


Improving Distinct Count Queries over Multiple Columns
Counting distinct values over multiple columns is a common requirement in data analysis. One way to achieve this is by using a subquery as shown in the provided code snippet. However, this approach can potentially impact performance.
Alternative Solution: Persisted Computed Columns
To enhance the performance of such queries, consider using persisted computed columns. A persisted computed column calculates and stores a value based on a defined expression. In this case, you can create a computed column that combines the two columns using a hash function or concatenation:
ALTER TABLE DocumentOutputItems ADD ComputedColumn AS HASHBYTES('MD5', DocumentId + ',' + DocumentSessionId) PERSISTED
Once persisted, the computed column becomes an indexed, deterministic column that can be used for fast queries. By counting the distinct values of this computed column, you can achieve the same result as the subquery approach:
SELECT COUNT(DISTINCT ComputedColumn) FROM DocumentOutputItems
Benefits:
- Improved performance: Persisted computed columns are optimized for fast queries by leveraging indexing and statistics.
- Reduced database resources: By using a single query instead of a subquery, you can minimize the resource usage of your database.
Note: The effectiveness of this approach depends on the data distribution and the proper configuration of the database settings.
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