I found some information regarding IN, JOINS and EXISTS, and there efficiency. But for me my question was never really answered, or the answer was not clearly stated.
My examples produce the same results.
Here are the two examples:
SELECT COUNT(DISTINCT A.ID)
FROM A
,B
,C
WHERE A.ID = B.ID
AND B.ID = C.ID
AND 'SOME OTHER CONDITIONS';
SELECT COUNT(DISTINCT A.ID)
FROM A
WHERE A.ID IN (SELECT DISTINCT B.ID
FROM B
,C
WHERE B.ID = C.ID
AND 'SOME CONDITION')
AND 'SOME CONDITION';
Running against a hundreds of millions of rows, is one of them clear more proficient than the other?
I tried it out in SQL with 100000 records and a very similar query without the conditions and saw the execution plan. The output result is the same for both.
Both have a query cost of 50%.
Also with statistics on, 1st has 3891 physical reads on table2 and 425 on table1, while the other has 4593 physical reads on table2 and 79 on table1. The logical reads and the read-ahead reads were almost similar for both the queries.
So clearly both queries work the same way.
My Query
Select count( distinct table1.column)
From table1 join table2
on table1.column= table2.column;
Select count (distinct column)
From table1
Where column in
(Select distinct column
from table2);
But, when I use Select column and not the count(distinct column) i.e. not aggregated, join have a query cost of 5% as compared to the other which has 95% and all reads are many times less in joins.
So for non-aggregated queries 'Joins' are more efficient than 'In'.
I think it depends on how much rows you "eliminate" from the inner select. If the inner select returns few rows it will be faster to execute the "IN". However I don't think there will be much difference, maybe the first example could use more memory because it need to store in memory the whole cartesian product of the three tables.
Unrequested hint: write your join conditions like this: FROM B JOIN C ON (B.ID = C.ID), it will be more clear, and in your WHERE clauses you will only have necessary conditions. Anywhere this won't effect performance, it was just a suggestion
Related
I was recently going through a lot of SQL code where Join sections were filled with complex subqueries, and started wondering if there is any benefit of joining subquery with limited column selection vs joining entire table and selecting only necessary columns.
To ilustrate that:
Let's say we have 2 tables: Table1, Table2 each with columns (PK, FK, a, b ,c, d, e, f).
I want to join Table1 with Table2, but retrieve only a few fields from Table2.
Which is more efficient, what are the benefits of each?
SELECT
Table1.*,
Table2.a,
Table2.b
FROM Table1
LEFT JOIN Table2 ON Table1.PK = Table2.FK
OR
SELECT
Table1.*,
Table2sub.*
FROM Table1
LEFT JOIN (SELECT FK, a, b FROM Table2) AS Table2sub ON Table1.PK = Table2sub.FK
SQL is a descriptive language, not a procedural language. That is, a SQL query describes what the result set looks like, not how the result is produced.
In fact, what the engine runs is called a directed acyclic graph (DAG) -- and that looks nothing like a query. The SQL engine first parses the query, then compiles it, then optimizes it to produce the DAG.
SQL Server has a good optimizer. It is not going to be confused by subqueries. Some SQL compilers are not quite as smart and will materialize the subquery -- which could have a big impact on performance.
If you look at the execution plans, you will see that they are the same in this case.
I have an SQL query which uses cartesian product on a large table. However, I only need one column from one of the tables. Would it actually perform better, if I selected only that one column before using the cartesian product?
So, in other words, would this:
SELECT A.Id, B.Id
FROM (SELECT Id FROM Table1) AS A , Table2 AS B;
be faster than this, given that Table1 has more columns than Id?:
SELECT A.Id, B.Id
FROM Table1 AS A , Table2 AS B;
Or does the number of columns not matter?
On most databases, the two forms would have the same execution plan.
The first could would be worse on a database (such as MySQL) that materializes subqueries.
The second should be better with indexes on the two tables . . . table1(id) and table2(id). The index would be used to get the value rather than the base data.
Try it out yourself! But generally speaking having a subquery reduce the number of rows will help improve the performance. Your query should, however, be written differently:
select a.id aid, b.id bid from
(Select id from table1 where id=<specific_id>) a, table2 b
I've hit a bit of a situation and my novice level SQL experience has met it's match.
I have a query
SELECT a.One,
a.Two,
a.Three,
a.Four,
b.One,
b.Two
FROM table1 a
INNER JOIN table2 b on b.Four = a.Nine
and b.Six like a.One
and b.Seven like b.Two
Table1 is 25000 rows
Table2 is 22 million rows
like clause works like this 'test%', so it should utilize the indexes I have and I don't think I need a full text index because its trailing and not preceding.
