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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 to LEFT JOIN because the performance of LEFT JOIN is better, despite what I know. After I changed it, the speed of query got significantly improved.

I would like to know why LEFT JOIN is faster than INNER JOIN?

My SQL command look like below: SELECT * FROM A INNER JOIN B ON ... INNER JOIN C ON ... INNER JOIN D and so on

Update: This is brief of my schema.

FROM sidisaleshdrmly a -- NOT HAVE PK AND FK INNER JOIN sidisalesdetmly b -- THIS TABLE ALSO HAVE NO PK AND FK ON a.CompanyCd = b.CompanyCd AND a.SPRNo = b.SPRNo AND a.SuffixNo = b.SuffixNo AND a.dnno = b.dnno INNER JOIN exFSlipDet h -- PK = CompanyCd, FSlipNo, FSlipSuffix, FSlipLine ON a.CompanyCd = h.CompanyCd AND a.sprno = h.AcctSPRNo INNER JOIN exFSlipHdr c -- PK = CompanyCd, FSlipNo, FSlipSuffix ON c.CompanyCd = h.CompanyCd AND c.FSlipNo = h.FSlipNo AND c.FSlipSuffix = h.FSlipSuffix INNER JOIN coMappingExpParty d -- NO PK AND FK ON c.CompanyCd = d.CompanyCd AND c.CountryCd = d.CountryCd INNER JOIN coProduct e -- PK = CompanyCd, ProductSalesCd ON b.CompanyCd = e.CompanyCd AND b.ProductSalesCd = e.ProductSalesCd LEFT JOIN coUOM i -- PK = UOMId ON h.UOMId = i.UOMId INNER JOIN coProductOldInformation j -- PK = CompanyCd, BFStatus, SpecCd ON a.CompanyCd = j.CompanyCd AND b.BFStatus = j.BFStatus AND b.ProductSalesCd = j.ProductSalesCd INNER JOIN coProductGroup1 g1 -- PK = CompanyCd, ProductCategoryCd, UsedDepartment, ProductGroup1Cd ON e.ProductGroup1Cd = g1.ProductGroup1Cd INNER JOIN coProductGroup2 g2 -- PK = CompanyCd, ProductCategoryCd, UsedDepartment, ProductGroup2Cd ON e.ProductGroup1Cd = g2.ProductGroup1Cd
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    Do you project any attribute from coUOM? If not you may be able to use a semi join. If yes, you would be able to use UNION as an alternative. Posting just your FROM clause is inadequate information here. Commented Dec 15, 2011 at 9:44
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    I've wondered this so often (because I see all the time). Commented Mar 16, 2013 at 22:44
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    Did you miss out an Order By in your brief schema? I just recently faced an issue where changing an INNER JOIN to LEFT OUTER JOIN speeds up the query from 3 minutes to 10 seconds. If you really have Order By in your query, I will explain further as an answer. It looked like all the answers didn't really explain the case that I faced. Commented Oct 12, 2015 at 10:55

9 Answers 9

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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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16 Comments

There is another scenario that can lead to an OUTER JOIN performing better than an INNER JOIN. See my answer below.
I want to point out that there is basically no database documentation to support the idea that inner joins and outer joins performance differently. Outer joins are slightly more expensive than inner joins, because of the volume of the data and the size of the result set. However, the underlying algorithms (msdn.microsoft.com/en-us/library/ms191426(v=sql.105).aspx) are the same for both types of joins. Performance should be similar when they return the similar amounts of data.
@Aaronaught . . . This answer was referenced in a comment that said something to the effect that "outer joins perform significantly worse than inner joins". I commented just to be sure that this misinterpretation doesn't spread.
I think this answer is misleading in one important aspect: Because it states "A LEFT JOIN is absolutely not faster than an INNER JOIN". This line is not correct. It is theoretically not faster than an INNER JOIN. It is NOT "absolutely not faster." The question is specifically a performance question. In practice I have now seen a few systems (by very big companies!) where INNER JOIN was ridiculously slow compared to OUTER JOIN. Theory and practice are very different things.
@DavidFrenkel: That is highly unlikely. I'd ask to see an A/B comparison, with execution plans, if you believe that such a discrepancy is possible. Possibly it is related to cached query/execution plans, or bad statistics.
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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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8 Comments

