I have two tables: TableA and TableB (as in the following picture):
The result should be as in the following figure:
What is the best way to get result (as in the table Result) using mssql query?
Thanks.
If I understand correctly, you want the date/value pairs that don't exist.
Generate the list of all date/value pairs using a cross join. Then filter out the ones you don't want:
select b.value, d.date
from tableb b cross join
(select distinct date from tablea a) d
where not exists (select 1 from tablea a where a.date = d.date and a.value = b.value)
Related
I'm trying to take the distinct IDs that appear in table a, filter table b for only these distinct IDs from table a, and present the remaining columns from b. I've tried:
SELECT * FROM
(
SELECT DISTINCT
a.ID,
a.test_group,
b.ch_name,
b.donation_amt
FROM table_a a
INNER JOIN table_b b
ON a.ID=b.ID
ORDER by a.ID;
) t
This doesn't seem to work. This query worked:
SELECT DISTINCT a.ID, a.test_group, b.ch_name, b.donation_amt
FROM table_a a
inner join table_b b
on a.ID = b.ID
order by a.ID
But I'm not entirely sure this is the correct way to go about it. Is this second query only going to take unique combinations of a.ID and a.test_group or does it know to only take distinct values of a.ID which is what I want.
Your first and second query are similar.(just that you can not use ; inside your query) Both will produce the same result.
Even your second query which you think is giving you desired output, can not produce the output what you actually want.
Distinct works on the entire column list of the select clause.
In your case, if for the same a.id there is different a.test_group available then it will have multiple records with same a.id and different a.test_group.
I am trying to join 2 tables. Table_A has ~145k rows whereas Table_B has ~205k rows.
They have two columns in common (i.e. ISIN and date). However, when I execute this query:
SELECT A.*,
B.column_name
FROM Table_A
JOIN
Table_B ON A.date = B.date
WHERE A.isin = B.isin
I get a table with more than 147k rows. How is it possible? Shouldn't it return a table with at most ~145k rows?
What you are seeing indicates that, for some of the records in Table_A, there are several records in Table_B that satisfy the join conditions (equality on the (date, isin) tuple).
To exhibit these records, you can do:
select B.date, B.isin
from Table_A
join Table_B on A.date = B.date and A.isin = B.isin
group by B.date, B.isin
having count(*) > 1
It's up to you to define how to handle those duplicates. For example:
if the duplicates have different values in column column_name, then you can decide to pull out the maximum or minimum value
or use another column to filter on the top or lower record within the duplicates
if the duplicates are true duplicates, then you can use select distinct in a subquery to dedup them before joining
... other solutions are possible ...
If you want one row per table A, then use outer apply:
SELECT A.*,
B.column_name
FROM Table_A a OUTER APPLY
(SELECT TOP (1) b.*
FROM Table_B b
WHERE A.date = B.date AND A.isin = B.isin
ORDER BY ? -- you can specify *which* row you want when there are duplicates
) b;
OUTER APPLY implements a lateral join. The TOP (1) ensures that at most one row is returned. The OUTER (as opposed to CROSS) ensures that nothing is filtered out. In this case, you could also phrase it as a correlated subquery.
All that said, your data does not seem to be what you really expect. You should figure out where the duplicates are coming from. The place to start is:
select b.date, b.isin, count(*)
from tableb b
group by b.date, b.isin
having count(*) >= 2;
This will show you the duplicates, so you can figure out what to do about them.
Duplicate possibilities is already discuss.
When millions of records are use in join then often due to poor Cardianility Estimate,
record return are not accurate.
For this just change join order,
SELECT A.*,
B.column_name
FROM Table_A
JOIN
Table_B ON A.isin = B.isin
and
A.date = B.date
Also create non clustered index on both table.
Create NonClustered index isin_date_table_A on Table_A(isin,date)include(*Table_A)
*Table_A= comma seperated list Table_A column which is require in resultset
Create NonClustered index isin_date_table_B on Table_B(isin,date)include(column_nameA)
Update STATISTICS Table_A
Update STATISTICS Table_B
Keeping the DATE columns of both tables in the same format in the JOIN condition you should be getting the result as expected.
Select A.*, B.column_name
from Table_A
join Table_B on to_date(a.date,'DD-MON-YY') = to_date(b.date,'DD-MON-YY')
where A.isin = B.isin
I have 2 tables, A and B.
I need all columns from A + 1 column from B in my select.