I have an index that exists and works very efficiently when I use a straight equals instead of a like.
When I look at the query plan, I see that I am going through every row in table2 (which I was suprised). How does the inner join work in terms of what gets executed first? Does it combine the three columns as the join? Or does it Join with the first column, then second, then third.
Is there a better way to write this query?
The problem is that an index can only be used for one like 'pattern%' comparison. This is an inequality, so index usage stops at the first one.
You might have luck by changing the query to a union:
SELECT a.One, a.Two, a.Three, a.Four, b.One, b.Two
FROM table1 a INNER JOIN
table2 b
ON b.Four = a.Nine and b.Six like a.One
UNION
SELECT a.One, a.Two, a.Three, a.Four, b.One, b.Two
FROM table1 a INNER JOIN
table2 b
ON b.Four = a.Nine and bb.Seven like b.Two;
Then, set up the indexes on a(Nine, One) and b(Four, Two). Although the two subqueries should use the indexes, you may get a lot of matches for the intermediate results slowing down the query.
Okay, I know there are a few posts that discuss this, but my problem cannot be solved by a conditional where statement on a join (the common solution).
I have three join statements, and depending on the query parameters, I may need to run any combination of the three. My Join statement is quite expensive, so I want to only do the join when the query needs it, and I'm not prepared to write a 7 combination IF..ELSE.. statement to fulfill those combinations.
Here is what I've used for solutions thus far, but all of these have been less than ideal:
LEFT JOIN joinedTable jt
ON jt.someCol = someCol
WHERE jt.someCol = conditions
OR #neededJoin is null
(This is just too expensive, because I'm performing the join even when I don't need it, just not evaluating the join)
OUTER APPLY
(SELECT TOP(1) * FROM joinedTable jt
WHERE jt.someCol = someCol
AND #neededjoin is null)
(this is even more expensive than always left joining)
SELECT #sql = #sql + ' INNER JOIN joinedTable jt ' +
' ON jt.someCol = someCol ' +
' WHERE (conditions...) '
(this one is IDEAL, and how it is written now, but I'm trying to convert it away from dynamic SQL).
Any thoughts or help would be great!
EDIT:
If I take the dynamic SQL approach, I'm trying to figure out what would be most efficient with regards to structuring my query. Given that I have three optional conditions, and I need the results from all of them my current query does something like this:
IF condition one
SELECT from db
INNER JOIN condition one
UNION
IF condition two
SELECT from db
INNER JOIN condition two
UNION
IF condition three
SELECT from db
INNER JOIN condition three
My non-dynamic query does this task by performing left joins:
SELECT from db
LEFT JOIN condition one
LEFT JOIN condition two
LEFT JOIN condition three
WHERE condition one is true
OR condition two is true
OR condition three is true
Which makes more sense to do? since all of the code from the "SELECT from db" statement is the same? It appears that the union condition is more efficient, but my query is VERY long because of it....
Thanks!
LEFT JOIN
joinedTable jt ON jt.someCol = someCol AND jt.someCol = conditions AND #neededjoin ...
...
OR
LEFT JOIN
(
SELECT col1, someCol, col2 FROM joinedTable WHERE someCol = conditions AND #neededjoin ...
) jt ON jt.someCol = someCol
...
OR
;WITH jtCTE AS
(SELECT col1, someCol, col2 FROM joinedTable WHERE someCol = conditions AND #neededjoin ...)
SELECT
...
LEFT JOIN
jtCTE ON jtCTE.someCol = someCol
...
To be honest, there is no such construct as a conditional JOIN unless you use literals.
If it's in the SQL statement it's evaluated... so don't have it in the SQL statement by using dynamic SQL or IF ELSE
the dynamic sql solution is usually the best for these situations, but if you really need to get away from that a series of if statments in a stroed porc will do the job. It's a pain and you have to write much more code but it will be faster than trying to make joins conditional in the statement itself.
I would go for a simple and straightforward approach like this:
DECLARE #ret TABLE(...) ;
IF <coondition one> BEGIN ;
INSERT INTO #ret() SELECT ...
END ;
IF <coondition two> BEGIN ;
INSERT INTO #ret() SELECT ...
END ;
IF <coondition three> BEGIN ;
INSERT INTO #ret() SELECT ...
END ;
SELECT DISTINCT ... FROM #ret ;
Edit: I am suggesting a table variable, not a temporary table, so that the procedure will not recompile every time it runs. Generally speaking, three simpler inserts have a better chance of getting better execution plans than one big huge monster query combining all three.
