I want to know what is faster, assuming I have the following queries and they retrieve the same data
select * from tableA a inner join tableB b on a.id = b.id where b.columnX = value
or
select * from tableA inner join (select * from tableB where b.columnX = value) b on a.id = b.id
I think makes sense to reduce the dataset from tableB in advanced, but I dont find anything to backup my perception.
In a database such as Teradata, the two should have exactly the same performance characteristics.
SQL is not a procedural language. A SQL query describes the result set. It does not specify the sequence of actions.
SQL engines process a query in three steps:
Parse the query.
Optimize the parsed query.
Execute the optimized query.
The second step gives the engine a lot of flexibility. And most query engines will be quite intelligent about ignoring subqueries, using indexes and partitions based on where clauses, and so on.
Most SQL dialects compile your query into an execution plan. Teradata and most SQL system show the expected execution plan with the "explain" command. Teradata has a visual explain too, which is simple to learn from
It depends on the data volumes and key type in each table, if any method would be advantageous
Most SQL compilers will work this out correctly using the current table statistics (data size and spread)
In some SQL systems your second command would be worse, as it may force a full temporary table build by ALL fields on tableB
It should be (not that I recommend this query style at all)
select * from tableA inner join (select id from tableB where columnX = value) b on a.id = b.id
In most cases, don't worry about this, unless you have a specific performance issue, and then use the explain commands to work out why
A better way in general is to use common table expressions (CTE) to break the problem down. This leads to better queries that can be tested and maintain over the long term
Whenever you come across such scenarios wherein you feel that which query would yeild the results faster in teradata, please use the EXPLAIN plan in teradata - which would properly dictate how the PE is going to retrieve records. If you are using Teradata sql assistant then you can select the query and press F6.
The DBMS decides the access path that will be used to resolve the query, you can't decide it, but you can do certain things like declaring indexes so that the DBMS takes those indexes into consideration when deciding which access path it will use to resolve the query, and then you will get a better performance.
For instance, in this example you are filtering tableB by b.columnX, normally if there are no indexes declared for tableB the DBMS will have to do a full table scan to determine which rows fulfill that condition, but suppose you declare an index on tableB by columnX, in that case the DBMS will probably consider that index and determine an access path that makes use of the index, getting a much better performance than a full table scan, specially if the table is big.
Related
For an example:
In table a we have 1000000 rows
In table b we have 5 rows
It's more faster if we use
select * from b inner join a on b.id = a.id
than
select * from a inner join b on a.id = b.id
No, JOIN order doesn't matter, the query engine will reorganize their order based on statistics for indexes and other stuff. JOIN by order is changed during optimization.
You might test it all by yourself, download some test databases like AdventureWorks or Northwind or try it on your database, you might do this:
select show actual execution plan and run first query
change JOIN order and now run the query again
compare execution plans
They should be identical as the query engine will reorganize them according to other factors.
The only caveat is the Option FORCE ORDER which will force joins to happen in the exact order you have them specified.
It is unlikely. There are lots of factors on the speed of joining two tables. That is why database engines have an optimization phase, where they consider different ways of implementing the query.
There are many different options:
Nested loops, scanning b first and then a.
Nested loops, scanning a first and then b.
Sorting both tables and using a merge join.
Hashing both tables and using a hash join.
Using an index on b.id.
Using an index on a.id.
And these are just high level descriptions -- there are multiple ways to implement some of these methods. Tables can also be partitioned adding further complexity.
Join order is just one consideration.
In this case, the result of the query is likely to depend on the size of the data being returned, rather than the actual algorithm used for fetching the data.
For an sql query like this.
Select * from TABLE_A a
JOIN TABLE_B b
ON a.propertyA = b.propertyA
JOIN TABLE_C
ON b.propertyB = c.propertyB
Does the sequence of the tables matter. It wont matter in results, but do they affect the performance?
One can assume that the data in table C is much larger that a or b.
For each sql statement, the engine will create a query plan. So no matter how you put them, the engine will chose a correct path to build the query.
