Reputation: 141
I'm having a performance problem.
I created a table that receives data from a file, I do a BULK INSERT
. Then I do a SELECT
with multiple INNER JOIN
s (11 inner joins) to insert into another table with the right data.
When I run this SELECT
, it takes too long (more than a hour) and then I stop it. My solution was to break this query into 3, creating @temp
tables. To my surprise, that takes 3 minutes. That's what I'm trying to understand, WHY breaking my query into 3 was FASTER than one select statement. Here is my query:
SELECT t1.ReturnINT, t1.ReturnBIT, t2.ReturnINT, t3.ReturnINT, t5.ReturnINT, t1.ReturnDateTime
FROM t1
INNER JOIN t2
ON t2.my_column_varchar = t1.my_column_varchar
INNER JOIN t3
ON t3.my_column_number = t1.my_column_number AND t2.my_column_ID = t3.my_column_ID
INNER JOIN t4
ON t4.my_column_varchar = t1.my_column_varchar
INNER JOIN t5
ON t5.my_column_int = t1.my_column_int AND t5.my_column_int = t4.my_column_int AND t2.my_column_int = t5.my_column_int
INNER JOIN t6
ON t6.my_column_int = t5.my_column_int AND t6.my_column_int = t2.my_column_int
INNER JOIN t7
ON t7.my_column_int = t6.my_column_int
INNER JOIN t8
ON t8.my_column_int = t3.my_column_int AND t8.my_column_datetime = t1.my_column_datetime
INNER JOIN t9
ON t9.my_column_int = t3.my_column_int AND t8.my_column_datetime BETWEEN t9.my_column_datetime1 AND t9.datetime1 + t9.my_column_datetime2
INNER JOIN t10
ON t10.my_column_int = t9.my_column_int AND t10.my_column_int = t6.my_column_int
INNER JOIN t11
ON t11.my_column_int = t9.my_column_int AND t8.my_column_datetime = t11.my_column_datetime
----EDITED----
There is NO where clause, my query is exactly as I put here.
Here is my broken querys, i forget to put them here. It runs in 3 minutes.
DECLARE @temp TABLE (
<Some_columns>
)
INSERT INTO @temp
SELECT <My_Linked_Columns>
FROM t1
INNER JOIN t2
ON t2.my_column_varchar = t1.my_column_varchar
INNER JOIN t3
ON t3.my_column_number = t1.my_column_number AND t2.my_column_ID = t3.my_column_ID
INNER JOIN t4
ON t4.my_column_varchar = t1.my_column_varchar
INNER JOIN t5
ON t5.my_column_int = t1.my_column_int AND t5.my_column_int = t4.my_column_int AND t2.my_column_int = t5.my_column_int
DECLARE @temp2 TABLE(
<Some_Columns>
)
INSERT INTO @temp2
SELECT <More_Linked_Columns>
FROM @temp as temp
INNER JOIN t6
ON t6.my_column_int = temp.my_column_int AND t6.my_column_int = temp.my_column_int
INNER JOIN t7
ON t7.my_column_int = t6.my_column_int
INNER JOIN t8
ON t8.my_column_int = temp.my_column_int AND t8.my_column_datetime = temp.my_column_datetime
DECLARE @temp3 TABLE(
<Some_Columns>
)
INSERT INTO @temp3
SELECT <More_Linked_Columns>
FROM @temp2 AS temp2
INNER JOIN t9
ON t9.my_column_int = temp2.my_column_int AND temp2.my_column_datetime BETWEEN t9.my_column_datetime1 AND t9.datetime1 + t9.my_column_datetime2
INNER JOIN t10
ON t10.my_column_int = t9.my_column_int AND t10.my_column_int = temp2.my_column_int
INNER JOIN t11
ON t11.my_column_int = t9.my_column_int AND temp2.my_column_datetime = t11.my_column_datetime
SELECT <All_Final_Columns>
FROM @temp3
----EDITED 3----
Studying more things I discovered a problem in execution plan. I have a Nested Loop that estimates 1 row but it actually returns 1.204.014 rows. I guess the problem is exactly here, but I didn't find out how to solve this problem without breaking my query in 3 parts (Now I know why breaking it is faster hehehe)
Upvotes: 7
Views: 19946
Reputation: 121
Could be a few different things but from what it sounds like, you have checked your indexes and execution plan. I'd suggest Adam Mechanic's video about 'row goals' and using the top statement, which would work similarly to how the temp tables worked.
SELECT *
FROM
(SELECT top (2000000000) t1.ReturnINT,
t1.ReturnBIT,
t2.ReturnINT,
t3.ReturnINT,
t5.ReturnINT,
t1.ReturnDateTime
FROM t1
INNER JOIN t2 ON t2.my_column_varchar = t1.my_column_varchar
INNER JOIN t3 ON t3.my_column_number = t1.my_column_number
AND t2.my_column_ID = t3.my_column_ID
INNER JOIN t4 ON t4.my_column_varchar = t1.my_column_varchar
INNER JOIN t5 ON t5.my_column_int = t1.my_column_int
AND t5.my_column_int = t4.my_column_int
AND t2.my_column_int = t5.my_column_int
INNER JOIN t6 ON t6.my_column_int = t5.my_column_int
AND t6.my_column_int = t2.my_column_int
INNER JOIN t7 ON t7.my_column_int = t6.my_column_int
INNER JOIN t8 ON t8.my_column_int = t3.my_column_int
AND t8.my_column_datetime = t1.my_column_datetime
INNER JOIN t9 ON t9.my_column_int = t3.my_column_int
AND t8.my_column_datetime BETWEEN t9.my_column_datetime1
AND t9.datetime1 + t9.my_column_datetime2
INNER JOIN t10 ON t10.my_column_int = t9.my_column_int
AND t10.my_column_int = t6.my_column_int
INNER JOIN t11 ON t11.my_column_int = t9.my_column_int
AND t8.my_column_datetime = t11.my_column_datetime
)
I had a similar issue but it had a where clause after several joins and took a 10 minute query and reduced it to 39 seconds.
Upvotes: 0
Reputation: 4006
With the right index or indexes the original query should execute very quickly (lest than one second if you page the data). Don't use temp tables as a hack for not being able to come up with a reasonable query.
Upvotes: 0
Reputation: 6771
In general, you want the query optimizer to join the tables in such a way that will limit the result set as much as possible. If you have table A with 1 million rows, table B with 1 million rows, and table C with 10 rows, you'd want to inner join from table C to A or B first, this would give you at most 10 records (assuming a 1:1 match) to then join to the last table. If you joined A to B first you'd be joining on all 1 million rows from each, which would take quite a bit longer.
Usually the query optimizer is "good enough" at picking the join order, but in your case it was not. The best method I've seen for forcing the join order was demonstrated by Adam Mechanic in a blog post here. It involves using a TOP clause on the tables you want to begin the join from. The query optimizer will then get the result set from those tables first, and you can really limit the total number of rows and increase query performance. I use this method whenever possible.
Upvotes: 2
Reputation: 17126
Most common reasons:
Reason 1: When two tables having n and m rows participating in INNER JOIN
have many to many relationship, then the INNER JOIN
can near a CROSS JOIN
and can produce result set with more than MAX(n,m) rows, theoretically n x m rows are possible.
Now imagine many such tables in INNER JOIN
.
This will result in the result set becoming bigger and bigger and will start eating into the allocated memory area.
This could be a reason why temp tables might help you.
Reason 2: You do not have INDEX
built on the columns you are joining tables on.
Reason 3: Do you have functions in WHERE
clause?
Upvotes: 7