How Can I Improve SQL Server COUNT(*) Performance for Large Tables?

SQL Server Count(*) Performance

Various count(*) performance issues can arise in SQL Server when dealing with large tables, such as those with millions of rows. Let's explore the underlying reasons and potential solutions.

Optimization for Exact Count

When performing an exact equality check (e.g., if (select count() from BookChapters) = 0), SQL Server optimizes the query by using an existence check (if exists(select from BookChapters)). This optimization skips the actual row counting, resulting in faster query execution.

Performance Penalty for Inequality Checks

However, when using inequality checks (e.g., if (select count() from BookChapters) = 1 or if (select count() from BookChapters) > 1), SQL Server relies on index lookups or table scans. Since the BookChapters table lacks any non-clustered indexes, in this case, a full table scan is performed. This time-intensive operation explains the significant slowdown.

Alternative Techniques for Faster Counting

To enhance performance, consider the following techniques when dealing with large tables:

• Using Sysindexes Table (SQL Server 2000-2008):

Extract row counts from the sysindexes table, which provides a quick and reliable estimation of table rows.

• Calculating Row Count from Partitions (SQL Server 2005 and Later):

Utilize the sys.partitions table to sum the rows associated with each partition of a table or clustered index. This provides an accurate and efficient row count.

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