I actually ran into this problem when building out extremely dynamic queries. I had left in an INNER JOIN that I was using and not pulling data from, and when I switched it to a LEFT JOIN (out of shear curiosity) the query actually ran faster.
EDIT - Clarified the conditions that must exist for the optimizer to drop the outer joined table from the execution plan.
One minor clarification to your answer: When the foreign key column is non-nullable, the INNER JOIN and the LEFT JOIN become semantically equivalent (i.e. your suggested WHERE clause is redundant); the only difference would be the execution plan.
Although this shows a seemingly trivial example indeed, this is an extraordinarily insightful answer!
+1: I seem to have run into this on a few queries where I was using inner joins with some very large tables. The inner join was causing a spill into tempdb in the query plan (I assume for the reason stated above -- and my server lacking the RAM to hold everything in memory). Switching to left joins eliminated the spill to tempdb, result being that some of my 20-30 second queries now run in fractions of a second. This is a very important gotcha seeing as most people seem to make the blanket assumption that inner joins are faster.
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If everything works as it should it shouldn't, BUT we all know everything doesn't work the way it should especially when it comes to the query optimizer, query plan caching and statistics.

First I would suggest rebuilding index and statistics, then clearing the query plan cache just to make sure that's not screwing things up. However I've experienced problems even when that's done.

I've experienced some cases where a left join has been faster than a inner join.

The underlying reason is this: If you have two tables and you join on a column with an index (on both tables). The inner join will produce the same result no matter if you loop over the entries in the index on table one and match with index on table two as if you would do the reverse: Loop over entries in the index on table two and match with index in table one. The problem is when you have misleading statistics, the query optimizer will use the statistics of the index to find the table with least matching entries (based on your other criteria). If you have two tables with 1 million in each, in table one you have 10 rows matching and in table two you have 100000 rows matching. The best way would be to do an index scan on table one and matching 10 times in table two. The reverse would be an index scan that loops over 100000 rows and tries to match 100000 times and only 10 succeed. So if the statistics isn't correct the optimizer might choose the wrong table and index to loop over.

If the optimizer chooses to optimize the left join in the order it is written it will perform better than the inner join.

BUT, the optimizer may also optimize a left join sub-optimally as a left semi join. To make it choose the one you want you can use the force order hint.

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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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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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Your statement about "outer-joined" is misleading and potentially incorrect. Outer means that the data on the other-side need not exist - and if it doesn't substitute NULL. Under specific circumstances the RDBMS may "skip" them (see above answer from dbenham). HOWEVER - outer vs inner can cause your query to return radically different results. INNER means - give results for which an item is in BOTH A & B. LEFT OUTER means all of A, and optionally B if it exists. First case - you get some rows, in second you get ALL rows.
@ripvlan Of course, outer and inner joins aren't always interchangeable. The original question was about performance, which implies that we're talking about cases in which either join would return the same result set.
Yes and - the OUTER could cause a performance issue because it will cause all rows (more data) to be returned. Your assumption that the queries result in the same output is a fair one - however it isn't true in the general case and specific to each db design. And for those not 100% familiar with relational algebra could cause them grief. My point is only to offer more insight to people reading this looking for advice and that a LEFT/RIGHT won't magically solve a problem and could cause more issues. It's a power left for level 300 :-)
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Have done a number of comparisons between left outer and inner joins and have not been able to find a consisten difference. There are many variables. Am working on a reporting database with thousands of tables many with a large number of fields, many changes over time (vendor versions and local workflow) . It is not possible to create all of the combinations of covering indexes to meet the needs of such a wide variety of queries and handle historical data. Have seen inner queries kill server performance because two large (millions to tens of millions of rows) tables are inner joined both pulling a large number of fields and no covering index exists.

The biggest issue though, doesn't seem to appeaer in the discussions above. Maybe your database is well designed with triggers and well designed transaction processing to ensure good data. Mine frequently has NULL values where they aren't expected. Yes the table definitions could enforce no-Nulls but that isn't an option in my environment.

So the question is... do you design your query only for speed, a higher priority for transaction processing that runs the same code thousands of times a minute. Or do you go for accuracy that a left outer join will provide. Remember that inner joins must find matches on both sides, so an unexpected NULL will not only remove data from the two tables but possibly entire rows of information. And it happens so nicely, no error messages.

You can be very fast as getting 90% of the needed data and not discover the inner joins have silently removed information. Sometimes inner joins can be faster, but I don't believe anyone making that assumption unless they have reviewed the execution plan. Speed is important, but accuracy is more important.

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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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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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From my comparisons, I find that they have the exact same execution plan. There're three scenarios:

  1. If and when they return the same results, they have the same speed. However, we must keep in mind that they are not the same queries, and that LEFT JOIN will possibly return more results (when some ON conditions aren't met) --- this is why it's usually slower.

  2. When the main table (first non-const one in the execution plan) has a restrictive condition (WHERE id = ?) and the corresponding ON condition is on a NULL value, the "right" table is not joined --- this is when LEFT JOIN is faster.

  3. As discussed in Point 1, usually INNER JOIN is more restrictive and returns fewer results and is therefore faster.

Both use (the same) indices.

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