INNER JOIN vs LEFT JOIN performance in SQL Server

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名媛妹妹
名媛妹妹 2020-11-22 11:51

I\'ve created SQL command that uses INNER JOIN on 9 tables, anyway this command takes a very long time (more than five minutes). So my folk suggested me to change INNER JOIN

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  • 2020-11-22 12:13

    Outer joins can offer superior performance when used in views.

    Say you have a query that involves a view, and that view is comprised of 10 tables joined together. Say your query only happens to use columns from 3 out of those 10 tables.

    If those 10 tables had been inner-joined together, then the query optimizer would have to join them all even though your query itself doesn't need 7 out of 10 of the tables. That's because the inner joins themselves might filter down the data, making them essential to compute.

    If those 10 tables had been outer-joined together instead, then the query optimizer would only actually join the ones that were necessary: 3 out of 10 of them in this case. That's because the joins themselves are no longer filtering the data, and thus unused joins can be skipped.

    Source: http://www.sqlservercentral.com/blogs/sql_coach/2010/07/29/poor-little-misunderstood-views/

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  • 2020-11-22 12:14

    Try both queries (the one with inner and left join) with OPTION (FORCE ORDER) at the end and post the results. OPTION (FORCE ORDER) is a query hint that forces the optimizer to build the execution plan with the join order you provided in the query.

    If INNER JOIN starts performing as fast as LEFT JOIN, it's because:

    • In a query composed entirely by INNER JOINs, the join order doesn't matter. This gives freedom for the query optimizer to order the joins as it sees fit, so the problem might rely on the optimizer.
    • With LEFT JOIN, that's not the case because changing the join order will alter the results of the query. This means the engine must follow the join order you provided on the query, which might be better than the optimized one.

    Don't know if this answers your question but I was once in a project that featured highly complex queries making calculations, which completely messed up the optimizer. We had cases where a FORCE ORDER would reduce the execution time of a query from 5 minutes to 10 seconds.

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  • 2020-11-22 12:15

    I found something interesting in SQL server when checking if inner joins are faster than left joins.

    If you dont include the items of the left joined table, in the select statement, the left join will be faster than the same query with inner join.

    If you do include the left joined table in the select statement, the inner join with the same query was equal or faster than the left join.

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  • 2020-11-22 12:20

    A LEFT JOIN is absolutely not faster than an INNER JOIN. In fact, it's slower; by definition, an outer join (LEFT JOIN or RIGHT JOIN) has to do all the work of an INNER JOIN plus the extra work of null-extending the results. It would also be expected to return more rows, further increasing the total execution time simply due to the larger size of the result set.

    (And even if a LEFT JOIN were faster in specific situations due to some difficult-to-imagine confluence of factors, it is not functionally equivalent to an INNER JOIN, so you cannot simply go replacing all instances of one with the other!)

    Most likely your performance problems lie elsewhere, such as not having a candidate key or foreign key indexed properly. 9 tables is quite a lot to be joining so the slowdown could literally be almost anywhere. If you post your schema, we might be able to provide more details.


    Edit:

    Reflecting further on this, I could think of one circumstance under which a LEFT JOIN might be faster than an INNER JOIN, and that is when:

    • Some of the tables are very small (say, under 10 rows);
    • The tables do not have sufficient indexes to cover the query.

    Consider this example:

    CREATE TABLE #Test1
    (
        ID int NOT NULL PRIMARY KEY,
        Name varchar(50) NOT NULL
    )
    INSERT #Test1 (ID, Name) VALUES (1, 'One')
    INSERT #Test1 (ID, Name) VALUES (2, 'Two')
    INSERT #Test1 (ID, Name) VALUES (3, 'Three')
    INSERT #Test1 (ID, Name) VALUES (4, 'Four')
    INSERT #Test1 (ID, Name) VALUES (5, 'Five')
    
    CREATE TABLE #Test2
    (
        ID int NOT NULL PRIMARY KEY,
        Name varchar(50) NOT NULL
    )
    INSERT #Test2 (ID, Name) VALUES (1, 'One')
    INSERT #Test2 (ID, Name) VALUES (2, 'Two')
    INSERT #Test2 (ID, Name) VALUES (3, 'Three')
    INSERT #Test2 (ID, Name) VALUES (4, 'Four')
    INSERT #Test2 (ID, Name) VALUES (5, 'Five')
    
