![]() ![]() Our conclusion does not apply at all here. join will be evaluated before its result is cross-joined to T1 (to be further filtered down by any joining condition that might be found the WHERE clause). SQL Server will evaluate each individual comma-separated item independently of the others before cross-joining them all together. When you have a mix of joins like this: FROM Now, SQL Server allows you to mix comma joins and conventional joins in the same FROM clause. You can see, though, that the joining condition in this case comes in an entirely different clause, the WHERE clause. A joining condition makes it an inner join. Without a joining condition, a comma join is essentially a cross join. ![]() This type of join, sometimes referred to as comma join, is still supported by most, if not all, platforms, including SQL Server. Prior to introduction of the explicit JOIN syntax, joins were specified like this: FROM Mixing comma joins and conventional joins In this example, the first join we encounter as we parse the FROM clause, is not yet completely specified by the time the second one is. ![]() We concluded that the joins are evaluated in the order they are specified in the FROM clause. You could still argue that our conclusion stands here, although it is not as clear-cut in this situation. So in this case, T2 is joined to T3 first, then the result of the join is joined to T1. However the former join's declaration is not complete at that point: its ON subclause is the one at the end and is logically evaluated only after the JOIN T3 ON. In the above case, JOIN T2 is encountered before JOIN T3. Syntactically, a join may be specified inside another join, like this: FROM However, there are variations worth mentioning where our conclusion does not apply, or at least not as straightforwardly. Your example matches that pattern, so the conclusion applies to it as well. Note that the conclusion above applies to the most conventional join syntax, namely this: FROM That means that logically, the joins are executed in the order they are specified in the FROM clause. Executing the query, you will see that actually it is the first one. Since these two interpretations give such different results, it is clear that only one can be true. Therefore, this second interpretation would mean that all T1 rows should be present in the result. When this result set is then outer-joined to T1, T1 being on the outer side, you will get a final result containing all the rows from T1 and those from the T2- T3 inner join that match the outer join condition: T2.BARNCH_CODE T2.CUSTOMER_NUM T3.CUSTOMER_NUM Now if the inner join is executed first, then it will produce a result set containing the rows from T2 and T3 that match the inner join's condition: This way some of T1 rows will be excluded from the final result set. ![]() T1.BRANCH_CODE T2.BARNCH_CODE T2.CUSTOMER_NUM T3.CUSTOMER_NUM Joining that result further with T3 using an inner join on a condition that uses a T2 column will eliminate the non-matches – and, therefore, corresponding T1 rows, – because a null cannot satisfy the join's equals condition: T1.BRANCH_CODE T2.BARNCH_CODE T2.CUSTOMER_NUM If the left join evaluates first, then its result will have nulls in the T2 columns where T1 rows had no match: There are two joins here and two possibilities in which order they are executed. More specifically, let us assume these are the three tables: T1 T2 T3īRANCH_CODE BRANCH_CODE CUSTOMER_NUM CUSTOMER_NUM Let us assume that some rows in T1 have no matches in T2. One way to determine the logical order of joins is to replace the first inner join in your example with a left outer join: SELECT * ![]()
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