More on plans you have http://en.wikipedia.org/wiki/Query_plan
There are ways, considering what RDBMS you are using to enforce the query order and plan, using hints, however, if you feel that the engine does no chose the correct path.
Sometimes Order of table creates a difference here,(when you are using different joins)
Actually our Joins working on Cross Product Concept
If you are using query like this A join B join C
It will be treated like this (A*B)*C)
Means first result comes after joining A and B table then it will make join with C table
So if after inner joining A (100 record) and B (200 record) if it will give (100 record)
And then these ( 100 record ) will compare with (1000 record of C)
No.
Well, there is a very, very tiny chance of this happening, see this article by Jonathan Lewis. Basically, the number of possible join orders grows very quickly, and there's not enough time for the Optimizer to check them all. The sequence of the tables may be used as a tie-breaker in some very rare cases. But I've never seen this happen, or even heard about it happening, to anybody in real life. You don't need to worry about it.
I'm not sure where/how I specify this SQL Spatial Index hint on my query :-
SELECT Whatever
FROM Table1 a
INNER JOIN Table2 b ON a.Id = b.Id
WHERE #SomeBoundingBox.STIntersects(b.SomeGeographyShape) = 1
When I run the query, it's NOT using the Spatial Hint. Yes, I'm using the the latest version SQL Server 2008 r2 (v 10.5.1600.1).
So to compare the query speed by forcing the hint, I tried...
SELECT Whatever
FROM Table1 a
INNER JOIN Table2 b WITH (INDEX(MySpatialIndex)) ON a.Id = b.Id
WHERE #SomeBoundingBox.STIntersects(b.SomeGeographyShape) = 1
and that worked but it was really poor performance. I was wondering if it was trying to use my hint to do the a.Id = b.Id join (which i don't want to use the hint, for).
Any suggestions?
UPDATE:
Added Query Plan. The bulk of the cost is the JOIN between the two tables. The Filter (where clause) takes up the 2nd most costly part.
I would suggest NOT forcing the hint. There is a reason that SQL Server is choosing the execution plan that it is, and as you suspected, forcing another plan will almost always result in decreased performance.
Instead, what you want to do is examine your indexes and query execution plans in detail, follow each node of the execution plan (especially ones with a high relative cost) and see if you can do what SQL Server wants you to do in order to pick up your MySpatialIndex index without you forcing it to do so. Usually, it will just be a missing field from an index that will cause the execution plan to work out just as you wish... with no forcing necessary.
Why do you think that the issue is in the ON clause? You're using function in the WHERE part applied to the b table - that is why you have fullscan over your a table, and partial scan over b table.
I'm doing some reading on SQL Server performance:
http://www.amazon.com/Inside-Microsoft-SQL-Server-2005/dp/0735623139/ref=sr_1_6?ie=UTF8&s=books&qid=1267032068&sr=8-6
One of the surprising things I came across was how it processes the "FROM" phase in its Logical Processing. From what I understand, SQL Server will do the following:
1) For the first two tables, it will create a virtual table (VT1) consisting of a Cartesian join of the two tables
2) For every additional table, it will create a Cartesian join of VT1 and the additional table, with the result becoming VT1
I'm sure there is alot more to it under the covers, but at face value, this seems like it would involve a huge amount of processing/memory if you're dealing with big tables (and big queries).
I was just wondering whether anyone had a quick explanation of how SQL Server is able to do this in any sort of realistic time/space frame?
The carthesian join is just a description of the result, not an actual result. After the full carthesian join of tables A, B, C...X, the filter operators are applied (still as a definition), things like ON clauses of the join and WHERE clauses of the query. In the end this definition is in turn transformed into an execution plan, which will contain physicall operators like Nested Loops or Hash Join or Merge Join, and this operators, when iterated, will produce the results as requested in the query definition.
So the big 100x100x100x100... carthesian cube is never materialized, is just a definition.
