In Azure SQL Database, as in other relational database systems, handling NULL values in columns that are indexed or involved in JOIN operations can have specific implications on index performance and the execution plans generated by the SQL Server query optimizer. Understanding these implications is crucial for optimizing query performance and ensuring efficient data retrieval. Here are the key impacts:

1. Index Performance

• Index Size and Utilization: NULL values are included in indexes unless filtered out explicitly. If a column contains a significant number of NULL values, this can lead to larger index sizes and potentially lower index efficiency, as the SQL Server engine has to process and possibly ignore these NULL entries during query execution.

• Filtered Indexes: To improve index efficiency, you can create filtered indexes that exclude NULL values when they are not relevant to the query workload. This can significantly reduce index size and improve query performance by focusing on the meaningful data subset.

CREATE INDEX idx_columnname_not_null
ON tablename(columnname)
WHERE columnname IS NOT NULL;

2. Query Execution Plans

• JOIN Operations: The presence of NULL values can affect how the query optimizer chooses to execute JOIN operations. In SQL, NULL values are considered unknown, and therefore, two NULL values are not considered equal. This behavior impacts how rows are matched in joins:

  • In an inner join, if one or both join columns contain NULL, rows with NULL in either side of the join condition will not be matched, potentially leading to fewer rows in the result set than expected.

  • In outer joins, rows with NULL in the join column of the preserved table will appear in the result set, but matching on NULL values will not occur, affecting the completeness of joined data.

• Optimization Choices: SQL Server's query optimizer may make different choices regarding indexes, join algorithms (nested loops, merge join, hash join), or whether to perform index scans versus seeks based on the distribution of NULL values and the presence of filtered indexes.

3. Query Performance and Results

• SARGability: Searches, arguments, and joins that involve columns with NULL values can sometimes be non-SARGable (Search ARGument Able), meaning they cannot efficiently utilize indexes. This is particularly the case for complex predicates involving NULL comparisons, which might force the optimizer to resort to table scans.

• Unexpected Results: Queries involving comparisons with NULL values (column = NULL or column != NULL) without appropriate handling (IS NULL or IS NOT NULL) can lead to unexpected results, potentially leading to full table scans if the optimizer cannot effectively use indexes due to the uncertainty introduced by NULL comparisons.

Best Practices

• Use IS NULL/IS NOT NULL: Always use IS NULL or IS NOT NULL for comparisons instead of = NULL or != NULL to ensure accurate results and better query performance.

• Consider Filtered Indexes: Use filtered indexes to exclude NULL values when they are not needed, reducing index size and improving efficiency.

• Handle NULLs in Application Logic: If possible, handle NULL logic in application code to simplify SQL queries and improve their performance.

By understanding and strategically managing the impact of NULL values on indexes and JOIN operations, you can optimize the performance of your Azure SQL Database and ensure that your queries return the expected results efficiently.