count
FROM table t1,
LATERAL (
SELECT count(*)
FROM table t2
WHERE t1.uid = t2.uid
AND t2.action=switch
AND t2.state=on
AND (t1.timestamp - t2.timestamp) < 1000
) counts
WHERE action=move AND item IS NOT NULL
GROUP BY item;
I'm not sure if I've replicated this exactly. You might not need the GROUP BY in the outer clause if you have a filter for the specific events you want to aggregate. Basically the lateral will just let you subselect on the table while referencing the row you are subselecting for.
Need to get total sum of defect between main_date column and past 365 day (a year) from it, if any, for a single ID.
And The value need to be populated for each row.
Have tried below queries and tried to use CSUM also but it's not working:
1) select sum(Defect) as "sum",Id,MAIN_DT
from check_diff
where MAIN_DT between ADD_MONTHS(MAIN_DT,-12) and MAIN_DT group by 2,3;
2)select Defect,
Type1,
Type2,
Id,
MAIN_DT,
ADD_MONTHS(TIM_MAIN_DT,-12) year_old,
CSUM(Defect,MAIN_DT)
from check_diff
where
MAIN_DT between ADD_MONTHS(MAIN_DT,-12) and MAIN_DT group by id;
The expected output is as below:
Defect Type1 Type2 Id main_dt sum
1 a a 1 3/10/2017 1
99 a a 1 4/10/2018 99
0 a b 1 7/26/2018 99
1 a b 1 11/21/2018 100
1 a c 2 12/20/2018 1
Teradata doesn't support RANGE for Cumulative Sums, but you can rewrite it using a Correlated Scalar SUbquery:
select Defect, Id, MAIN_DT,
( select sum(Defect) as "sum"
from check_diff as t2
where t2.Id = t1.Id
and t2.MAIN_DT > ADD_MONTHS(t1.MAIN_DT,-12)
and t2.MAIN_DT <= t1.MAIN_DT group by 2,3;
) as dt
from check_diff as t1
Performance might be bad depending on the overall number of rows and the number of rows per ID.
Sorry for this question, but i cannot resolve this simple query.
I have this table:
ID_Type Item
-----------------
A 1
P 2
P 3
A 4
P 5
A 6
I need to calculate a "group" incremental counter based on ID_Type Field where This field has an "A" Value. This is the expected result:
ID_Type Item Counter
-----------------------------
A 1 1
P 2 1
P 3 1
A 4 2
P 5 2
A 6 3
So every time a record with ID_Type='A' appear, I need to increment the counter. Any help will be apreciated.
In SQL Server 2012+, you can use a cumulative sum:
select t.*,
sum(case when id_type = 'A' then 1 else 0 end) over (order by item) as counter
from t;
This will be much more efficient than a correlated subquery approach, particularly on larger data sets.
One way is a subquery:
SELECT ID_Type, Item, (
SELECT COUNT(*) FROM MyTable t2
WHERE t2.Item <= t1.Item
AND t2.ID_Type='A'
) AS Counter
FROM MyTable t1
ORDER BY Item ASC
This will work on any version of SQL Server.
After many attempts I have failed at this and hoping someone can help. The query returns every entry a user makes when items are made in the factory against and order number. For example
Order Number Entry type Quantity
3000 1 1000
3000 1 500
3000 2 300
3000 2 100
4000 2 1000
5000 1 1000
What I want to the query do is to return filter the results like this
If the order number has an entry type 1 and 2 return the row which is type 1 only
otherwise just return row whatever the type is for that order number.
So the above would end up:
Order Number Entry type Quantity
3000 1 1000
3000 1 500
4000 2 1000
5000 1 1000
Currently my query (DB2, in very basic terms looks like this ) and was correct until a change request came through!
Select * from bookings where type=1 or type=2
thanks!
select * from bookings
left outer join (
select order_number,
max(case when type=1 then 1 else 0 end) +
max(case when type=2 then 1 else 0 end) as type_1_and_2
from bookings
group by order_number
) has_1_and_2 on
type_1_and_2 = 2
has_1_and_2.order_number = bookings.order_number
where
bookings.type = 1 or
has_1_and_2.order_number is null
Find all the orders that have both type 1 and type 2, and then join it.
If the row matched the join, only return it if it is type 1
If the row did not match the join (has_type_2.order_number is null) return it no matter what the type is.
A "common table expression" [CTE] can often simplify your logic. You can think of it as a way to break a complex problem into conceptual steps. In the example below, you can think of g as the name of the result set of the CTE, which will then be joined to
WITH g as
( SELECT order_number, min(type) as low_type
FROM bookings
GROUP BY order_number
)
SELECT b.*
FROM g
JOIN bookings b ON g.order_number = b.order_number
AND g.low_type = b.type
The JOIN ON conditions will work so that if both types are present then low_type will be 1, and only that type of record will be chosen. If there is only one type it will be identical to low_type.
This should work fine as long as 1 and 2 are the only types allowed in the bookings table. If not then you can simply add a WHERE clause in the CTE and in the outer SELECT.