    SELECT *
    FROM #Test1 t1
    INNER JOIN #Test2 t2
    ON t2.Name = t1.Name
    
    SELECT *
    FROM #Test1 t1
    LEFT JOIN #Test2 t2
    ON t2.Name = t1.Name
    
    DROP TABLE #Test1
    DROP TABLE #Test2
    

    If you run this and view the execution plan, you'll see that the INNER JOIN query does indeed cost more than the LEFT JOIN, because it satisfies the two criteria above. It's because SQL Server wants to do a hash match for the INNER JOIN, but does nested loops for the LEFT JOIN; the former is normally much faster, but since the number of rows is so tiny and there's no index to use, the hashing operation turns out to be the most expensive part of the query.

    You can see the same effect by writing a program in your favourite programming language to perform a large number of lookups on a list with 5 elements, vs. a hash table with 5 elements. Because of the size, the hash table version is actually slower. But increase it to 50 elements, or 5000 elements, and the list version slows to a crawl, because it's O(N) vs. O(1) for the hashtable.

    But change this query to be on the ID column instead of Name and you'll see a very different story. In that case, it does nested loops for both queries, but the INNER JOIN version is able to replace one of the clustered index scans with a seek - meaning that this will literally be an order of magnitude faster with a large number of rows.

    So the conclusion is more or less what I mentioned several paragraphs above; this is almost certainly an indexing or index coverage problem, possibly combined with one or more very small tables. Those are the only circumstances under which SQL Server might sometimes choose a worse execution plan for an INNER JOIN than a LEFT JOIN.

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  • 2020-11-22 12:22

    There is one important scenario that can lead to an outer join being faster than an inner join that has not been discussed yet.

    When using an outer join, the optimizer is always free to drop the outer joined table from the execution plan if the join columns are the PK of the outer table, and none of the outer table columns are referenced outside of the outer join itself. For example SELECT A.* FROM A LEFT OUTER JOIN B ON A.KEY=B.KEY and B.KEY is the PK for B. Both Oracle (I believe I was using release 10) and Sql Server (I used 2008 R2) prune table B from the execution plan.

    The same is not necessarily true for an inner join: SELECT A.* FROM A INNER JOIN B ON A.KEY=B.KEY may or may not require B in the execution plan depending on what constraints exist.

    If A.KEY is a nullable foreign key referencing B.KEY, then the optimizer cannot drop B from the plan because it must confirm that a B row exists for every A row.

    If A.KEY is a mandatory foreign key referencing B.KEY, then the optimizer is free to drop B from the plan because the constraints guarantee the existence of the row. But just because the optimizer can drop the table from the plan, doesn't mean it will. SQL Server 2008 R2 does NOT drop B from the plan. Oracle 10 DOES drop B from the plan. It is easy to see how the outer join will out-perform the inner join on SQL Server in this case.

    This is a trivial example, and not practical for a stand-alone query. Why join to a table if you don't need to?

    But this could be a very important design consideration when designing views. Frequently a "do-everything" view is built that joins everything a user might need related to a central table. (Especially if there are naive users doing ad-hoc queries that do not understand the relational model) The view may include all the relevent columns from many tables. But the end users might only access columns from a subset of the tables within the view. If the tables are joined with outer joins, then the optimizer can (and does) drop the un-needed tables from the plan.

    It is critical to make sure that the view using outer joins gives the correct results. As Aaronaught has said - you cannot blindly substitute OUTER JOIN for INNER JOIN and expect the same results. But there are times when it can be useful for performance reasons when using views.

    One last note - I haven't tested the impact on performance in light of the above, but in theory it seems you should be able to safely replace an INNER JOIN with an OUTER JOIN if you also add the condition <FOREIGN_KEY> IS NOT NULL to the where clause.

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  • 2020-11-22 12:23

    Your performance problems are more likely to be because of the number of joins you are doing and whether the columns you are joining on have indexes or not.

    Worst case you could easily be doing 9 whole table scans for each join.

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