NOT IN vs NOT EXISTS

I always default to NOT EXISTS.

The execution plans may be the same at the moment but if either column is altered in the future to allow NULLs the NOT IN version will need to do more work (even if no NULLs are actually present in the data) and the semantics of NOT IN if NULLs are present are unlikely to be the ones you want anyway.

When neither Products.ProductID or [Order Details].ProductID allow NULLs the NOT IN will be treated identically to the following query.

SELECT ProductID,
       ProductName
FROM   Products p
WHERE  NOT EXISTS (SELECT *
                   FROM   [Order Details] od
                   WHERE  p.ProductId = od.ProductId) 

The exact plan may vary but for my example data I get the following.

https://i.stack.imgur.com/lCTsG.png

A reasonably common misconception seems to be that correlated sub queries are always "bad" compared to joins. They certainly can be when they force a nested loops plan (sub query evaluated row by row) but this plan includes an anti semi join logical operator. Anti semi joins are not restricted to nested loops but can use hash or merge (as in this example) joins too.

/*Not valid syntax but better reflects the plan*/ 
SELECT p.ProductID,
       p.ProductName
FROM   Products p
       LEFT ANTI SEMI JOIN [Order Details] od
         ON p.ProductId = od.ProductId 

If [Order Details].ProductID is NULL-able the query then becomes

SELECT ProductID,
       ProductName
FROM   Products p
WHERE  NOT EXISTS (SELECT *
                   FROM   [Order Details] od
                   WHERE  p.ProductId = od.ProductId)
       AND NOT EXISTS (SELECT *
                       FROM   [Order Details]
                       WHERE  ProductId IS NULL) 

The reason for this is that the correct semantics if [Order Details] contains any NULL ProductIds is to return no results. See the extra anti semi join and row count spool to verify this that is added to the plan.

https://i.stack.imgur.com/mPYhd.png

If Products.ProductID is also changed to become NULL-able the query then becomes

SELECT ProductID,
       ProductName
FROM   Products p
WHERE  NOT EXISTS (SELECT *
                   FROM   [Order Details] od
                   WHERE  p.ProductId = od.ProductId)
       AND NOT EXISTS (SELECT *
                       FROM   [Order Details]
                       WHERE  ProductId IS NULL)
       AND NOT EXISTS (SELECT *
                       FROM   (SELECT TOP 1 *
                               FROM   [Order Details]) S
                       WHERE  p.ProductID IS NULL) 

The reason for that one is because a NULL Products.ProductId should not be returned in the results except if the NOT IN sub query were to return no results at all (i.e. the [Order Details] table is empty). In which case it should. In the plan for my sample data this is implemented by adding another anti semi join as below.

https://i.stack.imgur.com/8XAh1.png

The effect of this is shown in the blog post already linked by Buckley. In the example there the number of logical reads increase from around 400 to 500,000.

Additionally the fact that a single NULL can reduce the row count to zero makes cardinality estimation very difficult. If SQL Server assumes that this will happen but in fact there were no NULL rows in the data the rest of the execution plan may be catastrophically worse, if this is just part of a larger query, with inappropriate nested loops causing repeated execution of an expensive sub tree for example.

This is not the only possible execution plan for a NOT IN on a NULL-able column however. This article shows another one for a query against the AdventureWorks2008 database.

For the NOT IN on a NOT NULL column or the NOT EXISTS against either a nullable or non nullable column it gives the following plan.

https://i.stack.imgur.com/nahUD.png

When the column changes to NULL-able the NOT IN plan now looks like

https://i.stack.imgur.com/8o9PQ.png

It adds an extra inner join operator to the plan. This apparatus is explained here. It is all there to convert the previous single correlated index seek on Sales.SalesOrderDetail.ProductID = <correlated_product_id> to two seeks per outer row. The additional one is on WHERE Sales.SalesOrderDetail.ProductID IS NULL.

As this is under an anti semi join if that one returns any rows the second seek will not occur. However if Sales.SalesOrderDetail does not contain any NULL ProductIDs it will double the number of seek operations required.

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Also be aware that NOT IN is not equivalent to NOT EXISTS when it comes to null.

This post explains it very well

http://sqlinthewild.co.za/index.php/2010/02/18/not-exists-vs-not-in/

When the subquery returns even one null, NOT IN will not match any rows. The reason for this can be found by looking at the details of what the NOT IN operation actually means. Let’s say, for illustration purposes that there are 4 rows in the table called t, there’s a column called ID with values 1..4 WHERE SomeValue NOT IN (SELECT AVal FROM t) is equivalent to WHERE SomeValue != (SELECT AVal FROM t WHERE ID=1) AND SomeValue != (SELECT AVal FROM t WHERE ID=2) AND SomeValue != (SELECT AVal FROM t WHERE ID=3) AND SomeValue != (SELECT AVal FROM t WHERE ID=4) Let’s further say that AVal is NULL where ID = 4. Hence that != comparison returns UNKNOWN. The logical truth table for AND states that UNKNOWN and TRUE is UNKNOWN, UNKNOWN and FALSE is FALSE. There is no value that can be AND’d with UNKNOWN to produce the result TRUE Hence, if any row of that subquery returns NULL, the entire NOT IN operator will evaluate to either FALSE or NULL and no records will be returned

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If the execution planner says they're the same, they're the same. Use whichever one will make your intention more obvious -- in this case, the second.

