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 ..
Related
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 2 tables, both of which contain distinct id values. Some of the id values might occur in both tables and some are unique to each table. Table1 has 10,910 rows and Table2 has 11,304 rows
When running a left join query:
SELECT COUNT(DISTINCT a.id)
FROM table1 a
JOIN table2 b on a.id = b.id
I get a total of 10,896 rows or 10,896 ids shared across both tables.
However, when I run a FULL OUTER JOIN on the 2 tables like this:
SELECT COUNT(DISTINCT a.id)
FROM table1 a
FULL OUTER JOIN EACH table2 b on a.id = b.id
I get total of 10,896 rows, but I was expecting all 10,910 rows from table1.
I am wondering if there is an issue with my query syntax.
As you are using EACH - it looks like you are running your queries in Legacy SQL mode.
In BigQuery Legacy SQL - COUNT(DISTINCT) function is probabilistic - gives statistical approximation and is not guaranteed to be exact.
You can use EXACT_COUNT_DISTINCT() function instead - this one gives you exact number but a little more expensive on back-end
Even better option - just use Standard SQL
For your specific query you will only need to remove EACH keyword and it should work as a charm
#standardSQL
SELECT COUNT(DISTINCT a.id)
FROM table1 a
JOIN table2 b on a.id = b.id
and
#standardSQL
SELECT COUNT(DISTINCT a.id)
FROM table1 a
FULL OUTER JOIN table2 b on a.id = b.id
I added the original query as a subquery and counted ids and produced the expected results. Still a little strange, but it works.
SELECT EXACT_COUNT_DISTINCT(a.id)
FROM
(SELECT a.id AS a.id,
b.id AS b.id
FROM table1 a FULL OUTER JOIN EACH table2 b on a.id = b.id))
It is because you count in both case the number of non-null lines for table a by using a count(distinct a.id).
Use a count(*) and it should works.
You will have to add coalesce... BigQuery, unlike traditional SQL does not recognize fields unless used explicitly
SELECT COUNT(DISTINCT coalesce(a.id,b.id))
FROM table1 a
FULL OUTER JOIN EACH table2 b on a.id = b.id
This query will now take full effect of full outer join :)
I saw answers to a related question, but couldn't really apply what they are doing to my specific case.
I have a large table (300k rows) that I need to join with another even larger (1-2M rows) table efficiently. For my purposes, I only need to know whether a matching row exists in the second table. I came up with a nested query like so:
SELECT
id,
CASE cnt WHEN 0 then 'NO_MATCH' else 'YES_MATCH' end as match_exists
FROM
(
SELECT
A.id as id, count(*) as cnt
FROM
A, B
WHERE
A.id = B.foreing_id
GROUP BY A.id
) AS id_and_matches_count
Is there a better and/or more efficient way to do it?
Thanks!
You just want a left outer join:
SELECT
A.id as id, count(B.foreing_id) as cnt
FROM A
LEFT OUTER JOIN B ON
A.id = B.foreing_id
GROUP BY A.id
If I have two tables - Table_A and Table_B - and if I am using LEFT JOIN to join them, how can I filter only those rows from Table_B which joined with the rows in the Table_A more than once?
DB flavor: Teradata
If I'm not mistaken Teradata supports window functions, so this might work:
select *
from (
select a.*,
b.*
count(*) over (partition by a.MyCol) as cnt
from Table_A a
left join Table_B b ON a.MyCol = b.MyCol
where ... -- Conditions
) t
where cnt > 1
(not tested)
Here is a Teradata-specific version of your accepted answer:
select a.*,
b.*
from Table_A a
left join Table_B b
ON a.MyCol = b.MyCol
where ... -- Conditions
QUALIFY count(*) over (partition by a.MyCol) > 1
Note that QUALIFY is a Teradata extension to the ANSI standard (and a handy one at that).
may be it's help for you
1) you can used INNER JOIN .
2) you can also check joind row is not null or blank .
Select a.*,b.* from Table_A a
left join Table_B b on condition
HAVING COUNT(DISTINCT a.value)>1
make necessary edits and check
I have two tables with binding primary key in database and I desire to find a disjoint set between them. For example,
Table1 has columns (ID, Name) and sample data: (1 ,John), (2, Peter), (3, Mary)
Table2 has columns (ID, Address) and sample data: (1, address2), (2, address2)
So how do I create a SQL query so I can fetch the row with ID from table1 that is not in table2. In this case, (3, Mary) should be returned?
PS: The ID is the primary key for those two tables.
Try this
SELECT ID, Name
FROM Table1
WHERE ID NOT IN (SELECT ID FROM Table2)
Use LEFT JOIN
SELECT a.*
FROM table1 a
LEFT JOIN table2 b
on a.ID = b.ID
WHERE b.id IS NULL
There are basically 3 approaches to that: not exists, not in and left join / is null.
LEFT JOIN with IS NULL
SELECT l.*
FROM t_left l
LEFT JOIN
t_right r
ON r.value = l.value
WHERE r.value IS NULL
NOT IN
SELECT l.*
FROM t_left l
WHERE l.value NOT IN
(
SELECT value
FROM t_right r
)
NOT EXISTS
SELECT l.*
FROM t_left l
WHERE NOT EXISTS
(
SELECT NULL
FROM t_right r
WHERE r.value = l.value
)
Which one is better? The answer to this question might be better to be broken down to major specific RDBMS vendors. Generally speaking, one should avoid using select ... where ... in (select...) when the magnitude of number of records in the sub-query is unknown. Some vendors might limit the size. Oracle, for example, has a limit of 1,000. Best thing to do is to try all three and show the execution plan.
Specifically form PostgreSQL, execution plan of NOT EXISTS and LEFT JOIN / IS NULL are the same. I personally prefer the NOT EXISTS option because it shows better the intent. After all the semantic is that you want to find records in A that its pk do not exist in B.
Old but still gold, specific to PostgreSQL though: https://explainextended.com/2009/09/16/not-in-vs-not-exists-vs-left-join-is-null-postgresql/
Fast Alternative
I ran some tests (on postgres 9.5) using two tables with ~2M rows each. This query below performed at least 5* better than the other queries proposed:
-- Count
SELECT count(*) FROM (
(SELECT id FROM table1) EXCEPT (SELECT id FROM table2)
) t1_not_in_t2;
-- Get full row
SELECT table1.* FROM (
(SELECT id FROM table1) EXCEPT (SELECT id FROM table2)
) t1_not_in_t2 JOIN table1 ON t1_not_in_t2.id=table1.id;
Keeping in mind the points made in #John Woo's comment/link above, this is how I typically would handle it:
SELECT t1.ID, t1.Name
FROM Table1 t1
WHERE NOT EXISTS (
SELECT TOP 1 NULL
FROM Table2 t2
WHERE t1.ID = t2.ID
)
SELECT COUNT(ID) FROM tblA a
WHERE a.ID NOT IN (SELECT b.ID FROM tblB b) --For count
SELECT ID FROM tblA a
WHERE a.ID NOT IN (SELECT b.ID FROM tblB b) --For results