Performance Tuning SQL Server Joins

We have a query that contains two subselects containing an aggregate function (SUM, Count, etc.) in the SELECT part. The query was performing sluggishly. We were able to isolate the problem down to the aggregate function in the subselect.

To rectify the problem, we reorganized the query so that there was still an aggregate function in the SELECT part, but replaced the subselects with a series of JOINS. The query executed much faster.

So, if this holds true — developers, as a rule, should use JOINS in lieu of subselects when the subselect contains aggregate functions. [7.0, 2000, 2005] Tip provided by Silverscape Technologies, Inc (www.silverscape.net) Updated 8-21-2006

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If you have a query with many joins, one alternative to de-normalizing a table to boost performance is to use an Indexed View to pre-join the tables. An Indexed View, which is only available from SQL Server 2000 and 2005 Enterprise Editions, allows you to create a view that is actually a physical object that has its own clustered index. Whenever a base table of the Indexed View is updated, the Indexed View is also updated. As you can imagine, this can potentially reduce INSERT, UPDATE, and DELETE performance on the base tables. You will have to perform tests, comparing the pros and cons of performance in order to determine whether or not using an Indexed View to avoid joins in query is worth the extra performance cost caused by using them. [2000, 2005] Updated 8-21-2006

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If you have a query that uses a LEFT OUTER JOIN, check it carefully to be sure that is the type of join you really want to use. As you may know, a LEFT OUTER JOIN is used to create a result set that includes all of the rows from the left table specified in the clause, not just the ones in which the joined columns match. In addition, when a row in the left table has no matching rows in the right table, the result set row contains NULL values for all the selected columns coming from the right table. If this is what you want, then use this type of join.

The problem is that in the real world, a LEFT OUTER JOIN is rarely needed, and many developers use them by mistake. While you may end up with the data you want, you may also end up with more than the data you want, which contributes to unnecessary overhead and poor performance. Because of this, always closely examine why you are using a LEFT OUTER JOIN in your queries, and only use them if they are exactly what you need. Otherwise, use a JOIN that is more appropriate to your needs. [6.5, 7.0, 2000, 2005] Updated 8-21-2006

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If you are having difficulty tuning the performance of a poorly performing query that has one or more JOINs, check to see if they query plan created by the query optimizer is using a hash join. When the query optimizer is asked to join two tables that don’t have appropriate indexes, it will often perform a hash join.

A hash join is resource intensive (especially CPU and I/O) and can slow the performance of your join. If the query in question is run often, you should consider adding appropriate indexes. For example, if you are joining column1 in table1 to column5 in table2, then column1 in table1 and column5 in table2 need to have indexes.

Once indexes are added to the appropriate columns used in the joins in your query, the query optimizer will most likely be able to use these indexes, performing a nested-loop join instead of a hash join, and performance will improve. [7.0, 2000, 2005] Updated 8-21-2006

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