Understanding NULLs and the NOT IN
Clause
Inconsistencies often arise when using NOT IN
clauses compared to LEFT JOIN
s, especially when dealing with NULL
values. Let's examine this with two example queries:
Query A:
SELECT 'true' WHERE 3 IN (1, 2, 3, NULL);
Query B:
SELECT 'true' WHERE 3 NOT IN (1, 2, NULL);
Query A produces a result, while Query B doesn't. This difference stems from how SQL handles comparisons involving NULL
values.
Dissecting the Queries
Let's break down each query to understand the behavior:
Query A:
This query can be simplified to:
SELECT 'true' WHERE 3 = 1 OR 3 = 2 OR 3 = 3 OR 3 = NULL;
Because 3 = 3
evaluates to TRUE
, the query returns a result.
Query B:
This query simplifies to:
SELECT 'true' WHERE 3 != 1 AND 3 != 2 AND 3 != NULL;
With ANSI_NULLS
enabled (the default in most SQL databases), 3 != NULL
evaluates to UNKNOWN
. An AND
condition with UNKNOWN
results in the entire predicate being UNKNOWN
, leading to no rows being returned.
If ANSI_NULLS
is disabled, 3 != NULL
evaluates to TRUE
, potentially returning a row.
Conclusion
The presence of NULL
values within a NOT IN
clause significantly impacts query results due to the three-valued logic of SQL (TRUE, FALSE, UNKNOWN) and the setting of ANSI_NULLS
. It's crucial to be aware of this behavior when working with NULL
values to avoid unexpected outcomes. Using LEFT JOIN
and IS NULL
checks often provides a more reliable alternative for handling NULL
values in such scenarios.
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