I have tables A, B, C, where A represents items which can have zero or more sub-items stored in C. B table only has 2 foreign keys to connect A and C.
I have this sql query:
select * from A
where not exists (select * from B natural join C where B.id = A.id and C.value > 10);
Which says: "Give me every item from table A where all sub-items have value less than 10.
Is there a way to optimize this? And is there a way to write this not using exists operator?
There are three commonly used ways to test if a value is in one table but not another:
NOT EXISTS
NOT IN
LEFT JOIN ... WHERE ... IS NULL
You have already shown code for the first. Here is the second:
SELECT *
FROM A
WHERE id NOT IN (
SELECT b.id
FROM B
NATURAL JOIN C
WHERE C.value > 10
)
And with a left join:
SELECT *
FROM A
LEFT JOIN (
SELECT b.id
FROM B
NATURAL JOIN C
WHERE C.value > 10
) BC
ON A.id = BC.id
WHERE BC.id IS NULL
Depending on the database type and version, the three different methods can result in different query plans with different performance characteristics.
Related
I'll consider three simple tables. A, B are my entity tables and C is an intermediate table that creates a many-to-many relationship between A & B.
Schemas:
A: (id INTEGER PRIMARY KEY)
B: (id INTEGER PRIMARY KEY)
C: (
A_id INTEGER,
B_id INTEGER,
FOREIGN KEY(A_id) REFERENCES A(id),
FOREIGN KEY(B_id) REFERENCES B(id)
)
Now, consider the below query
SELECT
A.id
FROM A
LEFT OUTER JOIN C
ON (A.id = C.A_id)
LEFT OUTER JOIN B
ON (C.B_id = B.id)
WHERE ...;
This query would result in duplicate values of A.id, which is expected because C might have multiple rows associated with each row of A. My question is what's the best way to eliminate these duplicates and get the A records. I only need the A records.
I am aware of two ways,
-- Using DISTINCT
SELECT
DISTINCT(A.id), ...
FROM A
LEFT OUTER JOIN C
ON (A.id = C.A_id)
LEFT OUTER JOIN B
ON (C.B_id = B.id)
WHERE ...
ORDER BY A.id;
And
-- Or using A.id IN (above query)/ A.id = Any(above query)
SELECT
...
FROM A
WHERE A.id IN (
SELECT
A.id
FROM A
LEFT OUTER JOIN C
ON (A.id = C.A_id)
LEFT OUTER JOIN B
ON (C.B_id = B.id)
WHERE ...
);
I'm using PostgreSQL. I need to include all the tables for filtering, so not joining a table cannot be considered as an improvement. I've analyzed both the queries but I still feel there might be a better way to do this(in terms of performance).
Any help is really appreciated!
I would suggest exists:
SELECT A.id
FROM A
WHERE EXISTS (SELECT 1
FROM C JOIN
B
ON C.B_id = B.id
WHERE A.id = C.A_id AND . . .
)
You can also try following query:
SELECT
a.* -- or whatever columns you need of a
FROM a
WHERE EXISTS(
SELECT 1
FROM c
WHERE c.a_id = a.id
)
Note, that there is no need to join table b as the existence of the row in c always guarantees for the row in b and you do not need any information contained in this row/table.
Perhaps even more clean might be:
SELECT DISTINCT
a.* -- or whatever columns you need of a
FROM a
LEFT JOIN c
You can have a look at the query plans and execution times using EXPLAIN ANALYZE <query>. Perhaps this gives you a hint on what to use best.
But be aware of caching, repeat both queries multiple times this way to see comparable results.
I've 3 tables A, B, C. I want to list the intersection count.
Way 1:-
select count(id) from A a join B b on a.id = b.id join C c on B.id = C.id;
Result Count - X
Way 2:-
SELECT count(id) FROM A WHERE id IN (SELECT id FROM B WHERE id IN (SELECT id FROM C));
Result Count - Y
The result count in each of the query is different. What exactly is wrong?
A JOIN can multiply the number of rows as well as filtering out rows.
