The idea that COUNT(column_name) is faster than COUNT(*) in SQL Server is a common misconception. Here's a detailed explanation of the performance and behavior of these two queries:
- COUNT(*) counts all rows in the result set, regardless of whether any columns contain NULL values.
- It uses an optimized internal mechanism that doesn’t require reading specific column data. Instead, SQL Server counts rows at the physical storage level, which is typically very efficient.
- COUNT(column_name) counts the non-NULL values in the specified column.
- SQL Server needs to evaluate each value in the column to determine if it is NULL or not, which can introduce additional overhead, especially if the column contains many NULL values.
- Index Optimization: COUNT(*) can leverage a narrow, non-clustered index (or clustered index) to quickly count rows without reading specific column data.
- Less Logical Work: COUNT(*) doesn’t require the engine to examine the NULL state of any column, making it straightforward and efficient.
- Engine-Specific Optimizations: SQL Server optimizes COUNT(*) internally for performance since it’s commonly used.
In rare cases, COUNT(column_name) can seem faster if:
- Indexes on the Column: The column being counted has a highly optimized non-clustered index, making it faster to access compared to reading all rows.
- Filtered Data: If your query has a WHERE clause that significantly limits the data set, and the column is indexed, COUNT(column_name) might perform better due to fewer rows being examined.
- If you want the total number of rows, always use COUNT(*) because it is optimized for that purpose.
- Use COUNT(column_name) only when you need to exclude NULL values from the count.
- For very large datasets, ensure proper indexing to optimize either query type.
In practice, SQL Server's query optimizer often minimizes the performance difference between the two, making them comparable in most cases when indexes and query plans are properly configured