However, we can not guess-timate performance. we must benchmark to determine it. Yet simpler code chunks are better for readability and maintainability.
Try this:
LEFT JOIN joinedTable jt
ON jt.someCol = someCol
AND jt.someCol = conditions
AND #neededJoin = 1 -- or whatever indicates join is needed
I think you'll find it is good performance and does what you need.
Update
If this doesn't give the performance I claimed, then perhaps that's because the last time I did this using joins to a table. The value I needed could come from one of 3 tables, based on 2 columns, so I built a 'join-map' table like so:
Col1 Col2 TableCode
1 2 A
1 4 A
1 3 B
1 5 B
2 2 C
2 5 C
1 11 C
Then,
SELECT
V.*,
LookedUpValue =
CASE M.TableCode
WHEN 'A' THEN A.Value
WHEN 'B' THEN B.Value
WHEN 'C' THEN C.Value
END
FROM
ValueMaster V
INNER JOIN JoinMap M ON V.Col1 = M.oOl1 AND V.Col2 = M.Col2
LEFT JOIN TableA A ON M.TableCode = 'A'
LEFT JOIN TableB B ON M.TableCode = 'B'
LEFT JOIN TableC C ON M.TableCode = 'C'
This gave me a huge performance improvement querying these tables (most of them dozens or hundreds of million-row tables).
This is why I'm asking if you actually get improved performance. Of course it's going to throw a join into the execution plan and assign it some cost, but overall it's going to do a lot less work than some plan that just indiscriminately joins all 3 tables and then Coalesce()s to find the right value.
If you find that compared to dynamic SQL it's only 5% more expensive to do the joins this way, but with the indiscriminate joins is 100% more expensive, it might be worth it to you to do this because of the correctness, clarity, and simplicity over dynamic SQL, all of which are probably more valuable than a small improvement (depending on what you're doing, of course).
Whether the cost scales with the number of rows is also another factor to consider. If even with a huge amount of data you only save 200ms of CPU on a query that isn't run dozens of times a second, it's a no-brainer to use it.
The reason I keep hammering on the fact that I think it's going to perform well is that even with a hash match, it wouldn't have any rows to probe with, or it wouldn't have any rows to create a hash of. The hash operation is going to stop a lot earlier compared to using the WHERE clause OR-style query of your initial post.
The dynamic SQL solution is best in most respects; you are trying to run different queries with different numbers of joins without rewriting the query to do different numbers of joins - and that doesn't work very well in terms of performance.
When I was doing this sort of stuff an æon or so ago (say the early 90s), the language I used was I4GL and the queries were built using its CONSTRUCT statement. This was used to generate part of a WHERE clause, so (based on the user input), the filter criteria it generated might look like:
a.column1 BETWEEN 1 AND 50 AND
b.column2 = 'ABCD' AND
c.column3 > 10
In those days, we didn't have the modern JOIN notations; I'm going to have to improvise a bit as we go. Typically there is a core table (or a set of core tables) that are always part of the query; there are also some tables that are optionally part of the query. In the example above, I assume that 'c' is the alias for the main table. The way the code worked would be:
Note that table 'a' was referenced in the query:
Add 'FullTableName AS a' to the FROM clause
Add a join condition 'AND a.join1 = c.join1' to the WHERE clause
Note that table 'b' was referenced...
Add bits to the FROM clause and WHERE clause.
Assemble the SELECT statement from the select-list (usually fixed), the FROM clause and the WHERE clause (occasionally with decorations such as GROUP BY, HAVING or ORDER BY too).
The same basic technique should be applied here - but the details are slightly different.
First of all, you don't have the string to analyze; you know from other circumstances which tables you need to add to your query. So, you still need to design things so that they can be assembled, but...
The SELECT clause with its select-list is probably fixed. It will identify the tables that must be present in the query because values are pulled from those tables.
The FROM clause will probably consist of a series of joins.
One part will be the core query:
FROM CoreTable1 AS C1
JOIN CoreTable2 AS C2
ON C1.JoinColumn = C2.JoinColumn
JOIN CoreTable3 AS M
ON M.PrimaryKey = C1.ForeignKey
Other tables can be added as necessary:
JOIN AuxilliaryTable1 AS A
ON M.ForeignKey1 = A.PrimaryKey
Or you can specify a full query:
JOIN (SELECT RelevantColumn1, RelevantColumn2
FROM AuxilliaryTable1
WHERE Column1 BETWEEN 1 AND 50) AS A
In the first case, you have to remember to add the WHERE criterion to the main WHERE clause, and trust the DBMS Optimizer to move the condition into the JOIN table as shown. A good optimizer will do that automatically; a poor one might not. Use query plans to help you determine how able your DBMS is.