In this case, the second count should be the correct one because nothing is double counted -- assuming id is unique in a. If not, it needs count(distinct a.id).
The equivalent using JOIN would use COUNT(DISTINCT):
select count(distinct a.id)
from A a join
B b
on a.id = b.id join
C c
on B.id = C.id;
I mention this for completeness but do not recommend this approach. Multiplying the number of rows just to remove them using distinct is inefficient.
In many databases, the most efficient method might be:
select count(*)
from a
where exists (select 1 from b where b.id = a.id) and
exists (select 1 from c where c.id = a.id);
Note: This assumes there are indexes on the id columns and that id is unique in a.
I have this SQL problem: I have tables A and B. Table A has columns id and name, Table B amount and id which is a foreign key to table A.id.
I need to return all table A rows that don't have their id stored in table B. Any ideas?
So the complete opposite is:
SELECT *
FROM a
LEFT OUTER JOIN b ON a.id = b.id;
Here row what I need is left out of result
Just add a where clause:
SELECT a.*
FROM a LEFT OUTER JOIN
b
ON a.id = b.id
WHERE b.id IS NULL;
You can also use NOT EXISTS:
select a.*
from a
where not exists (select 1 from b where b.id = a.id);
In most databases, the two methods typically have similar performance.
I've 3 tables, viz A, B & c.
B & C has forign key of A.
Now I want to run a query on A, in such a way, that only records of B are returned.
That is, I want to exclude all the results of C and show only results of B, when a query is executed on all the records of A.
Hope, I've the question makes sense.
If you want to return all records of A and any matching records from B then something a left outer join is appropriate:
SELECT a.*, b.*
FROM a, b
WHERE a.id = b.id
This will return each record from A and populate values from B where there is a match. This will also return multiple rows for records that occur in A if there are multiple rows in B that match.
Just because there is a foreign key in C that references something in table A, it won't be returned unless you use it in your query.
If you just want to return all records from B when the foreign key appears in A then maybe you want:
SELECT *
FROM B
WHERE B.id in (SELECT id FROM A)
AND B.id not in (SELECT id FROM C)
or
SELECT *
FROM B
WHERE EXISTS (SELECT 1 FROM A JOIN B on A.id = B.id)
AND NOT EXISTS (SELECT 1 FROM C JOIN B on C.id = B.id)
All these assume that id is the key which is common.
Is this what you want?
select a.*
from a
where exists (select 1 from b where b.aid = a.aid) and
not exists (select 1 from c where c.aid = c.aid);
When using a SQL join, is it possible to keep only rows that have a single row for the left table?
For example:
select * from A, B where A.id = B.a_id;
a1 b1
a2 b1
a2 b2
In this case, I want to remove all except the first row, where a single row from A matched exactly 1 row from B.
I'm using MySQL.
This should work in MySQL:
select * from A, B where A.id = B.a_id GROUP BY A.id HAVING COUNT(*) = 1;
For those of you not using MySQL, you will need to use aggregate functions (like min() or max()) on all the columns (except A.id) so your database engine doesn't complain.
It helps if you specify the keys of your tables when asking a question such as this. It isn't obvious from your example what the key of B might be (assuming it has one).
Here's a possible solution assuming that ID is a candidate key of table B.
SELECT *
FROM A, B
WHERE B.id =
(SELECT MIN(B.id)
FROM B
WHERE A.id = B.a_id);
First, I would recommend using the JOIN syntax instead of the outdated syntax of separating tables by commas. Second, if A.id is the primary key of the table A, then you need only inspect table B for duplicates:
Select ...
From A
Join B
On B.a_id = A.id
Where Exists (
Select 1
From B B2
Where B2.a_id = A.id
Having Count(*) = 1
)
This avoids the cost of counting matching rows, which can be expensive for large tables.
As usual, when comparing various possible solutions, benchmarking / comparing the execution plans is suggested.
select
*
from
A
join B on A.id = B.a_id
where
not exists (
select
1
from
B B2
where
A.id = b2.a_id
and b2.id != b.id
)