Unfortunately, B has multiples rows(all identicals) for 1 row in A
on the join condition.
I tried but I can't isolate one row in A for one row in B with left join for example while keeping my select.
How can I do this query ? Query in ORACLE SQL
Thanks in advance.
This is a good use for outer apply. The structure of the query looks like this:
select a.*, b.col
from a outer apply
(select top 1 b.col
from b
where b.? = a.?
) b;
Normally, you would only use top 1 with order by. In this case, it doesn't seem to make a difference which row you choose.
You can group by on all columns from A, and then use an aggregate (like max or min) to pick any of the identical B values:
select a.*
, b.min_col1
from TableA a
left join
(
select a_id
, min(col1) as min_col1
from TableB
group by
a_id
) b
on b.a_id = a.id
I have two tables:
I want to output the following:
I tried this statement:
SELECT TableA.bu_code
, SUM(TableB.count_invalid_date) AS TotalInvDate
FROM TableA
LEFT JOIN TableB ON TableA.bu_code = TableB.bu_code
GROUP BY TableA.bu_code
But it doesn't show every row represented in TableA, instead it does this:
Is there a single SQL statement that can output what I want?
You could use a left join after performing the group by:
SELECT a.bu_code, COALESCE (TotalInvDate, 0)
FROM TableA a
LEFT JOIN (SELECT bu_code, SUM(count_invalid_date) AS TotalInvDate
FROM TableB
GROUP BY bu_code) b ON a.bu_code = b.bu_code
There may be orphaned TableB rows without a parent row in TableA.
If so, use this GROUP BY syntax to see them.
GROUP BY ROLLUP(TableA.bu_code)
Refer to this Microsoft SQL-Server page on the GROUP BY clause for more details on the ROLLUP option.
SELECT A.bu_code AS [bu_code],
ISNULL(sum( B.count_invalid_date),0) AS [TotalInvDate]
FROM
TableA A
left JOIN
TableB B
ON
A.bu_code=B.bu_code
GROUP BY
A.bu_code
Not quite sure how to ask this, but I have 2 tables that are related in a 1 to many relationship, I need to select all records in the "1" table that have less than three records in the "many' table.
select b.foreignkey,count(b.foreignkey) as bidcount
from b
where b.foreignkey in (select a.id from a) and bidcount< 3
group by b.foreignkey
this doesn't work at all I know but I am at a loss how to do this.
I need to in the end select all the records from the "a" table based on this criteria. Sorry if that is confusing!
Just using your code, not tested:
SELECT
b.foreignkey,
count(b.foreignkey) as bidcount
FROM
b
WHERE
b.foreignkey IN (SELECT a.id FROM a)
GROUP BY
b.foreignkey
HAVING
count(b.foreignkey) < 3
Try this:
SELECT t1.id,COUNT(t2.parentId)
FROM table1 as t1
INNER JOIN table2 as t2
ON t1.id = t2.parentId
GROUP BY t1.id
HAVING COUNT(t2.parentId) < 3
You didn't mention which version of SQL Server you're using - if you're on SQL Server 2005 or newer, you could use this CTE (Common Table Expression):
;WITH ChildRows AS
(
SELECT A.Id, COUNT(b.Id) AS 'BCount'
FROM
dbo.TableA A
INNER JOIN
dbo.TableB B ON B.TableAId = A.Id
)
SELECT A.*, R.BCount
FROM dbo.TableA A
INNER JOIN ChildRows R ON A.Id = R.Id
The inner SELECT lists the Id columns from TableA and the count of the child rows associated with those (using the INNER JOIN to TableB) - and the outer SELECT just builds on top of that result set and shows all fields from table A (and the count from the B table)
if you want to return all fields of your (1) table in one query, I suggest you consider using CROSS APPLY:
SELECT t1.* FROM table_1 t1
CROSS APPLY (SELECT COUNT(*) cnt FROM Table_Many t2 WHERE t2.fk = t1.pk) a
where a.cnt < 3
in some particular cases, based on your indices and db structure, this query may run 4 times faster than the GROUP BY method
you have posted this question in sql server, I have a answer in oracle database system (don't know whether it will run in sql server as well or not)
this is as follow-
select [desired column list] from
(select b.*, count(*) over (partition by b.foreignkey) c_1
from b
where b.foreignkey in (select a.id from a) )
where c_1 < 3 ;
i hope it should work on sql server as well...
if not please let me update ..