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When it comes to managing high volume tables in DB2, the key to optimal performance lies in efficient index design. DB2 11.5, like MySQL 8.0, SQL Server 2019, Azure SQL, and Azure Synapse, uses B-tree indexes. In DB2, these indexes can be clustered or non-clustered, and the choice between these two types can significantly impact your database's performance.

A clustered index determines the physical order of data in a table. It's similar to a telephone directory, which is arranged by last name. The benefit of a clustered index is that it speeds up data retrieval because the database engine can quickly find a specific row. However, because a table can only have one clustered index (since the data can only be sorted in one way), you must be strategic in deciding which columns to include in this index.

On the other hand, a non-clustered index is more like an index in a book. It doesn’t determine the physical order of data, but it creates a logical order that the database engine can use to locate data more quickly. A table can have multiple non-clustered indexes, making them a versatile tool for optimizing DB2 performance.

Let's look at an example of how to create a clustered index in DB2. The following SQL code creates a clustered index called 'sales_idx' on the 'sales' table, using the 'sales_date' column:

-- DB2 code to create a clustered index

CREATE UNIQUE INDEX sales_idx

ON sales (sales_date)

CLUSTER

In addition to choosing the right index type, it’s crucial to evaluate the columns you include in your indexes. Indexes are most efficient when they're designed around the queries that your applications most frequently use. For example, if a query often filters on the 'sales_date' and 'product_id' columns, an index that includes these columns can significantly speed up this query.

Another critical aspect of DB2 index design is managing index fragmentation. Over time, as data is inserted, updated, and deleted, your indexes can become fragmented, leading to wasted space and decreased performance. Fortunately, DB2 provides a REORG command to defragment and reorganize your indexes. Here's an example:

-- DB2 REORG command to defragment an index

CALL SYSPROC.ADMIN_CMD('REORG INDEX sales.sales_idx')

In conclusion, efficient index design is vital for managing high volume tables in DB2. By choosing the right index type, carefully selecting your indexed columns, and regularly managing index fragmentation, you can ensure that your DB2 database performs optimally, even under heavy load.