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Actually, I believe this would be the fastest:

SELECT ProductID, ProductName 
    FROM Northwind..Products p  
          outer join Northwind..[Order Details] od on p.ProductId = od.ProductId)
WHERE od.ProductId is null

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I have a table which has about 120,000 records and need to select only those which does not exist (matched with a varchar column) in four other tables with number of rows approx 1500, 4000, 40000, 200. All the involved tables have unique index on the concerned Varchar column.

NOT IN took about 10 mins, NOT EXISTS took 4 secs.

I have a recursive query which might had some untuned section which might have contributed to the 10 mins, but the other option taking 4 secs explains, atleast to me that NOT EXISTS is far better or at least that IN and EXISTS are not exactly the same and always worth a check before going ahead with code.

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I was using

SELECT * from TABLE1 WHERE Col1 NOT IN (SELECT Col1 FROM TABLE2)

and found that it was giving wrong results (By wrong I mean no results). As there was a NULL in TABLE2.Col1.

While changing the query to

SELECT * from TABLE1 T1 WHERE NOT EXISTS (SELECT Col1 FROM TABLE2 T2 WHERE T1.Col1 = T2.Col2)

gave me the correct results.

Since then I have started using NOT EXISTS every where.

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In your specific example they are the same, because the optimizer has figured out what you are trying to do is the same in both examples. But it is possible that in non-trivial examples the optimizer may not do this, and in that case there are reasons to prefer one to other on occasion.

NOT IN should be preferred if you are testing multiple rows in your outer select. The subquery inside the NOT IN statement can be evaluated at the beginning of the execution, and the temporary table can be checked against each value in the outer select, rather than re-running the subselect every time as would be required with the NOT EXISTS statement.

If the subquery must be correlated with the outer select, then NOT EXISTS may be preferable, since the optimizer may discover a simplification that prevents the creation of any temporary tables to perform the same function.

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Database table model

Let’s assume we have the following two tables in our database, that form a one-to-many table relationship.

https://i.stack.imgur.com/uD3tb.png

The student table is the parent, and the student_grade is the child table since it has a student_id Foreign Key column referencing the id Primary Key column in the student table.

The student table contains the following two records:

id first_name last_name admission_score 1 Alice Smith 8.95 2 Bob Johnson 8.75

And, the student_grade table stores the grades the students received:

id class_name grade student_id 1 Math 10 1 2 Math 9.5 1 3 Math 9.75 1 4 Science 9.5 1 5 Science 9 1 6 Science 9.25 1 7 Math 8.5 2 8 Math 9.5 2 9 Math 9 2 10 Science 10 2 11 Science 9.4 2

SQL EXISTS

Let’s say we want to get all students that have received a 10 grade in Math class.

If we are only interested in the student identifier, then we can run a query like this one:

SELECT
    student_grade.student_id
FROM
    student_grade
WHERE
    student_grade.grade = 10 AND
    student_grade.class_name = 'Math'
ORDER BY
    student_grade.student_id

But, the application is interested in displaying the full name of a student, not just the identifier, so we need info from the student table as well.

In order to filter the student records that have a 10 grade in Math, we can use the EXISTS SQL operator, like this:

SELECT
    id, first_name, last_name
FROM
    student
WHERE EXISTS (
    SELECT 1
    FROM
        student_grade
    WHERE
        student_grade.student_id = student.id AND
        student_grade.grade = 10 AND
        student_grade.class_name = 'Math'
)
ORDER BY id

When running the query above, we can see that only the Alice row is selected:

id first_name last_name 1 Alice Smith

The outer query selects the student row columns we are interested in returning to the client. However, the WHERE clause is using the EXISTS operator with an associated inner subquery.

The EXISTS operator returns true if the subquery returns at least one record and false if no row is selected. The database engine does not have to run the subquery entirely. If a single record is matched, the EXISTS operator returns true, and the associated other query row is selected.

The inner subquery is correlated because the student_id column of the student_grade table is matched against the id column of the outer student table.

SQL NOT EXISTS

Let’s consider we want to select all students that have no grade lower than 9. For this, we can use NOT EXISTS, which negates the logic of the EXISTS operator.

Therefore, the NOT EXISTS operator returns true if the underlying subquery returns no record. However, if a single record is matched by the inner subquery, the NOT EXISTS operator will return false, and the subquery execution can be stopped.

To match all student records that have no associated student_grade with a value lower than 9, we can run the following SQL query:

SELECT
    id, first_name, last_name
FROM
    student
WHERE NOT EXISTS (
    SELECT 1
    FROM
        student_grade
    WHERE
        student_grade.student_id = student.id AND
        student_grade.grade < 9
)
ORDER BY id

When running the query above, we can see that only the Alice record is matched:

id first_name last_name 1 Alice Smith

So, the advantage of using the SQL EXISTS and NOT EXISTS operators is that the inner subquery execution can be stopped as long as a matching record is found.

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They are very similar but not really the same.

In terms of efficiency, I've found the left join is null statement more efficient (when an abundance of rows are to be selected that is)

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If the optimizer says they are the same then consider the human factor. I prefer to see NOT EXISTS :)

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It depends..

SELECT x.col
FROM big_table x
WHERE x.key IN( SELECT key FROM really_big_table );

would not be relatively slow the isn't much to limit size of what the query check to see if they key is in. EXISTS would be preferable in this case.

But, depending on the DBMS's optimizer, this could be no different.

As an example of when EXISTS is better

SELECT x.col
FROM big_table x
WHERE EXISTS( SELECT key FROM really_big_table WHERE key = x.key);
  AND id = very_limiting_criteria

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