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Query optimization is a fundamental aspect of database management. It involves constructing SQL queries in such a way that they execute as efficiently as possible. The DB2 database system from IBM has a number of features that can assist in query optimization. One of these features is the use of index hints. In this article, we will discuss DB2 query optimization and how to use index hints for better performance.

SQL Server 2016 and 2017, MySQL 5.7, and Azure SQL, like DB2, have query optimization techniques, but DB2 stands out due to its advanced index hinting feature. An index hint is a directive to the DB2 query optimizer to use a particular index to retrieve the data. If the hint is followed, DB2 can bypass the usual process of determining the best access path, potentially saving processing time.

To illustrate the application of index hints in DB2, let's consider an example. Suppose we have a table USERS with columns USER_ID and NAME, and an index IDX_NAME on the NAME column. We want to retrieve all user details where the NAME is 'John'.

SELECT * FROM USERS 

WHERE NAME = 'John' 

OPTIMIZE FOR 1 ROW 

FOR FETCH ONLY WITH UR;

DB2 ordinarily decides on the best access path. However, we can instruct it to use the index IDX_NAME by adding the INDEX hint in our query, as shown below:

-- DB2 code goes here 

SELECT * FROM USERS -- add line break after this 

WHERE NAME = 'John' -- add line break after this 

USE INDEX (IDX_NAME) -- add the index hint here 

OPTIMIZE FOR 1 ROW -- add line break after this 

FOR FETCH ONLY WITH UR;

Please note that using index hints should be done judiciously. It's a powerful tool, but can lead to performance degradation if used incorrectly. It's advisable to thoroughly understand the database structure and the data distribution before using index hints. Regularly updating statistics can also help DB2 make better optimization decisions.

In conclusion, DB2 query optimization is a crucial aspect of managing a DB2 database. Index hints can be a powerful tool in your optimization toolkit, but should be used wisely. Regularly updating statistics and having a deep understanding of your database structure and data distribution can aid in making the best use of this feature. Happy optimizing!