Add the WHERE clause for any inter-table criteria not covered in the joining operations, and any filter criteria based on the core tables. Note that I'm thinking primarily in terms of extra criteria (AND operations) rather than alternative criteria (OR operations), but you can deal with OR too as long as you are careful to parenthesize the expressions sufficiently.
Occasionally, you may have to add a couple of JOIN conditions to connect a table to the core of the query - that is not dreadfully unusual.
Add any GROUP BY, HAVING or ORDER BY clauses (or limits, or any other decorations).
Note that you need a good understanding of the database schema and the join conditions. Basically, this is coding in your programming language the way you have to think about constructing the query. As long as you understand this and your schema, there aren't any insuperable problems.
Good luck...
Just because no one else mentioned this, here's something that you could use (not dynamic). If the syntax looks weird, it's because I tested it in Oracle.
Basically, you turn your joined tables into sub-selects that have a where clause that returns nothing if your condition does not match. If the condition does match, then the sub-select returns data for that table. The Case statement lets you pick which column is returned in the overall select.
with m as (select 1 Num, 'One' Txt from dual union select 2, 'Two' from dual union select 3, 'Three' from dual),
t1 as (select 1 Num from dual union select 11 from dual),
t2 as (select 2 Num from dual union select 22 from dual),
t3 as (select 3 Num from dual union select 33 from dual)
SELECT m.*
,CASE 1
WHEN 1 THEN
t1.Num
WHEN 2 THEN
t2.Num
WHEN 3 THEN
t3.Num
END SelectedNum
FROM m
LEFT JOIN (SELECT * FROM t1 WHERE 1 = 1) t1 ON m.Num = t1.Num
LEFT JOIN (SELECT * FROM t2 WHERE 1 = 2) t2 ON m.Num = t2.Num
LEFT JOIN (SELECT * FROM t3 WHERE 1 = 3) t3 ON m.Num = t3.Num
I have a particularly slow query due to the vast amount of information being joined together. However I needed to add a where clause in the shape of id in (select id from table).
I want to know if there is any gain from the following, and more pressing, will it even give the desired results.
select a.* from a where a.id in (select id from b where b.id = a.id)
as an alternative to:
select a.* from a where a.id in (select id from b)
Update:
MySQL
Can't be more specific sorry
table a is effectively a join between 7 different tables.
use of * is for examples
Edit, b doesn't get selected
Your question was about the difference between these two:
select a.* from a where a.id in (select id from b where b.id = a.id)
select a.* from a where a.id in (select id from b)
The former is a correlated subquery. It may cause MySQL to execute the subquery for each row of a.
The latter is a non-correlated subquery. MySQL should be able to execute it once and cache the results for comparison against each row of a.
I would use the latter.
Both queries you list are the equivalent of:
select a.*
from a
inner join b on b.id = a.id
Almost all optimizers will execute them in the same way.
You could post a real execution plan, and someone here might give you a way to speed it up. It helps if you specify what database server you are using.
YMMV, but I've often found using EXISTS instead of IN makes queries run faster.
SELECT a.* FROM a WHERE EXISTS (SELECT 1 FROM b WHERE b.id = a.id)
Of course, without seeing the rest of the query and the context, this may not make the query any faster.
JOINing may be a more preferable option, but if a.id appears more than once in the id column of b, you would have to throw a DISTINCT in there, and you more than likely go backwards in terms of optimization.
I would never use a subquery like this. A join would be much faster.
select a.*
from a
join b on a.id = b.id
Of course don't use select * either (especially never use it when doing a join as at least one field is repeated) and it wastes network resources to send unnneeded data.
Have you looked at the execution plan?
How about
select a.*
from a
inner join b
on a.id = b.id
presumably the id fields are primary keys?
Select a.* from a
inner join (Select distinct id from b) c
on a.ID = c.AssetID
I tried all 3 versions and they ran about the same. The execution plan was the same (inner join, IN (with and without where clause in subquery), Exists)
Since you are not selecting any other fields from B, I prefer to use the Where IN(Select...) Anyone would look at the query and know what you are trying to do (Only show in a if in b.).
your problem is most likely in the seven tables within "a"
make the FROM table contain the "a.id"
make the next join: inner join b on a.id = b.id
then join in the other six tables.
you really need to show the entire query, list all indexes, and approximate row counts of each table if you want real help