If you are really interested in how SQL Server does what it does, please read this book:
http://www.amazon.com/Microsoft-SQL-Server-2008-Internals/dp/0735626243/ref=sr_1_1?ie=UTF8&s=books&qid=1267033666&sr=8-1
In reality the optimiser will look at the whole query, estimated rows, statistics, constraints etc
Logically, it is in the order mentioned though
Contrived example:
SELECT
BT.col1, LT.col2
FROm
BigTable BT
JOIN
LT.Table LT ON BT.FKCol = LT.PKCol
WHERE
LT.PKCol = 2
ORDER BY
BT.col1
The cartesian of BT and LT could be 100s of millions.
But the optimiser:
knows PKCol is unique so it expects only one row
can use statistics to estimate the number of rows from BT
looks for indexes (eg covering index on BT for FKCol INLCUDE col1)
will probably apply the WHERE first
will look ahead for an ORDER BY or GROUP BY for example to see if it can save some spooling (resorting)
I don't know the resource you are reading, but what you describe is the behavior of:
SELECT ... FROM tableA, tableB, tableC, ....
This uses a cartesian join (also called a cross join) and is very expensive. With large enough datasets SQL Server (or any RDBMS) can't do this in any sort of realistic time/space frame.
Using an ON clause and specifying the JOIN type performs vastly better:
SELECT ... FROM tableA JOIN tableB on tableB.a_id = tableA.a_id
In real applications cross joins should be rare or at least limited to very small datasets. For many applications it's not uncommon to never have a cross join.
which one is faster
select * from parents p
inner join children c on p.id = c.pid
where p.x = 2
OR
select * from
(select * from parents where p.x = 2)
p
inner join children c on p.id = c.pid
where p.x = 2
In MySQL, the first one is faster:
SELECT *
FROM parents p
INNER JOIN
children c
ON c.pid = p.id
WHERE p.x = 2
, since using an inline view implies generating and passing the records twice.
In other engines, they are usually optimized to use one execution plan.
MySQL is not very good in parallelizing and pipelining the result streams.
Like this query:
SELECT *
FROM mytable
LIMIT 1
is instant, while this one (which is semantically identical):
SELECT *
FROM (
SELECT *
FROM mytable
)
LIMIT 1
will first select all values from mytable, buffer them somewhere and then fetch the first record.
For Oracle, SQL Server and PostgreSQL, the queries above (and both of your queries) will most probably yield the same execution plans.
I know this is a simple case, but your first option is much more readable than the second one. As long as the two query plans are comparable I'd always opt for the more maintainable SQL code which your first example is for me.
It depends on how good the database is at optimising the query.
If the database manages to optimise the second one into the first one, they are equally fast, otherwise the first one is faster.
The first one gives more freedom for the database to optimise the query. The second one suggests a specific order of doing things. Either the database is able to see past this and optimise it into a single query, or it will run the query as two separate queries with the subquery as an intermediate result.
A database like SQL Server keeps statistics on what the database tables contain, which it uses to determine how to execute the query in the most efficient way. For example, depending on what will elliminate most records it can either start with joining the tables or filtering the parents table on the condition. If you write a query that forces a specific order, that might not be the most efficient order.
I'd think the first. I'm not sure if the optimizer would use any indexes on the the derived table in the second query, or if it would copy out all the rows that match into memory before joining back to the children.
This is why you have DBAs. It depends entirely on the DBMS, and how your tables and indexes are configured, as to which one runs the fastest.
Database tuning is not a set-and-forget operation, it should be done regularly, as the data changes, to ensure your database runs at peak performance. The question is not really meaningful without specifying:
which DBMS you are asking about.
what indexes you have on the tables.
a host of other possible configuration items (which may also depend on the DBMS, such as clustering).
You should run both those queries through the query optimizer to see which one is fastest, then start using that one. That's assuming the difference in noticeable in the first place. If the difference is minimal, go for the easiest to read/maintain.
For me, in the second query you are saying, I don't trust the optimizer to optimize this query so I'll provide some 'hints'.
I'd say, trust the optimizer until it let's you down and only then consider trying to do the optimizer's job for it.